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Alewaidat H, Bataineh Z, Bani-Ahmad M, Alali M, Almakhadmeh A. Investigation of the diagnostic importance and accuracy of CT in the chest compared to the RT-PCR test for suspected COVID-19 patients in Jordan. F1000Res 2023; 12:741. [PMID: 37822316 PMCID: PMC10562777 DOI: 10.12688/f1000research.130388.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/09/2023] [Indexed: 10/13/2023] Open
Abstract
This article aims to synthesize the existing literature on the implementation of public policies to incentivize the development of treatments for rare diseases, (diseases with very low prevalence and therefore with low commercial interest) otherwise known as orphan drugs. The implementation of these incentives in the United States (US), Japan, and in the European Union (EU) seems to be related to a substantial increase in treatments for these diseases, and has influenced the way the pharmaceutical research & development (R&D) system operates beyond this policy area. Despite the success of the Orphan Drug model, the academic literature also highlights the negative implications that these public policies have on affordability and access to orphan drugs, as well as on the prioritization of certain disease rare areas over others. The synthesis focuses mostly on the United States' Orphan Drug Act (ODA) as a model for subsequent policies in other regions and countries. It starts with a historical overview of the creation of the term "rare diseases", continues with a summary of the evidence available on the US ODA's positive and negative impacts, and provides a summary of the different proposals to reform these incentives in light of the negative outcomes described. Finally, it describes some key aspects of the Japanese and European policies, as well as some of the challenges captured in the literature related to their impact in Low- and Middle-Income Countries (LMICs).
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Affiliation(s)
- Haytham Alewaidat
- Applied Medical Sciences, Jordan University of Science and Technology, irbid, 22110, Jordan
| | - Ziad Bataineh
- Anatomy, Jordan University of Science and Technology, Irbid, 22110, Jordan
| | - Mohammad Bani-Ahmad
- Medical Laboratory Science, Jordan University of Science and Technology, Irbid, 22110, Jordan
| | - Manar Alali
- Medical Laboratory Science, Zarqa University, Zarqa, Jordan
| | - Ali Almakhadmeh
- Radiologic Technology, Jordan University of Science and Technology, Irbid, 22110, Jordan
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Castellanos-Bermejo JE, Cervantes-Guevara G, Cervantes-Pérez E, Cervantes-Cardona GA, Ramírez-Ochoa S, Fuentes-Orozco C, Delgado-Hernández G, Tavares-Ortega JA, Gómez-Mejía E, Chejfec-Ciociano JM, Flores-Prado JA, Barbosa-Camacho FJ, González-Ojeda A. Diagnostic Efficacy of Chest Computed Tomography with a Dual-Reviewer Approach in Patients Diagnosed with Pneumonia Secondary to Severe Acute Respiratory Syndrome Coronavirus 2. Tomography 2023; 9:1617-1628. [PMID: 37736982 PMCID: PMC10514805 DOI: 10.3390/tomography9050129] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 08/16/2023] [Accepted: 08/22/2023] [Indexed: 09/23/2023] Open
Abstract
To compare the diagnostic effectiveness of chest computed tomography (CT) utilizing a single- versus a dual-reviewer approach in patients with pneumonia secondary to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we conducted a retrospective observational study of data from a cross-section of 4809 patients with probable SARS-CoV-2 from March to November 2020. All patients had a CT radiological report and reverse-transcription polymerase chain reaction (PCR) results. A dual-reviewer approach was applied to two groups while conducting a comparative examination of the data. Reviewer 1 reported 108 patients negative and 374 patients positive for coronavirus disease 2019 (COVID-19) in group A, and 266 negative and 142 positive in group B. Reviewer 2 reported 150 patients negative and 332 patients positive for COVID-19 in group A, and 277 negative and 131 positive in group B. The consensus result reported 87 patients negative and 395 positive for COVID-19 in group A and 274 negative and 134 positive in group B. These findings suggest that a dual-reviewer approach improves chest CT diagnosis compared to a conventional single-reviewer approach.
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Affiliation(s)
- Jaime E. Castellanos-Bermejo
- Departamento de Radiología e Imagen, Hospital General Regional 110, Instituto Mexicano del Seguro Social, Guadalajara 44716, Mexico;
| | - Gabino Cervantes-Guevara
- Departamento de Bienestar y Desarrollo Sustentable, Centro Universitario del Norte, Universidad de Guadalajara, Colotlán 46200, Mexico;
- Departamento de Gastroenterología, Hospital Civil de Guadalajara Fray Antonio Alcalde, Universidad de Guadalajara, Guadalajara 44280, Mexico
| | - Enrique Cervantes-Pérez
- Departamento de Medicina Interna, Hospital Civil de Guadalajara Fray Antonio Alcalde, Guadalajara 44280, Mexico; (E.C.-P.)
- Centro Universitario de Tlajomulco, Universidad de Guadalajara, Tlajomulco de Zúñiga 45641, Mexico
| | - Guillermo A. Cervantes-Cardona
- Departamento de Disciplinas Filosóficas, Metodológicas e Instrumentales, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44340, Mexico;
| | - Sol Ramírez-Ochoa
- Departamento de Gastroenterología, Hospital Civil de Guadalajara Fray Antonio Alcalde, Universidad de Guadalajara, Guadalajara 44280, Mexico
| | - Clotilde Fuentes-Orozco
- Unidad de Investigación Biomédica 02, Unidad Médica de alta especialidad, Hospital de Especialidades Centro Médico Nacional de Occidente, Instituto Mexicano del Seguro Social, Guadalajara 44329, Mexico; (C.F.-O.); (G.D.-H.); (J.A.T.-O.); (E.G.-M.); (J.M.C.-C.); (J.A.F.-P.)
| | - Gonzalo Delgado-Hernández
- Unidad de Investigación Biomédica 02, Unidad Médica de alta especialidad, Hospital de Especialidades Centro Médico Nacional de Occidente, Instituto Mexicano del Seguro Social, Guadalajara 44329, Mexico; (C.F.-O.); (G.D.-H.); (J.A.T.-O.); (E.G.-M.); (J.M.C.-C.); (J.A.F.-P.)
| | - Jaime A. Tavares-Ortega
- Unidad de Investigación Biomédica 02, Unidad Médica de alta especialidad, Hospital de Especialidades Centro Médico Nacional de Occidente, Instituto Mexicano del Seguro Social, Guadalajara 44329, Mexico; (C.F.-O.); (G.D.-H.); (J.A.T.-O.); (E.G.-M.); (J.M.C.-C.); (J.A.F.-P.)
| | - Erika Gómez-Mejía
- Unidad de Investigación Biomédica 02, Unidad Médica de alta especialidad, Hospital de Especialidades Centro Médico Nacional de Occidente, Instituto Mexicano del Seguro Social, Guadalajara 44329, Mexico; (C.F.-O.); (G.D.-H.); (J.A.T.-O.); (E.G.-M.); (J.M.C.-C.); (J.A.F.-P.)
| | - Jonathan M. Chejfec-Ciociano
- Unidad de Investigación Biomédica 02, Unidad Médica de alta especialidad, Hospital de Especialidades Centro Médico Nacional de Occidente, Instituto Mexicano del Seguro Social, Guadalajara 44329, Mexico; (C.F.-O.); (G.D.-H.); (J.A.T.-O.); (E.G.-M.); (J.M.C.-C.); (J.A.F.-P.)
| | - Juan A. Flores-Prado
- Unidad de Investigación Biomédica 02, Unidad Médica de alta especialidad, Hospital de Especialidades Centro Médico Nacional de Occidente, Instituto Mexicano del Seguro Social, Guadalajara 44329, Mexico; (C.F.-O.); (G.D.-H.); (J.A.T.-O.); (E.G.-M.); (J.M.C.-C.); (J.A.F.-P.)
| | - Francisco J. Barbosa-Camacho
- Departamento de Psiquiatría, Hospital Civil de Guadalajara Fray Antonio Alcalde, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara 44280, Mexico;
| | - Alejandro González-Ojeda
- Unidad de Investigación Biomédica 02, Unidad Médica de alta especialidad, Hospital de Especialidades Centro Médico Nacional de Occidente, Instituto Mexicano del Seguro Social, Guadalajara 44329, Mexico; (C.F.-O.); (G.D.-H.); (J.A.T.-O.); (E.G.-M.); (J.M.C.-C.); (J.A.F.-P.)
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Hazem M, Ali SI, AlAlwan QM, Al Jabr IK, Alshehri SAF, AlAlwan MQ, Alsaeed MI, Aldawood M, Turkistani JA, Amin YA. Diagnostic Performance of the Radiological Society of North America Consensus Statement for Reporting COVID-19 Chest CT Findings: A Revisit. J Clin Med 2023; 12:5180. [PMID: 37629222 PMCID: PMC10455816 DOI: 10.3390/jcm12165180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Revised: 07/24/2023] [Accepted: 08/05/2023] [Indexed: 08/27/2023] Open
Abstract
Coronavirus disease 2019 (COVID-19) is a highly contagious respiratory disease that leads to variable degrees of illness, and which may be fatal. We evaluated the diagnostic performance of each chest computed tomography (CT) reporting category recommended by the Expert Consensus of the Radiological Society of North America (RSNA) in comparison with that of reverse transcription polymerase chain reaction (RT-PCR). We aimed to add an analysis of this form of reporting in the Middle East, as few studies have been performed there. Between July 2021 and February 2022, 184 patients with a mean age of 55.56 ± 16.71 years and probable COVID-19 infections were included in this retrospective study. Approximately 64.67% (119 patients) were male, while 35.33% (65 patients) were female. Within 7 days, all patients underwent CT and RT-PCR examinations. According to a statement by the RSNA, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of each CT reporting category were calculated, and the RT-PCR results were used as a standard reference. The RT-PCR results confirmed a final diagnosis of COVID-19 infection in 60.33% of the patients. For COVID-19 diagnoses, the typical category (n = 88) had a sensitivity, specificity, PPV, and accuracy of 74.8%, 93.2%, 94.3%, and 92.5%, respectively. For non-COVID-19 diagnoses, the PPVs for the atypical (n = 22) and negative (n = 46) categories were 81.8% and 89.1%, respectively. The PPV for the indeterminate (n = 28) category was 67.9%, with a low sensitivity of 17.1%. However, the RSNA's four chest CT reporting categories provide a strong diagnostic foundation and are highly correlated with the RT-PCR results for the typical, atypical, and negative categories, but they are weaker for the indeterminate category.
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Affiliation(s)
- Mohammed Hazem
- Department of Surgery, Collage of Medicine, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia; (I.K.A.J.); (S.A.F.A.)
- Diagnostic and Interventional Radiology Department, Faculty of Medicine, Sohag University, Sohag 82524, Egypt;
| | - Sayed Ibrahim Ali
- Department of Family and Community Medicine, Collage of Medicine, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia; (S.I.A.); (J.A.T.)
- Educational Psychology Department, College of Education, Helwan University, Cairo 11795, Egypt
| | - Qasem M. AlAlwan
- Department of Radiology, King Fahd Hospital Hofuf, Al-Ahsa 36441, Saudi Arabia; (Q.M.A.); (M.Q.A.)
| | - Ibrahim Khalid Al Jabr
- Department of Surgery, Collage of Medicine, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia; (I.K.A.J.); (S.A.F.A.)
| | - Sarah Abdulrahman F. Alshehri
- Department of Surgery, Collage of Medicine, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia; (I.K.A.J.); (S.A.F.A.)
| | - Mohammed Q. AlAlwan
- Department of Radiology, King Fahd Hospital Hofuf, Al-Ahsa 36441, Saudi Arabia; (Q.M.A.); (M.Q.A.)
| | | | - Mohammed Aldawood
- Collage of Medicine, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia;
| | - Jamela A. Turkistani
- Department of Family and Community Medicine, Collage of Medicine, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia; (S.I.A.); (J.A.T.)
| | - Yasser Abdelkarim Amin
- Diagnostic and Interventional Radiology Department, Faculty of Medicine, Sohag University, Sohag 82524, Egypt;
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Nam BD, Hong H, Yoon SH. Diagnostic performance of standardized typical CT findings for COVID-19: a systematic review and meta-analysis. Insights Imaging 2023; 14:96. [PMID: 37222857 DOI: 10.1186/s13244-023-01429-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 04/14/2023] [Indexed: 05/25/2023] Open
Abstract
OBJECTIVE To meta-analyze diagnostic performance measures of standardized typical CT findings for COVID-19 and examine these measures by region and national income. METHODS MEDLINE and Embase were searched from January 2020 to April 2022 for diagnostic studies using the Radiological Society of North America (RSNA) classification or the COVID-19 Reporting and Data System (CO-RADS) for COVID-19. Patient and study characteristics were extracted. We pooled the diagnostic performance of typical CT findings in the RSNA and CO-RADS systems and interobserver agreement. Meta-regression was performed to examine the effect of potential explanatory factors on the diagnostic performance of the typical CT findings. RESULTS We included 42 diagnostic performance studies with 6777 PCR-positive and 9955 PCR-negative patients from 18 developing and 24 developed countries covering the Americas, Europe, Asia, and Africa. The pooled sensitivity was 70% (95% confidence interval [CI]: 65%, 74%; I2 = 92%), and the pooled specificity was 90% (95% CI 86%, 93%; I2 = 94%) for the typical CT findings of COVID-19. The sensitivity and specificity of the typical CT findings did not differ significantly by national income and the region of the study (p > 0.1, respectively). The pooled interobserver agreement from 19 studies was 0.72 (95% CI 0.63, 0.81; I2 = 99%) for the typical CT findings and 0.67 (95% CI 0.61, 0.74; I2 = 99%) for the overall CT classifications. CONCLUSION The standardized typical CT findings for COVID-19 provided moderate sensitivity and high specificity globally, regardless of region and national income, and were highly reproducible between radiologists. CRITICAL RELEVANCE STATEMENT Standardized typical CT findings for COVID-19 provided a reproducible high diagnostic accuracy globally. KEY POINTS Standardized typical CT findings for COVID-19 provide high sensitivity and specificity. Typical CT findings show high diagnosability regardless of region or income. The interobserver agreement for typical findings of COVID-19 is substantial.
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Affiliation(s)
- Bo Da Nam
- Department of Radiology, Soonchunhyang University College of Medicine, Soonchunhyang University Seoul Hospital, Seoul, Republic of Korea
| | - Hyunsook Hong
- Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Republic of Korea
| | - Soon Ho Yoon
- Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
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Benmessaoud M, Dadouch A, Maghnouj A, Lemmassi A, Tahiri M, El-Ouardi Y, Ait Ouaggou I. Establishment of local diagnostic reference levels for paediatric abdominal-pelvis and Chest-abdominal-pelvis computed tomography in Morocco: suggests the need for improved optimization efforts. RADIATION PROTECTION DOSIMETRY 2023:7160592. [PMID: 37177805 DOI: 10.1093/rpd/ncad149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 03/25/2023] [Accepted: 04/05/2023] [Indexed: 05/15/2023]
Abstract
The purpose of the current study was to derive the local diagnostic reference levels (LDRLs) for paediatric abdominal-pelvis (AP) and chest-abdominal-pelvis (CAP) computed tomography in Morocco. The data were gathered retrospectively from two hospitals for 6 months. The LDRLs were defined by volume CT dose index (CTDIvol), dose-length product (DLP) per sequence, DLP per procedure and size-specific dose estimates (SSDE). The SSDE assessment was based on the effective diameters of patients scanned. A total of 630 CT examinations were collected involving 324 AP and 306 CAP scans. The proposed LDRLs for AP, in terms of CTDIvol (mGy), were 6.9, 8.5, 8.5 and 8.5 for < 1, 1 to < 5, 5 to < 10 and 10 to < 15 y age groups, respectively. In terms of DLP (mGy.cm) per procedure, they were 436.3, 534.5, 687.9 and 961.7. In terms of SSDE (mGy), thet were 16.73, 16.83, 17.5 and 15.8 for < 1, 1 to < 5, 5 to < 10 and 10 to < 15 y, respectively. The corresponding LDRLs for CAP, in terms of CTDIvol (mGy), were 7.3, 7.3, 7.3 and 10.35. In terms of DLP (mGy.cm) per procedure, they were 531, 622.5, 705 and 936. In terms of SSDE (mGy), they were 16.22, 15.05, 14.47 and 15.2, respectively, for the four age groups. The derived dose levels were mostly higher than those found in other studies, which demonstrates the need for dose optimization and paediatric protocol standardization as well as the timeliness of the intent to establish not only local DRLs but national ones in the near future.
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Affiliation(s)
- Mounir Benmessaoud
- Sidi Mohamed Ben Abdellah University, Faculty of Sciences Dhar EL Mahraz, Fez, Morocco
| | - Ahmed Dadouch
- Sidi Mohamed Ben Abdellah University, Faculty of Sciences Dhar EL Mahraz, Fez, Morocco
| | - Abdelmajid Maghnouj
- Sidi Mohamed Ben Abdellah University, Faculty of Sciences Dhar EL Mahraz, Fez, Morocco
| | - Assiya Lemmassi
- Sidi Mohamed Ben Abdellah University, Higher School of Technology, Fez, Morocco
| | - Maroine Tahiri
- Hassan First University, Higher Institute of Health Sciences, Settat, Morocco
| | - Youssef El-Ouardi
- Sidi Mohamed Ben Abdellah University, Faculty of Sciences Dhar EL Mahraz, Fez, Morocco
| | - Ibrahim Ait Ouaggou
- University Mohammed First, National School of Applied Sciences, Oujda, Morocco
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Benmessaoud M, Dadouch A, Maghnouj A, Lemmassi A, Ouaggou IA, Ouhadda H, El-Ouardi Y. Local diagnostic reference levels for paediatric chest computed tomography in Morocco. Radiat Phys Chem Oxf Engl 1993 2023. [DOI: 10.1016/j.radphyschem.2023.110794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
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Zolfaghari Emameh R, Heshmatnia J. Management, control, and decision making in unexpected recurrent venous thromboembolism in COVID-19: a case report. J Med Case Rep 2023; 17:101. [PMID: 36934279 PMCID: PMC10024637 DOI: 10.1186/s13256-023-03800-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 02/01/2023] [Indexed: 03/20/2023] Open
Abstract
BACKGROUND Coronavirus disease 2019 was spread worldwide, as a pandemic, from December 2019. Venous thromboembolism events can inflict patients with coronavirus disease 2019 during the hospitalization or convalescent period. Therefore, monitoring of these patients, in terms of venous thromboembolism events signs and symptoms, and timely management of antithrombotic agents are of great importance. CASE REPORT A 45-year-old Iranian man, who is the first author of this case report, was infected by severe acute respiratory syndrome coronavirus 2 and displayed the typical signs and symptoms of coronavirus disease 2019. Although reverse transcription polymerase chain reaction for coronavirus disease 2019, and specific immunoglobulin M and immunoglobulin G against severe acute respiratory syndrome coronavirus 2, were negative at first, chest computed tomography scan showed the characteristic pattern of lung involvement of a coronavirus disease 2019 infection including bilateral and multilobar ground-glass opacities. At that time, there were no signs or symptoms of deep-vein thrombosis or pulmonary thromboembolism, so these were not investigated. About 30 hours after hospital discharge, the patient presented back to the hospital with acute-onset chest pain. We instantly tested his blood for D-dimer, and sent him to take a Doppler sonography of his lower legs and a chest computed tomography angiography in search of pulmonary thromboembolism and deep-vein thrombosis. Although we could confirm pulmonary thromboembolism with computed tomography angiography in our patient, there were no signs or symptoms of venous thromboembolism in his lower legs, and color Doppler sonography of lower limbs was normal. So, the patient was treated with rivaroxaban as an antithrombotic agent. After some days, he was discharged in good condition. About 1 month later, he was referred to our hospital because of left lower limb edema. Although he was under antithrombotic therapy, color Doppler sonography of lower limbs revealed acute deep-vein thrombosis of the left leg. Hence, we decided to shift antithrombotic therapy from rivaroxaban to warfarin, as it is more potent than rivaroxaban in recurrent venous thromboembolism and when taking new oral anticoagulants. Unlike rivaroxaban, which needs no blood test to monitor its efficacy but has a warning for signs and symptoms of bleeding, warfarin therapy must be monitored carefully by regular blood tests for prothrombin time and international normalized ratio to maintain them in the therapeutic range. The patient was informed about the bleeding cautions, and required regular check of prothrombin time and international normalized ratio to maintain them in the proper and advised range of treatment (international normalized ratio therapeutic range 2-3). CONCLUSION In the case of unexpected recurrent venous thromboembolism in coronavirus disease 2019, especially when patients are taking rivaroxaban or other new oral anticoagulants, such drugs should be substituted by warfarin, with routine follow-up, to maintain the value of prothrombin time and international normalized ratio within the therapeutic range.
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Affiliation(s)
- Reza Zolfaghari Emameh
- grid.419420.a0000 0000 8676 7464Department of Energy and Environmental Biotechnology, National Institute of Genetic Engineering and Biotechnology (NIGEB), 14965/161, Tehran, Iran
| | - Jalal Heshmatnia
- grid.411600.2Chronic Respiratory Diseases Research Center (CRDRC), National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Hou N, Wang L, Li M, Xie B, He L, Guo M, Liu S, Wang M, Zhang R, Wang K. Do COVID-19 CT features vary between patients from within and outside mainland China? Findings from a meta-analysis. Front Public Health 2022; 10:939095. [PMID: 36311632 PMCID: PMC9616120 DOI: 10.3389/fpubh.2022.939095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 07/25/2022] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Chest computerized tomography (CT) plays an important role in detecting patients with suspected coronavirus disease 2019 (COVID-19), however, there are no systematic summaries on whether the chest CT findings of patients within mainland China are applicable to those found in patients outside. METHODS Relevant studies were retrieved comprehensively by searching PubMed, Embase, and Cochrane Library databases before 15 April 2022. Quality assessment of diagnostic accuracy studies (QUADAS) was used to evaluate the quality of the included studies, which were divided into two groups according to whether they were in mainland China or outside. Data on diagnostic performance, unilateral or bilateral lung involvement, and typical chest CT imaging appearances were extracted, and then, meta-analyses were performed with R software to compare the CT features of COVID-19 pneumonia between patients from within and outside mainland China. RESULTS Of the 8,258 studies screened, 19 studies with 3,400 patients in mainland China and 14 studies with 554 outside mainland China were included. Overall, the risk of quality assessment and publication bias was low. The diagnostic value of chest CT is similar between patients from within and outside mainland China (93, 91%). The pooled incidence of unilateral lung involvement (15, 7%), the crazy-paving sign (31, 21%), mixed ground-glass opacities (GGO) and consolidations (51, 35%), air bronchogram (44, 25%), vascular engorgement (59, 33%), bronchial wall thickening (19, 12%), and septal thickening (39, 26%) in patients from mainland China were significantly higher than those from outside; however, the incidence rates of bilateral lung involvement (75, 84%), GGO (78, 87%), consolidations (45, 58%), nodules (12, 17%), and pleural effusion (9, 15%) were significantly lower. CONCLUSION Considering that the chest CT features of patients in mainland China may not reflect those of the patients abroad, radiologists and clinicians should be familiar with various CT presentations suggestive of COVID-19 in different regions.
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Affiliation(s)
- Nianzong Hou
- Center of Gallbladder Disease, Shanghai East Hospital, Institute of Gallstone Disease, School of Medicine, Tongji University, Shanghai, China
- Department of Hand and Foot Surgery, Zibo Central Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Zibo, China
| | - Lin Wang
- Department of Critical Care Medicine, Zibo Central Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Zibo, China
| | - Mingzhe Li
- School of Molecular and Cellular Biology, University of Leeds, Leeds, United Kingdom
| | - Bing Xie
- Department of Hand and Foot Surgery, Zibo Central Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Zibo, China
| | - Lu He
- Department of Urology, Dongfeng Hospital, Hubei University of Medicine, Shiyan, China
| | - Mingyu Guo
- Department of Hand and Foot Surgery, Zibo Central Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Zibo, China
| | - Shuo Liu
- Department of Hand and Foot Surgery, Zibo Central Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Zibo, China
| | - Meiyu Wang
- Department of Cardiology, The People's Hospital of Zhangdian District, Zibo, China
| | - Rumin Zhang
- Department of Critical Care Medicine, Zibo Central Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Zibo, China
| | - Kai Wang
- Department of Critical Care Medicine, Zibo Central Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Zibo, China
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Danna PS, Buoni GF, Bor S, Coda C, Abruzzese F, Bertoli M, Giaivia V, Airoldi C, Castello LM, Saba L, Carriero A. May an incidental finding on chest CT be a predictor of access in intensive care unit? Role of hepatic steatosis in patients affected by SARS-CoV-2. J Public Health Res 2022; 11:22799036221115779. [DOI: 10.1177/22799036221115779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 07/09/2022] [Indexed: 11/17/2022] Open
Abstract
Background: Due to the high prevalence of hepatic steatosis (HS), the aim of the study is to verify the frequency of HS incidentally detected in chest computed tomography (CT) imaging in our population affected by SARS-CoV-2 and to investigate its association with the severity of the infection and outcome in terms of hospitalization. Design and methods: We retrospectively analyzed 500 patients with flu syndrome and clinically suspected of having Sars-CoV-2 infection who underwent unenhanced chest CT and have positive RT-PCR tests for Sars-CoV-2 RNA. Two radiologists both with >5 years of thoracic imaging experience, evaluated the images in consensus, without knowing the RT-PCR results. Liver density was measured by a region of interest (ROI), using a liver attenuation value ≤40 Hounsfield units (HU). Results: On 480 patients, 23.1% (111/480) had an incidental findings of HS on chest CT. The steatosis group, included 83 (74.7%) males and 28 (25.3%) females. Patients with HS were more likely to be hospitalized in the intensive care unit (ICU). On univariate analysis, there is a correlation between probability to be intubate (access in the ICU) and HS: patients with HS are twice as likely to be intubated (OR 2.04, CI 95% 1.11–3.73). Conclusion: Chest CT is an important diagnostic tool for COVID-19 and can provide information about the prognosis of the disease. HS can easily be detected on chest CT taken for the diagnosis of the COVID-19 disease, is an important sign for a poor prognosis and possible predictor of admission in ICU.
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Affiliation(s)
- Pietro S.C. Danna
- Department of Diagnosis and Treatment Services, Radiodiagnostics, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy
| | - Giada Francesca Buoni
- Department of Diagnosis and Treatment Services, Radiodiagnostics, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy
| | - Simone Bor
- Department of Diagnosis and Treatment Services, Radiodiagnostics, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy
| | - Carolina Coda
- Department of Diagnosis and Treatment Services, Radiodiagnostics, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy
| | - Flavia Abruzzese
- Department of Diagnosis and Treatment Services, Radiodiagnostics, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy
| | - Matteo Bertoli
- Department of Translational Medicine, Universita del Piemonte Orientale, Novara, Italy
| | - Valentina Giaivia
- Department of Translational Medicine, Universita del Piemonte Orientale, Novara, Italy
| | - Chiara Airoldi
- Department of Translational Medicine, Universita del Piemonte Orientale, Novara, Italy
| | - Luigi Mario Castello
- Department of Translational Medicine, Universita del Piemonte Orientale, Novara, Italy
| | - Luca Saba
- Department of Medical Sciences, University of Cagliari, Cagliari, Italy
| | - Alessandro Carriero
- Department of Diagnosis and Treatment Services, Radiodiagnostics, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy
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Mehta V, Jyoti D, Guria RT, Sharma CB. Correlation between chest CT and RT-PCR testing in India's second COVID-19 wave: a retrospective cohort study. BMJ Evid Based Med 2022; 27:305-312. [PMID: 35058302 DOI: 10.1136/bmjebm-2021-111801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/20/2021] [Indexed: 11/03/2022]
Abstract
OBJECTIVES To assess the diagnostic accuracy of chest CT in clinically suspected patients with COVID-19 using reverse transcriptase PCR (RT-PCR) as the reference standard and establish the correlation between CT Severity Score (CTSS) and RT-PCR results. DESIGN AND SETTING Retrospective cohort study. Single-centre tertiary care hospital-based study. PARTICIPANTS We enrolled 112 clinically suspected patients with COVID-19 between 1 April 2021 and 31 May 2021. Chest CT and RT-PCR tests were performed for all patients at a time interval of no longer than 7 days between the two tests. Patients with prior chronic respiratory illnesses were excluded. The diagnostic performance of chest CT was evaluated using RT-PCR as the reference standard. The CTSS was calculated for all patients with positive chest CT findings, and it was correlated with results of the RT-PCR assay. MAIN OUTCOME MEASURES The primary outcome measures were determination of the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy of chest CT using RT-PCR as the standard of reference. The correlation between CTSS and RT-PCR was the secondary outcome. RESULTS 85/112 (76%) patients tested positive on the RT-PCR whereas 91/112 (81%) had chest CT findings typical of SARS-CoV-2 infection. Chest CT had a sensitivity of 90.6% (95% CI 82.3% to 95.8%), a specificity of 48.1% (95% CI 28.7% to 68.0%), a PPV of 84.6% (95% CI 79.2% to 88.8%), an NPV of 61.9% (95% CI 43.0% to 77.8%) and an accuracy of 80.4% (95% CI 71.8% to 87.3%). There was a significant correlation between the CTSS and RT-PCR positivity (p value=0.003). CONCLUSION In our experience, chest CT has a good sensitivity and provides a reliable diagnostic tool for moderate-to-severe COVID-19 cases in resource limited settings.
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Affiliation(s)
- Vishal Mehta
- Department of Medicine, Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India
| | - Divya Jyoti
- Department of Medicine, Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India
| | - Rishi Tuhin Guria
- Department of Medicine, Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India
| | - Chandra Bhushan Sharma
- Department of Medicine, Rajendra Institute of Medical Sciences, Ranchi, Jharkhand, India
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11
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Martin C, Cheng N, Chang B, Arya N, Diaz MJ, Lin K, Umair M, Waller J, Henry T. Update on the limited sensitivity of computed tomography relative to RT-PCR for COVID-19: a systematic review. Pol J Radiol 2022; 87:e381-e391. [PMID: 35979154 PMCID: PMC9373863 DOI: 10.5114/pjr.2022.118238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 10/15/2021] [Indexed: 01/08/2023] Open
Abstract
Purpose The global and ongoing COVID-19 outbreak has compelled the need for timely and reliable methods of detection for SARS-CoV-2 infection. Although reverse transcription-polymerase chain reaction (RT-PCR) has been widely accepted as a reference standard for COVID-19 diagnosis, several early studies have suggested the superior sensitivity of computed tomography (CT) in identifying SARS-CoV-2 infection. In a previous systematic review, we stratified studies based on risk for bias to evaluate the true sensitivity of CT for detecting SARS-CoV-2 infection. This study revisits our prior analysis, incorporating more current data to assess the sensitivity of CT for COVID-19. Material and methods The PubMed and Google Scholar databases were searched for relevant articles published between 1 January 2020, and 25 April 2021. Exclusion criteria included lack of specification regarding whether the study cohort was adult or paediatric, whether patients were symptomatic or asymptomatic, and not identifying the source of RT-PCR specimens. Ultimately, 62 studies were included for systematic review and were subsequently stratified by risk for bias using the QUADAS-2 quality assessment tool. Sensitivity data were extracted for random effects meta-analyses. Results The average sensitivity for COVID-19 reported by the high-risk-of-bias studies was 68% [CI: 58, 80; range: 38-96%] for RT-PCR and 91% [CI: 87, 96; range: 47-100%] for CT. The average sensitivity reported by the low-risk-of-bias studies was 84% [CI: 0.75, 0.94; range: 70-97%] for RT-PCR and 78% [CI: 71, 0.86; range: 44-92%] for CT. Conclusions On average, the high-risk-of bias studies underestimated the sensitivity of RT-PCR and overestimated the sensitivity of CT for COVID-19. Given the incorporation of recently published low-risk-of-bias articles, the sensitivities according to low-risk-of-bias studies for both RT-PCR and CT were higher than previously reported.
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Affiliation(s)
| | - Nina Cheng
- Drexel University College of Medicine, Philadelphia, PA 19129, USA
| | - Bryant Chang
- Drexel University College of Medicine, Philadelphia, PA 19129, USA
| | - Namrata Arya
- Mayo Clinic Alix School of Medicine, Scottsdale, AZ 85259, USA
| | | | - Keldon Lin
- Mayo Clinic Alix School of Medicine, Scottsdale, AZ 85259, USA
| | - Muhammad Umair
- Johns Hopkins Department of Radiology & Radiological Sciences, Baltimore, MD 21205, USA
| | - Joseph Waller
- Drexel University College of Medicine, Philadelphia, PA 19129, USA
| | - Travis Henry
- Department of Radiology, Duke University School of Medicine, USA
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12
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Shim SR, Kim SJ, Hong M, Lee J, Kang MG, Han HW. Diagnostic Performance of Antigen Rapid Diagnostic Tests, Chest Computed Tomography, and Lung Point-of-Care-Ultrasonography for SARS-CoV-2 Compared with RT-PCR Testing: A Systematic Review and Network Meta-Analysis. Diagnostics (Basel) 2022; 12:1302. [PMID: 35741112 PMCID: PMC9222155 DOI: 10.3390/diagnostics12061302] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 05/04/2022] [Accepted: 05/20/2022] [Indexed: 12/10/2022] Open
Abstract
(1) Background: The comparative performance of various diagnostic methods for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection remains unclear. This study aimed to investigate the comparison of the 3 index test performances of rapid antigen diagnostic tests (RDTs), chest computed tomography (CT), and lung point-of-care-ultrasonography (US) with reverse transcription-polymerase chain reaction (RT-PCR), the reference standard, to provide more evidence-based data on the appropriate use of these index tests. (2) Methods: We retrieved data from electronic literature searches of PubMed, Cochrane Library, and EMBASE from 1 January 2020, to 1 April 2021. Diagnostic performance was examined using bivariate random-effects diagnostic test accuracy (DTA) and Bayesian network meta-analysis (NMA) models. (3) Results: Of the 3992 studies identified in our search, 118 including 69,445 participants met our selection criteria. Among these, 69 RDT, 38 CT, and 15 US studies in the pairwise meta-analysis were included for DTA with NMA. CT and US had high sensitivity of 0.852 (95% credible interval (CrI), 0.791-0.914) and 0.879 (95% CrI, 0.784-0.973), respectively. RDT had high specificity, 0.978 (95% CrI, 0.960-0.996). In accuracy assessment, RDT and CT had a relatively higher than US. However, there was no significant difference in accuracy between the 3 index tests. (4) Conclusions: This meta-analysis suggests that, compared with the reference standard RT-PCR, the 3 index tests (RDTs, chest CT, and lung US) had similar and complementary performances for diagnosis of SARS-CoV-2 infection. To manage and control COVID-19 effectively, future large-scale prospective studies could be used to obtain an optimal timely diagnostic process that identifies the condition of the patient accurately.
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Affiliation(s)
- Sung Ryul Shim
- Department of Health and Medical Informatics, Kyungnam University College of Health Sciences, Changwon 51767, Korea;
| | - Seong-Jang Kim
- Department of Nuclear Medicine, Pusan National University Yangsan Hospital, Yangsan 50615, Korea;
- Department of Nuclear Medicine, College of Medicine, Pusan National University, Yangsan 50615, Korea
- BioMedical Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan 50615, Korea
| | - Myunghee Hong
- Department of Biomedical Informatics, CHA University School of Medicine, CHA University, Seongnam 13488, Korea;
- Institute for Biomedical Informatics, School of Medicine, CHA University, Seongnam 13488, Korea
| | - Jonghoo Lee
- Department of Internal Medicine, Jeju National University Hospital, Jeju National University School of Medicine, Jeju 63241, Korea;
| | - Min-Gyu Kang
- Department of Internal Medicine, Chungbuk National University College of Medicine, Chungbuk National University Hospital, Cheongju 28644, Korea;
| | - Hyun Wook Han
- Department of Biomedical Informatics, CHA University School of Medicine, CHA University, Seongnam 13488, Korea;
- Institute for Biomedical Informatics, School of Medicine, CHA University, Seongnam 13488, Korea
- Institute of Basic Medical Sciences, School of Medicine, CHA University, Seongnam 13488, Korea
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13
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Ebrahimzadeh S, Islam N, Dawit H, Salameh JP, Kazi S, Fabiano N, Treanor L, Absi M, Ahmad F, Rooprai P, Al Khalil A, Harper K, Kamra N, Leeflang MM, Hooft L, van der Pol CB, Prager R, Hare SS, Dennie C, Spijker R, Deeks JJ, Dinnes J, Jenniskens K, Korevaar DA, Cohen JF, Van den Bruel A, Takwoingi Y, van de Wijgert J, Wang J, Pena E, Sabongui S, McInnes MD. Thoracic imaging tests for the diagnosis of COVID-19. Cochrane Database Syst Rev 2022; 5:CD013639. [PMID: 35575286 PMCID: PMC9109458 DOI: 10.1002/14651858.cd013639.pub5] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
BACKGROUND Our March 2021 edition of this review showed thoracic imaging computed tomography (CT) to be sensitive and moderately specific in diagnosing COVID-19 pneumonia. This new edition is an update of the review. OBJECTIVES Our objectives were to evaluate the diagnostic accuracy of thoracic imaging in people with suspected COVID-19; assess the rate of positive imaging in people who had an initial reverse transcriptase polymerase chain reaction (RT-PCR) negative result and a positive RT-PCR result on follow-up; and evaluate the accuracy of thoracic imaging for screening COVID-19 in asymptomatic individuals. The secondary objective was to assess threshold effects of index test positivity on accuracy. SEARCH METHODS We searched the COVID-19 Living Evidence Database from the University of Bern, the Cochrane COVID-19 Study Register, The Stephen B. Thacker CDC Library, and repositories of COVID-19 publications through to 17 February 2021. We did not apply any language restrictions. SELECTION CRITERIA We included diagnostic accuracy studies of all designs, except for case-control, that recruited participants of any age group suspected to have COVID-19. Studies had to assess chest CT, chest X-ray, or ultrasound of the lungs for the diagnosis of COVID-19, use a reference standard that included RT-PCR, and report estimates of test accuracy or provide data from which we could compute estimates. We excluded studies that used imaging as part of the reference standard and studies that excluded participants with normal index test results. DATA COLLECTION AND ANALYSIS The review authors independently and in duplicate screened articles, extracted data and assessed risk of bias and applicability concerns using QUADAS-2. We presented sensitivity and specificity per study on paired forest plots, and summarized pooled estimates in tables. We used a bivariate meta-analysis model where appropriate. MAIN RESULTS We included 98 studies in this review. Of these, 94 were included for evaluating the diagnostic accuracy of thoracic imaging in the evaluation of people with suspected COVID-19. Eight studies were included for assessing the rate of positive imaging in individuals with initial RT-PCR negative results and positive RT-PCR results on follow-up, and 10 studies were included for evaluating the accuracy of thoracic imaging for imagining asymptomatic individuals. For all 98 included studies, risk of bias was high or unclear in 52 (53%) studies with respect to participant selection, in 64 (65%) studies with respect to reference standard, in 46 (47%) studies with respect to index test, and in 48 (49%) studies with respect to flow and timing. Concerns about the applicability of the evidence to: participants were high or unclear in eight (8%) studies; index test were high or unclear in seven (7%) studies; and reference standard were high or unclear in seven (7%) studies. Imaging in people with suspected COVID-19 We included 94 studies. Eighty-seven studies evaluated one imaging modality, and seven studies evaluated two imaging modalities. All studies used RT-PCR alone or in combination with other criteria (for example, clinical signs and symptoms, positive contacts) as the reference standard for the diagnosis of COVID-19. For chest CT (69 studies, 28285 participants, 14,342 (51%) cases), sensitivities ranged from 45% to 100%, and specificities from 10% to 99%. The pooled sensitivity of chest CT was 86.9% (95% confidence interval (CI) 83.6 to 89.6), and pooled specificity was 78.3% (95% CI 73.7 to 82.3). Definition for index test positivity was a source of heterogeneity for sensitivity, but not specificity. Reference standard was not a source of heterogeneity. For chest X-ray (17 studies, 8529 participants, 5303 (62%) cases), the sensitivity ranged from 44% to 94% and specificity from 24 to 93%. The pooled sensitivity of chest X-ray was 73.1% (95% CI 64. to -80.5), and pooled specificity was 73.3% (95% CI 61.9 to 82.2). Definition for index test positivity was not found to be a source of heterogeneity. Definition for index test positivity and reference standard were not found to be sources of heterogeneity. For ultrasound of the lungs (15 studies, 2410 participants, 1158 (48%) cases), the sensitivity ranged from 73% to 94% and the specificity ranged from 21% to 98%. The pooled sensitivity of ultrasound was 88.9% (95% CI 84.9 to 92.0), and the pooled specificity was 72.2% (95% CI 58.8 to 82.5). Definition for index test positivity and reference standard were not found to be sources of heterogeneity. Indirect comparisons of modalities evaluated across all 94 studies indicated that chest CT and ultrasound gave higher sensitivity estimates than X-ray (P = 0.0003 and P = 0.001, respectively). Chest CT and ultrasound gave similar sensitivities (P=0.42). All modalities had similar specificities (CT versus X-ray P = 0.36; CT versus ultrasound P = 0.32; X-ray versus ultrasound P = 0.89). Imaging in PCR-negative people who subsequently became positive For rate of positive imaging in individuals with initial RT-PCR negative results, we included 8 studies (7 CT, 1 ultrasound) with a total of 198 participants suspected of having COVID-19, all of whom had a final diagnosis of COVID-19. Most studies (7/8) evaluated CT. Of 177 participants with initially negative RT-PCR who had positive RT-PCR results on follow-up testing, 75.8% (95% CI 45.3 to 92.2) had positive CT findings. Imaging in asymptomatic PCR-positive people For imaging asymptomatic individuals, we included 10 studies (7 CT, 1 X-ray, 2 ultrasound) with a total of 3548 asymptomatic participants, of whom 364 (10%) had a final diagnosis of COVID-19. For chest CT (7 studies, 3134 participants, 315 (10%) cases), the pooled sensitivity was 55.7% (95% CI 35.4 to 74.3) and the pooled specificity was 91.1% (95% CI 82.6 to 95.7). AUTHORS' CONCLUSIONS Chest CT and ultrasound of the lungs are sensitive and moderately specific in diagnosing COVID-19. Chest X-ray is moderately sensitive and moderately specific in diagnosing COVID-19. Thus, chest CT and ultrasound may have more utility for ruling out COVID-19 than for differentiating SARS-CoV-2 infection from other causes of respiratory illness. The uncertainty resulting from high or unclear risk of bias and the heterogeneity of included studies limit our ability to confidently draw conclusions based on our results.
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Affiliation(s)
- Sanam Ebrahimzadeh
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Nayaar Islam
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
- Department of Radiology, University of Ottawa, Ottawa, Canada
| | - Haben Dawit
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
- Department of Radiology, University of Ottawa, Ottawa, Canada
| | | | - Sakib Kazi
- Department of Radiology, University of Ottawa, Ottawa, Canada
| | | | - Lee Treanor
- Department of Radiology, University of Ottawa, Ottawa, Canada
| | - Marissa Absi
- Department of Radiology, University of Ottawa, Ottawa, Canada
| | - Faraz Ahmad
- Department of Radiology, University of Ottawa, Ottawa, Canada
| | - Paul Rooprai
- Department of Radiology, University of Ottawa, Ottawa, Canada
| | - Ahmed Al Khalil
- Department of Radiology, University of Ottawa, Ottawa, Canada
| | - Kelly Harper
- Department of Radiology, University of Ottawa, Ottawa, Canada
| | - Neil Kamra
- Department of Radiology, University of Ottawa, Ottawa, Canada
| | - Mariska Mg Leeflang
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Lotty Hooft
- Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht , Netherlands
| | | | - Ross Prager
- Department of Medicine, University of Ottawa, Ottawa, Canada
| | - Samanjit S Hare
- Department of Radiology, Royal Free London NHS Trust, London , UK
| | - Carole Dennie
- Department of Radiology, University of Ottawa, Ottawa, Canada
- Department of Medical Imaging, The Ottawa Hospital, Ottawa, Canada
| | - René Spijker
- Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht , Netherlands
- Medical Library, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health, Amsterdam, Netherlands
| | - Jonathan J Deeks
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
| | - Jacqueline Dinnes
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
| | - Kevin Jenniskens
- Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Daniël A Korevaar
- Department of Respiratory Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Jérémie F Cohen
- Obstetrical, Perinatal and Pediatric Epidemiology Research Team (EPOPé), Centre of Research in Epidemiology and Statistics (CRESS), UMR1153, Université de Paris, Paris, France
| | | | - Yemisi Takwoingi
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
| | - Janneke van de Wijgert
- Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
- Institute of Infection, Veterinary, and Ecological Sciences, University of Liverpool, Liverpool, UK
| | - Junfeng Wang
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
| | - Elena Pena
- Department of Radiology, University of Ottawa, Ottawa, Canada
- Department of Medical Imaging, The Ottawa Hospital, Ottawa, Canada
| | | | - Matthew Df McInnes
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
- Department of Radiology, University of Ottawa, Ottawa, Canada
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Jin KN, Do KH, Nam BD, Hwang SH, Choi M, Yong HS. [Korean Clinical Imaging Guidelines for Justification of Diagnostic Imaging Study for COVID-19]. TAEHAN YONGSANG UIHAKHOE CHI 2022; 83:265-283. [PMID: 36237918 PMCID: PMC9514447 DOI: 10.3348/jksr.2021.0117] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 09/10/2021] [Accepted: 09/17/2021] [Indexed: 06/16/2023]
Abstract
To develop Korean coronavirus disease (COVID-19) chest imaging justification guidelines, eight key questions were selected and the following recommendations were made with the evidence-based clinical imaging guideline adaptation methodology. It is appropriate not to use chest imaging tests (chest radiograph or CT) for the diagnosis of COVID-19 in asymptomatic patients. If reverse transcription-polymerase chain reaction testing is not available or if results are delayed or are initially negative in the presence of symptoms suggestive of COVID-19, chest imaging tests may be considered. In addition to clinical evaluations and laboratory tests, chest imaging may be contemplated to determine hospital admission for asymptomatic or mildly symptomatic unhospitalized patients with confirmed COVID-19. In hospitalized patients with confirmed COVID-19, chest imaging may be advised to determine or modify treatment alternatives. CT angiography may be considered if hemoptysis or pulmonary embolism is clinically suspected in a patient with confirmed COVID-19. For COVID-19 patients with improved symptoms, chest imaging is not recommended to make decisions regarding hospital discharge. For patients with functional impairment after recovery from COVID-19, chest imaging may be considered to distinguish a potentially treatable disease.
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Hassan MR, Ismail WN, Chowdhury A, Hossain S, Huda S, Hassan MM. A framework of genetic algorithm-based CNN on multi-access edge computing for automated detection of COVID-19. THE JOURNAL OF SUPERCOMPUTING 2022; 78:10250-10274. [PMID: 35079199 PMCID: PMC8776397 DOI: 10.1007/s11227-021-04222-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 11/17/2021] [Indexed: 05/05/2023]
Abstract
This paper designs and develops a computational intelligence-based framework using convolutional neural network (CNN) and genetic algorithm (GA) to detect COVID-19 cases. The framework utilizes a multi-access edge computing technology such that end-user can access available resources as well the CNN on the cloud. Early detection of COVID-19 can improve treatment and mitigate transmission. During peaks of infection, hospitals worldwide have suffered from heavy patient loads, bed shortages, inadequate testing kits and short-staffing problems. Due to the time-consuming nature of the standard RT-PCR test, the lack of expert radiologists, and evaluation issues relating to poor quality images, patients with severe conditions are sometimes unable to receive timely treatment. It is thus recommended to incorporate computational intelligence methodologies, which provides highly accurate detection in a matter of minutes, alongside traditional testing as an emergency measure. CNN has achieved extraordinary performance in numerous computational intelligence tasks. However, finding a systematic, automatic and optimal set of hyperparameters for building an efficient CNN for complex tasks remains challenging. Moreover, due to advancement of technology, data are collected at sparse location and hence accumulation of data from such a diverse sparse location poses a challenge. In this article, we propose a framework of computational intelligence-based algorithm that utilize the recent 5G mobile technology of multi-access edge computing along with a new CNN-model for automatic COVID-19 detection using raw chest X-ray images. This algorithm suggests that anyone having a 5G device (e.g., 5G mobile phone) should be able to use the CNN-based automatic COVID-19 detection tool. As part of the proposed automated model, the model introduces a novel CNN structure with the genetic algorithm (GA) for hyperparameter tuning. One such combination of GA and CNN is new in the application of COVID-19 detection/classification. The experimental results show that the developed framework could classify COVID-19 X-ray images with 98.48% accuracy which is higher than any of the performances achieved by other studies.
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Affiliation(s)
- Md Rafiul Hassan
- College of Arts and Sciences, University of Maine at Presque Isle, Presque Isle, ME04769 USA
| | - Walaa N. Ismail
- Faculty of Computers and Information, Minia University, Minia, 61519 Egypt
| | | | | | - Shamsul Huda
- School of Information Technology, Deakin University, Melbourne, Australia
| | - Mohammad Mehedi Hassan
- Department of Information Systems, College of Computer and Information Sciences, King Saud University, Riyadh, 11543 Saudi Arabia
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16
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Stański M, Gąsiorowski Ł, Wykrętowicz M, Majewska NK, Katulska K. COVID-19 pandemic in flu season. Chest computed tomography - what we know so far. Pol J Radiol 2021; 86:e692-e699. [PMID: 35059062 PMCID: PMC8757012 DOI: 10.5114/pjr.2021.112377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Accepted: 03/22/2021] [Indexed: 11/17/2022] Open
Abstract
Chest computed tomography (CT) is proven to have high sensitivity in COVID-19 diagnosis. It is available in most emergency wards, and in contrast to polymerase chain reaction (PCR) it can be obtained in several minutes. However, its imaging features change during the course of the disease and overlap with other viral pneumonias, including influenza pneumonia. In this brief analysis we review the recent literature about chest CT features, useful radiological scales, and COVID-19 differentiation with other viral infections.
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Affiliation(s)
- Marcin Stański
- Correspondence address: Marcin Stański, Department of General Radiology and Neuroradiology, Poznan University of Medical Sciences, Poznan, Poland, e-mail:
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Alhasan M, Hasaneen M. The Role and Challenges of Clinical Imaging During COVID-19 Outbreak. JOURNAL OF DIAGNOSTIC MEDICAL SONOGRAPHY 2021. [DOI: 10.1177/87564793211056903] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Objective: The Radiology department played a crucial role in detecting and following up with the COVID-19 disease during the pandemic. The purpose of this review was to highlight and discuss the role of each imaging modality, in the radiology department, that can help in the current pandemic and to determine the challenges faced by staff and how to overcome them. Materials and Methods: A literature search was performed using different databases, including PubMed, Google scholar, and the college electronic library to access 2020 published related articles. Results: A chest computed tomogram (CT) was found to be superior to a chest radiograph, with regards to the early detection of COVID-19. Utilizing lung point of care ultrasound (POCUS) with pediatric patients, demonstrated excellent sensitivity and specificity, compared to a chest radiography. In addition, lung ultrasound (LUS) showed a high correlation with the disease severity assessed with CT. However, magnetic resonance imaging (MRI) has some limiting factors with regard to its clinical utilization, due to signal loss. The reported challenges that the radiology department faced were mainly related to infection control, staff workload, and the training of students. Conclusion: The choice of an imaging modality to provide a COVID-19 diagnosis is debatable. It depends on several factors that should be carefully considered, such as disease stage, mobility of the patient, and ease of applying infection control procedures. The pros and cons of each imaging modality were highlighted, as part of this review. To control the spread of the infection, precautionary measures such as the use of portable radiographic equipment and the use of personal protective equipment (PPE) must be implemented.
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Affiliation(s)
- Mustafa Alhasan
- Department of Radiography and Medical Imaging, Fatima College of Health Sciences, Abu Dhabi, United Arab Emirates
- Radiologic Technology Program, Applied Medical Sciences College, Jordan University of Science and Technology, Irbid, Jordan
| | - Mohamed Hasaneen
- Department of Radiography and Medical Imaging, Fatima College of Health Sciences, Abu Dhabi, United Arab Emirates
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18
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Inui S, Gonoi W, Kurokawa R, Nakai Y, Watanabe Y, Sakurai K, Ishida M, Fujikawa A, Abe O. The role of chest imaging in the diagnosis, management, and monitoring of coronavirus disease 2019 (COVID-19). Insights Imaging 2021; 12:155. [PMID: 34727257 PMCID: PMC8561360 DOI: 10.1186/s13244-021-01096-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Accepted: 09/22/2021] [Indexed: 02/07/2023] Open
Abstract
Coronavirus disease 2019 (COVID-19) pandemic has posed a major public health crisis all over the world. The role of chest imaging, especially computed tomography (CT), has evolved during the pandemic paralleling the accumulation of scientific evidence. In the early stage of the pandemic, the performance of chest imaging for COVID-19 has widely been debated especially in the context of comparison to real-time reverse transcription polymerase chain reaction. Current evidence is against the use of chest imaging for routine screening of COVID-19 contrary to the initial expectations. It still has an integral role to play, however, in its work up and staging, especially when assessing complications or disease progression. Chest CT is gold standard imaging modality for COVID-19 pneumonia; in some situations, chest X-ray or ultrasound may be an effective alternative. The most important role of radiologists in this context is to be able to identify those patients at greatest risk of imminent clinical decompensation by learning to stratify cases of COVID-19 on the basis of radiologic imaging in the most efficient and timely fashion possible. The present availability of multiple and more refined CT grading systems and classification is now making this task easier and thereby contributing to the recent improvements achieved in COVID-19 treatment and outcomes. In this article, evidence of chest imaging regarding diagnosis, management and monitoring of COVID-19 will be chronologically reviewed.
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Affiliation(s)
- Shohei Inui
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
- Department of Radiology, Japan Self-Defense Forces Central Hospital, 1-2-24, Ikejiri, Setagaya-ku, Tokyo, 154-0001, Japan.
| | - Wataru Gonoi
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Ryo Kurokawa
- Division of Neuroradiology, Department of Radiology, University of Michigan, 1500 E Medical Center Dr, UH B2, Ann Arbor, MI, 48109, USA
| | - Yudai Nakai
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Yusuke Watanabe
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Keita Sakurai
- Department of Radiology, National Center for Geriatrics and Gerontology, 7-430, Morioka-cho, Obu, Aichi, 474-8511, Japan
| | - Masanori Ishida
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Akira Fujikawa
- Department of Radiology, Japan Self-Defense Forces Central Hospital, 1-2-24, Ikejiri, Setagaya-ku, Tokyo, 154-0001, Japan
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
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Lee JH, Hong H, Kim H, Lee CH, Goo JM, Yoon SH. CT Examinations for COVID-19: A Systematic Review of Protocols, Radiation Dose, and Numbers Needed to Diagnose and Predict. TAEHAN YONGSANG UIHAKHOE CHI 2021; 82:1505-1523. [PMID: 36238884 PMCID: PMC9431975 DOI: 10.3348/jksr.2021.0096] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 07/25/2021] [Accepted: 07/28/2021] [Indexed: 05/31/2023]
Abstract
Purpose Although chest CT has been discussed as a first-line test for coronavirus disease 2019 (COVID-19), little research has explored the implications of CT exposure in the population. To review chest CT protocols and radiation doses in COVID-19 publications and explore the number needed to diagnose (NND) and the number needed to predict (NNP) if CT is used as a first-line test. Materials and Methods We searched nine highly cited radiology journals to identify studies discussing the CT-based diagnosis of COVID-19 pneumonia. Study-level information on the CT protocol and radiation dose was collected, and the doses were compared with each national diagnostic reference level (DRL). The NND and NNP, which depends on the test positive rate (TPR), were calculated, given a CT sensitivity of 94% (95% confidence interval [CI]: 91%-96%) and specificity of 37% (95% CI: 26%-50%), and applied to the early outbreak in Wuhan, New York, and Italy. Results From 86 studies, the CT protocol and radiation dose were reported in 81 (94.2%) and 17 studies (19.8%), respectively. Low-dose chest CT was used more than twice as often as standard-dose chest CT (39.5% vs.18.6%), while the remaining studies (44.2%) did not provide relevant information. The radiation doses were lower than the national DRLs in 15 of the 17 studies (88.2%) that reported doses. The NND was 3.2 scans (95% CI: 2.2-6.0). The NNPs at TPRs of 50%, 25%, 10%, and 5% were 2.2, 3.6, 8.0, 15.5 scans, respectively. In Wuhan, 35418 (TPR, 58%; 95% CI: 27710-56755) to 44840 (TPR, 38%; 95% CI: 35161-68164) individuals were estimated to have undergone CT examinations to diagnose 17365 patients. During the early surge in New York and Italy, daily NNDs changed up to 5.4 and 10.9 times, respectively, within 10 weeks. Conclusion Low-dose CT protocols were described in less than half of COVID-19 publications, and radiation doses were frequently lacking. The number of populations involved in a first-line diagnostic CT test could vary dynamically according to daily TPR; therefore, caution is required in future planning.
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Kundu R, Singh PK, Mirjalili S, Sarkar R. COVID-19 detection from lung CT-Scans using a fuzzy integral-based CNN ensemble. Comput Biol Med 2021; 138:104895. [PMID: 34649147 PMCID: PMC8483997 DOI: 10.1016/j.compbiomed.2021.104895] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 09/19/2021] [Accepted: 09/22/2021] [Indexed: 12/16/2022]
Abstract
The COVID-19 pandemic has collapsed the public healthcare systems, along with severely damaging the economy of the world. The SARS-CoV-2 virus also known as the coronavirus, led to community spread, causing the death of more than a million people worldwide. The primary reason for the uncontrolled spread of the virus is the lack of provision for population-wise screening. The apparatus for RT-PCR based COVID-19 detection is scarce and the testing process takes 6-9 h. The test is also not satisfactorily sensitive (71% sensitive only). Hence, Computer-Aided Detection techniques based on deep learning methods can be used in such a scenario using other modalities like chest CT-scan images for more accurate and sensitive screening. In this paper, we propose a method that uses a Sugeno fuzzy integral ensemble of four pre-trained deep learning models, namely, VGG-11, GoogLeNet, SqueezeNet v1.1 and Wide ResNet-50-2, for classification of chest CT-scan images into COVID and Non-COVID categories. The proposed framework has been tested on a publicly available dataset for evaluation and it achieves 98.93% accuracy and 98.93% sensitivity on the same. The model outperforms state-of-the-art methods on the same dataset and proves to be a reliable COVID-19 detector. The relevant source codes for the proposed approach can be found at: https://github.com/Rohit-Kundu/Fuzzy-Integral-Covid-Detection.
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Affiliation(s)
- Rohit Kundu
- Department of Electrical Engineering, Jadavpur University, 188, Raja S. C. Mallick Road, Kolkata-700032, West Bengal, India
| | - Pawan Kumar Singh
- Department of Information Technology, Jadavpur University, Jadavpur University Second Campus, Plot No. 8, Salt Lake Bypass, LB Block, Sector III, Salt Lake City, Kolkata-700106, West Bengal, India
| | - Seyedali Mirjalili
- Centre for Artificial Intelligence Research and Optimization, Torrens University, Australia,Yonser Frontier Lab, Yonsei University, South Korea,Corresponding author. Centre for Artificial Intelligence Research and Optimization, Torrens University, Australia
| | - Ram Sarkar
- Department of Computer Science & Engineering, Jadavpur University, 188, Raja S. C. Mallick Road, Kolkata-700032, West Bengal, India
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21
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Liu J, Yang X, Zhu Y, Zhu Y, Liu J, Zeng X, Li H. Diagnostic value of chest computed tomography imaging for COVID-19 based on reverse transcription-polymerase chain reaction: a meta-analysis. Infect Dis Poverty 2021; 10:126. [PMID: 34674774 PMCID: PMC8529575 DOI: 10.1186/s40249-021-00910-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 10/08/2021] [Indexed: 11/11/2022] Open
Abstract
Background The computed tomography (CT) diagnostic value of COVID-19 is controversial. We summarized the value of chest CT in the diagnosis of COVID-19 through a meta-analysis based on the reference standard. Methods All Chinese and English studies related to the diagnostic value of CT for COVID-19 across multiple publication platforms, was searched for and collected. Studies quality evaluation and plotting the risk of bias were estimated. A heterogeneity test and meta-analysis, including plotting sensitivity (Sen), specificity (Spe) forest plots, pooled positive likelihood ratio (+LR), negative likelihood ratio (-LR), dignostic odds ratio (DOR) values and 95% confidence interval (CI), were estimated. If there was a threshold effect, summary receiver operating characteristic curves (SROC) was further plotted. Pooled area under the receiver operating characteristic curve (AUROC) and 95% CI were also calculated. Results Twenty diagnostic studies that represented a total of 9004 patients were included from 20 pieces of literatures after assessing all the aggregated studies. The reason for heterogeneity was caused by the threshold effect, so the AUROC = 0.91 (95% CI: 0.89–0.94) for chest CT of COVID-19. Pooled sensitivity, specificity, +LR, -LR from 20 studies were 0.91 (95% CI: 0.88–0.94), 0.71 (95% CI: 0.59–0.80), 3.1(95% CI: 2.2–4.4), 0.12 (95% CI: 0.09–0.17), separately. The I2 was 85.6% (P = 0.001) by Q-test. Conclusions The results of this study showed that CT diagnosis of COVID-19 was close to the reference standard. The diagnostic value of chest CT may be further enhanced if there is a unified COVID-19 diagnostic standard. However, please pay attention to rational use of CT. Graphic Abstract ![]()
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Affiliation(s)
- Jing Liu
- Department of Radiology, The Affiliated Infectious Diseases Hospital of Soochow University, The Fifth People's Hospital of Suzhou, Suzhou, 215000, Jiangsu, People's Republic of China
| | - Xue Yang
- Department of Radiology, Beijing Youan Hospital Capital Medical University, Beijing, 100069, People's Republic of China
| | - Yunxian Zhu
- Department of Radiology, The Affiliated Infectious Diseases Hospital of Soochow University, The Fifth People's Hospital of Suzhou, Suzhou, 215000, Jiangsu, People's Republic of China
| | - Yi Zhu
- Department of Radiology, The Affiliated Infectious Diseases Hospital of Soochow University, The Fifth People's Hospital of Suzhou, Suzhou, 215000, Jiangsu, People's Republic of China
| | - Jingzhe Liu
- Department of Radiology, The First Hospital of Tsinghua University, Beijing, 100016, People's Republic of China
| | - Xiantao Zeng
- Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, 430071, Hubei, People's Republic of China
| | - Hongjun Li
- Department of Radiology, Beijing Youan Hospital Capital Medical University, Beijing, 100069, People's Republic of China.
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22
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Wan Q, Chen M, Zhang Z, Yuan Y, Wang H, Hao Y, Nie W, Wu L, Chen S. Machine Learning of Serum Metabolic Patterns Encodes Asymptomatic SARS-CoV-2 Infection. Front Chem 2021; 9:746134. [PMID: 34660538 PMCID: PMC8517325 DOI: 10.3389/fchem.2021.746134] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 09/06/2021] [Indexed: 01/12/2023] Open
Abstract
Asymptomatic COVID-19 has become one of the biggest challenges for controlling the spread of the SARS-CoV-2. Diagnosis of asymptomatic COVID-19 mainly depends on quantitative reverse transcription PCR (qRT-PCR), which is typically time-consuming and requires expensive reagents. The application is limited in countries that lack sufficient resources to handle large-scale assay during the COVID-19 outbreak. Here, we demonstrated a new approach to detect the asymptomatic SARS-CoV-2 infection using serum metabolic patterns combined with ensemble learning. The direct patterns of metabolites and lipids were extracted by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) within 1 s with simple sample preparation. A new ensemble learning model was developed using stacking strategy with a new voting algorithm. This approach was validated in a large cohort of 274 samples (92 asymptomatic COVID-19 and 182 healthy control), and provided the high accuracy of 93.4%, with only 5% false negative and 7% false positive rates. We also identified a biomarker panel of ten metabolites and lipids, as well as the altered metabolic pathways during asymptomatic SARS-CoV-2 Infection. The proposed rapid and low-cost approach holds promise to apply in the large-scale asymptomatic COVID-19 screening.
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Affiliation(s)
- Qiongqiong Wan
- The Institute for Advanced Studies, Wuhan University, Wuhan, China
| | - Moran Chen
- The Institute for Advanced Studies, Wuhan University, Wuhan, China
| | - Zheng Zhang
- School of Life Sciences, Central China Normal University, Wuhan, China
| | - Yu Yuan
- Hubei Key Laboratory of Environmental Health (Incubating), Department of Occupational and Environmental Health, Huazhong University of Science and Technology, Wuhan, China
| | - Hao Wang
- Hubei Key Laboratory of Environmental Health (Incubating), Department of Occupational and Environmental Health, Huazhong University of Science and Technology, Wuhan, China
| | - Yanhong Hao
- The Institute for Advanced Studies, Wuhan University, Wuhan, China
| | - Wenjing Nie
- The Institute for Advanced Studies, Wuhan University, Wuhan, China
| | - Liang Wu
- The Institute for Advanced Studies, Wuhan University, Wuhan, China
| | - Suming Chen
- The Institute for Advanced Studies, Wuhan University, Wuhan, China
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23
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Koc AM, Altin L, Acar T, Ari A, Adibelli ZH. How did radiologists' diagnostic performance has changed in COVID-19 pneumonia: A single-centre retrospective study. Int J Clin Pract 2021; 75:e14693. [PMID: 34338397 PMCID: PMC8420402 DOI: 10.1111/ijcp.14693] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 02/23/2021] [Accepted: 07/27/2021] [Indexed: 12/20/2022] Open
Abstract
AIMS Delay and false positivity in PCR test results have necessitated accurate chest CT reporting for the management of patients with COVID-19-suspected symptoms. Pandemic related workload and level of experience on covid-dedicated chest CT scans might have affected the diagnostic performance of on-call radiologists. The aim of this study was to reveal the interpretation errors (IEs) in chest CT reports of COVID-19-suspected patients admitted to the Emergency Room (ER). METHODS Chest CT scans between March and June 2020 were re-evaluated and compared with the former reports and PCR test results. CT scan results were classified into four groups. Parenchymal involvement ratios, radiology departments' workload, COVID-19-related educational activities have been examined. RESULTS Out of 5721 Chest CT scans, 783 CTs belonging to 664 patients (340 female, 324 male) were included in this study. PCR test was positive in 398; negative in 385 cases. PCR positivity was found to be highest in "normal" and "typical for covid" groups whereas lowest in "atypical for covid" and "not covid" groups. 5%-25% parenchymal involvement ratio was found in 84.2% of the cases. Regarding the number of chest CT scans performed, radiologists' workload has found to be increased six-folds. With the re-evaluation, a total of 145 IEs (18.5%) have been found. IEs were mostly precipitated in the first two months (88.3%) and mostly in the "not covid" class (60%) regardless of PCR positivity. COVID-19 and radiology entitled educational activities along with the ER admission rates within the first two months of the pandemic have seemed to be related to the decline of IEs within time. CONCLUSION COVID-19 pandemic made a great impact on radiology departments with an inevitable burden of daily chest CT reporting. This workload and concomitant factors have effects on diagnostic challenges in COVID-19 pneumonia.
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Affiliation(s)
- Ali Murat Koc
- Department of RadiologyIzmir Bozyaka Education and Research HospitalUniversity of Health SciencesIzmirTurkey
| | - Levent Altin
- Department of RadiologyIzmir Bozyaka Education and Research HospitalUniversity of Health SciencesIzmirTurkey
| | - Turker Acar
- Department of RadiologyIzmir Bozyaka Education and Research HospitalUniversity of Health SciencesIzmirTurkey
| | - Alpay Ari
- Department of Infectious DiseasesIzmir Bozyaka Education and Research HospitalUniversity of Health SciencesIzmirTurkey
| | - Zehra Hilal Adibelli
- Department of RadiologyIzmir Bozyaka Education and Research HospitalUniversity of Health SciencesIzmirTurkey
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24
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Muljadi R, Yuniarti M, Tan R, Pratama TA, Prasetya IB, Widysanto A, Octavius GS. Descriptive Analysis of Chest Computed Tomography Scan in Coronavirus Disease 2019 Pneumonia: Correlation with Reverse Transcription-polymerase Chain Reaction and Clinical Features. Open Access Maced J Med Sci 2021; 9:865-871. [DOI: 10.3889/oamjms.2021.6224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND: Reverse transcriptase-polymerase chain reaction (RT-PCR) is the primary diagnostic tool to confirm coronavirus disease 2019 (COVID-2019) due to its high specificity. However, it has relatively low sensitivity and time consuming. In contrast, chest computed tomography (CT) has high sensitivity and achieves quick results. It may, therefore, play a critical role in screening and diagnosing COVID-19. A cross-sectional study was done in 212 patients with confirmed cases and patients under surveillance for COVID-19 tested for RT-PCR and chest CT scan. Statistical analysis was performed using SPSS Version 23 (Statistical Package for the Social Sciences, IBM Corp., Armonk, NY, USA).
AIM: We aim to investigate the diagnostic value of chest CT in correlation to RT-PCR in Indonesia.
METHODS: A cross-sectional study was done in 212 patients with confirmed cases and patients under surveillance for COVID-19 tested for RT-PCR and chest CT scan. Statistical analysis was performed using SPSS Version 23 (Statistical Package for the Social Sciences, IBM Corp., Armonk, NY, USA).
RESULTS: From a total of 212 patients, 92% of them were diagnosed as confirmed cases of COVID-19. It was found that the sensitivity of CT scan for COVID-19 patients was 72.3% (65.5% and 78.5%) with positive predictive value (PPV) of 93.9% (90.9% and 96.0%) and the sensitivity and PPV improve in symptomatic patients. Typical chest CT scan lesions were 8.0 times which were more likely (3.9–16.4; p <0.001) to be detected in symptomatic patients while patients with severe CT scan findings were 4.4 times more likely (3.0–6.5; p <0.001) to be admitted to the intensive care unit.
CONCLUSION: A high PPV suggests that a chest CT scan can detect COVID-19 lesions, but the absence of the lesions would not exclude the disease’s presence.
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Benmessaoud M, Housni A, Elmabrouki M, Essasnaoui F, Sadiki N, Dadouch A, Labzour A. DERIVATION OF LOCAL DIAGNOSTIC REFERENCE LEVELS FOR COMMON ADULT COMPUTED TOMOGRAPHY EXAMINATIONS IN MOROCCAN HOSPITAL. RADIATION PROTECTION DOSIMETRY 2021; 194:208-213. [PMID: 34240220 DOI: 10.1093/rpd/ncab095] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 05/11/2021] [Accepted: 06/04/2021] [Indexed: 06/13/2023]
Abstract
The purpose was to derive local diagnostic reference levels (LDRLs) for adults common computed tomography (CT) examinations in Moroccan hospital. The data of patients were collected retrospectively from one facility for 2 months period. The proposed LDRLs were defined as 75th percentile of spreads for CT dose index-volume (CTDIvol) and dose length product (DLP). Findings were compared with diagnostic reference levels (DRLs) of France, Australia and Egypt. A total of 259 cases were enrolled including 53% of male and 47% of female. The corresponding LDRLs in terms of CTDIvol (mGy) were 58, 15, 15 and 14 for head, chest, abdomen-pelvis and chest-abdomen-pelvis CT examinations, respectively. For DLP (mGy.cm) were 1298, 944, 1874 and 2026, respectively. The proposed LDRLs for CTDIvol were almost similar to DRLs of Australia, higher than those of France and lower than Egyptian DRLs. In terms of DLP, LDRLs were higher than compared studies with exception of head CT, which were lower and higher for CTDIvol than Egyptian DRLs. The results highlight higher radiation doses during adult CT scans, indicating the need to spread the same investigation regarding other imaging procedures including different radiological examinations across Moroccan hospitals.
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Affiliation(s)
- M Benmessaoud
- Faculty of Sciences Dhar EL Mahraz, Sidi Mohamed Ben Abdellah University, B.P.30000, Fez, Morocco
| | - A Housni
- Higher Institute of Nursing Professions and Health Techniques, B.P.30000, Fez, Morocco
| | - M Elmabrouki
- Higher Institute of Nursing Professions and Health Techniques, B.P.30000, Fez, Morocco
| | - F Essasnaoui
- Higher Institute of Nursing Professions and Health Techniques, B.P.30000, Fez, Morocco
| | - N Sadiki
- Higher Institute of Nursing Professions and Health Techniques, B.P.30000, Fez, Morocco
| | - A Dadouch
- Faculty of Sciences Dhar EL Mahraz, Sidi Mohamed Ben Abdellah University, B.P.30000, Fez, Morocco
| | - A Labzour
- Engineering Sciences Laboratory, Multidisciplinary Faculty, Sidi Mohamed Ben Abdellah University,B.P 1223, Taza, Morocco
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26
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Assaad S, Zrounba P, Cropet C, Blay JY. Mortality of patients with solid and haematological cancers presenting with symptoms of COVID-19 with vs without detectable SARS-COV-2: a French nationwide prospective cohort study. Br J Cancer 2021; 125:658-671. [PMID: 34135471 PMCID: PMC8206183 DOI: 10.1038/s41416-021-01452-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 04/26/2021] [Accepted: 05/27/2021] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Over 30 million COVID-19 cases have been diagnosed worldwide from late 2019. Among frail persons, cancer patients are at high risk of death from COVID-19. METHODS The French prospective cohort ONCOVID-19 enrolled patients with solid or haematological tumour, receiving anticancer treatment and presenting with clinical symptoms suggestive of COVID-19. COVID-19 was confirmed through detectable SARS-CoV2 by RT-PCR (repeated twice if negative first) and/or specific CT-scan. The study aims to assess the 28-day mortality rate after the first COVID test. RESULTS From March 1st to May 21st 2020, 23 French cancer centres and hospitals enrolled 1230 cancer patients with suspicion of COVID-19, including 1162 (94.5%) matching the inclusion criteria. We identified 425 (36.6%) COVID-19 positive patients including 155 (13.3%) diagnosed with CT-scan only, while 737 (63.4%) patients were COVID-19 negative. Death at day-28 occurred in 116/425 (27.8%) COVID-19 positive patients, and in 118/737 (16.3%) COVID-19 negative patients (p < 0·0001). With a median follow-up of 2.1 (1.6-2.4) months, 310 (26.7%) deaths were reported including 143 (33.6%) in the COVID-19 positive population, and 167 (22.7%) in the COVID-19 negative patients. Male gender, age, metastatic disease, immunosuppressive treatments, lymphopenia, COVID-19 diagnosis and diabetes were independent risk factors for death. CONCLUSION Patients with solid and haematological cancers presenting COVID-19 symptoms with SARS-CoV-2 RT-PCR confirmed or not are both at high-risk of early mortality. COVID-19 is reported as the cause of death in 50% of COVID-19 positive patients with cancer. CLINICAL TRIAL REGISTRATION This trial is registered with ClinicalTrials.gov, number NCT04363632.
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Affiliation(s)
- Souad Assaad
- Medical Oncology Department, Centre Léon Bérard, Lyon, France.
| | | | - Claire Cropet
- Department of Clinical Research and Innovation, Centre Léon Bérard, Lyon, France
| | - Jean-Yves Blay
- Medical Oncology Department, Centre Léon Bérard, Lyon, France.
- Université Claude Bernard, Lyon, France & Unicancer, Paris, France.
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27
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Yang S, Pan X, Yuan D, Zeng P, Jia P. Cross-disciplinary approaches to assist with nucleic acid testing for SARS-CoV-2. Appl Microbiol Biotechnol 2021; 105:6291-6299. [PMID: 34423408 PMCID: PMC8380513 DOI: 10.1007/s00253-021-11498-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 07/30/2021] [Accepted: 08/03/2021] [Indexed: 12/28/2022]
Abstract
Improving the capacity of detecting positive severe acute respiratory syndrome coronavirus 2 is critical for identifying the infection of coronavirus disease 2019 (COVID-19) precisely and thereby curbing the pandemic. Cross-disciplinary approaches may improve the efficiency of COVID-19 diagnosis by compensating to some extent the limitations encountered by traditional test methods during the COVID-19 pandemic. Combining computed tomography (CT), serum-specific antibody detection, and nanopore sequencing with nucleic acid testing for individual testing may improve the accuracy of identifying COVID-19 patients. At community or even regional/national levels, the combination of pooled screening and spatial epidemiological strategies may enable the detection of early transmission of epidemics in a cost-effective way, which is also less affected by restricted access to diagnostic tests and kit supplies. This would significantly advance our capacity of curbing epidemics as soon as possible, and better prepare us for entering a new era of high-impact and high-frequency epidemics.
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Affiliation(s)
- Shujuan Yang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- International Institute of Spatial Lifecourse Epidemiology (ISLE), Wuhan University, Wuhan, China
| | - Xiongfeng Pan
- International Institute of Spatial Lifecourse Epidemiology (ISLE), Wuhan University, Wuhan, China
- Xiangya School of Public Health, Central South University, Changsha, China
| | - Dan Yuan
- Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Peibin Zeng
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
| | - Peng Jia
- International Institute of Spatial Lifecourse Epidemiology (ISLE), Wuhan University, Wuhan, China.
- School of Resources and Environmental Science, Wuhan University, Wuhan, China.
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Monárrez-Espino J, Zubía-Nevárez CI, Reyes-Silva L, Castillo-Palencia JP, Castañeda-Delgado JE, Herrera van-Oostdam AS, López-Hernández Y. Clinical Factors Associated with COVID-19 Severity in Mexican Patients: Cross-Sectional Analysis from a Multicentric Hospital Study. Healthcare (Basel) 2021; 9:healthcare9070895. [PMID: 34356272 PMCID: PMC8307927 DOI: 10.3390/healthcare9070895] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 06/16/2021] [Accepted: 06/23/2021] [Indexed: 12/20/2022] Open
Abstract
(1) Background: Latin America has been harshly hit by SARS-CoV-2, but reporting from this region is still incomplete. This study aimed at identifying and comparing clinical characteristics of patients with COVID-19 at different stages of disease severity. (2) Methods: Cross-sectional multicentric study. Individuals with nasopharyngeal PCR were categorized into four groups: (1) negative, (2) positive, not hospitalized, (3) positive, hospitalized with/without supplementary oxygen, and (4) positive, intubated. Clinical and laboratory data were compared, using group 1 as the reference. Multivariate multinomial logistic regression was used to compare adjusted odds ratios. (3) Results: Nine variables remained in the model, explaining 76% of the variability. Men had increased odds, from 1.90 (95%CI 0.87–4.15) in the comparison of 2 vs. 1, to 3.66 (1.12–11.9) in 4 vs. 1. Diabetes and obesity were strong predictors. For diabetes, the odds for groups 2, 3, and 4 were 1.56 (0.29–8.16), 12.8 (2.50–65.8), and 16.1 (2.87–90.2); for obesity, these were 0.79 (0.31–2.05), 3.38 (1.04–10.9), and 4.10 (1.16–14.4), respectively. Fever, myalgia/arthralgia, cough, dyspnea, and neutrophilia were associated with the more severe COVID-19 group. Anosmia/dysgeusia were more likely to occur in group 2 (25.5; 2.51–259). (4) Conclusion: The results point to relevant differences in clinical and laboratory features of COVID-19 by level of severity that can be used in medical practice.
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Affiliation(s)
- Joel Monárrez-Espino
- Department of Health Research, Christus Muguerza del Parque Hospital, Chihuahua 31000, Mexico;
- Vice Presidency of Health Sciences, Medical Specialties Program, University of Monterrey, San Pedro Garza García 66238, Mexico;
- Correspondence: (J.M.-E.); (Y.L.-H.); Tel.: +52-614-4397-932 (J.M.-E.)
| | - Carolina Ivette Zubía-Nevárez
- Vice Presidency of Health Sciences, Medical Specialties Program, University of Monterrey, San Pedro Garza García 66238, Mexico;
| | - Lorena Reyes-Silva
- Department of Health Research, Christus Muguerza del Parque Hospital, Chihuahua 31000, Mexico;
| | - Juan Pablo Castillo-Palencia
- General Hospital of Soledad de Graciano Sánchez, San Luis Potosí Health Services, Soledad de Graciano Sánchez 78435, Mexico;
| | | | | | - Yamilé López-Hernández
- Metabolomics and Proteomics Laboratory, Mexican Council of Science and Technology, Zacatecas Autonomous University, Zacatecas 98000, Mexico
- Correspondence: (J.M.-E.); (Y.L.-H.); Tel.: +52-614-4397-932 (J.M.-E.)
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Chung SC, Marlow S, Tobias N, Alogna A, Alogna I, You SL, Khunti K, McKee M, Michie S, Pillay D. Lessons from countries implementing find, test, trace, isolation and support policies in the rapid response of the COVID-19 pandemic: a systematic review. BMJ Open 2021; 11:e047832. [PMID: 34187854 PMCID: PMC8251680 DOI: 10.1136/bmjopen-2020-047832] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
OBJECTIVE To systematically learn lessons from the experiences of countries implementing find, test, trace, isolate, support (FTTIS) in the first wave of the COVID-19 pandemic. DESIGN, DATA SOURCES AND ELIGIBILITY CRITERIA We searched MEDLINE (PubMed), Cochrane Library, SCOPUS and JSTOR, initially between 31 May 2019 and 21 January 2021. Research articles and reviews on the use of contact tracing, testing, self-isolation and quarantine for COVID-19 management were included in the review. DATA EXTRACTION AND SYNTHESIS We extracted information including study objective, design, methods, main findings and implications. These were tabulated and a narrative synthesis was undertaken given the diverse research designs, methods and implications. RESULTS We identified and included 118 eligible studies. We identified the core elements of an effective find, test, trace, isolate, support (FTTIS) system needed to interrupt the spread of a novel infectious disease, where treatment or vaccination was not yet available, as pertained in the initial stages of the COVID-19 pandemic. We report methods used to shorten case finding time, improve accuracy and efficiency of tests, coordinate stakeholders and actors involved in an FTTIS system, support individuals isolating and make appropriate use of digital tools. CONCLUSIONS We identified in our systematic review the key components of an FTTIS system. These include border controls, restricted entry, inbound traveller quarantine and comprehensive case finding; repeated testing to minimise false diagnoses and pooled testing in resource-limited circumstances; extended quarantine period and the use of digital tools for contact tracing and self-isolation. Support for mental or physical health and livelihoods is needed for individuals undergoing self-isolation/quarantine. An integrated system with rolling-wave planning can best use effective FTTIS tools to respond to the fast-changing COVID-19 pandemic. Results of the review may inform countries considering implementing these measures.
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Affiliation(s)
- Sheng-Chia Chung
- Institute of Health Informatics, University College London, London, UK
| | - Sushila Marlow
- Department of Chemical Engineering, University College London, London, UK
| | - Nicholas Tobias
- Bartlett School of Planning, University College London, London, UK
| | | | - Ivano Alogna
- British Institute of International and Comparative Law, London, UK
| | - San-Lin You
- Department of Medicine, College of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan
- Big Data Research Center, College of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan
| | - Kamlesh Khunti
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Martin McKee
- European Centre on Health of Societies in Transition, London School of Hygiene and Tropical Medicine, London, UK
| | - Susan Michie
- Centre for Behaviour Change, Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Deenan Pillay
- Division of Infection and Immunity, University College London, London, UK
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Torres A, Fors M, Rivero T, Pantoja K, Ballaz S. Comparison between RT-qPCR for SARS-CoV-2 and expanded triage in sputum of symptomatic and asymptomatic COVID-19 subjects in Ecuador. BMC Infect Dis 2021; 21:558. [PMID: 34118895 PMCID: PMC8195713 DOI: 10.1186/s12879-021-06272-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 05/06/2021] [Indexed: 11/26/2022] Open
Abstract
Background The quantitative reverse transcriptase-polymerase chain reaction (RT-qPCR) effectively detects the SARS-COV-2 virus. SARS-CoV-2 Nevertheless, some critical gaps remain in the identification and monitoring of asymptomatic people. Methods This retrospective study included 733 asymptomatic and symptomatic COVID-19 subjects, who were submitted to the RT-qPCR test. The objective was to assess the efficacy of an expanded triage of subjects undergoing the RT-qPCR test for SARS-COV-2 to identify the largest possible number of COVID-19 cases in a hospital setting in Ecuador. SARS-CoV-2 Firstly, the sensitivity and specificity as well as the predictive values of an expanded triage method were calculated. In addition, the Kappa coefficient was also determined to assess the concordance between laboratory test results and the expanded triage. Results Of a total of 733 sputum samples; 229 were RT-qPCR-positive (31.2%) and mortality rate reached 1.2%. Overall sensitivity and specificity were 86.0% (95% confidence interval: 81.0–90.0%) and 37.0% (95% confidence interval: 32.0–41.0%) respectively, with a diagnostic accuracy of 52.0% and a Kappa coefficient of 0.73. An association between the positivity of the test and its performance before 10 days was found. Conclusions The clinical sensitivity for COVID-19 detection was within acceptable standards, but the specificity still fell below the values of reference. The lack of symptoms did not always mean to have a negative SARS-COV-2 RT-qPCR test. The expanded triage identified a still unnoticed percentage of asymptomatic subjects showing positive results for the SARS-COV-2 RT-qPCR test. The study also revealed a significant relationship between the number of RT-qPCR-positive cases and the performance of the molecular diagnosis within the first 10 days of COVID-19 in the symptomatic group.
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Affiliation(s)
- Ariel Torres
- Medicina General Integral, Máster en Enfermedades Infecciosas, Hospital Gineco-obstétrico Nueva Aurora Luz Elena Arismendi, Quito, Ecuador
| | - Martha Fors
- Escuela de Medicina, Facultad de Ciencias de la Salud, Redondel del Ciclista, Antigua Via a Nayón, Universidad de las Américas, 170125, Quito, Ecuador.
| | - Tamaris Rivero
- Medicina General Integral, Hospital General Santo Domingo de los Tsáchilas, Santo Domingo, Ecuador
| | - Karina Pantoja
- Enfermería, Hospital General Santo Domingo de los Tsáchilas, Santo Domingo, Ecuador
| | - Santiago Ballaz
- Escuela de Ciencias Biológicas e Ingeniería, Universidad Yachay Tech, Hacienda San José s/n, San Miguel de Urcuquí, Ibarra, Ecuador.,Facultad de Ciencias Médicas Enrique Ortega Moreira, Universidad Espíritu Santo, Samborondón, Ecuador
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Pang C, Hou Q, Yang Z, Ren L. Chest computed tomography as a primary tool in COVID-19 detection: an update meta-analysis. Clin Transl Imaging 2021; 9:341-351. [PMID: 34055674 PMCID: PMC8149579 DOI: 10.1007/s40336-021-00434-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 05/19/2021] [Indexed: 02/07/2023]
Abstract
PURPOSE A growing number of publications have paid close attention to the chest computed tomography (CT) detection of COVID-19 with inconsistent diagnostic accuracy, the present meta-analysis assessed the available evidence regarding the overall performance of chest CT for COVID-19. METHODS 2 × 2 diagnostic table was extracted from each of the included studies. Data on specificity (SPE), sensitivity (SEN), negative likelihood ratio (LR-), positive likelihood ratio (LR+), and diagnostic odds ratio (DOR) were calculated purposefully. RESULTS Fifteen COVID-19 related publications met our inclusion criteria and were judged qualified for the meta-analysis. The following were summary estimates for diagnostic parameters of chest CT for COVID-19: SPE, 0.49 (95% CI 46-52%); SEN, 0.94 (95% CI 93-95%); LR-, 0.15 (95% CI 11-20%); LR+, 1.93 (95% CI 145-256%); DOR, 17.14 (95% CI 918-3199%); and the area under the receiver operating characteristic curve (AUC), 0.93. CONCLUSION Chest CT has high SEN, but the SPE is not ideal. It is highly recommended to use a combination of different diagnostic tools to achieve sufficient SEN and SPE. It should be taken into account as a diagnostic tool for current COVID-19 detection, especially for patients with symptoms. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s40336-021-00434-z.
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Affiliation(s)
- Caishuang Pang
- Chongqing Medical University, NO.1, Yi Xue Yuan Road, Yuzhong District, Chongqing, 400016 China
| | - Qingtao Hou
- Department of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016 China
| | - Zhaowei Yang
- Chongqing Medical University, NO.1, Yi Xue Yuan Road, Yuzhong District, Chongqing, 400016 China
| | - Liwei Ren
- Chongqing Medical University, NO.1, Yi Xue Yuan Road, Yuzhong District, Chongqing, 400016 China
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Diagnostic performance of Radiological Society of North America structured reporting language for chest computed tomography findings in patients with COVID-19. Jpn J Radiol 2021; 39:877-888. [PMID: 33956298 PMCID: PMC8101342 DOI: 10.1007/s11604-021-01128-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 04/28/2021] [Indexed: 01/19/2023]
Abstract
PURPOSE To evaluate the diagnostic performance of the RSNA structured reporting language for chest CT findings in patients with COVID-19. MATERIAL AND METHODS Patients with suspected COVID-19 who underwent chest CT and RT-PCR tests were enrolled consecutively in this retrospective study, regardless of symptoms. Imaging findings were categorized as "typical", "indeterminate", "atypical", or "negative" according to RSNA reporting language and compared to RT-PCR. "Single, round GGO" and "single, peripheral GGO," do not fit the reporting language, were also analyzed as "indeterminate" patterns. RESULTS Of the 1186 patients included in the analysis, the diagnosis of COVID-19 was confirmed in 388 patients. Of the 388 patients, CT findings were categorized as "typical" in 248, "indeterminate" in 77, and "negative" in 63. The sensitivity, specificity, and accuracy of "typical" findings were 63.9, 99.0, and 87.5% for COVID-19, respectively. In addition to the "typical" findings, the highest diagnostic accuracy of 92.2% was achieved when the "single, peripheral GGO" and "single, round GGO" were considered to be CT-positive. CONCLUSION The RSNA reporting language has significant diagnostic performance for identifying COVID-19 pneumonia. CT findings that do not exactly fit the RSNA reporting language, such as "single, round GGO" and "single, peripheral GGO" improve diagnostic performance.
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Karam M, Althuwaikh S, Alazemi M, Abul A, Hayre A, Alsaif A, Barlow G. Chest CT versus RT-PCR for the detection of COVID-19: systematic review and meta-analysis of comparative studies. JRSM Open 2021; 12:20542704211011837. [PMID: 34035931 PMCID: PMC8127597 DOI: 10.1177/20542704211011837] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
OBJECTIVES To compare the performance of chest computed tomography (CT) scan versus reverse transcription polymerase chain reaction (RT-PCR) as the reference standard in the initial diagnostic assessment of coronavirus disease 2019 (COVID-19) patients. DESIGN A systematic review and meta-analysis were performed as per the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. A search of electronic information was conducted using the following databases: MEDLINE, EMBASE, EMCARE, CINAHL and the Cochrane Central Register of Controlled Trials. SETTING Studies that compared the diagnostic performance within the same patient cohort of chest CT scan versus RT-PCR in COVID-19 suspected patients. PARTICIPANTS Thirteen non-randomised studies enrolling 4092 patients were identified. MAIN OUTCOME MEASURES Sensitivity, specificity and accuracy were primary outcome measures. Secondary outcomes included other test performance characteristics and discrepant findings between both investigations. RESULTS Chest CT had a median sensitivity, specificity and accuracy of 0.91 (range 0.82-0.98), 0.775 (0.25-1.00) and 0.87 (0.68-0.99), respectively, with RT-PCR as the reference. Importantly, early small, China-based studies tended to favour chest CT versus later larger, non-China studies. CONCLUSIONS A relatively high false positive rate can be expected with chest CT. It is possible it may still be useful to provide circumstantial evidence, however, in some patients with a suspicious clinical presentation of COVID-19 and negative initial Severe Acute Respiratory Syndrome Coronavirus 2 RT-PCR tests, but more evidence is required in this context. In acute cardiorespiratory presentations, negative CT scan and RT-PCR tests is likely to be reassuring.
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Affiliation(s)
| | | | - Mohammad Alazemi
- School of Medical Sciences, University of Manchester, Manchester, UK
| | - Ahmad Abul
- School of Medicine, University of Leeds, Leeds, UK
| | - Amrit Hayre
- School of Medicine, University of Leeds, Leeds, UK
| | | | - Gavin Barlow
- Experimental Medicine and Biomedicine, Hull York Medical School, University of York, York, UK
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Kumar H, Fernandez CJ, Kolpattil S, Munavvar M, Pappachan JM. Discrepancies in the clinical and radiological profiles of COVID-19: A case-based discussion and review of literature. World J Radiol 2021; 13:75-93. [PMID: 33968311 PMCID: PMC8069347 DOI: 10.4329/wjr.v13.i4.75] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 04/03/2021] [Accepted: 04/13/2021] [Indexed: 02/06/2023] Open
Abstract
The current gold standard for the diagnosis of coronavirus disease-19 (COVID-19) is a positive reverse transcriptase polymerase chain reaction (RT-PCR) test, on the background of clinical suspicion. However, RT-PCR has its limitations; this includes issues of low sensitivity, sampling errors and appropriate timing of specimen collection. As pulmonary involvement is the most common manifestation of severe COVID-19, early and appropriate lung imaging is important to aid diagnosis. However, gross discrepancies can occur between the clinical and imaging findings in patients with COVID-19, which can mislead clinicians in their decision making. Although chest X-ray (CXR) has a low sensitivity for the diagnosis of COVID-19 associated lung disease, especially in the earlier stages, a positive CXR increases the pre-test probability of COVID-19. CXR scoring systems have shown to be useful, such as the COVID-19 opacification rating score which helps to predict the need of tracheal intubation. Furthermore, artificial intelligence-based algorithms have also shown promise in differentiating COVID-19 pneumonia on CXR from other lung diseases. Although costlier than CXR, unenhanced computed tomographic (CT) chest scans have a higher sensitivity, but lesser specificity compared to RT-PCR for the diagnosis of COVID-19 pneumonia. A semi-quantitative CT scoring system has been shown to predict short-term mortality. The routine use of CT pulmonary angiography as a first-line imaging modality in patients with suspected COVID-19 is not justifiable due to the risk of contrast nephropathy. Scoring systems similar to those pioneered in CXR and CT can be used to effectively plan and manage hospital resources such as ventilators. Lung ultrasound is useful in the assessment of critically ill COVID-19 patients in the hands of an experienced operator. Moreover, it is a convenient tool to monitor disease progression, as it is cheap, non-invasive, easily accessible and easy to sterilise. Newer lung imaging modalities such as magnetic resonance imaging (MRI) for safe imaging among children, adolescents and pregnant women are rapidly evolving. Imaging modalities are also essential for evaluating the extra-pulmonary manifestations of COVID-19: these include cranial imaging with CT or MRI; cardiac imaging with ultrasonography (US), CT and MRI; and abdominal imaging with US or CT. This review critically analyses the utility of each imaging modality to empower clinicians to use them appropriately in the management of patients with COVID-19 infection.
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Affiliation(s)
- Hemant Kumar
- College of Medical and Dental Sciences, University of Birmingham, Birmingham B15 2TH, United Kingdom
| | | | - Sangeetha Kolpattil
- Department of Radiology, University Hospitals of Morecambe Bay NHS Trust, Lancaster LA1 4RP, United Kingdom
| | - Mohamed Munavvar
- Department of Pulmonology & Chest Diseases, Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT, United Kingdom
| | - Joseph M Pappachan
- Department of Medicine & Endocrinology, Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT, United Kingdom
- Faculty of Science, Manchester Metropolitan University, Manchester M15 6BH, United Kingdom
- Faculty of Biology, Medicine & Health, The University of Manchester, Manchester M13 9PL, United Kingdom
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Salem Salamh AB, Salamah AA, Akyüz HI. A Study of a New Technique of the CT Scan View and Disease Classification Protocol Based on Level Challenges in Cases of Coronavirus Disease. Radiol Res Pract 2021; 2021:5554408. [PMID: 33791127 PMCID: PMC7996048 DOI: 10.1155/2021/5554408] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 02/21/2021] [Accepted: 03/04/2021] [Indexed: 02/06/2023] Open
Abstract
The chest Computer Tomography (CT scan) is used in the diagnosis of coronavirus disease 2019 (COVID-19) and is an important complement to the Reverse Transcription Polymerase Chain Reaction (RT-PCR) test. The paper aims to improve the radiological diagnosis in the case of coronavirus disease COVID-19 pneumonia on forms of noninvasive approaches with conventional and high-resolution computer tomography (HRCT) scan images upon chest CT images of patients confirmed with mild to severe findings. The preliminary study is to compare the radiological findings of COVID-19 pneumonia in conventional chest CT images with images processed by a new tool and reviewed by expert radiologists. The researchers used a new filter called Golden Key Tool (GK-Tool) which has confirmed the improvement in the quality and diagnostic efficacy of images acquired using our modified images. Further, Convolution Neural Networks (CNNs) architecture called VGG face was used to classify chest CT images. The classification has been performed by using VGG face on various datasets which are considered as a protocol to diagnose COVID-19, Non-COVID-19 (other lung diseases), and normal cases (no findings on chest CT). Accordingly, the performance evaluation of the GK-Tool was fairly good as shown in the first set of results, where 80-95% of participants show a good to excellent assessment of the new images view in the case of COVID-19 patients. The results, in general, illustrate good recognition rates in the diagnosis and, therefore, would be significantly higher in normal cases with COVID-19. These results could reduce the radiologist's workload burden and play a major role in the decision-making process.
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Affiliation(s)
- Ahmed B. Salem Salamh
- Institute of Science, Material Science and Engineering, Kastamonu University, Kuzey Kent /P.O. Box, 37150, Kastamonu, Kastamonu, Turkey
| | | | - Halil Ibrahim Akyüz
- Computer and Teaching Technologies Education, Kastamonu University, Kuzey Kent /P.O. Box, 37150, Kastamonu, Kastamonu, Turkey
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Islam N, Ebrahimzadeh S, Salameh JP, Kazi S, Fabiano N, Treanor L, Absi M, Hallgrimson Z, Leeflang MM, Hooft L, van der Pol CB, Prager R, Hare SS, Dennie C, Spijker R, Deeks JJ, Dinnes J, Jenniskens K, Korevaar DA, Cohen JF, Van den Bruel A, Takwoingi Y, van de Wijgert J, Damen JA, Wang J, McInnes MD. Thoracic imaging tests for the diagnosis of COVID-19. Cochrane Database Syst Rev 2021; 3:CD013639. [PMID: 33724443 PMCID: PMC8078565 DOI: 10.1002/14651858.cd013639.pub4] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
BACKGROUND The respiratory illness caused by SARS-CoV-2 infection continues to present diagnostic challenges. Our 2020 edition of this review showed thoracic (chest) imaging to be sensitive and moderately specific in the diagnosis of coronavirus disease 2019 (COVID-19). In this update, we include new relevant studies, and have removed studies with case-control designs, and those not intended to be diagnostic test accuracy studies. OBJECTIVES To evaluate the diagnostic accuracy of thoracic imaging (computed tomography (CT), X-ray and ultrasound) in people with suspected COVID-19. SEARCH METHODS We searched the COVID-19 Living Evidence Database from the University of Bern, the Cochrane COVID-19 Study Register, The Stephen B. Thacker CDC Library, and repositories of COVID-19 publications through to 30 September 2020. We did not apply any language restrictions. SELECTION CRITERIA We included studies of all designs, except for case-control, that recruited participants of any age group suspected to have COVID-19 and that reported estimates of test accuracy or provided data from which we could compute estimates. DATA COLLECTION AND ANALYSIS The review authors independently and in duplicate screened articles, extracted data and assessed risk of bias and applicability concerns using the QUADAS-2 domain-list. We presented the results of estimated sensitivity and specificity using paired forest plots, and we summarised pooled estimates in tables. We used a bivariate meta-analysis model where appropriate. We presented the uncertainty of accuracy estimates using 95% confidence intervals (CIs). MAIN RESULTS We included 51 studies with 19,775 participants suspected of having COVID-19, of whom 10,155 (51%) had a final diagnosis of COVID-19. Forty-seven studies evaluated one imaging modality each, and four studies evaluated two imaging modalities each. All studies used RT-PCR as the reference standard for the diagnosis of COVID-19, with 47 studies using only RT-PCR and four studies using a combination of RT-PCR and other criteria (such as clinical signs, imaging tests, positive contacts, and follow-up phone calls) as the reference standard. Studies were conducted in Europe (33), Asia (13), North America (3) and South America (2); including only adults (26), all ages (21), children only (1), adults over 70 years (1), and unclear (2); in inpatients (2), outpatients (32), and setting unclear (17). Risk of bias was high or unclear in thirty-two (63%) studies with respect to participant selection, 40 (78%) studies with respect to reference standard, 30 (59%) studies with respect to index test, and 24 (47%) studies with respect to participant flow. For chest CT (41 studies, 16,133 participants, 8110 (50%) cases), the sensitivity ranged from 56.3% to 100%, and specificity ranged from 25.4% to 97.4%. The pooled sensitivity of chest CT was 87.9% (95% CI 84.6 to 90.6) and the pooled specificity was 80.0% (95% CI 74.9 to 84.3). There was no statistical evidence indicating that reference standard conduct and definition for index test positivity were sources of heterogeneity for CT studies. Nine chest CT studies (2807 participants, 1139 (41%) cases) used the COVID-19 Reporting and Data System (CO-RADS) scoring system, which has five thresholds to define index test positivity. At a CO-RADS threshold of 5 (7 studies), the sensitivity ranged from 41.5% to 77.9% and the pooled sensitivity was 67.0% (95% CI 56.4 to 76.2); the specificity ranged from 83.5% to 96.2%; and the pooled specificity was 91.3% (95% CI 87.6 to 94.0). At a CO-RADS threshold of 4 (7 studies), the sensitivity ranged from 56.3% to 92.9% and the pooled sensitivity was 83.5% (95% CI 74.4 to 89.7); the specificity ranged from 77.2% to 90.4% and the pooled specificity was 83.6% (95% CI 80.5 to 86.4). For chest X-ray (9 studies, 3694 participants, 2111 (57%) cases) the sensitivity ranged from 51.9% to 94.4% and specificity ranged from 40.4% to 88.9%. The pooled sensitivity of chest X-ray was 80.6% (95% CI 69.1 to 88.6) and the pooled specificity was 71.5% (95% CI 59.8 to 80.8). For ultrasound of the lungs (5 studies, 446 participants, 211 (47%) cases) the sensitivity ranged from 68.2% to 96.8% and specificity ranged from 21.3% to 78.9%. The pooled sensitivity of ultrasound was 86.4% (95% CI 72.7 to 93.9) and the pooled specificity was 54.6% (95% CI 35.3 to 72.6). Based on an indirect comparison using all included studies, chest CT had a higher specificity than ultrasound. For indirect comparisons of chest CT and chest X-ray, or chest X-ray and ultrasound, the data did not show differences in specificity or sensitivity. AUTHORS' CONCLUSIONS Our findings indicate that chest CT is sensitive and moderately specific for the diagnosis of COVID-19. Chest X-ray is moderately sensitive and moderately specific for the diagnosis of COVID-19. Ultrasound is sensitive but not specific for the diagnosis of COVID-19. Thus, chest CT and ultrasound may have more utility for excluding COVID-19 than for differentiating SARS-CoV-2 infection from other causes of respiratory illness. Future diagnostic accuracy studies should pre-define positive imaging findings, include direct comparisons of the various modalities of interest in the same participant population, and implement improved reporting practices.
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Affiliation(s)
- Nayaar Islam
- Department of Radiology , University of Ottawa, Ottawa, Canada
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | | | | | - Sakib Kazi
- Department of Radiology , University of Ottawa, Ottawa, Canada
| | | | - Lee Treanor
- Department of Radiology, University of Ottawa, Ottawa, Canada
| | - Marissa Absi
- Department of Radiology, University of Ottawa, Ottawa, Canada
| | | | - Mariska Mg Leeflang
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Lotty Hooft
- Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht , Netherlands
| | | | - Ross Prager
- Department of Medicine, University of Ottawa , Ottawa, Canada
| | - Samanjit S Hare
- Department of Radiology , Royal Free London NHS Trust, London , UK
| | - Carole Dennie
- Department of Radiology , University of Ottawa, Ottawa, Canada
- Department of Medical Imaging, The Ottawa Hospital, Ottawa, Canada
| | - René Spijker
- Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht , Netherlands
- Medical Library, Amsterdam UMC, University of Amsterdam, Amsterdam Public Health, Amsterdam, Netherlands
| | - Jonathan J Deeks
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Jacqueline Dinnes
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham , UK
| | - Kevin Jenniskens
- Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Daniël A Korevaar
- Department of Respiratory Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Jérémie F Cohen
- Obstetrical, Perinatal and Pediatric Epidemiology Research Team (EPOPé), Centre of Research in Epidemiology and Statistics (CRESS), UMR1153, Université de Paris, Paris, France
| | | | - Yemisi Takwoingi
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Janneke van de Wijgert
- Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
- Institute of Infection, Veterinary, and Ecological Sciences, University of Liverpool, Liverpool, UK
| | - Johanna Aag Damen
- Cochrane Netherlands, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Junfeng Wang
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
| | - Matthew Df McInnes
- Department of Radiology, University of Ottawa, Ottawa, Canada
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
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Schiaffino S, Albano D, Cozzi A, Messina C, Arioli R, Bnà C, Bruno A, Carbonaro LA, Carriero A, Carriero S, Danna PSC, D'Ascoli E, De Berardinis C, Della Pepa G, Falaschi Z, Gitto S, Malavazos AE, Mauri G, Monfardini L, Paschè A, Rizzati R, Secchi F, Vanzulli A, Tombini V, Vicentin I, Zagaria D, Sardanelli F, Sconfienza LM. CT-derived Chest Muscle Metrics for Outcome Prediction in Patients with COVID-19. Radiology 2021; 300:E328-E336. [PMID: 33724065 PMCID: PMC7971428 DOI: 10.1148/radiol.2021204141] [Citation(s) in RCA: 60] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Background Lower muscle mass is a known predictor of unfavorable outcomes, but its prognostic impact on patients with COVID-19 is unknown. Purpose To investigate the contribution of CT-derived muscle status in predicting clinical outcomes in patients with COVID-19. Materials and Methods Clinical or laboratory data and outcomes (intensive care unit [ICU] admission and death) were retrospectively retrieved for patients with reverse transcriptase polymerase chain reaction-confirmed SARS-CoV-2 infection, who underwent chest CT on admission in four hospitals in Northern Italy from February 21 to April 30, 2020. The extent and type of pulmonary involvement, mediastinal lymphadenopathy, and pleural effusion were assessed. Cross-sectional areas and attenuation by paravertebral muscles were measured on axial CT images at the T5 and T12 vertebral level. Multivariable linear and binary logistic regression, including calculation of odds ratios (ORs) with 95% CIs, were used to build four models to predict ICU admission and death, which were tested and compared by using receiver operating characteristic curve analysis. Results A total of 552 patients (364 men and 188 women; median age, 65 years [interquartile range, 54-75 years]) were included. In a CT-based model, lower-than-median T5 paravertebral muscle areas showed the highest ORs for ICU admission (OR, 4.8; 95% CI: 2.7, 8.5; P < .001) and death (OR, 2.3; 95% CI: 1.0, 2.9; P = .03). When clinical variables were included in the model, lower-than-median T5 paravertebral muscle areas still showed the highest ORs for both ICU admission (OR, 4.3; 95%: CI: 2.5, 7.7; P < .001) and death (OR, 2.3; 95% CI: 1.3, 3.7; P = .001). At receiver operating characteristic analysis, the CT-based model and the model including clinical variables showed the same area under the receiver operating characteristic curve (AUC) for ICU admission prediction (AUC, 0.83; P = .38) and were not different in terms of predicting death (AUC, 0.86 vs AUC, 0.87, respectively; P = .28). Conclusion In hospitalized patients with COVID-19, lower muscle mass on CT images was independently associated with intensive care unit admission and in-hospital mortality. © RSNA, 2021 Online supplemental material is available for this article.
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Affiliation(s)
- Simone Schiaffino
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Domenico Albano
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Andrea Cozzi
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Carmelo Messina
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Roberto Arioli
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Claudio Bnà
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Antonio Bruno
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Luca A Carbonaro
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Alessandro Carriero
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Serena Carriero
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Pietro S C Danna
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Elisa D'Ascoli
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Claudia De Berardinis
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Gianmarco Della Pepa
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Zeno Falaschi
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Salvatore Gitto
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Alexis E Malavazos
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Giovanni Mauri
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Lorenzo Monfardini
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Alessio Paschè
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Roberto Rizzati
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Francesco Secchi
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Angelo Vanzulli
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Valeria Tombini
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Ilaria Vicentin
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Domenico Zagaria
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Francesco Sardanelli
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
| | - Luca M Sconfienza
- From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.)
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Brogna B, Bignardi E, Brogna C, Volpe M, Lombardi G, Rosa A, Gagliardi G, Capasso PFM, Gravino E, Maio F, Pane F, Picariello V, Buono M, Colucci L, Musto LA. A Pictorial Review of the Role of Imaging in the Detection, Management, Histopathological Correlations, and Complications of COVID-19 Pneumonia. Diagnostics (Basel) 2021; 11:437. [PMID: 33806423 PMCID: PMC8000129 DOI: 10.3390/diagnostics11030437] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2020] [Revised: 02/22/2021] [Accepted: 02/27/2021] [Indexed: 02/07/2023] Open
Abstract
Imaging plays an important role in the detection of coronavirus (COVID-19) pneumonia in both managing the disease and evaluating the complications. Imaging with chest computed tomography (CT) can also have a potential predictive and prognostic role in COVID-19 patient outcomes. The aim of this pictorial review is to describe the role of imaging with chest X-ray (CXR), lung ultrasound (LUS), and CT in the diagnosis and management of COVID-19 pneumonia, the current indications, the scores proposed for each modality, the advantages/limitations of each modality and their role in detecting complications, and the histopathological correlations.
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Affiliation(s)
- Barbara Brogna
- Department of Radiology, San Giuseppe Moscati Hospital, Contrada Amoretta, 83100 Avellino, Italy; (M.V.); (G.L.); (A.R.); (G.G.); (P.F.M.C.); (E.G.); (F.M.); (F.P.); (V.P.); (M.B.); (L.C.); (L.A.M.)
| | - Elio Bignardi
- Radiology Unit, Cotugno Hospital, Naples, Via Quagliariello 54, 80131 Naples, Italy;
| | - Claudia Brogna
- Neuropsychiatric Unit ASL Avellino, Via Degli Imbimbo 10/12, 83100 Avellino, Italy;
| | - Mena Volpe
- Department of Radiology, San Giuseppe Moscati Hospital, Contrada Amoretta, 83100 Avellino, Italy; (M.V.); (G.L.); (A.R.); (G.G.); (P.F.M.C.); (E.G.); (F.M.); (F.P.); (V.P.); (M.B.); (L.C.); (L.A.M.)
| | - Giulio Lombardi
- Department of Radiology, San Giuseppe Moscati Hospital, Contrada Amoretta, 83100 Avellino, Italy; (M.V.); (G.L.); (A.R.); (G.G.); (P.F.M.C.); (E.G.); (F.M.); (F.P.); (V.P.); (M.B.); (L.C.); (L.A.M.)
| | - Alessandro Rosa
- Department of Radiology, San Giuseppe Moscati Hospital, Contrada Amoretta, 83100 Avellino, Italy; (M.V.); (G.L.); (A.R.); (G.G.); (P.F.M.C.); (E.G.); (F.M.); (F.P.); (V.P.); (M.B.); (L.C.); (L.A.M.)
| | - Giuliano Gagliardi
- Department of Radiology, San Giuseppe Moscati Hospital, Contrada Amoretta, 83100 Avellino, Italy; (M.V.); (G.L.); (A.R.); (G.G.); (P.F.M.C.); (E.G.); (F.M.); (F.P.); (V.P.); (M.B.); (L.C.); (L.A.M.)
| | - Pietro Fabio Maurizio Capasso
- Department of Radiology, San Giuseppe Moscati Hospital, Contrada Amoretta, 83100 Avellino, Italy; (M.V.); (G.L.); (A.R.); (G.G.); (P.F.M.C.); (E.G.); (F.M.); (F.P.); (V.P.); (M.B.); (L.C.); (L.A.M.)
| | - Enzo Gravino
- Department of Radiology, San Giuseppe Moscati Hospital, Contrada Amoretta, 83100 Avellino, Italy; (M.V.); (G.L.); (A.R.); (G.G.); (P.F.M.C.); (E.G.); (F.M.); (F.P.); (V.P.); (M.B.); (L.C.); (L.A.M.)
| | - Francesca Maio
- Department of Radiology, San Giuseppe Moscati Hospital, Contrada Amoretta, 83100 Avellino, Italy; (M.V.); (G.L.); (A.R.); (G.G.); (P.F.M.C.); (E.G.); (F.M.); (F.P.); (V.P.); (M.B.); (L.C.); (L.A.M.)
| | - Francesco Pane
- Department of Radiology, San Giuseppe Moscati Hospital, Contrada Amoretta, 83100 Avellino, Italy; (M.V.); (G.L.); (A.R.); (G.G.); (P.F.M.C.); (E.G.); (F.M.); (F.P.); (V.P.); (M.B.); (L.C.); (L.A.M.)
| | - Valentina Picariello
- Department of Radiology, San Giuseppe Moscati Hospital, Contrada Amoretta, 83100 Avellino, Italy; (M.V.); (G.L.); (A.R.); (G.G.); (P.F.M.C.); (E.G.); (F.M.); (F.P.); (V.P.); (M.B.); (L.C.); (L.A.M.)
| | - Marcella Buono
- Department of Radiology, San Giuseppe Moscati Hospital, Contrada Amoretta, 83100 Avellino, Italy; (M.V.); (G.L.); (A.R.); (G.G.); (P.F.M.C.); (E.G.); (F.M.); (F.P.); (V.P.); (M.B.); (L.C.); (L.A.M.)
| | - Lorenzo Colucci
- Department of Radiology, San Giuseppe Moscati Hospital, Contrada Amoretta, 83100 Avellino, Italy; (M.V.); (G.L.); (A.R.); (G.G.); (P.F.M.C.); (E.G.); (F.M.); (F.P.); (V.P.); (M.B.); (L.C.); (L.A.M.)
| | - Lanfranco Aquilino Musto
- Department of Radiology, San Giuseppe Moscati Hospital, Contrada Amoretta, 83100 Avellino, Italy; (M.V.); (G.L.); (A.R.); (G.G.); (P.F.M.C.); (E.G.); (F.M.); (F.P.); (V.P.); (M.B.); (L.C.); (L.A.M.)
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Patrucco F, Carriero A, Falaschi Z, Paschè A, Gavelli F, Airoldi C, Bellan M, Sainaghi PP, Solidoro P, Balbo PE. COVID-19 Diagnosis in Case of Two Negative Nasopharyngeal Swabs: Association between Chest CT and Bronchoalveolar Lavage Results. Radiology 2021; 298:E152-E155. [PMID: 33399508 PMCID: PMC7903987 DOI: 10.1148/radiol.2020203776] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 10/07/2020] [Accepted: 11/18/2020] [Indexed: 01/31/2023]
Abstract
See also the editorial by Little in this issue.
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Affiliation(s)
- Filippo Patrucco
- From the Medical Department, Respiratory Diseases Unit (F.P., P.E.B.), Department of Diagnosis and Treatment Services, Radiodiagnostics (A.C., Z.F., A.P.), Emergency Medicine Department (F.G.), and Medical Department, Internal Medicine Unit (M.B., P.P.S.), Azienda Ospedaliero Universitaria Maggiore della Carità di Novara, C.so Mazzini 18, 28100 Novara, Italy; Translational Medicine Department, University of Piemonte Orientale Amedeo Avogadro, Novara, Italy (F.P., F.G., C.A., M.B.); and Medical Sciences Department, University of Torino, Turin, Italy (P.S.)
| | - Alessandro Carriero
- From the Medical Department, Respiratory Diseases Unit (F.P., P.E.B.), Department of Diagnosis and Treatment Services, Radiodiagnostics (A.C., Z.F., A.P.), Emergency Medicine Department (F.G.), and Medical Department, Internal Medicine Unit (M.B., P.P.S.), Azienda Ospedaliero Universitaria Maggiore della Carità di Novara, C.so Mazzini 18, 28100 Novara, Italy; Translational Medicine Department, University of Piemonte Orientale Amedeo Avogadro, Novara, Italy (F.P., F.G., C.A., M.B.); and Medical Sciences Department, University of Torino, Turin, Italy (P.S.)
| | - Zeno Falaschi
- From the Medical Department, Respiratory Diseases Unit (F.P., P.E.B.), Department of Diagnosis and Treatment Services, Radiodiagnostics (A.C., Z.F., A.P.), Emergency Medicine Department (F.G.), and Medical Department, Internal Medicine Unit (M.B., P.P.S.), Azienda Ospedaliero Universitaria Maggiore della Carità di Novara, C.so Mazzini 18, 28100 Novara, Italy; Translational Medicine Department, University of Piemonte Orientale Amedeo Avogadro, Novara, Italy (F.P., F.G., C.A., M.B.); and Medical Sciences Department, University of Torino, Turin, Italy (P.S.)
| | - Alessio Paschè
- From the Medical Department, Respiratory Diseases Unit (F.P., P.E.B.), Department of Diagnosis and Treatment Services, Radiodiagnostics (A.C., Z.F., A.P.), Emergency Medicine Department (F.G.), and Medical Department, Internal Medicine Unit (M.B., P.P.S.), Azienda Ospedaliero Universitaria Maggiore della Carità di Novara, C.so Mazzini 18, 28100 Novara, Italy; Translational Medicine Department, University of Piemonte Orientale Amedeo Avogadro, Novara, Italy (F.P., F.G., C.A., M.B.); and Medical Sciences Department, University of Torino, Turin, Italy (P.S.)
| | - Francesco Gavelli
- From the Medical Department, Respiratory Diseases Unit (F.P., P.E.B.), Department of Diagnosis and Treatment Services, Radiodiagnostics (A.C., Z.F., A.P.), Emergency Medicine Department (F.G.), and Medical Department, Internal Medicine Unit (M.B., P.P.S.), Azienda Ospedaliero Universitaria Maggiore della Carità di Novara, C.so Mazzini 18, 28100 Novara, Italy; Translational Medicine Department, University of Piemonte Orientale Amedeo Avogadro, Novara, Italy (F.P., F.G., C.A., M.B.); and Medical Sciences Department, University of Torino, Turin, Italy (P.S.)
| | - Chiara Airoldi
- From the Medical Department, Respiratory Diseases Unit (F.P., P.E.B.), Department of Diagnosis and Treatment Services, Radiodiagnostics (A.C., Z.F., A.P.), Emergency Medicine Department (F.G.), and Medical Department, Internal Medicine Unit (M.B., P.P.S.), Azienda Ospedaliero Universitaria Maggiore della Carità di Novara, C.so Mazzini 18, 28100 Novara, Italy; Translational Medicine Department, University of Piemonte Orientale Amedeo Avogadro, Novara, Italy (F.P., F.G., C.A., M.B.); and Medical Sciences Department, University of Torino, Turin, Italy (P.S.)
| | - Mattia Bellan
- From the Medical Department, Respiratory Diseases Unit (F.P., P.E.B.), Department of Diagnosis and Treatment Services, Radiodiagnostics (A.C., Z.F., A.P.), Emergency Medicine Department (F.G.), and Medical Department, Internal Medicine Unit (M.B., P.P.S.), Azienda Ospedaliero Universitaria Maggiore della Carità di Novara, C.so Mazzini 18, 28100 Novara, Italy; Translational Medicine Department, University of Piemonte Orientale Amedeo Avogadro, Novara, Italy (F.P., F.G., C.A., M.B.); and Medical Sciences Department, University of Torino, Turin, Italy (P.S.)
| | - Pier Paolo Sainaghi
- From the Medical Department, Respiratory Diseases Unit (F.P., P.E.B.), Department of Diagnosis and Treatment Services, Radiodiagnostics (A.C., Z.F., A.P.), Emergency Medicine Department (F.G.), and Medical Department, Internal Medicine Unit (M.B., P.P.S.), Azienda Ospedaliero Universitaria Maggiore della Carità di Novara, C.so Mazzini 18, 28100 Novara, Italy; Translational Medicine Department, University of Piemonte Orientale Amedeo Avogadro, Novara, Italy (F.P., F.G., C.A., M.B.); and Medical Sciences Department, University of Torino, Turin, Italy (P.S.)
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Kwee RM, Adams HJA, Kwee TC. Diagnostic Performance of CO-RADS and the RSNA Classification System in Evaluating COVID-19 at Chest CT: A Meta-Analysis. Radiol Cardiothorac Imaging 2021; 3:e200510. [PMID: 33778660 PMCID: PMC7808356 DOI: 10.1148/ryct.2021200510] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
PURPOSE To determine the diagnostic performance of the COVID-19 Reporting and Data System (CO-RADS) and the Radiological Society of North America (RSNA) categorizations in patients with clinically suspected coronavirus disease 2019 (COVID-19) infection. MATERIALS AND METHODS In this meta-analysis, studies from 2020, up to August 24, 2020 were assessed for inclusion criteria of studies that used CO-RADS or the RSNA categories for scoring chest CT in patients with suspected COVID-19. A total of 186 studies were identified. After review of abstracts and text, a total of nine studies were included in this study. Patient information (n¸ age, sex), CO-RADS and RSNA scoring categories, and other study characteristics were extracted. Study quality was assessed with the QUADAS-2 tool. Meta-analysis was performed with a random effects model. RESULTS Nine studies (3283 patients) were included. Overall study quality was good, except for risk of non-performance of repeated reverse transcriptase polymerase chain reaction (RT-PCR) after negative initial RT-PCR and persistent clinical suspicion in four studies. Pooled COVID-19 frequencies in CO-RADS categories were: 1, 8.8%; 2, 11.1%; 3, 24.6%; 4, 61.9%; and 5, 89.6%. Pooled COVID-19 frequencies in RSNA classification categories were: negative 14.4%; atypical, 5.7%; indeterminate, 44.9%; and typical, 92.5%. Pooled pairs of sensitivity and specificity using CO-RADS thresholds were the following: at least 3, 92.5% (95% CI: 87.1, 95.7) and 69.2% (95%: CI: 60.8, 76.4); at least 4, 85.8% (95% CI: 78.7, 90.9) and 84.6% (95% CI: 79.5, 88.5); and 5, 70.4% (95% CI: 60.2, 78.9) and 93.1% (95% CI: 87.7, 96.2). Pooled pairs of sensitivity and specificity using RSNA classification thresholds for indeterminate were 90.2% (95% CI: 87.5, 92.3) and 75.1% (95% CI: 68.9, 80.4) and for typical were 65.2% (95% CI: 37.0, 85.7) and 94.9% (95% CI: 86.4, 98.2). CONCLUSION COVID-19 infection frequency was higher in patients categorized with higher CORADS and RSNA classification categories.
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Affiliation(s)
- Robert M. Kwee
- From the Department of Radiology, Zuyderland Medical Center, Heerlen/Sittard/Geleen, The Netherlands (R.M.K.); Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands. (H.J.A.A.); Department of Radiology, Nuclear Medicine and Molecular Imaging University Medical Center Groningen, University of Groningen, Groningen, The Netherlands (T.C.K.)
| | - Hugo J. A. Adams
- From the Department of Radiology, Zuyderland Medical Center, Heerlen/Sittard/Geleen, The Netherlands (R.M.K.); Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands. (H.J.A.A.); Department of Radiology, Nuclear Medicine and Molecular Imaging University Medical Center Groningen, University of Groningen, Groningen, The Netherlands (T.C.K.)
| | - Thomas C. Kwee
- From the Department of Radiology, Zuyderland Medical Center, Heerlen/Sittard/Geleen, The Netherlands (R.M.K.); Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands. (H.J.A.A.); Department of Radiology, Nuclear Medicine and Molecular Imaging University Medical Center Groningen, University of Groningen, Groningen, The Netherlands (T.C.K.)
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Al-Umairi RS, Al-Kalbani J, Al-Tai S, Al-Abri A, Al-Kindi F, Kamona A. COVID-19 Associated Pneumonia: A review of chest radiograph and computed tomography findings. Sultan Qaboos Univ Med J 2021; 21:e4-e11. [PMID: 33777418 PMCID: PMC7968910 DOI: 10.18295/squmj.2021.21.01.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 09/12/2020] [Accepted: 10/17/2020] [Indexed: 01/08/2023] Open
Abstract
Medical imaging, including chest radiography and computed tomography, plays a major role in the diagnosis and follow-up of patients with COVID-19 associated pneumonia. This review aims to summarise current information on this topic based on the existing literature. A search of the Google Scholar (Google LLC, Mountain View, California, USA) and MEDLINE® (National Library of Medicine, Bethesda, Maryland, USA) databases was conducted for articles published until April 2020. A total of 30 articles involving 4,002 patients were identified. The most frequently reported imaging findings were bilateral ground glass and consolidative pulmonary opacities with a predominant lower lobe and peripheral subpleural distribution.
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Affiliation(s)
| | | | - Saqar Al-Tai
- Department of Radiology, Royal Hospital, Muscat, Oman
| | - Ahmed Al-Abri
- Department of Radiology, Royal Hospital, Muscat, Oman
| | | | - Atheel Kamona
- Department of Radiology, Royal Hospital, Muscat, Oman
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Nair AV, Kumar D, Yadav SK, Nepal P, Jacob B, Al-Heidous M. Utility of visual coronary artery calcification on non-cardiac gated thoracic CT in predicting clinical severity and outcome in COVID-19. Clin Imaging 2021; 74:123-130. [PMID: 33485116 PMCID: PMC7834505 DOI: 10.1016/j.clinimag.2021.01.015] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 12/28/2020] [Accepted: 01/15/2021] [Indexed: 12/12/2022]
Abstract
Background Assessment of visual-coronary artery calcification on non-cardiac gated CT in COVID-19 patients could provide an objective approach to rapidly identify and triage clinically severe patients for early hospital admission to avert worse prognosis. Purpose To ascertain the role of semi-quantitative scoring in visual-coronary artery calcification score (V-CACS) for predicting the clinical severity and outcome in patients with COVID-19. Materials and methods With institutional review board approval this study included 67 COVID-19 confirmed patients who underwent non-cardiac gated CT chest in an inpatient setting. Two blinded radiologist (Radiologist-1 &2) assessed the V-CACS, CT Chest severity score (CT-SS). The clinical data including the requirement for oxygen support, assisted ventilation, ICU admission and outcome was assessed, and patients were clinically subdivided depending on clinical severity. Logistic regression analyses were performed to identify independent predictors. ROC curves analysis is performed for the assessment of performance and Pearson correlation were performed to looks for the associations. Results V-CACS cut off value of 3 (82.67% sensitivity and 54.55% specificity; AUC 0.75) and CT-SS with a cut off value of 21.5 (95.7% sensitivity and 63.6% specificity; AUC 0.87) are independent predictors for clinical severity and also the need for ICU admission or assisted ventilation. The pooling of both CT-SS and V-CACS (82.67% sensitivity and 86.4% specificity; AUC 0.92) are more reliable in terms of predicting the primary outcome of COVID-19 patients. On regression analysis, V-CACS and CT-SS are individual independent predictors of clinical severity in COVID-19 (Odds ratio, 1.72; 95% CI, 0.99–2.98; p = 0.05 and Odds ratio, 1.22; 95% CI, 1.08–1.39; p = 0.001 respectively). The area under the curve (AUC) for pooled V-CACS and CT-SS was 0.96 (95% CI 0.84–0.98) which correctly predicted 82.1% cases. Conclusion Logistic regression model using pooled Visual-Coronary artery calcification score and CT Chest severity score in non-cardiac gated CT can predict clinical severity and outcome in patients with COVID-19.
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Affiliation(s)
| | | | | | - Pankaj Nepal
- Frank H Netter School Of Medicine, Quinnipac University, CT, USA.
| | - Bamil Jacob
- Al Wakra Hospital, Hamad Medical Corporation, Qatar.
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Mirtajaddini M, Naderi N, Houshmand G, Taghavi S, Amin A. Challenge of coronavirus disease 2019-related myocarditis diagnosis in patients with negative real-time polymerase chain reaction test: A case series. Res Cardiovasc Med 2021. [DOI: 10.4103/rcm.rcm_5_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
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Yates A, Dempsey PJ, Vencken S, MacMahon PJ, Hutchinson BD. Structured reporting in portable chest radiographs: An essential tool in the diagnosis of COVID-19. Eur J Radiol 2021; 134:109414. [PMID: 33246271 PMCID: PMC7657021 DOI: 10.1016/j.ejrad.2020.109414] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 10/22/2020] [Accepted: 11/09/2020] [Indexed: 01/08/2023]
Abstract
PURPOSE To date, the majority of chest imaging studies in COVID-19 pneumonia have focused on CT. Evidence for the utility of chest radiographs (CXRs) in this population is less robust. Our objectives were to develop a systematic approach for reporting likelihood of COVID-19 pneumonia on CXRs, to measure the interobserver variability of this approach and to evaluate the diagnostic performance of CXRs compared to real-time reverse transcription polymerase chain reaction (RT-PCR). METHOD Retrospective review of patients suspected of having COVID-19 pneumonia who attended our emergency department and underwent both CXR and a RT-PCR were included. Two radiologists reviewed the CXRs, blind to the RT-PCR, and classified them according to a structured reporting template with five categories (Characteristic, High Suspicion, Indeterminate, Unlikely and Normal) which we devised. For analysis of diagnostic accuracy, Characteristic and High Suspicion CXRs were considered positive and the remaining categories negative. Concordance between the two assessors was also measured. RESULTS Of 582 patients (51 +/- 20 years), 143/582 (24.6 %) had a positive RT-PCR. The absolute concordance between the two assessors was 71.1 % (414/582) with a Fleiss-Cohen-weighted Cohen's κ of 0.81 (95 % confidence interval, 0.78-0.85). A patient with a positive CXR had an 88 % (95 % CI 80-96 %) probability of having a positive RT-PCR during a period of high incidence, early in the COVID-19 pandemic. CONCLUSION Using a structured approach, a positive CXR had a high likelihood of predicting a positive RT-PCR, with good interrater reliability. CXRs can be useful in identifying new cases of COVID-19.
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Affiliation(s)
- Andrew Yates
- Department of Radiology, Mater Misericordiae University Hospital, Dublin, Ireland.
| | - Philip J Dempsey
- Department of Radiology, Mater Misericordiae University Hospital, Dublin, Ireland.
| | - Sebastian Vencken
- Clinical Research Centre, School of Medicine, University College, Dublin, Ireland.
| | - Peter J MacMahon
- Department of Radiology, Mater Misericordiae University Hospital, Dublin, Ireland; School of Medicine, University College, Dublin, Ireland.
| | - Barry D Hutchinson
- Department of Radiology, Mater Misericordiae University Hospital, Dublin, Ireland.
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Polak WG, Fondevila C, Karam V, Adam R, Belli LS, Duvoux C. Reply to Rodriguez-Peralvarez et al. Transpl Int 2020; 33:1825-1826. [PMID: 33037657 PMCID: PMC7675308 DOI: 10.1111/tri.13765] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Wojciech G Polak
- Department of Surgery, Division of HPB and Transplant Surgery, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Constantino Fondevila
- Department of General and Digestive Surgery, Liver Transplant Unit, Hospital Clinic, IDIBAPS, CIBERehd, University of Barcelona, Barcelona, Spain
| | - Vincent Karam
- European Liver Transplant Registry, Centre Hépatobiliaire, Hôpital Universitaire, Paul Brousse, Villejuif, France
| | - Rene Adam
- Department of Hepatobiliary Surgery, Cancer and Transplantation, AP-HP Hôpital Universitaire Paul Brousse, Villejuif, France
| | - Luca S Belli
- Division of Hepatology and Gastroenterology, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Christophe Duvoux
- Medical Liver Transplant Unit and Liver Department, Henri Mondor Hospital AP-HP, Paris Est University, Champs-sur-Marne, France
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Zervides C, Sassi M, Kefala-Karli P, Sassis L. Impact of COVID-19 pandemic on radiographers in the Republic of Cyprus. A questionnaire survey. Radiography (Lond) 2020; 27:419-424. [PMID: 33092995 PMCID: PMC7546182 DOI: 10.1016/j.radi.2020.10.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 10/04/2020] [Accepted: 10/05/2020] [Indexed: 12/23/2022]
Abstract
INTRODUCTION Imaging is essential for the initial diagnosis and monitoring of the novel coronavirus, which emerged in Wuhan, China. This study aims to assess the insight of radiographers on how the COVID-19 pandemic has affected their work routine and if protective measures are applied. METHOD A prospective observational study was conducted among radiographers registered in the Cyprus Society of Registered Radiologic Technologists & Radiation Therapy Technologists. A questionnaire composed of 28 multiple choice questions was utilised, and the data analysis was performed using SPSS software with the statistical significance assumed as p-value < 0.05. RESULTS Out of 350 registered radiographers, 101 responses were received. The results showed that there are statistically significant differences regarding the working hours, the feeling of stress, the work effectiveness, the average examination time, the presence of a protocol used among the different workplaces of the participants; a private radiology centre, a private hospital or a public hospital, with a p-value 0.0022, 0.015, 0.027, 0.001, 0.0001 respectively. Also, statistically significant differences were observed in the decontamination methods used for equipment (p-value 0.007), for air (p-value 0.04) and when decontamination takes place (p-value 0.00032) among the different workplaces of the participants. Nonetheless, the majority of radiographers believe that their workplace is sufficiently provided with PPE, cleaning supplies, equipment, and with cleaning personnel and are optimistic regarding the adequacy of these provisions in the next three months. CONCLUSION This study showed that in the Republic of Cyprus, there are protocols regarding protective measures against COVID-19, and the radiographers are adequately trained on how to face an infectious disease outbreak. However, work is needed in order to develop protocols that reassure the safety of patients and medical personnel while managing the excess workload effectively. IMPLICATIONS FOR PRACTICE This study indicates the importance of applying protective measures and protocols in the radiology departments in order to minimise the spread of the virus.
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Affiliation(s)
- C Zervides
- University of Nicosia, School of Medicine, 21 Ilia Papakyriakou Street, 2414, Engomi, Nicosia, Cyprus.
| | - M Sassi
- Biotypos Medical Diagnostic Center, 2 Andrea Papandreou, 15127, Melissia, Athens, Greece
| | - P Kefala-Karli
- University of Nicosia, School of Medicine, 21 Ilia Papakyriakou Street, 2414, Engomi, Nicosia, Cyprus
| | - L Sassis
- University of Nicosia, School of Medicine, 21 Ilia Papakyriakou Street, 2414, Engomi, Nicosia, Cyprus
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Loukoul WA, Schaer C, Christ F, Cinquetti G, Naulet P. [The role of thoracic CT scan, a triage tool for suspected COVID-19 cases]. SOINS; LA REVUE DE REFERENCE INFIRMIERE 2020; 65:48-51. [PMID: 33357618 DOI: 10.1016/s0038-0814(20)30244-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
The SARS-Cov-2 pandemic took health care players across the world by surprise, including caregivers, managers and logisticians. In the absence of a vaccine or a specific therapy, detecting the disease at an early stage and isolating confirmed cases from the rest of the healthy population was soon considered to be essential. The RT-PCR technique was the gold standard method for testing for infection with the virus. It has high specificity but moderate sensitivity. It was difficult to access it during the first weeks of the pandemic. On the basis of the observations of the Chinese and Italian scientific community in particular, the recommendation was to combine use of the RT-PCR with a low-dose thoracic CT scan. In the absence of easy access to the RT-PCR, the use of the lung CT scan for a rapid triage of patients within emergency departments proved effective.
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Affiliation(s)
- Wassim Abou Loukoul
- Hôpital d'instruction des armées Legouest, 27 avenue de Plantières, BP 90001, 57077 Metz cedex 3, France
| | - Cédric Schaer
- Hôpital d'instruction des armées Legouest, 27 avenue de Plantières, BP 90001, 57077 Metz cedex 3, France
| | - Florian Christ
- Hôpital d'instruction des armées Legouest, 27 avenue de Plantières, BP 90001, 57077 Metz cedex 3, France
| | - Gaël Cinquetti
- Hôpital d'instruction des armées Legouest, 27 avenue de Plantières, BP 90001, 57077 Metz cedex 3, France
| | - Pierre Naulet
- Hôpital d'instruction des armées Legouest, 27 avenue de Plantières, BP 90001, 57077 Metz cedex 3, France.
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