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Chen R, Luo R, Xu Y, Ou J, Li X, Yang Y, Cao L, Wu Z, Luo W, Liu H. Second-Order Motion-Compensated Echo-Planar Cardiac Diffusion-Weighted MRI: Usefulness of Compressed Sensitivity Encoding. J Magn Reson Imaging 2024. [PMID: 38587265 DOI: 10.1002/jmri.29383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 03/23/2024] [Accepted: 03/25/2024] [Indexed: 04/09/2024] Open
Abstract
BACKGROUND Cardiac diffusion-weighted imaging (DWI) using second-order motion-compensated spin echo (M2C) can provide noninvasive in-vivo microstructural assessment, but limited by relatively low signal-to-noise ratio (SNR). Echo-planar imaging (EPI) with compressed sensitivity encoding (EPICS) could address these issues. PURPOSE To combine M2C DWI and EPCIS (M2C EPICS DWI), and compare image quality for M2C DWI. STUDY TYPE Prospective. POPULATION Ten ex-vivo hearts, 10 healthy volunteers (females, 5 [50%]; mean ± SD of age, 25 ± 4 years), and 12 patients with diseased hearts (female, 1 [8.3%]; mean ± SD of age, 44 ± 16 years; including coronary artery heart disease, congenital heart disease, dilated cardiomyopathy, amyloidosis, and myocarditis). FIELD STRENGTH/SEQUENCE 3-T, M2C EPICS DWI, and M2C DWI. ASSESSMENT The apparent SNR (aSNR) and the rating scores were used to evaluate and compared image quality of all three groups. The aSNR was calculated usingaSNR = Mean intensity myocardium / Standard deviation myocardium $$ \mathrm{aSNR}={\mathrm{Mean}\ \mathrm{intensity}}_{\mathrm{myocardium}}/{\mathrm{Standard}\ \mathrm{deviation}}_{\mathrm{myocardium}} $$ , and the myocardium was segmented manually. Three observers independently rated subjective image quality using a 5-point Likert scale. STATISTICAL TESTS Bland-Altman analysis and paired t-tests. The threshold for statistical significance was set at P < 0.05. RESULTS In healthy volunteers, the aSNR with a b-value of 450 s/mm2 acquired by M2C EPICS DWI was significantly higher than M2C DWI at in-plane resolutions of 3.0 × 3.0, 2.5 × 2.5, and 2.0 × 2.0 mm2. In patients with diseased hearts, the aSNR ofM2C EPICS DWI was also significantly higher than that for M2C DWI (bias of M2C EPICS-M2C = 1.999, 95% limits of agreement, 0.362 to 3.636; mean ± SD, 7.80 ± 1.37 vs. 5.80 ± 0.81). The ADC values of M2C EPICS was significantly higher than M2C DWI in in-vivo hearts. Over 80% of the images with rating scores for M2C EPICS DWI were higher than M2C DWI in in-vivo hearts. DATA CONCLUSION Cardiac imaging by M2C EPICS DWI may demonstrate better overall image quality and higher aSNR than M2C DWI. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Rui Chen
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Ruohong Luo
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Yongzhou Xu
- Department of MSC Clinical & Technical Solutions, Philips Healthcare, Shenzhen, China
| | - Jiehao Ou
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Xiaodan Li
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Yuelong Yang
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Liqi Cao
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Zhigang Wu
- Department of MSC Clinical & Technical Solutions, Philips Healthcare, Shenzhen, China
| | - Wei Luo
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Hui Liu
- Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China
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Huang J, Ferreira PF, Wang L, Wu Y, Aviles-Rivero AI, Schönlieb CB, Scott AD, Khalique Z, Dwornik M, Rajakulasingam R, De Silva R, Pennell DJ, Nielles-Vallespin S, Yang G. Deep learning-based diffusion tensor cardiac magnetic resonance reconstruction: a comparison study. Sci Rep 2024; 14:5658. [PMID: 38454072 PMCID: PMC10920645 DOI: 10.1038/s41598-024-55880-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 02/27/2024] [Indexed: 03/09/2024] Open
Abstract
In vivo cardiac diffusion tensor imaging (cDTI) is a promising Magnetic Resonance Imaging (MRI) technique for evaluating the microstructure of myocardial tissue in living hearts, providing insights into cardiac function and enabling the development of innovative therapeutic strategies. However, the integration of cDTI into routine clinical practice poses challenging due to the technical obstacles involved in the acquisition, such as low signal-to-noise ratio and prolonged scanning times. In this study, we investigated and implemented three different types of deep learning-based MRI reconstruction models for cDTI reconstruction. We evaluated the performance of these models based on the reconstruction quality assessment, the diffusion tensor parameter assessment as well as the computational cost assessment. Our results indicate that the models discussed in this study can be applied for clinical use at an acceleration factor (AF) of × 2 and × 4 , with the D5C5 model showing superior fidelity for reconstruction and the SwinMR model providing higher perceptual scores. There is no statistical difference from the reference for all diffusion tensor parameters at AF × 2 or most DT parameters at AF × 4 , and the quality of most diffusion tensor parameter maps is visually acceptable. SwinMR is recommended as the optimal approach for reconstruction at AF × 2 and AF × 4 . However, we believe that the models discussed in this study are not yet ready for clinical use at a higher AF. At AF × 8 , the performance of all models discussed remains limited, with only half of the diffusion tensor parameters being recovered to a level with no statistical difference from the reference. Some diffusion tensor parameter maps even provide wrong and misleading information.
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Grants
- Wellcome Trust
- RG/19/1/34160 British Heart Foundation
- This study was supported in part by the UKRI Future Leaders Fellowship (MR/V023799/1), BHF (RG/19/1/34160), the ERC IMI (101005122), the H2020 (952172), the MRC (MC/PC/21013), the Royal Society (IEC/NSFC/211235), the NVIDIA Academic Hardware Grant Program, EPSRC (EP/V029428/1, EP/S026045/1, EP/T003553/1, EP/N014588/1, EP/T017961/1), and the Cambridge Mathematics of Information in Healthcare Hub (CMIH) Partnership Fund.
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Affiliation(s)
- Jiahao Huang
- National Heart and Lung Institute, Imperial College London, London, SW7 2AZ, UK.
- Cardiovascular Research Centre, Royal Brompton Hospital, London, SW7 2AZ, UK.
- Bioengineering Department and Imperial-X, Imperial College London, London, W12 7SL, UK.
| | - Pedro F Ferreira
- National Heart and Lung Institute, Imperial College London, London, SW7 2AZ, UK
- Cardiovascular Research Centre, Royal Brompton Hospital, London, SW7 2AZ, UK
| | - Lichao Wang
- National Heart and Lung Institute, Imperial College London, London, SW7 2AZ, UK
- Department of Computing, Imperial College London, London, UK
| | - Yinzhe Wu
- National Heart and Lung Institute, Imperial College London, London, SW7 2AZ, UK
- Cardiovascular Research Centre, Royal Brompton Hospital, London, SW7 2AZ, UK
| | - Angelica I Aviles-Rivero
- Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK
| | - Carola-Bibiane Schönlieb
- Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK
| | - Andrew D Scott
- National Heart and Lung Institute, Imperial College London, London, SW7 2AZ, UK
- Cardiovascular Research Centre, Royal Brompton Hospital, London, SW7 2AZ, UK
| | - Zohya Khalique
- National Heart and Lung Institute, Imperial College London, London, SW7 2AZ, UK
- Cardiovascular Research Centre, Royal Brompton Hospital, London, SW7 2AZ, UK
| | - Maria Dwornik
- National Heart and Lung Institute, Imperial College London, London, SW7 2AZ, UK
- Cardiovascular Research Centre, Royal Brompton Hospital, London, SW7 2AZ, UK
| | - Ramyah Rajakulasingam
- National Heart and Lung Institute, Imperial College London, London, SW7 2AZ, UK
- Cardiovascular Research Centre, Royal Brompton Hospital, London, SW7 2AZ, UK
| | - Ranil De Silva
- National Heart and Lung Institute, Imperial College London, London, SW7 2AZ, UK
- Cardiovascular Research Centre, Royal Brompton Hospital, London, SW7 2AZ, UK
| | - Dudley J Pennell
- National Heart and Lung Institute, Imperial College London, London, SW7 2AZ, UK
- Cardiovascular Research Centre, Royal Brompton Hospital, London, SW7 2AZ, UK
| | - Sonia Nielles-Vallespin
- National Heart and Lung Institute, Imperial College London, London, SW7 2AZ, UK
- Cardiovascular Research Centre, Royal Brompton Hospital, London, SW7 2AZ, UK
| | - Guang Yang
- National Heart and Lung Institute, Imperial College London, London, SW7 2AZ, UK.
- Cardiovascular Research Centre, Royal Brompton Hospital, London, SW7 2AZ, UK.
- Bioengineering Department and Imperial-X, Imperial College London, London, W12 7SL, UK.
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Phipps K, van de Boomen M, Eder R, Michelhaugh SA, Spahillari A, Kim J, Parajuli S, Reese TG, Mekkaoui C, Das S, Gee D, Shah R, Sosnovik DE, Nguyen C. Accelerated in Vivo Cardiac Diffusion-Tensor MRI Using Residual Deep Learning-based Denoising in Participants with Obesity. Radiol Cardiothorac Imaging 2021; 3:e200580. [PMID: 34250491 DOI: 10.1148/ryct.2021200580] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Revised: 05/07/2021] [Accepted: 05/11/2021] [Indexed: 12/21/2022]
Abstract
Purpose To develop and assess a residual deep learning algorithm to accelerate in vivo cardiac diffusion-tensor MRI (DT-MRI) by reducing the number of averages while preserving image quality and DT-MRI parameters. Materials and Methods In this prospective study, a denoising convolutional neural network (DnCNN) for DT-MRI was developed; a total of 26 participants, including 20 without obesity (body mass index [BMI] < 30 kg/m2; mean age, 28 years ± 3 [standard deviation]; 11 women) and six with obesity (BMI ≥ 30 kg/m2; mean age, 48 years ± 11; five women), were recruited from June 19, 2019, to July 29, 2020. DT-MRI data were constructed at four averages (4Av), two averages (2Av), and one average (1Av) without and with the application of the DnCNN (4AvDnCNN, 2AvDnCNN, 1AvDnCNN). All data were compared against the reference DT-MRI data constructed at eight averages (8Av). Image quality, characterized by using the signal-to-noise ratio (SNR) and structural similarity index (SSIM), and the DT-MRI parameters of mean diffusivity (MD), fractional anisotropy (FA), and helix angle transmurality (HAT) were quantified. Results No differences were found in image quality or DT-MRI parameters between the accelerated 4AvDnCNN DT-MRI and the reference 8Av DT-MRI data for the SNR (29.1 ± 2.7 vs 30.5 ± 2.9), SSIM (0.97 ± 0.01), MD (1.3 µm2/msec ± 0.1 vs 1.31 µm2/msec ± 0.11), FA (0.32 ± 0.05 vs 0.30 ± 0.04), or HAT (1.10°/% ± 0.13 vs 1.11°/% ± 0.09). The relationship of a higher MD and lower FA and HAT in individuals with obesity compared with individuals without obesity in reference 8Av DT-MRI measurements was retained in 4AvDnCNN and 2AvDnCNN DT-MRI measurements but was not retained in 4Av or 2Av DT-MRI measurements. Conclusion Cardiac DT-MRI can be performed at an at least twofold-accelerated rate by using DnCNN to preserve image quality and DT-MRI parameter quantification.Keywords: Adults, Cardiac, Obesity, Technology Assessment, MR-Diffusion Tensor Imaging, Heart, Tissue CharacterizationSupplemental material is available for this article.© RSNA, 2021.
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Affiliation(s)
- Kellie Phipps
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th St, 4.213, Charlestown, MA 02129 (K.P., M.v.d.B., R.E., J.K., S.P., S.D., R.S., D.E.S., C.N.); Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands (M.v.d.B.); A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Mass (M.v.d.B., T.G.R., C.M., D.E.S., C.N.); Cardiology Division (S.A.M., A.S., S.D., R.S., D.E.S.) and Weight Center (D.G.), Massachusetts General Hospital, Boston, Mass; and Departments of Radiology (T.G.R., C.M.), Medicine (S.D., R.S., D.E.S., C.N.), and Surgery (D.G.), Harvard Medical School, Boston, Mass
| | - Maaike van de Boomen
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th St, 4.213, Charlestown, MA 02129 (K.P., M.v.d.B., R.E., J.K., S.P., S.D., R.S., D.E.S., C.N.); Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands (M.v.d.B.); A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Mass (M.v.d.B., T.G.R., C.M., D.E.S., C.N.); Cardiology Division (S.A.M., A.S., S.D., R.S., D.E.S.) and Weight Center (D.G.), Massachusetts General Hospital, Boston, Mass; and Departments of Radiology (T.G.R., C.M.), Medicine (S.D., R.S., D.E.S., C.N.), and Surgery (D.G.), Harvard Medical School, Boston, Mass
| | - Robert Eder
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th St, 4.213, Charlestown, MA 02129 (K.P., M.v.d.B., R.E., J.K., S.P., S.D., R.S., D.E.S., C.N.); Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands (M.v.d.B.); A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Mass (M.v.d.B., T.G.R., C.M., D.E.S., C.N.); Cardiology Division (S.A.M., A.S., S.D., R.S., D.E.S.) and Weight Center (D.G.), Massachusetts General Hospital, Boston, Mass; and Departments of Radiology (T.G.R., C.M.), Medicine (S.D., R.S., D.E.S., C.N.), and Surgery (D.G.), Harvard Medical School, Boston, Mass
| | - Sam Allen Michelhaugh
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th St, 4.213, Charlestown, MA 02129 (K.P., M.v.d.B., R.E., J.K., S.P., S.D., R.S., D.E.S., C.N.); Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands (M.v.d.B.); A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Mass (M.v.d.B., T.G.R., C.M., D.E.S., C.N.); Cardiology Division (S.A.M., A.S., S.D., R.S., D.E.S.) and Weight Center (D.G.), Massachusetts General Hospital, Boston, Mass; and Departments of Radiology (T.G.R., C.M.), Medicine (S.D., R.S., D.E.S., C.N.), and Surgery (D.G.), Harvard Medical School, Boston, Mass
| | - Aferdita Spahillari
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th St, 4.213, Charlestown, MA 02129 (K.P., M.v.d.B., R.E., J.K., S.P., S.D., R.S., D.E.S., C.N.); Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands (M.v.d.B.); A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Mass (M.v.d.B., T.G.R., C.M., D.E.S., C.N.); Cardiology Division (S.A.M., A.S., S.D., R.S., D.E.S.) and Weight Center (D.G.), Massachusetts General Hospital, Boston, Mass; and Departments of Radiology (T.G.R., C.M.), Medicine (S.D., R.S., D.E.S., C.N.), and Surgery (D.G.), Harvard Medical School, Boston, Mass
| | - Joan Kim
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th St, 4.213, Charlestown, MA 02129 (K.P., M.v.d.B., R.E., J.K., S.P., S.D., R.S., D.E.S., C.N.); Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands (M.v.d.B.); A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Mass (M.v.d.B., T.G.R., C.M., D.E.S., C.N.); Cardiology Division (S.A.M., A.S., S.D., R.S., D.E.S.) and Weight Center (D.G.), Massachusetts General Hospital, Boston, Mass; and Departments of Radiology (T.G.R., C.M.), Medicine (S.D., R.S., D.E.S., C.N.), and Surgery (D.G.), Harvard Medical School, Boston, Mass
| | - Shestruma Parajuli
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th St, 4.213, Charlestown, MA 02129 (K.P., M.v.d.B., R.E., J.K., S.P., S.D., R.S., D.E.S., C.N.); Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands (M.v.d.B.); A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Mass (M.v.d.B., T.G.R., C.M., D.E.S., C.N.); Cardiology Division (S.A.M., A.S., S.D., R.S., D.E.S.) and Weight Center (D.G.), Massachusetts General Hospital, Boston, Mass; and Departments of Radiology (T.G.R., C.M.), Medicine (S.D., R.S., D.E.S., C.N.), and Surgery (D.G.), Harvard Medical School, Boston, Mass
| | - Timothy G Reese
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th St, 4.213, Charlestown, MA 02129 (K.P., M.v.d.B., R.E., J.K., S.P., S.D., R.S., D.E.S., C.N.); Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands (M.v.d.B.); A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Mass (M.v.d.B., T.G.R., C.M., D.E.S., C.N.); Cardiology Division (S.A.M., A.S., S.D., R.S., D.E.S.) and Weight Center (D.G.), Massachusetts General Hospital, Boston, Mass; and Departments of Radiology (T.G.R., C.M.), Medicine (S.D., R.S., D.E.S., C.N.), and Surgery (D.G.), Harvard Medical School, Boston, Mass
| | - Choukri Mekkaoui
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th St, 4.213, Charlestown, MA 02129 (K.P., M.v.d.B., R.E., J.K., S.P., S.D., R.S., D.E.S., C.N.); Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands (M.v.d.B.); A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Mass (M.v.d.B., T.G.R., C.M., D.E.S., C.N.); Cardiology Division (S.A.M., A.S., S.D., R.S., D.E.S.) and Weight Center (D.G.), Massachusetts General Hospital, Boston, Mass; and Departments of Radiology (T.G.R., C.M.), Medicine (S.D., R.S., D.E.S., C.N.), and Surgery (D.G.), Harvard Medical School, Boston, Mass
| | - Saumya Das
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th St, 4.213, Charlestown, MA 02129 (K.P., M.v.d.B., R.E., J.K., S.P., S.D., R.S., D.E.S., C.N.); Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands (M.v.d.B.); A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Mass (M.v.d.B., T.G.R., C.M., D.E.S., C.N.); Cardiology Division (S.A.M., A.S., S.D., R.S., D.E.S.) and Weight Center (D.G.), Massachusetts General Hospital, Boston, Mass; and Departments of Radiology (T.G.R., C.M.), Medicine (S.D., R.S., D.E.S., C.N.), and Surgery (D.G.), Harvard Medical School, Boston, Mass
| | - Denise Gee
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th St, 4.213, Charlestown, MA 02129 (K.P., M.v.d.B., R.E., J.K., S.P., S.D., R.S., D.E.S., C.N.); Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands (M.v.d.B.); A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Mass (M.v.d.B., T.G.R., C.M., D.E.S., C.N.); Cardiology Division (S.A.M., A.S., S.D., R.S., D.E.S.) and Weight Center (D.G.), Massachusetts General Hospital, Boston, Mass; and Departments of Radiology (T.G.R., C.M.), Medicine (S.D., R.S., D.E.S., C.N.), and Surgery (D.G.), Harvard Medical School, Boston, Mass
| | - Ravi Shah
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th St, 4.213, Charlestown, MA 02129 (K.P., M.v.d.B., R.E., J.K., S.P., S.D., R.S., D.E.S., C.N.); Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands (M.v.d.B.); A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Mass (M.v.d.B., T.G.R., C.M., D.E.S., C.N.); Cardiology Division (S.A.M., A.S., S.D., R.S., D.E.S.) and Weight Center (D.G.), Massachusetts General Hospital, Boston, Mass; and Departments of Radiology (T.G.R., C.M.), Medicine (S.D., R.S., D.E.S., C.N.), and Surgery (D.G.), Harvard Medical School, Boston, Mass
| | - David E Sosnovik
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th St, 4.213, Charlestown, MA 02129 (K.P., M.v.d.B., R.E., J.K., S.P., S.D., R.S., D.E.S., C.N.); Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands (M.v.d.B.); A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Mass (M.v.d.B., T.G.R., C.M., D.E.S., C.N.); Cardiology Division (S.A.M., A.S., S.D., R.S., D.E.S.) and Weight Center (D.G.), Massachusetts General Hospital, Boston, Mass; and Departments of Radiology (T.G.R., C.M.), Medicine (S.D., R.S., D.E.S., C.N.), and Surgery (D.G.), Harvard Medical School, Boston, Mass
| | - Christopher Nguyen
- Cardiovascular Research Center, Massachusetts General Hospital, 149 13th St, 4.213, Charlestown, MA 02129 (K.P., M.v.d.B., R.E., J.K., S.P., S.D., R.S., D.E.S., C.N.); Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands (M.v.d.B.); A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Mass (M.v.d.B., T.G.R., C.M., D.E.S., C.N.); Cardiology Division (S.A.M., A.S., S.D., R.S., D.E.S.) and Weight Center (D.G.), Massachusetts General Hospital, Boston, Mass; and Departments of Radiology (T.G.R., C.M.), Medicine (S.D., R.S., D.E.S., C.N.), and Surgery (D.G.), Harvard Medical School, Boston, Mass
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