In the era of precision medicine, imaging plays a critical role in evaluating treatment response to various oncologic therapies. For decades, conventional morphologic assessments using cross-sectional imaging have been the standard for monitoring the effectiveness of systemic and locoregional therapies in patients with cancer. However, the development of new functional imaging tools has widened the scope of imaging from mere response assessment to patient selection and outcome prediction. Dual-energy CT (DECT), known for its superior material differentiation capabilities, shows promise in enhancing treatment response evaluation. DECT-based iodine quantification methods are increasingly being investigated as surrogates for assessing tumor vascularity and physiology, which is particularly important in patients undergoing emerging targeted therapies. The purpose of this review article is to discuss the current and emerging role of DECT in assessing treatment response in patients with malignant abdominal tumors. Keywords: CT-Dual Energy, Transcatheter Tumor Therapy, Tumor Response, Iodine Uptake, Therapeutic Response © RSNA, 2025.

This multicenter trial was conducted to evaluate MRI for the longitudinal management of incidental pulmonary nodules in heavy smokers.

239 participants (63.9 ± 8.4 years, 43-82 years) at risk of or with COPD GOLDI-IV from 16 centers prospectively underwent two rounds of same-day low-dose computed tomography (LDCT1&2) and MRI1&2 at an interval of three years in the nationwide COSYCONET trial. All exams were independently assessed for incidental pulmonary nodules in a standardized fashion by two blinded readers, incl. axis measurements and Lung-RADS categorization, with consensual LDCT results serving as the standard of reference. A change in diameter ≥ 2 mm was rated as progress. 11 patients underwent surgery for suspicious nodules after the first round.

Two hundred twenty-four of two hundred forty nodules (93.3%) persisted from LDCT1 to LDCT2, with a sensitivity of MRI2 of 82.8% and 81.5% for readers 1 and 2, respectively. Agreement in Lung-RADS categories between LDCT2 and MRI2 was substantial in per-nodule (κ = 0.62-0.70) and excellent in a per-patient (κ = 0.86-0.88) approach for both readers, respectively. Concordance between LDCT2 and MRI2 for growth was excellent to almost perfect (κ = 0.88-1.0). The accuracy of LDCT1 and MRI1 for lung cancer was 87.5%. Lung-RADS ≥ 3 category on MRI1 had higher accuracy for predicting progress (23.1% and 21.4%, respectively) than LDCT1 (15.8%).

Compared to LDCT, MRI shows similar capabilities for the longitudinal evaluation of incidental nodules in heavy smokers. Decision-making for nodule management guided by Lung-RADS seems feasible based on longitudinal MRI.

Question Can MRI serve as an alternative to low-dose CT (LDCT) for the longitudinal management of pulmonary nodules in heavy smokers, addressing concerns over radiation exposure? Findings MRI demonstrated substantial agreement with LDCT in detecting nodule growth, accurately categorizing Lung-RADS, and comparable accuracy in identifying malignancy over a three-year follow-up. Clinical relevance Longitudinal MRI demonstrates high consistency with LDCT in assessing the growth of incidental pulmonary nodules and categorizing per-patient Lung-RADS, offering a reliable, radiation-free alternative for monitoring and early malignancy detection in high-risk populations.

Advancements in tomographic medical imaging have revolutionized diagnostics and treatment monitoring by offering detailed 3D visualization of internal structures. Despite the significant value of computed tomography (CT), challenges such as high radiation dosage and cost barriers limit its accessibility, especially in low- and middle-income countries. Recognizing the potential of radiographic imaging in reconstructing CT images, this scoping review aims to explore the emerging field of synthesizing 3D CT-like images from 2D radiographs by examining the current methodologies.

A scoping review was carried out following PRISMA-SR guidelines. Eligibility criteria for the articles included full-text articles published up to September 9, 2024, studying methodologies for the synthesis of 3D CT images from 2D biplanar or four-projection x-ray images. Eligible articles were sourced from PubMed MEDLINE, Embase, and arXiv.

76 studies were included. The majority (50.8 %, n = 30) were published between 2010 and 2020 (38.2 %, n = 29) and from 2020 onwards (36.8 %, n = 28), with European (40.8 %, n = 31), North American (26.3 %, n = 20), and Asian (32.9 %, n = 25) institutions being primary contributors. Anatomical regions varied, with 17.1 % (n = 13) of studies not using clinical data. Further, studies focused on the chest (25 %, n = 19), spine and vertebrae (17.1 %, n = 13), coronary arteries (10.5 %, n = 8), and cranial structures (10.5 %, n = 8), among other anatomical regions. Convolutional neural networks (CNN) (19.7 %, n = 15), generative adversarial networks (21.1 %, n = 16) and statistical shape models (15.8 %, n = 12) emerged as the most applied methodologies. A limited number of studies included explored the use of conditional diffusion models, iterative reconstruction algorithms, statistical shape models, and digital tomosynthesis.

This scoping review summarizes current strategies and challenges in synthetic imaging generation. The development of 3D CT-like imaging from 2D radiographs could reduce radiation risk while simultaneously addressing financial and logistical obstacles that impede global access to CT imaging. Despite initial promising results, the field encounters challenges with varied methodologies and frequent lack of proper validation, requiring further research to define synthetic imaging's clinical role.

This study investigated the additional radiation exposure, influencing factors, and clinical significance of overlappingZ-axis coverage in abdominopelvic CT scans performed consecutively after same-day chest CT scans. Data from 761 patients were analyzed, with measuring the total and overlappingZ-axis coverage of the portal venous phase in abdominopelvic CT scans. The average overlapping portion was 33.8 ± 12.1 mm, accounting for approximately 7.0% of the total scan length, contributing a dose-length product of 33.4 mGy*cm and an effective radiation dose of 0.5 mSv. Male sex and the total scan length were identified as significant factors influencing overlap (p= 0.002 and < 0.001, respectively). Despite overlapping scans frequently imaging the lower lungs, only 8.4% of abdominopelvic CT reports specifically mentioned lower lung abnormalities, indicating limited clinical utility. These findings underscore the importance of optimizing CT protocols to minimize the total length of the body covered in abdominopelvic scans, thereby reducing unnecessary radiation exposure during concurrent chest and abdominopelvic CT scans.

Acute brain injury (ABI) is a complex disease process that begins with an initial insult followed by secondary injury resulting from disturbances in cerebral physiology. In the metabolically active brain, early recognition of physiologic derangements is critical in enabling clinicians with the insight to adjust therapeutic interventions and reduce risk of ischemia and permanent injury. Current established approaches for monitoring cerebral physiology include the neurologic physical examination, traditional brain imaging such as computed tomography (CT) and magnetic resonance imaging (MRI), electroencephalography (EEG), and bedside modalities such as invasive parenchymal probes and transcranial doppler ultrasound. Diffuse optical spectroscopy (DOS), diffuse correlation spectroscopy (DCS), and optical coherence tomography (OCT) are non-invasive optical techniques that have shown promise in measuring clinically relevant changes in cerebral physiology. These new modalities may offer clinicians significant benefits as they are safe, can be utilized at the point-of-care, and provide continuous measurements. This paper reviews major causes of primary and secondary ABI encountered in neurocritical care units, conventional measures of cerebral physiology during ABI, and emerging non-invasive optical techniques that have significant potential for translation to the bedside.

In computed tomography (CT) imaging, optimizing the balance between radiation dose and image quality is crucial due to the potentially harmful effects of radiation on patients. Although subjective assessments by radiologists are considered the gold standard in medical imaging, these evaluations can be time-consuming and costly. Thus, objective methods, such as the peak signal-to-noise ratio and structural similarity index measure, are often employed as alternatives. However, these metrics, initially developed for natural images, may not fully encapsulate the radiologists' assessment process. Consequently, interest in developing deep learning-based image quality assessment (IQA) methods that more closely align with radiologists' perceptions is growing. A significant barrier to this development has been the absence of open-source datasets and benchmark models specific to CT IQA. Addressing these challenges, we organized the Low-dose Computed Tomography Perceptual Image Quality Assessment Challenge in conjunction with the Medical Image Computing and Computer Assisted Intervention 2023. This event introduced the first open-source CT IQA dataset, consisting of 1,000 CT images of various quality, annotated with radiologists' assessment scores. As a benchmark, this challenge offers a comprehensive analysis of six submitted methods, providing valuable insight into their performance. This paper presents a summary of these methods and insights. This challenge underscores the potential for developing no-reference IQA methods that could exceed the capabilities of full-reference IQA methods, making a significant contribution to the research community with this novel dataset. The dataset is accessible at https://zenodo.org/records/7833096.

To assess the impact of artificial intelligence iterative reconstruction algorithms (AIIR) on image quality with phantom and clinical studies.

The phantom images were reconstructed with the hybrid iterative algorithm (HIR: Karl 3D-3, 5, 7, 9) and AIIR (grades 1-5) algorithm. Noise power spectra (NPS), task transfer functions (TTF) were measured, and additionally sharpness was assessed using a "blur metric" procedure. Sixty-two consecutive patients underwent standard-dose and low-dose unenhanced abdominal computed tomography (CT) scans, i.e., SDCT and LDCT groups, respectively. The SDCT images reconstructed using the Karl 3D-5, and the LDCT images reconstructed using the Karl 3D-5 and the AIIR-3 and 5, respectively. CT values, standard deviation (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were assessed for hepatic parenchyma and paravertebral muscles. Images were independently evaluated by two radiologists for image-quality, noise, sharpness, and lesion diagnostic confidence.

In the phantom study, AIIR algorithm provided higher TTF50% and NPS average spatial frequency compared to HIR. In the clinical study, there was no statistically significant difference in CT values among the four reconstruction images (p > 0.05). The LDCT group AIIR-3 obtained the lowest SD values and the highest mean CNR and SNR values compared to the other three groups (p < 0.05). For qualitative assessment, the image subjective characteristic scores of AIIR-5 in the LDCT group, compared with the SDCT group, were not statistically significant (p > 0.05).

AIIR reduces radiation dose levels by approximately 78% and still maintains the image quality of unenhanced abdominal CT compared to HIR with SDCT.

NCT06142539.

Due to the increasing use of imaging services, this study aimed to estimate the number of unnecessary imaging services, normal and abnormal imaging examinations, and their determinant factors.

This cross-sectional study was conducted at a district hospital in East Azerbaijan, Iran. Retrospective data were collected from the electronic medical records of patients referred to the Imaging Department between March and August 2022, using the Hospital Information System (HIS). Descriptive statistics and χ 2 tests were performed, followed by hierarchical logistic regression with AOR, 95% CI, using SPSS-24 for analysis.

About 28% of imaging examinations with abnormal results and 21% of the examinations with normal results were unnecessary. The probability of ultrasound abnormal imaging results was 67% lower than computed tomography (CT) scan (CT-scan) (adjusted odds ratio (AOR) = 0.33 (0.212-0.50); p < 0.001). One year increase of patient age is associated with a 1% lower likelihood of having normal imaging (AOR = 0.99 (0.98-0.99); p < 0/001). Women were 20% less likely than men to have abnormal imaging results (AOR = 0.80 (0.65-0.98); p = 0.035). The probability of necessary imaging decreases by 1% for 1 year increase in patient age (p = 0.017), on the other hand, the probability of unnecessary chest radiography was 5% higher than a brain CT-scan imaging (AOR = 2.05 (1.19-3.51); p = 0.009).

Unnecessary imaging were more frequently performed on the older patients. Additionally, ultrasound was less likely than CT-scans to show abnormal findings, while chest radiography was more frequently deemed unnecessary compared to brain CT-scans. These insights highlight the need for age- and modality-specific guidelines to reduce unnecessary imaging and improve diagnostic efficiency.

Currently, CT pulmonary angiogram (CTPA) for evaluating acute pulmonary embolism (PE) in emergency departments (EDs) is overused and with low yields. The goal of this study is to assess the impact of an evidence-based clinical decision support (CDS) tool, aimed at optimizing appropriate use of CTPA for evaluating PE.

The study was performed at EDs in a large health care system and included nine academic and community hospitals. The primary outcome was the percent difference in utilization (number of CTPAs performed per number of ED visits) and secondary outcome was yield (percentage of CTPAs positive for acute PE), comparing 12 months before (June 1, 2021, to May 31, 2022) versus 12 months after (June 1, 2022, to May 31, 2023) a systemwide implementation of the CDS. Univariate and multivariable analyses using logistic regression were performed to assess factors associated with diagnosis of acute PE. Statistical process control charts were used to assess monthly trends in utilization and yield.

Among 931,677 visits to EDs, 28,101 CTPAs were performed on 24,675 patients. In all, 14,825 CTPAs were performed among 455,038 visits (3.26%) pre-intervention and 13,276 among 476,639 visits (2.79%) postintervention, a 14.51% relative decrease in CTPA utilization (χ2, P < .001). CTPA yield remained unchanged (1,371 of 14,825 = 9.25% pre- versus 1,184 of 13,276 = 8.92% postintervention; χ2, P = .34). Patients with coronavirus disease of 2019 diagnosis before CTPA had higher probability of acute PE. Statistical process control charts demonstrated seasonal variation in utilization (Friedman test, P = .047).

Implementing a CDS based on validated decision rules was associated with a significant reduction in CTPA utilization. The change was immediate and sustained for 12 months postintervention.

This paper is part of a clinical practice guideline update on the risk assessment, diagnostic imaging, and microbiological evaluation of complicated intra-abdominal infections in adults, children, and pregnant people, developed by the Infectious Diseases Society of America. In this paper, the panel provides recommendations for diagnostic imaging of suspected acute diverticulitis. The panel's recommendations are based on evidence derived from systematic literature reviews and adhere to a standardized methodology for rating the certainty of evidence and strength of recommendation according to the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) approach.

To establish various radiomics models based on conventional CT scan images and enhanced CT images, explore their value in the classification of pheochromocytoma (PHEO) and lipid-poor adrenal adenoma (LPA) and screen the most parsimonious and efficient model.

The clinical and imaging data of 332 patients (352 lesions) with PHEO or LPA confirmed by surgical pathology in the Affiliated Hospital of Qingdao University were retrospectively analyzed. The region of interest (ROI) on conventional and enhanced CT images was delineated using ITK-SNAP software. Different radiomics signatures were constructed from the radiomics features extracted from conventional and enhanced CT images, and a radiomics score (Rad score) was calculated. A clinical model was established using demographic features and CT findings, while radiomics nomograms were established using multiple logistic regression analysis.The predictive efficiency of different models was evaluated using the area under curve (AUC) and receiver operating characteristic (ROC) curve. The Delong test was used to evaluate whether there were statistical differences in predictive efficiency between different models.

The radiomics signature based on conventional CT images showed AUCs of 0.97 (training cohort, 95% CI: 0.95∼1.00) and 0.97 (validation cohort, 95% CI: 0.92∼1.00). The AUCs of the nomogram model based on conventional scan CT images and enhanced CT images in the training cohort and the validation cohort were 0.97 (95% CI: 0.95∼1.00) and 0.97 (95% CI: 0.94~1.00) and 0.98 (95% CI: 0.97∼1.00) and 0.97 (95% CI: 0.94∼1.00), respectively. The prediction efficiency of models based on enhanced CT images was slightly higher than that of models based on conventional CT images, but these differences were statistically insignificant(P>0.05).

CT-based radiomics signatures and radiomics nomograms can be used to predict and identify PHEO and LPA. The model established based on conventional CT images has great identification and prediction efficiency, and it can also enable patients to avoid harm from radiation and contrast agents caused by the need for further enhancement scanning in traditional image examinations.

Cystic Fibrosis (CF) progresses through recurrent infection and inflammation, causing permanent lung function loss and airway remodeling. CT scans reveal abnormally low-density lung parenchyma in CF, but its microstructural nature remains insufficiently explored due to clinical CT limitations. To this end, diffusion-weighted 129Xe MRI is a non-invasive and validated measure of lung microstructure. In this work, we investigate microstructural changes in people with CF (pwCF) relative to age-matched, healthy subjects using comprehensive imaging and analysis involving pulmonary-function tests (PFTs), and 129Xe MRI.

38 healthy subjects (age 6-40; 17.2 ± 9.5 years) and 39 pwCF (age 6-40; 15.6 ± 8.0 years) underwent 129Xe-diffusion MRI and PFTs. The distribution of diffusion measurements (i.e., apparent diffusion coefficients (ADC) and morphometric parameters) was assessed via linear binning (LB). The resulting volume percentages of bins were compared between controls and pwCF. Mean ADC and morphometric parameters were also correlated with PFTs.

Mean whole-lung ADC correlated significantly with age (P < 0.001) for both controls and CF, and with PFTs (P < 0.05) specifically for pwCF. Although there was no significant difference in mean ADC between controls and pwCF (P = 0.334), age-adjusted LB indicated significant voxel-level diffusion (i.e., ADC and morphometric parameters) differences in pwCF compared to controls (P < 0.05).

129Xe diffusion MRI revealed microstructural abnormalities in CF lung disease. Smaller microstructural size may reflect compression from overall higher lung density due to interstitial inflammation, fibrosis, or other pathological changes. While elevated microstructural size may indicate emphysema-like remodeling due to chronic inflammation and infection.

When discussing radiation risks for patients who undergo many CT examinations, some question the risks, believing that most of these patients are already very sick and likely to die within a few years, thus negating worry about radiation risk. This study seeks to evaluate the validity of this notion.

In this retrospective single large-hospital study, patients who received CT exams in 2013 were sorted into four cumulative effective dose (CED) groups: Group A (>0 to <10 mSv), Group B (10 to <50 mSv), Group C (50 to < 100 mSv), and Group D (≥100 mSv). The death rates of patients in each group were analyzed, up to December 2023.

36,545 patients underwent CT examinations in 2013 (mean age, 56 ± 20 years, 51.4 % men). Death rates for all dose groups peaked in the year of imaging or 1 year after. At one year after imaging, Group D had 6.7 times and Group C had 4.3 times the death rate of Group A. However, a significant portion of these patients are alive after 10 years, with 1324/2756 patients (48.0 %) in Group C and 282/769 patients (36.7 %) in Group D with the potential to face radiation effects.

While it is true that patients receiving relatively higher doses (≥50 mSv) are more likely to die within the first two years of receiving such doses, nearly one-third to half remain alive a decade after their CT scans, potentially facing the effects of radiation. This knowledge may help policymakers and practitioners.

There are no guidelines in the literature for the use of a computed tomography (CT) protocol in the initial phase of acute pancreatitis (AP).

To evaluate the contribution of single portal venous phase CT compared to triple-phase CT protocol, performed in the initial phase of AP for severity assessment.

In this retrospective study, a total of 175 patients with acute pancreatitis who underwent initial triple-phase CT protocol (non-contrast, arterial phase, and portal venous phase) between D3 and D7 after the onset of symptoms were included. Analysis of AP severity and complications was independently assessed by two readers using three validated CT severity scores (CTSI, mCTSI, EPIC). All scores were applied to the triple-phase CT protocol and compared to the single portal venous phase. Inter-observer analyses were also performed.

No significant difference whatever the severity score was observed after analysis of the single portal venous phase compared with the triple-phase CT protocol (interstitial edematous pancreatitis: CTSI: 2 vs. 2, mCTSI: 2 vs. 2, EPIC: 1 vs. 1; necrotizing pancreatitis: CTSI: 6 vs. 6, mCTSI: 8 vs. 8, EPIC: 5 vs. 5). Inter-observer agreement was excellent (ICC = 0.96-0.99), whatever the severity score.

A triple-phase CT protocol performed at the initial phase of AP was no better than a single portal venous for assessing the severity of complications and could lead to a 63% reduction in irradiation.

Increases in computed tomography (CT) use may not always reflect clinical need or improve outcomes. This study aimed to demonstrate how population level data can be used to identify variations in care between patient groups, by analysing system-level changes in CT use around the diagnosis of new conditions.

Retrospective repeated cross-sectional observational study using West Australian linked administrative records, including 504,723 adults diagnosed with different conditions in 2006, 2012 and 2015. For 90 days pre/post diagnosis, CT use (any and 2+ scans), effective dose (mSv), lifetime attributable risk (LAR) of cancer incidence and mortality from CT, and costs were assessed.

CT use increased from 209.4 per 1000 new diagnoses in 2006 to 258.0 in 2015; increases were observed for all conditions except neoplasms. Healthcare system costs increased for all conditions but neoplasms and mental disorders. Effective dose increased substantially for respiratory (+2.5 mSv, +23.1%, P < 0.001) and circulatory conditions (+2.1 mSv, +15.4%, P < 0.001). The LAR of cancer incidence and mortality from CT increased for endocrine (incidence +23.4%, mortality +18.0%) and respiratory disorders (+21.7%, +23.3%). Mortality LAR increased for circulatory (+12.1%) and nervous system (+11.0%) disorders. The LAR of cancer incidence and mortality reduced for musculoskeletal system disorders, despite an increase in repeated CT in this group.

Use and costs increased for most conditions except neoplasms and mental and behavioural disorders. More strategic CT use may have occurred in musculoskeletal conditions, while use and radiation burden increased for respiratory, circulatory and nervous system conditions. Using this high-level approach we flag areas requiring deeper investigation into appropriateness and value of care.

Computed tomography perfusion (CTP) is a dynamic 4-dimensional imaging technique (3-dimensional volumes captured over approximately 1 min) in which cerebral blood flow is quantified by tracking the passage of a bolus of intravenous contrast with serial imaging of the brain. To diagnose and assess acute ischemic stroke, the standard method relies on summarizing acquired CTPs over the time axis to create maps that show different hemodynamic parameters, such as the timing of the bolus arrival and passage (Tmax and MTT), cerebral blood flow (CBF), and cerebral blood volume (CBV). However, producing accurate CTP maps requires the selection of an arterial input function (AIF), i.e. a time-concentration curve in one of the large feeding arteries of the brain, which is a highly error-prone procedure. Moreover, during approximately one minute of CT scanning, the brain is exposed to ionizing radiation that can alter tissue composition, and create free radicals that increase the risk of cancer. This paper proposes a novel end-to-end deep neural network that synthesizes CTP images to generate CTP maps using a learned LSTM Generative Adversarial Network (LSTM-GAN). Our proposed method can improve the precision and generalizability of CTP map extraction by eliminating the error-prone and expert-dependent AIF selection step. Further, our LSTM-GAN does not require the entire CTP time series and can produce CTP maps with a reduced number of time points. By reducing the scanning sequence from about 40 to 9 time points, the proposed method has the potential to minimize scanning time thereby reducing patient exposure to CT radiation. Our evaluations using the ISLES 2018 challenge dataset consisting of 63 patients showed that our model can generate CTP maps by using only 9 snapshots, without AIF selection, with an accuracy of 84.37 % .

To comprehensively assess the existing literature regarding the rapidly evolving in vivo application of magnetic resonance imaging (MRI) for potential applications, benefits, and challenges in dental implant surgery.

Electronic and manual searches were conducted in PubMed MEDLINE, EMBASE, Biosis, and Cochrane databases by two reviewers following the PICOS search strategy. This involved using medical subject headings (MeSH) terms, keywords, and their combinations.

Sixteen studies were included in this systematic review. Of the 16, nine studies focused on preoperative planning and follow-up phases, four evaluated image-guided implant surgery, while three examined artifact reduction techniques. The current literature highlights several MRI protocols that have recently investigated and evaluated the in vivo feasibility and accuracy, focusing on its potential to provide surgically relevant quantitative and qualitative parameters in the assessment of osseointegration, peri-implant soft tissues, surrounding anatomical structures, reduction of artifacts caused by dental implants, and geometric accuracy relevant to implant placement. Black Bone and MSVAT-SPACE MRI, acquired within a short time, demonstrate improved hard and soft tissue resolution and offer high sensitivity in detecting pathological changes, making them a valuable alternative in targeted cases where CBCT is insufficient. Given the data heterogeneity, a meta-analysis was not possible.

The results of this systematic review highlight the potential of dental MRI, within its indications and limitations, to provide perioperative surgically relevant parameters for accurate placement of dental implants.

Distal radius fractures (DRFs) are common upper extremity fractures and often require surgical fixation when they are intraarticular. Preoperative computed tomography (CT) has emerged as a surgical planning tool to evaluate intraarticular DRFs. Although CT affords additional details, patients receive higher radiation doses than standard radiographs. We aim to develop a low-dose CT (LDCT) protocol, relative to the institutional standard-dose CT wrist for intraarticular DRFs although providing adequate detail for surgical decision-making.

A single-institution prospective study was conducted on patients with intraarticular DRFs who underwent closed reduction and below-elbow splinting who otherwise would undergo wrist CT. Observations were defined as total measurements taken, with each view undergoing 44 measurements. Patients underwent 2 scans with a standard dose and a 10× dose reduction. Articular step and gap measurements were recorded in the sagittal and coronal images.

A total of 11 patients were enrolled (7 women and 4 men). The mean age was 55 years (SD = 20.1). There were a total of 4 reviewers: 1 attending surgeon, 2 resident physicians, and 1 student. When comparing LDCT and conventional-dose CT (CDCT), there were no significant differences in step and gap measurements across all reviewers.

This study demonstrated that LDCT provides comparable imaging quality for surgical planning as a CDCT without significant diagnostic decay in the setting of DRFs. This comes with the added benefit of a 10-fold reduction in radiation exposure. These results suggest that LDCT is an opportunity to reduce effective radiation in patients although providing beneficial preoperative imaging.

The study investigated radiation dose, vascular computed tomography (CT) enhancement and image quality of cardiac computed tomography angiography (CCTA) with and without bolus tracking (BT) methods in infants with congenital heart disease (CHD). The volume CT dose index (CTDIvol) and dose length product (DLP) were recorded for all CT scans, and the effective dose was obtained using a conversion factors. The CT number for the ascending aorta (AO) and pulmonary artery (PA), image noise of muscle tissue and contrast-to-noise ratio (CNR) were measured and calculated. The median values in the groups with and without BT were 2.20 mGy versus 0.44 mGy for CTDIvol, 8.10 mGy·cm versus 6.20 mGy·cm for DLP, and 0.66 mSv versus 0.51 mSv for effective dose (p < 0.001). There were no statistical differences in vascular CT enhancement, image noise, and CNR. CCTA without BT methods can reduce the radiation dose while maintaining vascular CT enhancement and image quality compared to CCTA with BT methods.

This study aimed to evaluate the image quality and lesion conspicuity of the deep learning image reconstruction (DLIR) algorithm compared with standard image reconstruction algorithms on abdominal enhanced computed tomography (CT) scanning with a wide range of body mass indexes (BMIs).

A total of 112 participants who underwent contrast-enhanced abdominal CT scans were divided into three groups according to BMIs: the 80-kVp group (BMI ≤ 23.9 kg/m2), 100-kVp group (BMI 24-28.9 kg/m2), and 120-kVp group (BMI ≥ 29 kg/m2). All images were reconstructed using filtered back projection (FBP), adaptive statistical iterative reconstruction-V of 50% level (IR), and DLIR at low, medium, and high levels (DL, DM, and DH, respectively). Subjective noise, artifact, overall image quality, and low- and high-contrast hepatic lesion conspicuity were all graded on a 5-point scale. The CT attenuation value (in HU), image noise, and contrast-to-noise ratio (CNR) were quantified and compared.

DM and DH improved the qualitative and quantitative parameters compared with FBP and IR for all three BMI groups. DH had the lowest image noise and highest CNR value, while DM had the highest subjective overall image quality and low- and high-contrast lesion conspicuity scores for the three BMI groups. Based on the FBP, the improvement in image quality and lesion conspicuity of DM and DH images was greater in the 80-kVp group than in the 100-kVp and 120-kVp groups.

For all BMIs, DLIR improves both image quality and hepatic lesion conspicuity, of which DM would be the best choice to balance both.

The study suggests that utilizing DLIR, particularly at the medium level, can significantly enhance image quality and lesion visibility on abdominal CT scans across a wide range of BMIs.

• DLIR improved the image quality and lesion conspicuity across a wide range of BMIs. • DLIR at medium level had the highest subjective parameters and lesion conspicuity scores among all reconstruction levels. • On the basis of the FBP, the 80-kVp group had improved image quality and lesion conspicuity more than the 100-kVp and 120-kVp groups.

Positron emission tomography/magnetic resonance imaging (PET/MRI) is a hybrid imaging technique that quantitatively combines the metabolic and functional data from positron emission tomography (PET) with anatomical and physiological information from MRI. As PET/MRI technology has advanced, its applications in cancer care have expanded. Recent studies have demonstrated that PET/MRI provides unique advantages in the field of radiotherapy and has become invaluable in guiding precision radiotherapy techniques. This review discusses the rationale and clinical evidence supporting the use of PET/MRI for radiation positioning, target delineation, efficacy evaluation, and patient surveillance.Critical relevance statement This article critically assesses the transformative role of PET/MRI in advancing precision radiotherapy, providing essential insights into improved radiation positioning, target delineation, efficacy evaluation, and patient surveillance in clinical radiology practice.Key points• The emergence of PET/MRI will be a key bridge for precise radiotherapy.• PET/MRI has unique advantages in the whole process of radiotherapy.• New tracers and nanoparticle probes will broaden the use of PET/MRI in radiation.• PET/MRI will be utilized more frequently for radiotherapy.

Low-dose computed tomography (CT) images suffer from noise and artifacts due to photon starvation and electronic noise. Recently, some works have attempted to use diffusion models to address the over-smoothness and training instability encountered by previous deep-learning-based denoising models. However, diffusion models suffer from long inference time due to a large number of sampling steps involved. Very recently, cold diffusion model generalizes classical diffusion models and has greater flexibility. Inspired by cold diffusion, this paper presents a novel COntextual eRror-modulated gEneralized Diffusion model for low-dose CT (LDCT) denoising, termed CoreDiff. First, CoreDiff utilizes LDCT images to displace the random Gaussian noise and employs a novel mean-preserving degradation operator to mimic the physical process of CT degradation, significantly reducing sampling steps thanks to the informative LDCT images as the starting point of the sampling process. Second, to alleviate the error accumulation problem caused by the imperfect restoration operator in the sampling process, we propose a novel ContextuaL Error-modulAted Restoration Network (CLEAR-Net), which can leverage contextual information to constrain the sampling process from structural distortion and modulate time step embedding features for better alignment with the input at the next time step. Third, to rapidly generalize the trained model to a new, unseen dose level with as few resources as possible, we devise a one-shot learning framework to make CoreDiff generalize faster and better using only one single LDCT image (un)paired with normal-dose CT (NDCT). Extensive experimental results on four datasets demonstrate that our CoreDiff outperforms competing methods in denoising and generalization performance, with clinically acceptable inference time. Source code is made available at https://github.com/qgao21/CoreDiff.

Neuroendocrine tumors (NET) are neoplasms that secrete peptides and neuroamines. For gastroenteropancreatic (GEP) NET, surgical resection represents the only curative option. Ten-year imaging surveillance programs are recommended due to long time-to-recurrence following resection. We performed retrospective chart review evaluating radiation exposure and practice patterns from surveillance of completely resected GEP NET.

We performed a retrospective cohort study of cases with well-differentiated GEP NET from January 2005 to July 2020. Location of primary, modality of imaging, and duration of follow-up were collected. Dosimetry data was collected to calculate effective dose.

62 cases were included with 422 surveillance scans performed. Cross-sectional imaging was used in 82% and functional imaging was used in 18% of scans. Mean number of scans per year was 1.25 (0.42-3). Mean total effective dose was 56.05 mSv (SD 45.56; 0 to 198 mSv) while mean total effective dose per year was 10.62 mSv (SD 9.35; 0 to 45 mSv). Over the recommended ten years of surveillance the estimated total effective dose was 106 mSv.

Surveillance of completely resected GEP NET results in cumulative radiation doses in the range associated with secondary malignancy development. Strategies to minimize radiation exposure in surveillance should be considered in future guideline development.

Management of primary headache (PHA) varies across emergency departments (ED), yet there is widespread agreement that computed tomography (CT) scans are overused. This study assessed emergency physicians' (EPs) PHA management and their attitudes towards head CT ordering.

A cross-sectional study was undertaken with EPs from one Canadian center. Drivers of physicians' perceptions regarding the appropriateness of CT ordering for patients with PHA were explored.

A total of 73 EPs (70% males; 48% with <10 years of practice) participated in the study. Most EPs (88%) did not order investigations for moderate-severe primary headaches; however, CT was the common investigation (47%) for headaches that did not improve. Computed tomography ordering was frequently motivated by the need for specialist consultation (64%) or admission (64%). A small proportion (27%) believed patients usually/frequently expected a scan. Nearly half of EPs (48%) identified patient imaging expectations/requests as a barrier to reducing CT ordering. Emergency physicians with CCFP (EM) certification were less likely to perceive CT ordering for patients with PHA as appropriate. Conversely, those who identified the possibility of missing a condition as a major barrier to limiting their CT use were more likely to perceive CT ordering for patients with PHA as appropriate.

Emergency physicians reported consistency and evidence-based medical management. They highlighted the complexities of limiting CT ordering and both their level of training and their perceived barriers for limiting CT ordering seem to be influencing their attitudes. Further studies could elucidate these and other factors influencing their practice.

To compare image quality, iodine intake, and radiation dose in overweight and obese patients undergoing abdominal computed tomography (CT) enhancement using different scanning modes and contrast medium.

Ninety overweight and obese patients (25 kg/m2≤body mass index (BMI)< 30 kg/m2 and BMI≥30 kg/m2) who underwent abdominal CT-enhanced examinations were randomized into three groups (A, B, and C) of 30 each and scanned using gemstone spectral imaging (GSI) +320 mgI/ml, 100 kVp + 370 mgI/ml, and 120 kVp + 370 mgI/ml, respectively. Reconstruct monochromatic energy images of group A at 50-70 keV (5 keV interval). The iodine intake and radiation dose of each group were recorded and calculated. The CT values, contrast-to-noise ratios (CNRs), and subjective scores of each subgroup image in group A versus images in groups B and C were by using one-way analysis of variance or Kruskal-Wallis H test, and the optimal keV of group A was selected.

The dual-phase CT values and CNRs of each part in group A were higher than or similar to those in groups B and C at 50-60 keV, and similar to or lower than those in groups B and C at 65 keV and 70 keV. The subjective scores of the dual-phase images in group A were lower than those of groups B and C at 50 keV and 55 keV, whereas no significant difference was seen at 60-70 keV. Compared to groups B and C, the iodine intake in group A decreased by 12.5% and 13.3%, respectively. The effective doses in groups A and B were 24.7% and 25.8% lower than those in group C, respectively.

GSI +320 mgI/ml for abdominal CT-enhanced in overweight patients satisfies image quality while reducing iodine intake and radiation dose, and the optimal keV was 60 keV.

Size-specific dose estimates (SSDEs) are dose indices that account for differences in body shape in computed tomography (CT) scans, allowing the evaluation of approximate absorbed doses in any cross section that could not be obtained with the volume CT dose index (CTDIvol). When using automatic exposure control (AEC), CTDIvol is modulated in the body axis direction, but the value displayed after the examination is the mean CTDIvol for the entire scan, and it is expected that the SSDE value will change depending on which value is used in the calculation. In this study, using a human body phantom, we examined the influence of whether the mean CTDIvol or the modulation value for each slice is used to calculate the SSDE on local organ dose evaluation. A program to calculate water equivalent diameter according to the procedure in the American Association of Physicists in Medicine Report No. 220 was developed and compared. As a result, SSDE calculated using the mean CTDIvol (local-SSDEmean) overestimated organ doses in the lung region by 18%-56% compared with those calculated by a web system for evaluating CT exposure doses (WAZA-ARIv2, Japan). In contrast, local-SSDEmodulated, which was calculated using the modulated value of the CTDIvol, was able to estimate the organ dose with a relative error of 10%-13%. The average local-SSDE over the entire body axis direction was not significantly different between the two methods, regardless of which method was used for CTDIvol. If the mean CTDIvol is stored in the Digital Imaging and Communications in Medicine (DICOM) header tag (0018, 9345) of the CT image and the modulated CTDIvol value is not available for each slice, the calculated local SSDE will contain many errors and will not correctly reflect the organ doses at the scan region. In such cases, it is available to use the method of evaluating local organ doses by multiplying the SSDE, which is the average of the SSDE for the entire scan, by a factor for each organ.

The exploration of non-invasive biomarkers for assessing tumor response is critical to optimize treatment decisions. In this study, we aimed at determining the potential role of RAI14 in the early diagnosis and evaluation of chemotherapy efficacy in triple-negative breast cancer (TNBC).

We recruited 116 patients newly diagnosed with breast cancer, 30 patients with benign breast disease and 30 healthy controls. In addition, 57 TNBC patients were collected in serum at different time points (C0, C2 and C4) for chemotherapy monitoring. The expression of serum RAI14 and CA15-3 were quantified by Elisa and electrochemiluminescence assay, respectively. Then we compared the performances of markers with the chemotherapy efficacy assessed by imaging.

RAI14 is significantly overexpressed in TNBC and is linked to adverse clinicopathological features such as tumor burden, CA15-3 levels and the ER, PR, and HER2 status of the patients. ROC curve analysis showed that RAI14 improves the diagnostic performance for CA15-3(AUCRAI14 = 0.934 vs. AUCCA15-3 = 0.836), especially embodied in early-stage breast cancer diagnosis and patients with CA15-3 negativity. Furthermore, RAI14 behaves well in reproducing treatment response which was consistent with clinical Imaging assessment.

Recent studies showed that RAI14 has a complementary effect to CA15-3 and a test combining the two parameters can improve the detection rate of early triple-negative breast cancer. At the same time, RAI14 plays a more important role in chemotherapy monitoring than CA15-3 as the change in its concentration is in line with the tumor volume variation. Taken together, RAI14 is a reliable novel marker in the early diagnosis and chemotherapy monitoring of triple-negative breast cancer.

Pancreatic ductal adenocarcinoma (PDAC), the most deadly solid malignancy, is typically detected late and at an inoperable stage. Early or incidental detection is associated with prolonged survival, but screening asymptomatic individuals for PDAC using a single test remains unfeasible due to the low prevalence and potential harms of false positives. Non-contrast computed tomography (CT), routinely performed for clinical indications, offers the potential for large-scale screening, however, identification of PDAC using non-contrast CT has long been considered impossible. Here, we develop a deep learning approach, pancreatic cancer detection with artificial intelligence (PANDA), that can detect and classify pancreatic lesions with high accuracy via non-contrast CT. PANDA is trained on a dataset of 3,208 patients from a single center. PANDA achieves an area under the receiver operating characteristic curve (AUC) of 0.986-0.996 for lesion detection in a multicenter validation involving 6,239 patients across 10 centers, outperforms the mean radiologist performance by 34.1% in sensitivity and 6.3% in specificity for PDAC identification, and achieves a sensitivity of 92.9% and specificity of 99.9% for lesion detection in a real-world multi-scenario validation consisting of 20,530 consecutive patients. Notably, PANDA utilized with non-contrast CT shows non-inferiority to radiology reports (using contrast-enhanced CT) in the differentiation of common pancreatic lesion subtypes. PANDA could potentially serve as a new tool for large-scale pancreatic cancer screening.

A well-established method does not exist to rule out a small bowel obstruction using an abdominal xray series with significant accuracy. The hypothesis of the study is that the ratio of an average small bowel diameter to lumbar spine diameter over 0.5 is most likely a small bowel obstruction.

An x-ray abdominal series measurement technique was applied to 41 subjects with a chief complaint of "abdominal pain" as part of a randomized retrospective case review to predict an obstruction v. non obstruction. A total number of 81 abdominal pain subjects with a mean age of 46.7 years were selected with 40 excluded due to normal small bowel gas pattern. The subject's medical information was unknown to the authors when reading their images. The measurement technique involved averaging the largest and smallest small bowel short axis diameters with comparison to the lowest clearly visible lumbar body width. The subjects' medical course as described in the medical chart or subsequent computed tomography scans were used as the referencing standard to determine presence of obstruction vs non-obstruction.

This method, called the Bowel-Spine Ratio (BSR), resulted in a sensitivity of 0.882 (0.622-0.979; 95% CI), specificity of 0.957 (0.760-0.998; 95% CI), accuracy of 94.7% (80.9%-99.1%; 95% CI) and a positive likelihood ratio of 21 for predicting a small bowel obstruction.

The abdominal series Bowel-Spine Ratio is a simple yet effective technique to screen for a small bowel obstruction using limited resources and to avoid unnecessary computed tomography scans with the potential to reduce health care costs.

Clinicians could have increased confidence in utilizing abdominal radiographs to evaluate for small bowel obstruction.

Sarcopenia has emerged as a significant prognostic factor in liver disease, posing a significant risk to patients in terms of morbidity and mortality. However, the evaluation of skeletal muscle mass and quality remains challenging, as cross-sectional imaging is not a suitable screening tool. In order to better include this crucial variable in the routine risk stratification of patients with chronic liver disease, there is an urgent need for simple and reliable non-invasive diagnostic tools for sarcopenia. Therefore, the use of ultrasound techniques has garnered attention as a promising alternative for detecting sarcopenia and muscle abnormalities. This narrative review aims to provide an overview of the current literature on the use of ultrasound as a diagnostic tool for sarcopenia, with particular focus on patients with cirrhosis, emphasizing its potential limitations and future prospects.

In 1971, the first computed tomography (CT) scan was performed on a patient's brain. Clinical CT systems were introduced in 1974 and dedicated to head imaging only. New technological developments, broader availability, and the clinical success of CT led to a steady growth in examination numbers. Most frequent indications for non-contrast CT (NCCT) of the head include the assessment of ischemia and stroke, intracranial hemorrhage and trauma, while CT angiography (CTA) has become the standard for first-line cerebrovascular evaluation; however, resulting improvements in patient management and clinical outcomes come at the cost of radiation exposure, increasing the risk for secondary morbidity. Therefore, radiation dose optimization should always be part of technical advancements in CT imaging but how can the dose be optimized? What dose reduction can be achieved without compromising diagnostic value, and what is the potential of the upcoming technologies artificial intelligence and photon counting CT? In this article, we look for answers to these questions by reviewing dose reduction techniques with respect to the major clinical indications of NCCT and CTA of the head, including a brief perspective on what to expect from current and future developments in CT technology with respect to radiation dose optimization.

In chest computed tomography (CT), the breasts located within the scan range receive a substantial radiation dose. Due to the risk of breast-related carcinogenesis, analyzing the breast dose for justification of CT examinations seems necessary. The main goal of this study is to overcome the limitations of conventional dosimetry methods, such as thermoluminescent dosimeters (TLDs) by introducing the adaptive neuro-fuzzy inference system (ANFIS) approach. In this study, the breast dose of 50 adult female patients who underwent chest CT examinations was measured directly by TLDs. Then, the ANFIS model was developed with four inputs including dose length product (DLP), volumetric CT dose index (CTDIvol), total mAs, and size-specific dose estimate (SSDE), and one output (TLD dose). Additionally, multiple linear regression (MLR) as a traditional prediction model was used for linear modeling and its results were compared with the ANFIS. The TLD reader results showed that the breast dose value was 12.37 ± 2.46 mGy. Performance indices of the ANFIS model, including root mean square error (RMSE) and correlation coefficient (R), were calculated at 0.172 and 0.93 for the testing dataset, respectively. Also, the ANFIS model had superior performance in predicting the breast dose than the MLR model (R = 0.805). This study demonstrates that the proposed ANFIS model is efficient for patient dose prediction in CT scans. Therefore, intelligence models such as ANFIS are suggested to estimate and optimize patient dose in CT examinations.

This study investigated the feasibility of both a reduced radiation dose and a 50% of contrast dose in multiphasic CT of the liver with a 70 kVp protocol compared with a standard-tube-voltage protocol derived from dual-energy (DE) CT (blended DE protocol) with a full-dose contrast-agents in the same patient group. This study included 46 patients who underwent multiphasic contrast-enhanced dynamic CT of the liver with both a 70 kVp and a blended DE protocols. For quantitative analysis, median CT values for the liver, aorta, and portal vein, as well as signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), were measured and calculated. In addition, as a qualitative analysis, the contrast effect and overall image quality of the abdominal organs were evaluated on a five-point scale. CNR and SNR of the hepatic parenchyma were not significantly different between the 70kV protocol and the Blended DE protocol in all phases. The 70 kVp protocol showed significantly better image quality compared with the blended DE protocol in the arterial phase (p = 0.035) and the equilibrium layer phase (p = 0.016). A 70 kVp CT protocol in combination with a reduced radiation dose and half-dose iodine load is feasible for multiphasic dynamic CT of the liver by maintaining the contrast enhancement effects and image quality in comparison with the blended DE CT protocol.

To evaluate the efficacy of low-dose CT (LDCT) with deep learning image reconstruction (DLIR) for the surveillance of pancreatic cystic lesions (PCLs) compared with standard-dose CT (SDCT) with adaptive statistical iterative reconstruction (ASIR-V).

The study enrolled 103 patients who underwent pancreatic CT for follow-up of incidentally detected PCLs. The CT protocol included LDCT in the pancreatic phase with 40% ASIR-V, DLIR at medium (DLIR-M) and high levels (DLIR-H), and SDCT in the portal-venous phase with 40% ASIR-V. The overall image quality and conspicuity of PCLs were qualitatively assessed using five-point scales by two radiologists. The size of PCLs, presence of thickened/enhancing walls, enhancing mural nodules, and main pancreatic duct dilatation were reviewed. CT noise and cyst-to-pancreas contrast-to-noise ratio (CNR) were measured. Qualitative and quantitative parameters were analyzed using the chi-squared test, one-way ANOVA, and t-test. Additionally, interobserver agreement was analyzed using the kappa and weighted-kappa statistics.

The volume CT dose-indexes in LDCT and SDCT were 3.0 ± 0.6 mGy and 8.4 ± 2.9 mGy, respectively. LDCT with DLIR-H showed the highest overall image quality, the lowest noise, and the highest CNR. The PCL conspicuity in LDCT with either DLIR-M or DLIR-H was not significantly different from that in SDCT with ASIR-V. Other findings depicting PCLs also revealed no significant differences between LDCT with DLIR and SDCT with ASIR-V. Moreover, the results revealed good or excellent interobserver agreement.

LDCT with DLIR has a comparable performance with SDCT for the follow-up of incidentally detected PCLs.

Multi-detector computed tomography (MDCT) is the gold standard non-invasive tool for evaluating aortic root dimensions. We assessed the agreement between 4D TEE and MDCT-derived aortic valve annular dimensions, coronary ostia height, and minor dimensions of sinuses of Valsalva (SoV) and sinotubular junction (STJ). In this prospective analytical study, we measured the annular area, annular perimeter, area-derived diameter, area-derived perimeter, left and right coronary ostial heights, and minor diameters of the SoV and the STJ using ECG-gated MDCT and 4D TEE. TEE measurements were calculated semi-automatically by the eSie valve software. We enrolled 43 adult patients (27 males, median age: 46 years). We found strong correlations and good agreement between the two modalities in annular dimensions (area, perimeter, area-derived diameter, and perimeter-derived diameter), left coronary ostial height, minimum STJ diameter, and minimum SoV diameters. Moderate correlations, and agreement, with relatively large differences between the 95% LOA, were demonstrated for the right coronary artery ostial height. 4D TEE correlates well with MDCT in measuring aortic annular dimensions, coronary ostial height, SoV minor diameter, and sinotubular junction minor diameter. Whether this can affect clinical outcomes is unknown. It could replace MDCT if the latter is unavailable or contraindicated.

Little guidance exists on how to stratify radiation dose according to diagnostic task. Changing dose for different cancer types is currently not informed by the American College of Radiology Dose Index Registry dose survey.

A total of 9602 patient examinations were pulled from 2 National Cancer Institute designated cancer centers. Computed tomography dose (CTDI vol ) was extracted, and patient water equivalent diameter was calculated. N-way analysis of variance was used to compare the dose levels between 2 protocols used at site 1, and three protocols used at site 2.

Sites 1 and 2 both independently stratified their doses according to cancer indications in similar ways. For example, both sites used lower doses ( P < 0.001) for follow-up of testicular cancer, leukemia, and lymphoma. Median dose at median patient size from lowest to highest dose level for site 1 were 17.9 (17.7-18.0) mGy (mean [95% confidence interval]) and 26.8 (26.2-27.4) mGy. For site 2, they were 12.1 (10.6-13.7) mGy, 25.5 (25.2-25.7) mGy, and 34.2 (33.8-34.5) mGy. Both sites had higher doses ( P < 0.001) between their routine and high-image-quality protocols, with an increase of 48% between these doses for site 1 and 25% for site 2. High-image-quality protocols were largely applied for detection of low-contrast liver lesions or subtle pelvic pathology.

We demonstrated that 2 cancer centers independently choose to stratify their cancer doses in similar ways. Sites 1 and 2 dose data were higher than the American College of Radiology Dose Index Registry dose survey data. We thus propose including a cancer-specific subset for the dose registry.

The objective of this paper was to compute the effective dose, as well as the lifetime attributable risk (LAR) of cancer related to whole-body positron emission tomography (PET)/computed tomography (CT) scan for 193 adult patients. The mean effective dose for all patients from a single PET/CT scan was 20.6 mSv. For males aged 40 y, a single PET/CT scan is associated with a LAR of cancer incidence of 0.169%. This risk increased to 0.85% if an annual surveillance protocol for 5 y was performed. For female patients aged 40 y, the LAR of cancer mortality increased from 0.126 to 0.63% if an annual surveillance protocol for 5 y was performed. Since PET/CT scans are associated with a high dose and a risk of developing cancer, it was important to balance the advantages and risks before conducting any scans. This is especially important for younger patients and those who are overweight.

This prospective study aimed to present, compare, and evaluate the suitability of five different magnetic resonance imaging (MRI) protocols (3D double-echo steady-state (DESS), 3D fast spin echo short-tau inversion recovery (SPACE-STIR), 3D fast spin echo spectral attenuated inversion recovery (SPACE-SPAIR), volumetric interpolated breath-hold examination (T1-VIBE-Dixon), and ultrashort echo time (UTE)) and for orthopantomogram (OPG)-like MRI reconstructions using a novel mandibular coil. Three readers assessed MR-OPGs of 21 volunteers regarding technical image quality (4, excellent; 0, severely reduced), susceptibility to artifacts (3, absence; 0, massive), and visualization of anatomical structures in the oral cavity and surrounding skeletal structures (4, fine details visible; 0, no structures visible). Average image quality was good (3.29 ± 0.83) for all MRI protocols, with UTE providing the best image quality (3.52 ± 0.62) and no to minor artifacts (2.56 ± 0.6). Full diagnostic interpretability of the osseous structures is best in VIBE-Dixon and UTE MR-OPGs. DESS provided excellent visualization of the finest details of the nervous tissue (3.95 ± 0.22). Intra-reader and inter-reader agreement between the readers was good to excellent for all protocols (ICCs 0.812-0.957). MR-OPGs provide indication-specific accurate imaging of the oral cavity and could contribute to the early detection of pathologies, staging, and radiological follow-up of oral and maxillofacial diseases.

A retrospective study.

To assess the validity and reliability of cervical sagittal alignment parameters from multipositional magnetic resonance imaging (MRI) and dynamic cervical radiography.

Hospital in Suzhou, China.

Patients who underwent both multipositional MRI and dynamic plain radiography of the cervical spine within a 2-week interval between January 2013 and October 2021 were retrospectively enrolled in this study. The C2-7 angle, C2-7 cervical sagittal vertical axis (C2-7 SVA), T1 slope (T1S), cervical tilt, cranial tilt, and K-line tilt were measured in three different positions (neutral, flexion, and extension) with multipositional MRI and dynamic radiography. Inter- and intraobserver reliabilities were assessed by intraclass correlation coefficients (ICCs). Pearson correlation coefficients were used for statistical analyses.

A total of 65 (30 males and 35 females) patients with a mean age of 53.4 years (range 23-69 years) were retrospectively enrolled in this study. Significant positive correlations were noted regarding all parameters between the plain radiographs and multipositional MRI images. Inter- and intraobserver reliabilities were excellent for all cervical sagittal alignment parameters measured in the two imaging modalities. All cervical sagittal parameters had significant positive correlations with those from multipositional MRI in all three positions (p < 0.05). Pearson correlation coefficients demonstrated moderate and strong correlations between the two examinations.

Cervical sagittal alignment parameters measured on multipositional MRI could reliably substitute for those measured on plain radiographs. Multipositional MRI is a valuable, radiation-free alternative for diagnostic evaluation in degenerative cervical diseases.