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Materka A, Jurek J. Using Deep Learning and B-Splines to Model Blood Vessel Lumen from 3D Images. SENSORS (BASEL, SWITZERLAND) 2024; 24:846. [PMID: 38339562 PMCID: PMC10857344 DOI: 10.3390/s24030846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Revised: 01/20/2024] [Accepted: 01/26/2024] [Indexed: 02/12/2024]
Abstract
Accurate geometric modeling of blood vessel lumen from 3D images is crucial for vessel quantification as part of the diagnosis, treatment, and monitoring of vascular diseases. Our method, unlike other approaches which assume a circular or elliptical vessel cross-section, employs parametric B-splines combined with image formation system equations to accurately localize the highly curved lumen boundaries. This approach avoids the need for image segmentation, which may reduce the localization accuracy due to spatial discretization. We demonstrate that the model parameters can be reliably identified by a feedforward neural network which, driven by the cross-section images, predicts the parameter values many times faster than a reference least-squares (LS) model fitting algorithm. We present and discuss two example applications, modeling the lower extremities of artery-vein complexes visualized in steady-state contrast-enhanced magnetic resonance images (MRI) and the coronary arteries pictured in computed tomography angiograms (CTA). Beyond applications in medical diagnosis, blood-flow simulation and vessel-phantom design, the method can serve as a tool for automated annotation of image datasets to train machine-learning algorithms.
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Affiliation(s)
- Andrzej Materka
- Institute of Electronics, Lodz University of Technology, 90-924 Lodz, Poland;
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Lecomte A, Serrand A, Marteau L, Carlier B, Manigold T, Letocart V, Warin Fresse K, Nguyen JM, Serfaty JM. Coronary artery assessment on pre transcatheter aortic valve implantation computed tomography may avoid the need for additional coronary angiography. Diagn Interv Imaging 2023; 104:547-551. [PMID: 37331824 DOI: 10.1016/j.diii.2023.06.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 06/07/2023] [Accepted: 06/09/2023] [Indexed: 06/20/2023]
Abstract
PURPOSE The purpose of this study was to evaluate the percentage of coronary angiography that can be securely avoided by the interpretation of coronary arteries on pre transcatheter aortic valve implantation CT (TAVI-CT), using CT images obtained with deep-learning reconstruction and motion correction algorithms. MATERIAL AND METHOD All consecutive patients who underwent TAVI-CT and coronary angiography, from December 2021 to July 2022 were screened for inclusion in the study. Patients who had previous coronary artery revascularization or who did not undergo TAVI were excluded. All TAVI-CT examinations were obtained using deep-learning reconstruction and motion correction algorithms. On TAVI-CT examinations, quality and stenosis of coronary artery were analyzed retrospectively. When insufficient image quality and/or when diagnosis or doubt of one significant coronary artery stenosis, patients were considered as having possible coronary artery stenosis. The results of coronary angiography were used as the standard of reference for significant CAS. RESULTS A total of 206 patients (92 men; mean age, 80.6 years) were included; of these 27/206 (13%) had significant coronary artery stenosis on coronary angiography and were referred for potential revascularization. Sensitivity, specificity, negative predictive value, positive predictive value, and accuracy of TAVI-CT to identify patients requiring coronary artery revascularization was 100% (95% confidence interval [CI]: 87.2-100%), 100% (95% CI: 96.3-100%), 54% (95% CI: 46.6-61.6), 25% (95% CI: 17.0-34.0%) and 60% (95% CI: 53.1-66.9%) respectively. Intra- and inter observer variability was substantial agreement for quality and decision to recommend coronary angiography. Mean reading time was 2 ± 1.2 (standard deviation) min (range: 1-5 min). Overall, TAVI-CT could potentially rule out indication for revascularization for 97 patients (47%). CONCLUSION Analysis of coronary artery on TAVI-CT using deep-learning reconstruction and motion correction algorithms can potentially safely avoid coronary angiography in 47% of patients.
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Affiliation(s)
- Adrien Lecomte
- Department of Cardiovascular Radiology, Nantes Université, CHU Nantes, 44000 Nantes, France.
| | - Aude Serrand
- Department of Cardiovascular Radiology, Nantes Université, CHU Nantes, 44000 Nantes, France
| | - Lara Marteau
- Department of Cardiovascular Radiology, Nantes Université, CHU Nantes, 44000 Nantes, France; Department of Cardiology, Nantes Université, CHU Nantes, Institut du thorax, 44000 Nantes, France; Department of Biostatistics and Epidemiology, CRCINA, INSERM U1232 Team2, CHU Nantes, 44000 Nantes, France; Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du thorax, F-44000 Nantes, France
| | - Baptiste Carlier
- Department of Cardiology, Nantes Université, CHU Nantes, Institut du thorax, 44000 Nantes, France
| | - Thibaut Manigold
- Department of Cardiology, Nantes Université, CHU Nantes, Institut du thorax, 44000 Nantes, France
| | - Vincent Letocart
- Department of Cardiology, Nantes Université, CHU Nantes, Institut du thorax, 44000 Nantes, France
| | - Karine Warin Fresse
- Department of Cardiovascular Radiology, Nantes Université, CHU Nantes, 44000 Nantes, France
| | - Jean-Michel Nguyen
- Department of Biostatistics and Epidemiology, CRCINA, INSERM U1232 Team2, CHU Nantes, 44000 Nantes, France
| | - Jean-Michel Serfaty
- Department of Cardiovascular Radiology, Nantes Université, CHU Nantes, 44000 Nantes, France; Department of Cardiology, Nantes Université, CHU Nantes, Institut du thorax, 44000 Nantes, France; Department of Biostatistics and Epidemiology, CRCINA, INSERM U1232 Team2, CHU Nantes, 44000 Nantes, France; Nantes Université, CHU Nantes, CNRS, INSERM, l'institut du thorax, F-44000 Nantes, France
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Severance LM, Pack JD, Contijoch FJ, McVeigh ER. Quantitative analysis of small coronary artery calcium detectability with an accurate simulation and validation on a clinical CT scanner. Med Phys 2023; 50:6060-6070. [PMID: 37523236 DOI: 10.1002/mp.16652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Accepted: 07/01/2023] [Indexed: 08/02/2023] Open
Abstract
BACKGROUND The absence of coronary artery calcium (CAC) measured via CT is associated with very favorable prognosis, and current guidelines recommend low-density lipoprotein cholesterol (LDL-c) lowering therapy for individuals with any CAC. This motivates early detection of small granules of CAC; however, calcium scan sensitivity for detecting very low levels of calcium has not been quantified. PURPOSE In this work, the size limit of detectability of small calcium hydroxyapatite (CaHA) granules with clinical CAC scanning was assessed using validated simulations. METHODS CT projections of digital 3D mathematical phantoms containing small CaHA granules were simulated analytically; images were reconstructed using a filter designed to reproduce the point spread function of a specific commercial scanner, and a relationship of HU number versus diameter was derived. These simulation results were validated with experimental measurements of HU versus diameter from phantoms containing small granules of CaHA on a GE Revolution CT scanner in the clinic; ground truth measurements of the CaHA granule diameters were obtained using a Zeiss Xradia 510 Versa high-resolution 3D micro-CT imaging system. Using experimental measurements on the clinical CT scanner, detectability was quantified with a detectability index (d') using a non-prewhitened matched filter. The effect of changes to reconstruction slice thickness and reconstruction kernel on granule detectability was evaluated. RESULTS Under typical clinical calcium scanning and reconstruction conditions, the minimum detectable diameter of a simulated spherical calcium granule with a clinically relevant CaHA density was 0.76 mm. The minimum detectable volume was 2.4 times smaller on images reconstructed at a slice thickness of 0.625 mm compared to 2.5 mm. The detectability index d' increased by a factor of 1.7 when images were reconstructed with 0.625 mm slices compared to 2.5 mm slices. d' did not change when images were reconstructed with the high-resolution BONE filter compared to the less sharp STANDARD resolution filter on the GE Revolution CT. CONCLUSIONS We have quantified detectability versus size of small calcium granules at the resolution limit of a widely available clinical CT scanner. Detectability increased significantly with reduced slice thickness and did not change with a sharper reconstruction kernel. The simulation can be used to calculate the trade-off between dose and CAC detectability.
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Affiliation(s)
- Lauren M Severance
- Department of Bioengineering, UC San Diego School of Engineering, La Jolla, California, USA
| | - Jed D Pack
- Radiation Systems Lab, GE Global Research, Niskayuna, New York, USA
| | - Francisco J Contijoch
- Department of Bioengineering, UC San Diego School of Engineering, La Jolla, California, USA
- Department of Radiology, UC San Diego School of Medicine, La Jolla, California, USA
| | - Elliot R McVeigh
- Department of Bioengineering, UC San Diego School of Engineering, La Jolla, California, USA
- Department of Radiology, UC San Diego School of Medicine, La Jolla, California, USA
- Department of Medicine, Division of Cardiology, UC San Diego School of Medicine, La Jolla, California, USA
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Kusk MW, Bromark CS, Hestbek-Møller M, Davidsen LØ, Precht H, Brage K. Pill or pump? Nitroglycerin 0.5 mg tablet vs 0.8 mg spray: Effect on proximal vessel diameters at Coronary CT Angiography (CCTA). Radiography (Lond) 2023; 29:918-925. [PMID: 37478639 DOI: 10.1016/j.radi.2023.07.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 06/22/2023] [Accepted: 07/07/2023] [Indexed: 07/23/2023]
Abstract
INTRODUCTION The administration of sublingual Nitroglycerin (NTG) prior to CT coronary angiography (CCTA) can be perfomed using pump spray or tablets. Choice of method seems to be based on local preference, rather than published guidelines. This retrospective analysis tested whether proximal coronary diameters differed dependent on the sublingual administration of 0.5 mg Nitroglycerin (NTG) tablets or 0.8 mg NTG spray. METHODS 287 ECG-gated CCTA studies with optimal image quality and Agatston scores<400 were included in this retrospective analysis. 143 of the patients were dosed with NTG tablets at a dose of 0.5 mg prior to CCTA. 144 patients received 2 puffs of 0.4 mg NTG spray for a total dose of 8 mg. All were scanned on a second-generation Dual Source CT. Diameters of proximal segments of Left Main (LM), Right (RCA), Left Anterior (LAD) and circumflex (CX) coronary arteries were measured using semi-automatic electronic callipers by two blinded readers. Results were summarised as the mean of maximum and minimum diameters. Sex-specific analysis of diameters was carried out using repeated-measures ANOVA for each vessel. Agreement between readers was examined with Bland-Altman analysis and intra-class-correlation coefficient (ICC). RESULTS No significant differences in coronary diameters were found except in the RCA for women and LM for men. In both cases, diameters were smaller in the spray group (11 and 9%, respectively). Reader agreement was excellent, with ICC>0.96 for all vessels, and no significant bias, except in CX (0.03 mm). CONCLUSIONS We found no evidence for the systematic superiority of either administration method in proximal coronary vessels. IMPLICATIONS FOR PRACTICE Choosing between tablet or spray NTG prior to CCTA can be guided by practical, economical and hygienic considerations alone.
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Affiliation(s)
- M W Kusk
- Imaging Research Initiative SouthWest (IRIS), Esbjerg, Denmark; Department of Radiology and Nuclear Medicine, Esbjerg Hospital - University Hospital of Southern Denmark, Denmark; University College Dublin, School of Medicine, Dublin, Ireland; Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark.
| | - C S Bromark
- Department of Radiology, Lillebaelt Hospital, University Hospitals of Southern Denmark, Kolding, Denmark
| | - M Hestbek-Møller
- Department of Radiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - L Ø Davidsen
- Department of Radiology, Odense University Hospital, Svendborg, Denmark
| | - H Precht
- Department of Radiology, Lillebaelt Hospital, University Hospitals of Southern Denmark, Kolding, Denmark; Health Sciences Research Centre, UCL University College, Odense, Denmark; Education of Radiography, UCL University College, Odense, Denmark; Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
| | - K Brage
- Education of Radiography, UCL University College, Odense, Denmark; Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
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Chen Z, Contijoch F, Colvert GM, Manohar A, Kahn AM, Narayan HK, McVeigh E. Detection of left ventricular wall motion abnormalities from volume rendering of 4DCT cardiac angiograms using deep learning. Front Cardiovasc Med 2022; 9:919751. [PMID: 35966529 PMCID: PMC9366190 DOI: 10.3389/fcvm.2022.919751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 05/27/2022] [Indexed: 12/02/2022] Open
Abstract
Background The presence of left ventricular (LV) wall motion abnormalities (WMA) is an independent indicator of adverse cardiovascular events in patients with cardiovascular diseases. We develop and evaluate the ability to detect cardiac wall motion abnormalities (WMA) from dynamic volume renderings (VR) of clinical 4D computed tomography (CT) angiograms using a deep learning (DL) framework. Methods Three hundred forty-three ECG-gated cardiac 4DCT studies (age: 61 ± 15, 60.1% male) were retrospectively evaluated. Volume-rendering videos of the LV blood pool were generated from 6 different perspectives (i.e., six views corresponding to every 60-degree rotation around the LV long axis); resulting in 2058 unique videos. Ground-truth WMA classification for each video was performed by evaluating the extent of impaired regional shortening visible (measured in the original 4DCT data). DL classification of each video for the presence of WMA was performed by first extracting image features frame-by-frame using a pre-trained Inception network and then evaluating the set of features using a long short-term memory network. Data were split into 60% for 5-fold cross-validation and 40% for testing. Results Volume rendering videos represent ~800-fold data compression of the 4DCT volumes. Per-video DL classification performance was high for both cross-validation (accuracy = 93.1%, sensitivity = 90.0% and specificity = 95.1%, κ: 0.86) and testing (90.9, 90.2, and 91.4% respectively, κ: 0.81). Per-study performance was also high (cross-validation: 93.7, 93.5, 93.8%, κ: 0.87; testing: 93.5, 91.9, 94.7%, κ: 0.87). By re-binning per-video results into the 6 regional views of the LV we showed DL was accurate (mean accuracy = 93.1 and 90.9% for cross-validation and testing cohort, respectively) for every region. DL classification strongly agreed (accuracy = 91.0%, κ: 0.81) with expert visual assessment. Conclusions Dynamic volume rendering of the LV blood pool combined with DL classification can accurately detect regional WMA from cardiac CT.
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Affiliation(s)
- Zhennong Chen
- Department of Bioengineering, UC San Diego School of Engineering, La Jolla, CA, United States
| | - Francisco Contijoch
- Department of Bioengineering, UC San Diego School of Engineering, La Jolla, CA, United States
- Department of Radiology, UC San Diego School of Medicine, La Jolla, CA, United States
| | - Gabrielle M. Colvert
- Department of Bioengineering, UC San Diego School of Engineering, La Jolla, CA, United States
| | - Ashish Manohar
- Department of Mechanical and Aerospace Engineering, UC San Diego School of Engineering, La Jolla, CA, United States
| | - Andrew M. Kahn
- Department of Cardiology, UC San Diego School of Medicine, La Jolla, CA, United States
| | - Hari K. Narayan
- Department of Pediatrics, UC San Diego School of Medicine, La Jolla, CA, United States
| | - Elliot McVeigh
- Department of Bioengineering, UC San Diego School of Engineering, La Jolla, CA, United States
- Department of Radiology, UC San Diego School of Medicine, La Jolla, CA, United States
- Department of Cardiology, UC San Diego School of Medicine, La Jolla, CA, United States
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Yamada M, Yamada Y, Nakahara T, Okuda S, Abe T, Kuribayashi S, Jinzaki M. Accuracy of ultra-high-resolution computed tomography with a 0.3-mm detector for quantitative assessment of coronary artery stenosis grading in comparison with conventional computed tomography: A phantom study. J Cardiovasc Comput Tomogr 2021; 16:239-244. [PMID: 34906436 DOI: 10.1016/j.jcct.2021.11.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2021] [Revised: 10/15/2021] [Accepted: 11/22/2021] [Indexed: 10/19/2022]
Abstract
BACKGROUND The development of ultra-high-resolution CT (U-HRCT) is expected to improve the accuracy of coronary stenosis evaluation. This study aimed to evaluate the accuracy of the stenosis severities of coronary artery phantoms estimated using U-HRCT by comparing them to those estimated with conventional CT. METHODS Coronary artery phantoms with non-calcified and calcified lesions were scanned with conventional CT (64-row × 0.625 mm) and U-HRCT (32-row × 0.3125 mm). The coronary artery phantoms had lumen diameters of 2.0, 3.0, and 4.0 mm with non-calcified lesions representing 0%, 25%, 50%, and 75% stenosis and 3.0 and 4.0 mm with calcified lesions representing 0%, 25%, 50%, and 75% stenosis. The lumen diameters at the stenotic and non-stenotic regions were measured, and the stenosis severities were compared with the true values. RESULTS For non-calcified lesions, conventional CT significantly underestimated the stenosis severity in the phantom showing 75% stenosis with lumen diameters of 2.0 and 3.0 mm (p < 0.05), while the estimated stenosis severities were not significantly different from the true values at all settings with U-HRCT. For the calcified lesions, conventional CT overestimated the stenosis severities at all settings (p < 0.05), while U-HRCT yielded estimations closer to the true values, although still with some overestimation (p < 0.05). CONCLUSION By using U-HRCT, the estimated stenosis severities of the coronary artery with non-calcified lesion become almost equal to the true value, while those with calcified lesion are still overestimated although they become closer to the true value.
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Affiliation(s)
- Minoru Yamada
- Department of Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan
| | - Yoshitake Yamada
- Department of Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan
| | - Takehiro Nakahara
- Department of Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan
| | - Shigeo Okuda
- Department of Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan
| | - Takayuki Abe
- Keio University School of Medicine, Clinical and Translational Research Center, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan; Yokohama City University School of Data Science, 22-2, Seto, Kanazawa, Yokohama, Kanagawa, 236-0027, Japan
| | - Sachio Kuribayashi
- Department of Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan; HIMEDIC Imaging Center at Lake Yamanaka, XIV Yamanakako B2F, 562-12 Hirano, Yamanashi, 401-0502, Japan
| | - Masahiro Jinzaki
- Department of Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan.
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Visualization of small visceral arteries on abdominal CT angiography using ultra-high-resolution CT scanner. Jpn J Radiol 2021; 39:889-897. [PMID: 33948788 PMCID: PMC8413175 DOI: 10.1007/s11604-021-01124-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Accepted: 04/15/2021] [Indexed: 01/12/2023]
Abstract
PURPOSE To evaluate the image quality and ability to delineate the small visceral arteries of high-resolution (HR) abdominal CT angiography (CTA) using an ultra-high-resolution computed tomography (UHR CT) scanner. MATERIALS AND METHODS Thirty-seven patients were enrolled who underwent abdominal CTA using a UHR CT scanner. The images were reconstructed with a matrix of 1024 × 1024 and 0.25 mm thickness for HR CTA and with a matrix of 512 × 512 and 0.5 mm thickness for normal resolution (NR) CTA. Maximum CT value, image quality, and delineation of the small arteries were compared between HR CTA and NR CTA. RESULTS HR CTA showed significantly higher maximum CT value, higher image quality, and better delineation of the small arteries than did NR CTA (P < .005). CONCLUSION HR CTA using a UHR CT scanner showed higher image quality than NR CTA and enhanced the delineation of visceral arteries.
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Samei E, Richards T, Segars WP, Daubert MA, Ivanov A, Rubin GD, Douglas PS, Hoffmann U. Task-dependent estimability index to assess the quality of cardiac computed tomography angiography for quantifying coronary stenosis. J Med Imaging (Bellingham) 2021; 8:013501. [PMID: 33447644 PMCID: PMC7797007 DOI: 10.1117/1.jmi.8.1.013501] [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: 06/09/2020] [Accepted: 12/11/2020] [Indexed: 11/25/2022] Open
Abstract
Purpose: Quantifying stenosis in cardiac computed tomography angiography (CTA) images remains a difficult task, as image noise and cardiac motion can degrade image quality and distort underlying anatomic information. The purpose of this study was to develop a computational framework to objectively assess the precision of quantifying coronary stenosis in cardiac CTA. Approach: The framework used models of coronary vessels and plaques, asymmetric motion point spread functions, CT image blur (task-based modulation transfer functions) and noise (noise-power spectrums), and an automated maximum-likelihood estimator implemented as a matched template squared-difference operator. These factors were integrated into an estimability index (e′) as a task-based measure of image quality in cardiac CTA. The e′ index was applied to assess how well it can to predict the quality of 132 clinical cases selected from the Prospective Multicenter Imaging Study for Evaluation of Chest Pain trial. The cases were divided into two cohorts, high quality and low quality, based on clinical scores and the concordance of clinical evaluations of cases by experienced cardiac imagers. The framework was also used to ascertain protocol factors for CTA Biomarker initiative of the Quantitative Imaging Biomarker Alliance (QIBA). Results: The e′ index categorized the patient datasets with an area under the curve of 0.985, an accuracy of 0.977, and an optimal e′ threshold of 25.58 corresponding to a stenosis estimation precision (standard deviation) of 3.91%. Data resampling and training–test validation methods demonstrated stable classifier thresholds and receiver operating curve performance. The framework was successfully applicable to the QIBA objective. Conclusions: A computational framework to objectively quantify stenosis estimation task performance was successfully implemented and was reflective of clinical results in the context of a prominent clinical trial with diverse sites, readers, scanners, acquisition protocols, and patients. It also demonstrated the potential for prospective optimization of imaging protocols toward targeted precision and measurement consistency in cardiac CT images.
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Affiliation(s)
- Ehsan Samei
- Carl E Ravin Advanced Imaging Labs, Department of Radiology, Durham, North Carolina, United States
| | - Taylor Richards
- Carl E Ravin Advanced Imaging Labs, Department of Radiology, Durham, North Carolina, United States
| | - William P Segars
- Carl E Ravin Advanced Imaging Labs, Department of Radiology, Durham, North Carolina, United States
| | - Melissa A Daubert
- Duke University Medical Center, Department of Medicine, Durham, North Carolina, United States
| | - Alex Ivanov
- Massachusetts General Hospital, Department of Radiology, Boston, Massachusetts, United States
| | - Geoffrey D Rubin
- Duke University Medical Center, Department of Radiology, Durham, North Carolina, United States
| | - Pamela S Douglas
- Duke University Medical Center, Department of Medicine, Durham, North Carolina, United States
| | - Udo Hoffmann
- Massachusetts General Hospital, Department of Radiology, Boston, Massachusetts, United States
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