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Okumura T, Koganezawa AS, Nakashima T, Ochi Y, Tsubouchi K, Murakami Y. Assessment of CT-to-physical density table for multiple image reconstruction functions with a large-bore scanner for radiotherapy treatment planning. Phys Med 2025; 133:104970. [PMID: 40187130 DOI: 10.1016/j.ejmp.2025.104970] [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] [Received: 03/28/2024] [Revised: 12/04/2024] [Accepted: 03/26/2025] [Indexed: 04/07/2025] Open
Abstract
PURPOSE To evaluate the performance of the Aquilion Exceed LB computed tomography (CT) scanner for radiotherapy treatment planning, this study examined the effect of different combinations of the image reconstruction function (IRF) (AiCE and AIDR) and scan parameters on the CT-to-physical density (CT-PD) table and radiation dose in the phantom, and the effect of different object positions on CT values. METHODS To investigate IRF's influence on each material, we calculated CT values by varying tube current, pitch, field of view (FOV), and phantom position for each IRF, comparing them with reference values using filtered back projection (FBP). Furthermore, we evaluated changes in depth dose values due to IRF differences using a solid phantom. RESULTS In the combinations of changes in IRF and scan parameters the change in CT value (ΔHU) of each material was within ±10 HU, except for most conditions. The change in physical density (ΔPD) was within ±0.02 g/cm3 for all combinations. For changes in phantom position, ΔHU was within ±25 HU for changes within the scan FOV, except for Bone 200 mg/cc and 1250 mg/cc. In areas outside the scan FOV with an expanded FOV, ΔHU was significantly larger than within the scan FOV. Variations in depth dose for different IRFs using solid phantoms were within ±0.5 %, except at material boundaries. CONCLUSION Our evaluations of the CT values and dose calculations suggested no need to change the CT-PD table, even with multiple IRFs.
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Affiliation(s)
- Takuro Okumura
- Department of Clinical Practice and Support, Hiroshima University Hospital, Hiroshima 734-8551, Japan
| | - Akito S Koganezawa
- Department of Information and Electronic Engineering, Faculty of Science and Engineering, Teikyo University, Tochigi 320-8551, Japan.
| | - Takeo Nakashima
- Department of Clinical Practice and Support, Hiroshima University Hospital, Hiroshima 734-8551, Japan
| | - Yusuke Ochi
- Department of Clinical Practice and Support, Hiroshima University Hospital, Hiroshima 734-8551, Japan
| | - Kento Tsubouchi
- Department of Clinical Practice and Support, Hiroshima University Hospital, Hiroshima 734-8551, Japan
| | - Yuji Murakami
- Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima 734-8551, Japan
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Abstract
ABSTRACT Computed tomography (CT) images display anatomic structures across 3 dimensions and are highly quantitative; they are the reference standard for 3-dimensional geometric measurements and are used for 3-dimensional printing of anatomic models and custom implants, as well as for radiation therapy treatment planning. The pixel intensity in CT images represents the linear x-ray attenuation coefficient of the imaged materials after linearly scaling the coefficients into a quantity known as CT numbers that is conveyed in Hounsfield units. When measured with the same scanner model, acquisition, and reconstruction parameters, the mean CT number of a material is highly reproducible, and quantitative applications of CT scanning that rely on the measured CT number, such as for assessing bone mineral density or coronary artery calcification, are well established. However, the strong dependence of CT numbers on x-ray beam spectra limits quantitative applications and standardization from achieving robust widespread success. This article reviews several quantitative applications of CT and the challenges they face, and describes the benefits brought by photon-counting detector (PCD) CT technology. The discussed benefits of PCD-CT include that it is inherently multienergy, expands material decomposition capabilities, and improves spatial resolution and geometric quantification. Further, the utility of virtual monoenergetic images to standardize CT numbers is discussed, as virtual monoenergetic images can be the default image type in PCD-CT due to the full-time spectral nature of the technology.
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Affiliation(s)
- Cynthia H. McCollough
- Department of Radiology, Mayo Clinic, 200 First St SW Rochester, MN, United States 55905
| | - Kishore Rajendran
- Department of Radiology, Mayo Clinic, 200 First St SW Rochester, MN, United States 55905
| | - Shuai Leng
- Department of Radiology, Mayo Clinic, 200 First St SW Rochester, MN, United States 55905
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Al-Hayek Y, Spuur K, Davidson R, Hayre C, Zheng X. The impacts of vertical off-centring, tube voltage, and phantom size on computed tomography numbers: An experimental study. Radiography (Lond) 2022; 28:641-647. [PMID: 35569317 DOI: 10.1016/j.radi.2022.04.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 04/18/2022] [Accepted: 04/23/2022] [Indexed: 10/18/2022]
Abstract
INTRODUCTION This experimental study explored the effect of vertical off-centring on computed tomography (CT) numbers in combination with various tube voltages and phantom sizes for two CT units. METHODS CIRS Model 062 Electron Density and system performance phantoms were imaged on Siemens Emotion 16-slice CT and GEMINI-GXL scanners, respectively. Uniformity and accuracy were evaluated as a function of vertical off-centring (20, 40, 60, and 80 mm above the gantry isocentre) using different water phantom sizes (18, 20, and 30 cm) and tube voltages (80, 90, 110, 120, 130 and 140 kVp). RESULTS Vertical off-centring and phantom size accounted for 92% of the recorded variance and the resultant change in CT numbers. The uniformity test recorded maximum changes of 14 and 27.2 HU for peripheral ROIs across the X- and Y-axes for an 80 mm phantom shift above the gantry isocentre on the GEMINI GXL and Siemens scanners, respectively. The absolute CT number differences between the superior and inferior ROIs were 13.7 HU for the 30 cm phantom and 4.8 HU for the 20 cm phantom for 80 mm vertical off-centring. The largest differences were observed at lower tube voltages. CONCLUSIONS It is essential to highlight the significance of CT number variation in clinical decision-making. Phantom off-centring affected the uniformity of these numbers, which were further impacted by the ROI position in this experimental study. CT number variation was more evident in peripheral phantom areas, lower tube voltages and larger phantom sizes. IMPLICATIONS FOR PRACTICE CT number is observed to be a variable under certain common conditions. This significantly impacts several applications where clinical decisions depend on CT number accuracy for tissue lesion characterisation.
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Affiliation(s)
- Y Al-Hayek
- School of Dentistry and Medical Sciences, Faculty of Science and Health, Charles Sturt University, Wagga Wagga, NSW 2650, Australia; Department of Medical Imaging, Faculty of Applied Health Sciences, The Hashemite University, Zarqa 13133, Jordan.
| | - K Spuur
- School of Dentistry and Medical Sciences, Faculty of Science and Health, Charles Sturt University, Wagga Wagga, NSW 2650, Australia.
| | - R Davidson
- School of Health Sciences, Faculty of Health, University of Canberra, Canberra, ACT 2601, Australia.
| | - C Hayre
- School of Dentistry and Medical Sciences, Faculty of Science and Health, Charles Sturt University, Wagga Wagga, NSW 2650, Australia.
| | - X Zheng
- School of Dentistry and Medical Sciences, Faculty of Science and Health, Charles Sturt University, Wagga Wagga, NSW 2650, Australia.
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Magat G, Oncu E, Ozcan S, Orhan K. Comparison of cone-beam computed tomography and digital panoramic radiography for detecting peri-implant alveolar bone changes using trabecular micro-structure analysis. J Korean Assoc Oral Maxillofac Surg 2022; 48:41-49. [PMID: 35221306 PMCID: PMC8890962 DOI: 10.5125/jkaoms.2022.48.1.41] [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: 08/02/2021] [Revised: 09/13/2021] [Accepted: 09/28/2021] [Indexed: 11/07/2022] Open
Abstract
Objectives We compared changes in fractal dimension (FD) and grayscale value (GSV) of peri-implant alveolar bone on digital panoramic radiography (DPR) and cone-beam computed tomography (CBCT) immediately after implant surgery and 12 months postoperative. Materials and Methods In this retrospective study, 16 patients who received posterior mandibular area dental implants with CBCT scans taken about 2 weeks after implantation and one year after implantation were analyzed. A region of interest was selected for each patient. FDs and GSVs were evaluated immediately after implant surgery and at 12-month follow-up to examine the functional loading of the implants. Results There were no significant differences between DPR and CBCT measurements of FD values (P>0.05). No significant differences were observed between FD values and GSVs calculated after implant surgery and at the 12-month follow-up (P>0.05). GSVs were not correlated with FD values (P>0.05). Conclusion The DPR and reconstructed panoramic CBCT images exhibit similar image quality for the assessment of FD. There were no changes in FD values or GSVs of the peri-implant trabecular bone structure at the 12-month postoperative evaluation of the functional loading of the implant in comparison to values immediately after implantation. GSVs representing bone mass do not align with FD values that predict bone microstructural parameters. Therefore, GSVs and FDs should be considered different parameters for assessing bone quality.
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Affiliation(s)
- Guldane Magat
- Department of Oral and Maxillofacial Radiology, Konya, Turkey
| | - Elif Oncu
- Department of Periodontology, Faculty of Dentistry, Necmettin Erbakan University, Konya, Turkey
| | - Sevgi Ozcan
- Department of Oral and Maxillofacial Radiology, Konya, Turkey
| | - Kaan Orhan
- Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Ankara University, Ankara, Turkey
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Li Y, Tan G, Vangel M, Hall J, Cai W. Influence of feature calculating parameters on the reproducibility of CT radiomic features: a thoracic phantom study. Quant Imaging Med Surg 2020; 10:1775-1785. [PMID: 32879856 DOI: 10.21037/qims-19-921] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Background Existing studies have demonstrated that imaging parameters may affect radiomic features. However, the influence of feature calculating parameters has been overlooked. The purpose of this study is to investigate the influence of feature calculating parameters (gray-level range and bin size) on the reproducibility of CT radiomic features. Methods Thirty-six CT scans from an anthropomorphic thoracic phantom were acquired with different imaging parameters including effective dose, pitch, slice thicknesses and reconstruction kernels. The influence of feature calculating parameters was investigated in terms of three gray-level ranges and eleven gray-level bin sizes. Feature reproducibility was assessed by the intraclass correlation coefficient (ICC) with the cutoff value of 0.8 and the coefficient of variation (CV) with the cutoff value of 20%. The agreements of reproducible features in different ranges and bin sizes were analyzed by Kendall's W test and Kappa test. The proportions of reproducible features, in terms of two calculating, four imaging and two segmentation parameters, were evaluated using Cochran's Q test and Dunn's test. Results For the three gray-level ranges, 50% (44/88) of features were reproducible with a perfect agreement (Kendall's W coefficient 0.844, P<0.001). Of the 72 features that may be influenced by gray-level bin size, 33.3% (24/72) were reproducible for 11 bin sizes with a perfect agreement (Kendall's W coefficient 0.879, P<0.001). For the proportions of reproducible features, there was no statistically significant difference among three ranges (P=0.420), but there was among eleven bin sizes (P=0.013). The proportions of reproducible features in feature calculating parameters were statistically significantly lower than those in imaging parameters (adjusted P<0.05). Conclusions Feature calculating parameters may have a greater influence than imaging parameters on the reproducibility of CT radiomic features, which should be given special attention in clinical applications.
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Affiliation(s)
- Ying Li
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Guanghua Tan
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Mark Vangel
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Jonathan Hall
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.,Department of Computer and Electrical Engineering, Boston University, Boston, MA, USA
| | - Wenli Cai
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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Gong Q, Li Q, Gavrielides MA, Petrick N. Data transformations for statistical assessment of quantitative imaging biomarkers: Application to lung nodule volumetry. Stat Methods Med Res 2020; 29:2749-2763. [PMID: 32133924 DOI: 10.1177/0962280220908619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Variance stabilization is an important step in the statistical assessment of quantitative imaging biomarkers. The objective of this study is to compare the Log and the Box-Cox transformations for variance stabilization in the context of assessing the performance of a particular quantitative imaging biomarker, the estimation of lung nodule volume from computed tomography images. First, a model is developed to generate and characterize repeated measurements typically observed in computed tomography lung nodule volume estimation. Given this model, we derive the parameter of the Box-Cox transformation that stabilizes the variance of the measurements across lung nodule volumes. Second, simulated, phantom, and clinical datasets are used to compare the Log and the Box-Cox transformations. Two metrics are used for quantifying the stability of the measurements across the transformed lung nodule volumes: the coefficient of variation for the standard deviation and the repeatability coefficient. The results for simulated, phantom, and clinical datasets show that the Box-Cox transformation generally had better variance stabilization performance compared to the Log transformation for lung nodule volume estimates from computed tomography scans.
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Affiliation(s)
- Qi Gong
- US Food and Drug Administration, CDRH/OSEL/DIDSR, Silver Spring, MD, USA
| | - Qin Li
- US Food and Drug Administration, CDRH/OSEL/DIDSR, Silver Spring, MD, USA
| | | | - Nicholas Petrick
- US Food and Drug Administration, CDRH/OSEL/DIDSR, Silver Spring, MD, USA
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A Novel Computer-Aided Diagnosis Scheme on Small Annotated Set: G2C-CAD. BIOMED RESEARCH INTERNATIONAL 2019; 2019:6425963. [PMID: 31119180 PMCID: PMC6500711 DOI: 10.1155/2019/6425963] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 03/05/2019] [Indexed: 11/18/2022]
Abstract
Purpose Computer-aided diagnosis (CAD) can aid in improving diagnostic level; however, the main problem currently faced by CAD is that it cannot obtain sufficient labeled samples. To solve this problem, in this study, we adopt a generative adversarial network (GAN) approach and design a semisupervised learning algorithm, named G2C-CAD. Methods From the National Cancer Institute (NCI) Lung Image Database Consortium (LIDC) dataset, we extracted four types of pulmonary nodule sign images closely related to lung cancer: noncentral calcification, lobulation, spiculation, and nonsolid/ground-glass opacity (GGO) texture, obtaining a total of 3,196 samples. In addition, we randomly selected 2,000 non-lesion image blocks as negative samples. We split the data 90% for training and 10% for testing. We designed a DCGAN generative adversarial framework and trained it on the small sample set. We also trained our designed CNN-based fuzzy Co-forest on the labeled small sample set and obtained a preliminary classifier. Then, coupled with the simulated unlabeled samples generated by the trained DCGAN, we conducted iterative semisupervised learning, which continually improved the classification performance of the fuzzy Co-forest until the termination condition was reached. Finally, we tested the fuzzy Co-forest and compared its performance with that of a C4.5 random decision forest and the G2C-CAD system without the fuzzy scheme, using ROC and confusion matrix for evaluation. Results Four different types of lung cancer-related signs were used in the classification experiment: noncentral calcification, lobulation, spiculation, and nonsolid/ground-glass opacity (GGO) texture, along with negative image samples. For these five classes, the G2C-CAD system obtained AUCs of 0.946, 0.912, 0.908, 0.887, and 0.939, respectively. The average accuracy of G2C-CAD exceeded that of the C4.5 random decision tree by 14%. G2C-CAD also obtained promising test results on the LISS signs dataset; its AUCs for GGO, lobulation, spiculation, pleural indentation, and negative image samples were 0.972, 0.964, 0.941, 0.967, and 0.953, respectively. Conclusion The experimental results show that G2C-CAD is an appropriate method for addressing the problem of insufficient labeled samples in the medical image analysis field. Moreover, our system can be used to establish a training sample library for CAD classification diagnosis, which is important for future medical image analysis.
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Fang R, Mazur T, Mutic S, Khan R. The impact of mass density variations on an electron Monte Carlo algorithm for radiotherapy dose calculations. PHYSICS & IMAGING IN RADIATION ONCOLOGY 2018; 8:1-7. [PMID: 33458409 PMCID: PMC7807677 DOI: 10.1016/j.phro.2018.10.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/08/2018] [Revised: 10/19/2018] [Accepted: 10/23/2018] [Indexed: 01/21/2023]
Abstract
Background and Purpose A key step in electron Monte Carlo dose calculation requires converting Computed Tomography (CT) numbers from a tomographic acquisition to a mass density. This study investigates the dosimetric consequences of perturbations applied to a calibration table between CT number and mass density. Materials and Methods A literature search was performed to define lower and upper bounds for physically reasonable perturbations to a reference CT number to mass density calibration table. Electron beam dose was calculated for ten patients using these variations and the results were compared to clinical plans originally derived with a reference calibration table. Dose differences both globally and in the Planning Target Volume (PTV) were assessed using dose- and volume-based metrics and 3- dimensional gamma analysis for each patient. Results Small but statistically significant differences were observed between perturbations and reference data for certain metrics including volume of the 50% prescription isodose. Upper and lower variations in CT number to mass density calibration yielded mean values of V50% that were 4.4% larger and 2.1% smaller than reference values respectively. Gamma analysis using 3%/3mm criteria indicated >99% passing rate for the PTV for all patients. Global gamma analysis for some patients showed larger discrepancies possibly due to large electron path lengths through inhomogeneities. Conclusions In most patients, physically reasonable perturbations in CT number to mass density curves will not induce clinically significant impact on calculated target dose distributions. Strong dependence of electron transport on voxel material may produce dose speckle throughout the volume. Care should be taken in evaluating critical structures at depths beyond the target volume in highly heterogeneous regions.
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Affiliation(s)
- Raymond Fang
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA
| | - Thomas Mazur
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA
| | - Sasa Mutic
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA
| | - Rao Khan
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA
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CT spectral parameters and serum tumour markers to differentiate histological types of cancer histology. Clin Radiol 2018; 73:1033-1040. [PMID: 30115364 DOI: 10.1016/j.crad.2018.07.104] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2018] [Accepted: 07/11/2018] [Indexed: 11/23/2022]
Abstract
AIM To evaluate lung cancer histology type using computed tomography (CT) spectral quantitative parameters combining with serum tumour markers. MATERIALS AND METHODS Patients with suspicious lung cancer underwent CT spectral imaging and serum tumour markers. CT spectral quantitative parameters including attenuation value, the slope of spectral curve (λ), iodine concentration, water concentration, and effective atomic number (Zeff) were acquired. Serum levels of tumour markers including carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), squamous cell carcinoma antigen (SCC-Ag), and cytokeratin fragment CYFRA21-1 were also obtained. All the values were compared among different histological types of lung cancer. The diagnostic efficiencies of serum tumour markers, CT spectral parameters, and a combination of them were computed by statistical analysis. RESULTS CEA and NSE levels were higher in adenocarcinoma and neuroendocrine tumour, respectively, while SCC-Ag and CYFRA21-1 levels were higher in squamous cell cancer. There was no significant difference in attenuation among the groups (p>0.05), whereas λ in the arterial phase, and Zeff and IC in both the arterial and venous phases were significantly different among groups (p<0.05). According to the area under the receiver operating characteristic (ROC) curve (AUC) and Youden's index, the diagnostic efficiency of serum tumour markers were higher than that of CT spectral parameters. Moreover, AUCs of combined serum and CT indicators were larger than that of combined serum markers and combined CT spectral parameters between squamous cell cancer and adenocarcinoma as well as between squamous cell cancer and neuroendocrine tumour. CONCLUSION CT spectral quantitative parameters and serum tumour markers are valuable in evaluating histological types of lung cancer. In combination they can significantly improve diagnostic efficiency.
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Abstract
The present study aimed to evaluate the application of gemstone spectral imaging (GSI) for multi-parameter quantitative measurement in lung cancer.The study retrospectively enrolled 30 patients with lung cancer who underwent chest contrast enhanced CT scan with GSI mode. The GSI viewer was used for image display and data analysis. Optimal energy value, CT values at 40 keV, 70 keV and optimal energy level, spectral curve slope, effective atomic number (Zeff), iodine concentration (IC), and water concentration (WC) at the region of interest were measured and analyzed by statistical methods.The optimal energy value for optimal contrast-to-noise ratio on plain scan, arterial phase and venous phase was 62.2 ± 5.38 keV, 50.63 ± 3.84 keV, and 52.5 ± 3.7 keV, respectively. There were significant differences in CT values at different energy levels on each scan phase (P = .033). The spectral curve slope values among 40 to 70 keV, 40 to 100 keV, and 40 to 140 keV were significantly different (P < .001). No significant difference with the slope between arterial phase and venous phase at each energy level interval was observed. Zeff on plain scan, arterial phase, and venous phase was 7.75 ± 0.15, 8.38 ± 0.37, and 8.38 ± 0.30, respectively. Positive correlation was observed among IC, normalized IC, and Zeff on enhanced scan.Multiparameter of GSI can be used for lung tumor lesion evaluation. Different parameters were correlated and provide multiple qualitative and quantitative information together.
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Affiliation(s)
- Yulin Jia
- Department of Imaging and Nuclear Medicine
| | - Xigang Xiao
- Department of Radiology, the First Affiliated Hospital
| | - Qiulian Sun
- Department of Radiology, the First Affiliated Hospital
| | - Huijie Jiang
- Department of Radiology, the Second Affiliated Hospital, Harbin Medical University, Harbin, Heilongjiang, China
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Vlahos I, Stefanidis K, Sheard S, Nair A, Sayer C, Moser J. Lung cancer screening: nodule identification and characterization. Transl Lung Cancer Res 2018; 7:288-303. [PMID: 30050767 DOI: 10.21037/tlcr.2018.05.02] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The accurate identification and characterization of small pulmonary nodules at low-dose CT is an essential requirement for the implementation of effective lung cancer screening. Individual reader detection performance is influenced by nodule characteristics and technical CT parameters but can be improved by training, the application of CT techniques, and by computer-aided techniques. However, the evaluation of nodule detection in lung cancer screening trials differs from the assessment of individual readers as it incorporates multiple readers, their inter-observer variability, reporting thresholds, and reflects the program accuracy in identifying lung cancer. Understanding detection and interpretation errors in screening trials aids in the implementation of lung cancer screening in clinical practice. Indeed, as CT screening moves to ever lower radiation doses, radiologists must be cognisant of new technical challenges in nodule assessment. Screen detected lung cancers demonstrate distinct morphological features from incidentally or symptomatically detected lung cancers. Hence characterization of screen detected nodules requires an awareness of emerging concepts in early lung cancer appearances and their impact on radiological assessment and malignancy prediction models. Ultimately many nodules remain indeterminate, but further imaging evaluation can be appropriate with judicious utilization of contrast enhanced CT or MRI techniques or functional evaluation by PET-CT.
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Affiliation(s)
- Ioannis Vlahos
- St George's NHS Foundation Hospitals Trust and School of Medicine, London, UK
| | | | | | - Arjun Nair
- Guy's and St Thomas' Hospital NHS Foundation Trust, London, UK
| | - Charles Sayer
- Brighton and Sussex University Hospitals Trust, Haywards Heath, UK
| | - Joanne Moser
- St George's NHS Foundation Hospitals Trust and School of Medicine, London, UK
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Larici AR, Farchione A, Franchi P, Ciliberto M, Cicchetti G, Calandriello L, del Ciello A, Bonomo L. Lung nodules: size still matters. Eur Respir Rev 2017; 26:26/146/170025. [DOI: 10.1183/16000617.0025-2017] [Citation(s) in RCA: 62] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2017] [Accepted: 10/28/2017] [Indexed: 12/18/2022] Open
Abstract
The incidence of indeterminate pulmonary nodules has risen constantly over the past few years. Determination of lung nodule malignancy is pivotal, because the early diagnosis of lung cancer could lead to a definitive intervention. According to the current international guidelines, size and growth rate represent the main indicators to determine the nature of a pulmonary nodule. However, there are some limitations in evaluating and characterising nodules when only their dimensions are taken into account. There is no single method for measuring nodules, and intrinsic errors, which can determine variations in nodule measurement and in growth assessment, do exist when performing measurements either manually or with automated or semi-automated methods. When considering subsolid nodules the presence and size of a solid component is the major determinant of malignancy and nodule management, as reported in the latest guidelines. Nevertheless, other nodule morphological characteristics have been associated with an increased risk of malignancy. In addition, the clinical context should not be overlooked in determining the probability of malignancy. Predictive models have been proposed as a potential means to overcome the limitations of a sized-based assessment of the malignancy risk for indeterminate pulmonary nodules.
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Variation in CT Number and Image Noise Uniformity According to Patient Positioning in MDCT. AJR Am J Roentgenol 2017; 208:1064-1072. [PMID: 28267350 DOI: 10.2214/ajr.16.17215] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
OBJECTIVE Many algorithms for clinical decision making rely on assessment of the CT number (expressed as Hounsfield units); however, to our knowledge, few, if any, studies have addressed how CT numbers change as a function of patient positioning within the scanner. MATERIALS AND METHODS An anthropomorphic phantom underwent imaging with varying amounts of vertical orientation misalignment with respect to isocenter. CT number and noise were measured using ROIs in the upper thorax, mid thorax, and abdomen. The degree of noise nonuniformity and changes in the CT number were assessed by comparing values obtained in the anterior versus posterior ROIs. To add clinical relevance, data on vertical mispositioning were collected from 20,316 clinical abdominal CT scans. Box-and-whisker plot analysis was used to identify the range of patient positioning. RESULTS Absolute CT number changes of more than 20 HU were observed for some ROIs at phantom positions of 10 cm from isocenter, with important differences noted between the thoracic and abdominal regions. Noise uniformity varied by more than twofold for all regions at 10 cm below isocenter. On clinical CT examinations, off-centering of more than 1, 2, 4, and 6 cm occurred for 41%, 19%, 1.9%, and 0.3% of patients, respectively. CONCLUSION Radiologists should treat CT number measurements with caution when patients are grossly mispositioned in the scanner. The substantial changes in attenuation values shown in the present study are large enough to warrant further investigation.
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Schmitt SM, Goodsitt MM, Fessler JA. Fast Variance Prediction for Iteratively Reconstructed CT Images With Locally Quadratic Regularization. IEEE TRANSACTIONS ON MEDICAL IMAGING 2017; 36:17-26. [PMID: 27448342 PMCID: PMC5217761 DOI: 10.1109/tmi.2016.2593259] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Predicting noise properties of iteratively reconstructed CT images is useful for analyzing reconstruction methods; for example, local noise power spectrum (NPS) predictions may be used to quantify the detectability of an image feature, to design regularization methods, or to determine dynamic tube current adjustment during a CT scan. This paper presents a method for fast prediction of reconstructed image variance and local NPS for statistical reconstruction methods using quadratic or locally quadratic regularization. Previous methods either require impractical computation times to generate an approximate map of the variance of each reconstructed voxel, or are restricted to specific CT geometries. Our method can produce a variance map of the entire image, for locally shift-invariant CT geometries with sufficiently fine angular sampling, using a computation time comparable to a single back-projection. The method requires only the projection data to be used in the reconstruction, not a reconstruction itself, and is reasonably accurate except near image edges where edge-preserving regularization behaves highly nonlinearly. We evaluate the accuracy of our method using reconstructions of both simulated CT data and real CT scans of a thorax phantom.
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Ma X, Siegelman J, Paik DS, Mulshine JL, St Pierre S, Buckler AJ. Volumes Learned: It Takes More Than Size to "Size Up" Pulmonary Lesions. Acad Radiol 2016; 23:1190-8. [PMID: 27287713 DOI: 10.1016/j.acra.2016.04.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2015] [Revised: 04/08/2016] [Accepted: 04/10/2016] [Indexed: 12/17/2022]
Abstract
RATIONALE AND OBJECTIVES This study aimed to review the current understanding and capabilities regarding use of imaging for noninvasive lesion characterization and its relationship to lung cancer screening and treatment. MATERIALS AND METHODS Our review of the state of the art was broken down into questions about the different lung cancer image phenotypes being characterized, the role of imaging and requirements for increasing its value with respect to increasing diagnostic confidence and quantitative assessment, and a review of the current capabilities with respect to those needs. RESULTS The preponderance of the literature has so far been focused on the measurement of lesion size, with increasing contributions being made to determine the formal performance of scanners, measurement tools, and human operators in terms of bias and variability. Concurrently, an increasing number of investigators are reporting utility and predictive value of measures other than size, and sensitivity and specificity is being reported. Relatively little has been documented on quantitative measurement of non-size features with corresponding estimation of measurement performance and reproducibility. CONCLUSIONS The weight of the evidence suggests characterization of pulmonary lesions built on quantitative measures adds value to the screening for, and treatment of, lung cancer. Advanced image analysis techniques may identify patterns or biomarkers not readily assessed by eye and may also facilitate management of multidimensional imaging data in such a way as to efficiently integrate it into the clinical workflow.
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Affiliation(s)
- Xiaonan Ma
- Elucid Bioimaging Inc., 225 Main Street, Wenham, MA 01984.
| | - Jenifer Siegelman
- Department of Radiology, Brigham and Women's Hospital, Boston Massachusetts; Department of Radiology (hospital-based), Harvard Medical School, Boston, Massachusetts
| | - David S Paik
- Elucid Bioimaging Inc., 225 Main Street, Wenham, MA 01984
| | - James L Mulshine
- Department of Internal Medicine, Rush University, Chicago, Illinois
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Buckler AJ, Danagoulian J, Johnson K, Peskin A, Gavrielides MA, Petrick N, Obuchowski NA, Beaumont H, Hadjiiski L, Jarecha R, Kuhnigk JM, Mantri N, McNitt-Gray M, Moltz JH, Nyiri G, Peterson S, Tervé P, Tietjen C, von Lavante E, Ma X, St Pierre S, Athelogou M. Inter-Method Performance Study of Tumor Volumetry Assessment on Computed Tomography Test-Retest Data. Acad Radiol 2015; 22:1393-408. [PMID: 26376841 PMCID: PMC4609285 DOI: 10.1016/j.acra.2015.08.007] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2015] [Revised: 07/31/2015] [Accepted: 08/07/2015] [Indexed: 11/20/2022]
Abstract
RATIONALE AND OBJECTIVES Tumor volume change has potential as a biomarker for diagnosis, therapy planning, and treatment response. Precision was evaluated and compared among semiautomated lung tumor volume measurement algorithms from clinical thoracic computed tomography data sets. The results inform approaches and testing requirements for establishing conformance with the Quantitative Imaging Biomarker Alliance (QIBA) Computed Tomography Volumetry Profile. MATERIALS AND METHODS Industry and academic groups participated in a challenge study. Intra-algorithm repeatability and inter-algorithm reproducibility were estimated. Relative magnitudes of various sources of variability were estimated using a linear mixed effects model. Segmentation boundaries were compared to provide a basis on which to optimize algorithm performance for developers. RESULTS Intra-algorithm repeatability ranged from 13% (best performing) to 100% (least performing), with most algorithms demonstrating improved repeatability as the tumor size increased. Inter-algorithm reproducibility was determined in three partitions and was found to be 58% for the four best performing groups, 70% for the set of groups meeting repeatability requirements, and 84% when all groups but the least performer were included. The best performing partition performed markedly better on tumors with equivalent diameters greater than 40 mm. Larger tumors benefitted by human editing but smaller tumors did not. One-fifth to one-half of the total variability came from sources independent of the algorithms. Segmentation boundaries differed substantially, not ony in overall volume but also in detail. CONCLUSIONS Nine of the 12 participating algorithms pass precision requirements similar to what is indicated in the QIBA Profile, with the caveat that the present study was not designed to explicitly evaluate algorithm profile conformance. Change in tumor volume can be measured with confidence to within ±14% using any of these nine algorithms on tumor sizes greater than 10 mm. No partition of the algorithms was able to meet the QIBA requirements for interchangeability down to 10 mm, although the partition comprising best performing algorithms did meet this requirement for a tumor size of greater than approximately 40 mm.
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Affiliation(s)
| | | | | | - Adele Peskin
- National Institute of Standards and Technology, Boulder, Colorado
| | | | | | | | | | - Lubomir Hadjiiski
- Department of Radiology, University of Michigan, Ann Arbor, Michigan
| | - Rudresh Jarecha
- Perceptive Informatics, Sundew Properties SEZ Pvt Ltd Mindspace, Hyderabad, Andhra Pradesh, India
| | - Jan-Martin Kuhnigk
- Fraunhofer MEVIS, Institute for Medical Image Computing, Bremen, Germany
| | | | - Michael McNitt-Gray
- Department of Radiology, University of California at Los Angeles, Los Angeles, California
| | - Jan H Moltz
- Fraunhofer MEVIS, Institute for Medical Image Computing, Bremen, Germany
| | | | | | | | - Christian Tietjen
- Siemens AG, Healthcare Sector, Imaging and Therapy Division, Forchheim, Germany
| | | | - Xiaonan Ma
- Elucid Bioimaging Inc., 225 Main Street, Wenham, MA 01984
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Campos MJDS, de Souza TS, Mota Júnior SL, Fraga MR, Vitral RWF. Bone mineral density in cone beam computed tomography: Only a few shades of gray. World J Radiol 2014; 6:607-12. [PMID: 25170398 PMCID: PMC4147441 DOI: 10.4329/wjr.v6.i8.607] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2013] [Revised: 03/11/2014] [Accepted: 04/25/2014] [Indexed: 02/06/2023] Open
Abstract
Cone beam computed tomography (CBCT) has often been used to determine the quality of craniofacial bone structures through the determination of mineral density, which is based on gray scales of the images obtained. However, there is no consensus regarding the accuracy of the determination of the gray scales in these exams. This study aims to provide a literature review concerning the reliability of CBCT to determine bone mineral density. The gray values obtained with CBCT show a linear relationship with the attenuation coefficients of the materials, Hounsfield Units values obtained with medical computed tomography, and density values from dual energy X-ray absorciometry. However, errors are expected when CBCT images are used to define the quality of the scanned structures because these images show inconsistencies and arbitrariness in the gray values, particularly when related to abrupt change in the density of the object, X-ray beam hardening effect, scattered radiation, projection data discontinuity-related effect, differences between CBCT devices, changes in the volume of the field of view (FOV), and changes in the relationships of size and position between the FOV and the object evaluated. A few methods of mathematical correction of the gray scales in CBCT have been proposed; however, they do not generate consistent values that are independent of the devices and their configurations or of the scanned objects. Thus, CBCT should not be considered the examination of choice for the determination of bone and soft tissue mineral density at the current stage, particularly when values obtained are to be compared to predetermined standard values. Comparisons between symmetrically positioned structures inside the FOV and in relation to the exomass of the object, as it occurs with the right and left sides of the skull, seem to be viable because the effects on the gray scale in the regions of interest are the same.
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Hashemi S, Mehrez H, Cobbold RSC, Paul NS. Optimal image reconstruction for detection and characterization of small pulmonary nodules during low-dose CT. Eur Radiol 2014; 24:1239-50. [PMID: 24658869 DOI: 10.1007/s00330-014-3142-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2013] [Revised: 02/18/2014] [Accepted: 03/04/2014] [Indexed: 12/21/2022]
Affiliation(s)
- SayedMasoud Hashemi
- Institute of Biomaterial and Biomedical Engineering, University of Toronto, Room RS-420A, 164 College Street, Toronto, ON, Canada, M5S 3G9
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20
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Zhao LQ, He W, Yan B, Wang HY, Wang J. The evaluation of haemodynamics in cirrhotic patients with spectral CT. Br J Radiol 2013; 86:20130228. [PMID: 23881800 DOI: 10.1259/bjr.20130228] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE To evaluate haemodynamics in cirrhotic patients with portal hypertension using spectral CT imaging. METHODS 118 cirrhotic patients with portal hypertension were included in the study group (further divided into Child-Pugh A, B and C subgroups). The control group consisted of 21 subjects with normal liver functionality. All subjects underwent three-phase spectral CT scans. Material decomposition images with water and iodine as basis material pairs were reconstructed. The iodine concentrations for the hepatic parenchyma in both arterial and portal venous phases were measured. The arterial iodine fraction (AIF) was obtained by dividing the iodine concentration in the hepatic arterial phase by that in the portal venous phase. AIF values from the study and control groups were compared using analysis of variance and between subgroups using a post-hoc test with Bonferroni correction, with a statistical significance of p<0.05. RESULTS The AIF was 0.25±0.05 in the control group, and 0.29±0.10, 0.37±0.12 and 0.43±0.14 in the study group with Child-Pugh Grades A, B and C, respectively. The difference in AIF between the control and study groups was statistically significant. The differences were statistically significant between the subgroups with multiple comparisons except between the control group and the Child-Pugh A group (p=0.685). CONCLUSION AIF measured in spectral CT could be used to evaluate the liver haemodynamics of cirrhotic patients. ADVANCES IN KNOWLEDGE The AIF, provided by spectral CT, could be used as a new parameter to observe liver haemodynamics.
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Affiliation(s)
- L-Q Zhao
- Department of Radiology, Beijing Friendship Hospital Affiliated to Capital Medical University, Beijing, China
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21
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Guerriero S, Pilloni M, Alcazar JL, Sedda F, Ajossa S, Mais V, Melis GB, Saba L. Tissue characterization using mean gray value analysis in deep infiltrating endometriosis. ULTRASOUND IN OBSTETRICS & GYNECOLOGY : THE OFFICIAL JOURNAL OF THE INTERNATIONAL SOCIETY OF ULTRASOUND IN OBSTETRICS AND GYNECOLOGY 2013; 41:459-464. [PMID: 22915525 DOI: 10.1002/uog.12292] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/31/2012] [Indexed: 06/01/2023]
Abstract
OBJECTIVES To investigate differences in tissue characterization using three-dimensional sonographic mean gray value (MGV) between retrocervical and rectosigmoid deeply infiltrating endometriosis, and to assess intra- and interobserver concordance in MGV quantification. METHODS In this retrospective study, stored ultrasound volumes from 50 premenopausal women (mean age, 32 years) with 57 histologically confirmed nodules of deep endometriosis were retrieved from our database for analysis. A single experienced operator had acquired all volumes. For each nodule, the MGV was evaluated using virtual organ computer-aided analysis (VOCAL) software with semiautomated sphere-sampling (1 cm3) from the central part of the nodule. In these patients the MGV was also quantified from the myometrium of the fundal part of the uterus. In addition, two observers calculated the MGV in a subset of 24 volumes in order to quantify inter- and intraobserver agreement using intraclass correlation coefficients (ICC). RESULTS Mean MGV was significantly higher in rectosigmoid nodules (n = 34) than in nodules with a retrocervical location (n = 23) (23.863 vs. 17.705; P < 0.001). MGV of the myometrium was significantly higher in comparison with that of nodules in both locations (P < 0.001 for both). Intra- and interobserver measurement reproducibility was excellent (ICC > 0.95). CONCLUSIONS Retrocervical and rectosigmoid endometriotic nodules display significantly different MGVs. Measurement of MGV is highly reproducible and its clinical value in the diagnosis and assessment of distribution of deep endometriosis should be assessed in future studies.
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Affiliation(s)
- S Guerriero
- Department of Obstetrics and Gynaecology, Azienda Ospedaliero Universitaria di Cagliari, Cagliari, Italy
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Pakdel A, Robert N, Fialkov J, Maloul A, Whyne C. Generalized method for computation of true thickness and x-ray intensity information in highly blurred sub-millimeter bone features in clinical CT images. Phys Med Biol 2012; 57:8099-116. [DOI: 10.1088/0031-9155/57/23/8099] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Ohno K, Ohkubo M, Marasinghe JC, Murao K, Matsumoto T, Wada S. Accuracy of lung nodule density on HRCT: analysis by PSF-based image simulation. J Appl Clin Med Phys 2012; 13:3868. [PMID: 23149779 PMCID: PMC5718548 DOI: 10.1120/jacmp.v13i6.3868] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2012] [Revised: 06/28/2012] [Accepted: 06/25/2012] [Indexed: 11/23/2022] Open
Abstract
A computed tomography (CT) image simulation technique based on the point spread function (PSF) was applied to analyze the accuracy of CT‐based clinical evaluations of lung nodule density. The PSF of the CT system was measured and used to perform the lung nodule image simulation. Then, the simulated image was resampled at intervals equal to the pixel size and the slice interval found in clinical high‐resolution CT (HRCT) images. On those images, the nodule density was measured by placing a region of interest (ROI) commonly used for routine clinical practice, and comparing the measured value with the true value (a known density of object function used in the image simulation). It was quantitatively determined that the measured nodule density depended on the nodule diameter and the image reconstruction parameters (kernel and slice thickness). In addition, the measured density fluctuated, depending on the offset between the nodule center and the image voxel center. This fluctuation was reduced by decreasing the slice interval (i.e., with the use of overlapping reconstruction), leading to a stable density evaluation. Our proposed method of PSF‐based image simulation accompanied with resampling enables a quantitative analysis of the accuracy of CT‐based evaluations of lung nodule density. These results could potentially reveal clinical misreadings in diagnosis, and lead to more accurate and precise density evaluations. They would also be of value for determining the optimum scan and reconstruction parameters, such as image reconstruction kernels and slice thicknesses/intervals. PACS numbers: 87.57.‐s, 87.57.cf, 87.57.Q‐
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Affiliation(s)
- Ken Ohno
- Department of Radiological Technology, School of Health Sciences, Faculty of Medicine, Niigata University, Niigata 951-8518, Japan
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Arisan V, Karabuda ZC, Avsever H, Özdemir T. Conventional multi-slice computed tomography (CT) and cone-beam CT (CBCT) for computer-assisted implant placement. Part I: relationship of radiographic gray density and implant stability. Clin Implant Dent Relat Res 2012; 15:893-906. [PMID: 22251553 DOI: 10.1111/j.1708-8208.2011.00436.x] [Citation(s) in RCA: 66] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
PURPOSE The relationship of conventional multi-slice computed tomography (CT)- and cone beam CT (CBCT)-based gray density values and the primary stability parameters of implants that were placed by stereolithographic surgical guides were analyzed in this study. MATERIALS AND METHODS Eighteen edentulous jaws were randomly scanned by a CT (CT group) or a CBCT scanner (CBCT group) and radiographic gray density was measured from the planned implants. A total of 108 implants were placed, and primary stability parameters were measured by insertion torque value (ITV) and resonance frequency analysis (RFA). Radiographic and subjective bone quality classification (BQC) was also classified. Results were analyzed by correlation tests and multiple regressions (p < .05). RESULTS CBCT-based gray density values (765 ± 97.32 voxel value) outside the implants were significantly higher than those of CT-based values (668.4 ± 110 Hounsfield unit, p < .001). Significant relations were found among the gray density values outside the implants, ITV (adjusted r(2) = 0.6142, p = .001 and adjusted r(2) = 0.5166, p = .0021), and RFA (adjusted r(2) = 0.5642, p = .0017 and adjusted r(2) = 0.5423, p = .0031 for CT and CBCT groups, respectively). Data from radiographic and subjective BQC were also in agreement. CONCLUSIONS Similar to the gray density values of CT, that of CBCT could also be predictive for the subjective BQC and primary implant stability. Results should be confirmed on different CBCT scanners.
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Affiliation(s)
- Volkan Arisan
- Research fellow, Department of Oral Implantology, Faculty of Dentistry, Istanbul University, Istanbul, Turkey; professor, Department of Oral Implantology, Faculty of Dentistry, Istanbul University, Istanbul, Turkey; assistant professor, Department of Oral Diagnosis and Radiology, Gülhane Military Medical Academy (GATA), Center of Dental Sciences, Ankara, Turkey; professor, Department of Oral Implantology, Faculty of Dentistry, Istanbul University, Istanbul, Turkey
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Ikeda M, Makino R, Imai K, Matsumoto M, Hitomi R. A method for estimating noise variance of CT image. Comput Med Imaging Graph 2010; 34:642-50. [PMID: 20797837 DOI: 10.1016/j.compmedimag.2010.07.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2009] [Revised: 07/29/2010] [Accepted: 07/30/2010] [Indexed: 10/19/2022]
Abstract
Rank et al. have proposed an algorithm for estimating image noise variance composed of the following three steps: the noisy image is first filtered by a difference operator; a histogram of local signal variances is then computed; and, finally the noise variance is estimated from a statistical evaluation of the histogram. We have verified the accuracy of this algorithm on a CT image by indirect methods, and have shown that this method is able to estimate CT image noise variance with reasonable accuracy, regardless of whether or not the noiseless image is uniform. Further, we have proposed a simple alternative method for the last two steps of the Rank et al. method. However, one must pay attention to the fact that the estimated noise variance will be biased when the nearest two pixels are correlated and that this algorithm does not work well if the assumption of stationarity of noise components is violated.
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Affiliation(s)
- Mitsuru Ikeda
- Department of Radiological Technology, Nagoya University School of Health Sciences, Higashi-ku, Nagoya, Japan.
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Buckler AJ, Schwartz LH, Petrick N, McNitt-Gray M, Zhao B, Fenimore C, Reeves AP, Mozley PD, Avila RS. Data sets for the qualification of volumetric CT as a quantitative imaging biomarker in lung cancer. OPTICS EXPRESS 2010; 18:15267-15282. [PMID: 20640013 DOI: 10.1364/oe.18.015267] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
The drug development industry is faced with increasing costs and decreasing success rates. New ways to understand biology as well as the increasing interest in personalized treatments for smaller patient segments requires new capabilities for the rapid assessment of treatment responses. Deployment of qualified imaging biomarkers lags apparent technology capabilities. The lack of consensus methods and qualification evidence needed for large-scale multi-center trials, as well as the standardization that allows them, are widely acknowledged to be the limiting factors. The current fragmentation in imaging vendor offerings, coupled with the independent activities of individual biopharmaceutical companies and their contract research organizations (CROs), may stand in the way of the greater opportunity were these efforts to be drawn together. A preliminary report, "Volumetric CT: a potential biomarker of response," of the Quantitative Imaging Biomarkers Alliance (QIBA) activity was presented at the Medical Imaging Continuum: Path Forward for Advancing the Uses of Medical Imaging in the Development of New Biopharmaceutical Products meeting of the Extended Pharmaceutical Research and Manufacturers of America (PhRMA) Imaging Group sponsored by the Drug Information Agency (DIA) in October 2008. The clinical context in Lung Cancer and a methodology for approaching the qualification of volumetric CT as a biomarker has since been reported [Acad. Radiol. 17, 100-106, 107-115 (2010)]. This report reviews the effort to collect and utilize publicly available data sets to provide a transparent environment in which to pursue the qualification activities in such a way as to allow independent peer review and verification of results. This article focuses specifically on our role as stewards of image sets for developing new tools.
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Goodsitt MM, Chan HP, Way TW, Schipper MJ, Larson SC, Christodoulou EG. Quantitative CT of lung nodules: dependence of calibration on patient body size, anatomic region, and calibration nodule size for single- and dual-energy techniques. Med Phys 2009; 36:3107-21. [PMID: 19673210 DOI: 10.1118/1.3148536] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
Calcium concentration may be a useful feature for distinguishing benign from malignant lung nodules in computer-aided diagnosis. The calcium concentration can be estimated from the measured CT number of the nodule and a CT number vs calcium concentration calibration line that is derived from CT scans of two or more calcium reference standards. To account for CT number nonuniformity in the reconstruction field, such calibration lines may be obtained at multiple locations within lung regions in an anthropomorphic phantom. The authors performed a study to investigate the effects of patient body size, anatomic region, and calibration nodule size on the derived calibration lines at ten lung region positions using both single energy (SE) and dual energy (DE) CT techniques. Simulated spherical lung nodules of two concentrations (50 and 100 mg/cc CaCO3) were employed. Nodules of three different diameters (4.8, 9.5, and 16 mm) were scanned in a simulated thorax section representing the middle of the chest with large lung regions. The 4.8 and 9.5 mm nodules were also scanned in a section representing the upper chest with smaller lung regions. Fat rings were added to the peripheries of the phantoms to simulate larger patients. Scans were acquired on a GE-VCT scanner at 80, 120, and 140 kVp and were repeated three times for each condition. The average absolute CT number separations between the calibration lines were computed. In addition, under- or overestimates were determined when the calibration lines for one condition (e.g., small patient) were used to estimate the CaCO3 concentrations of nodules for a different condition (e.g., large patient). The authors demonstrated that, in general, DE is a more accurate method for estimating the calcium contents of lung nodules. The DE calibration lines within the lung field were less affected by patient body size, calibration nodule size, and nodule position than the SE calibration lines. Under- or overestimates in CaCO3 concentrations of nodules were also in general smaller in quantity with DE than with SE. However, because the slopes of the calibration lines for DE were about one-half the slopes for SE, the relative improvement in the concentration estimates for DE as compared to SE was about one-half the relative improvement in the separation between the calibration lines. Results in the middle of the chest thorax section with large lungs were nearly completely consistent with the above generalization. On the other hand, results in the upper-chest thorax section with smaller lungs and greater amounts of muscle and bone were mixed. A repeat of the entire study in the upper thorax section yielded similar mixed results. Most of the inconsistencies occurred for the 4.8 mm nodules and may be attributed to errors caused by beam hardening, volume averaging, and insufficient sampling. Targeted, higher resolution reconstructions of the smaller nodules, application of high atomic number filters to the high energy x-ray beam for improved spectral separation, and other future developments in DECT may alleviate these problems and further substantiate the superior accuracy of DECT in quantifying the calcium concentrations of lung nodules.
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Affiliation(s)
- Mitchell M Goodsitt
- Department of Radiology, University of Michigan, Ann Arbor, Michigan 48109-5842, USA.
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28
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Gavrielides MA, Kinnard LM, Myers KJ, Petrick N. Noncalcified lung nodules: volumetric assessment with thoracic CT. Radiology 2009; 251:26-37. [PMID: 19332844 DOI: 10.1148/radiol.2511071897] [Citation(s) in RCA: 118] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Lung nodule volumetry is used for nodule diagnosis, as well as for monitoring tumor response to therapy. Volume measurement precision and accuracy depend on a number of factors, including image-acquisition and reconstruction parameters, nodule characteristics, and the performance of algorithms for nodule segmentation and volume estimation. The purpose of this article is to provide a review of published studies relevant to the computed tomographic (CT) volumetric analysis of lung nodules. A number of underexamined areas of research regarding volumetric accuracy are identified, including the measurement of nonsolid nodules, the effects of pitch and section overlap, and the effect of respiratory motion. The need for public databases of phantom scans, as well as of clinical data, is discussed. The review points to the need for continued research to examine volumetric accuracy as a function of a multitude of interrelated variables involved in the assessment of lung nodules. Understanding and quantifying the sources of volumetric measurement error in the assessment of lung nodules with CT would be a first step toward the development of methods to minimize that error through system improvements and to correctly account for any remaining error.
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Affiliation(s)
- Marios A Gavrielides
- National Institute of Biomedical Imaging and Bioengineering/Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD 20993-0002, USA.
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Giger ML, Chan HP, Boone J. Anniversary paper: History and status of CAD and quantitative image analysis: the role of Medical Physics and AAPM. Med Phys 2009; 35:5799-820. [PMID: 19175137 PMCID: PMC2673617 DOI: 10.1118/1.3013555] [Citation(s) in RCA: 172] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
The roles of physicists in medical imaging have expanded over the years, from the study of imaging systems (sources and detectors) and dose to the assessment of image quality and perception, the development of image processing techniques, and the development of image analysis methods to assist in detection and diagnosis. The latter is a natural extension of medical physicists' goals in developing imaging techniques to help physicians acquire diagnostic information and improve clinical decisions. Studies indicate that radiologists do not detect all abnormalities on images that are visible on retrospective review, and they do not always correctly characterize abnormalities that are found. Since the 1950s, the potential use of computers had been considered for analysis of radiographic abnormalities. In the mid-1980s, however, medical physicists and radiologists began major research efforts for computer-aided detection or computer-aided diagnosis (CAD), that is, using the computer output as an aid to radiologists-as opposed to a completely automatic computer interpretation-focusing initially on methods for the detection of lesions on chest radiographs and mammograms. Since then, extensive investigations of computerized image analysis for detection or diagnosis of abnormalities in a variety of 2D and 3D medical images have been conducted. The growth of CAD over the past 20 years has been tremendous-from the early days of time-consuming film digitization and CPU-intensive computations on a limited number of cases to its current status in which developed CAD approaches are evaluated rigorously on large clinically relevant databases. CAD research by medical physicists includes many aspects-collecting relevant normal and pathological cases; developing computer algorithms appropriate for the medical interpretation task including those for segmentation, feature extraction, and classifier design; developing methodology for assessing CAD performance; validating the algorithms using appropriate cases to measure performance and robustness; conducting observer studies with which to evaluate radiologists in the diagnostic task without and with the use of the computer aid; and ultimately assessing performance with a clinical trial. Medical physicists also have an important role in quantitative imaging, by validating the quantitative integrity of scanners and developing imaging techniques, and image analysis tools that extract quantitative data in a more accurate and automated fashion. As imaging systems become more complex and the need for better quantitative information from images grows, the future includes the combined research efforts from physicists working in CAD with those working on quantitative imaging systems to readily yield information on morphology, function, molecular structure, and more-from animal imaging research to clinical patient care. A historical review of CAD and a discussion of challenges for the future are presented here, along with the extension to quantitative image analysis.
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Affiliation(s)
- Maryellen L Giger
- Department of Radiology, University of Chicago, Chicago, Illinois 60637, USA.
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Katsumata A, Hirukawa A, Okumura S, Naitoh M, Fujishita M, Ariji E, Langlais RP. Relationship between density variability and imaging volume size in cone-beam computerized tomographic scanning of the maxillofacial region: an in vitro study. ACTA ACUST UNITED AC 2008; 107:420-5. [PMID: 18715805 DOI: 10.1016/j.tripleo.2008.05.049] [Citation(s) in RCA: 103] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2008] [Revised: 04/13/2008] [Accepted: 05/23/2008] [Indexed: 12/15/2022]
Abstract
OBJECTIVE In limited-volume cone-beam computerized tomography (CBCT) imaging, projection data discontinuity caused by maxillofacial hard tissue structures outside the reconstructed volume are reported to affect the density value of the hard and soft tissue structures within the volume. The intensity of this effect is purported to be related to the size of the imaging volume. The aim of this study was to characterize the effect of the size of the scanned volume on density values in vitro. STUDY DESIGN Test objects were positioned in a custom phantom in the following 4 patterns: bimandible and vertebrae, bimandible, left mandible and vertebrae, and left mandible. We used a newly developed flat panel detector CBCT system (Alphard Vega; Asahi Roentgen, Kyoto, Japan) to acquire scans of the left molar region using cylindrical volumes of approximately 5, 10, 15, and 20 cm in diameter and height. The density values of the mandible and the adjacent soft tissue regions were analyzed. RESULTS Highest density variability was observed in the smallest-volume (5 cm) scans. Density variability increased when more objects were included outside the area being imaged. Fewer effects were noted in CBCT scans of larger (10, 15, and 20 cm) volumes. CONCLUSION Larger-volume CBCT scans may yield more consistent density values. Smaller CBCT volumes have the advantages of better image resolution and lower radiation doses. The optimization of the image characteristics is maximized by careful consideration of the purpose of the CBCT examination.
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Affiliation(s)
- Akitoshi Katsumata
- Department of Oral Radiology, Asahi University School of Dentistry, Gifu, Japan.
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Evaluation of the spatial resolution of multiplanar reconstruction images. Radiol Phys Technol 2008; 1:229-33. [DOI: 10.1007/s12194-008-0033-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2008] [Revised: 06/02/2008] [Accepted: 06/03/2008] [Indexed: 11/26/2022]
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Way TW, Chan HP, Goodsitt MM, Sahiner B, Hadjiiski LM, Zhou C, Chughtai A. Effect of CT scanning parameters on volumetric measurements of pulmonary nodules by 3D active contour segmentation: a phantom study. Phys Med Biol 2008; 53:1295-312. [PMID: 18296763 PMCID: PMC2728556 DOI: 10.1088/0031-9155/53/5/009] [Citation(s) in RCA: 41] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The purpose of this study is to investigate the effects of CT scanning and reconstruction parameters on automated segmentation and volumetric measurements of nodules in CT images. Phantom nodules of known sizes were used so that segmentation accuracy could be quantified in comparison to ground-truth volumes. Spherical nodules having 4.8, 9.5 and 16 mm diameters and 50 and 100 mg cc(-1) calcium contents were embedded in lung-tissue-simulating foam which was inserted in the thoracic cavity of a chest section phantom. CT scans of the phantom were acquired with a 16-slice scanner at various tube currents, pitches, fields-of-view and slice thicknesses. Scans were also taken using identical techniques either within the same day or five months apart for study of reproducibility. The phantom nodules were segmented with a three-dimensional active contour (3DAC) model that we previously developed for use on patient nodules. The percentage volume errors relative to the ground-truth volumes were estimated under the various imaging conditions. There was no statistically significant difference in volume error for repeated CT scans or scans taken with techniques where only pitch, field of view, or tube current (mA) were changed. However, the slice thickness significantly (p < 0.05) affected the volume error. Therefore, to evaluate nodule growth, consistent imaging conditions and high resolution should be used for acquisition of the serial CT scans, especially for smaller nodules. Understanding the effects of scanning and reconstruction parameters on volume measurements by 3DAC allows better interpretation of data and assessment of growth. Tracking nodule growth with computerized segmentation methods would reduce inter- and intraobserver variabilities.
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Affiliation(s)
- Ted W Way
- Department of Radiology, University of Michigan, Ann Arbor, MI 48109, USA.
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Boone JM. Radiological interpretation 2020: toward quantitative image assessment. Med Phys 2008; 34:4173-9. [PMID: 18072481 DOI: 10.1118/1.2789501] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
The interpretation of medical images by radiologists is primarily and fundamentally a subjective activity, but there are a number of clinical applications such as tumor imaging where quantitative imaging (QI) metrics (such as tumor growth rate) would be valuable to the patient's care. It is predicted that the subjective interpretive environment of the past will, over the next decade, evolve toward the increased use of quantitative metrics for evaluating patient health from images. The increasing sophistication and resolution of modern tomographic scanners promote the development of meaningful quantitative end points, determined from images which are in turn produced using well-controlled imaging protocols. For the QI environment to expand, medical physicists, physicians, other researchers and equipment vendors need to work collaboratively to develop the quantitative protocols for imaging, scanner calibrations, and robust analytical software that will lead to the routine inclusion of quantitative parameters in the diagnosis and therapeutic assessment of human health. Most importantly, quantitative metrics need to be developed which have genuine impact on patient diagnosis and welfare, and only then will QI techniques become integrated into the clinical environment.
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Affiliation(s)
- John M Boone
- University of California, Davis, UC Davis Medical Center, 4860 Y Street, Ellison Building Suite 3100, Sacramento, California 95817, USA.
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Callol L, Roig F, Cuevas A, de Granda JI, Villegas F, Jareño J, Arias E, Albiach JM. Low-dose CT: a useful and accessible tool for the early diagnosis of lung cancer in selected populations. Lung Cancer 2007; 56:217-21. [PMID: 17316889 DOI: 10.1016/j.lungcan.2007.01.010] [Citation(s) in RCA: 41] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2006] [Revised: 11/23/2006] [Accepted: 12/22/2006] [Indexed: 11/24/2022]
Abstract
OBJECTIVE An evaluation is made of the effectiveness of low-dose computed tomography (LDCT) in diagnosing early stage lung cancer in the Autonomous Community of Madrid (Spain). METHODS The study comprised subjects over 50 years of age who were active smokers (or who had stopped smoking up to 6 months previously) who smoked more than 30 cigarettes daily for at least 15 years, or 20 cigarettes daily for 20 years, or more than 10packs/year and in contact with asbestos at work. The study group was evaluated using LDCT. For all participants in whom LDCT showed no pathological findings, or in those cases classified as benign, a new LDCT scan was performed 2 years after the first. In case of doubt regarding the benign nature of the findings, an assessment algorithm was applied. RESULTS Among the initial 482 candidates in the study group, 466 LDCT scans were performed at baseline, revealing 9 extrapulmonary lesions and 114 pulmonary lesions in 98 subjects. The latter raised diagnostic doubts in 32 cases; of these, 15 were confirmed as benign by high resolution computed tomography (HRCT). In the remaining 17 cases, stage IAp adenocarcinoma was diagnosed at baseline (0.2%). With LDCT after 2 years, an additional four adenocarcinomas were diagnosed-all in stage IAp (0.98%). The complete study, including prevalence cut-off and incidence calculation after 2 years, resulted in the diagnosis of five cancers (1.1%) and two false positive cases (28%). CONCLUSIONS The use of low-dose computed tomography in risk groups is valid for the early diagnosis of bronchogenic cancer. Nevertheless, significant problems remain, particularly those associated with false positive interpretations. The results of randomized studies on lung cancer mortality such as the US NLST trial and the Dutch-Belgian NELSON trial have to be awaited before any conclusion regarding the effectiveness of LDCT screening can be drawn.
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Affiliation(s)
- Luis Callol
- Servicio de Neumología, Hospital Central de la Defensa, Glorieta del Ejército s/n, 28047 Madrid, Spain
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