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Afzali M, Mueller L, Coveney S, Fasano F, Evans CJ, Engel M, Szczepankiewicz F, Teh I, Dall'Armellina E, Jones DK, Schneider JE. In vivo diffusion MRI of the human heart using a 300 mT/m gradient system. Magn Reson Med 2024; 92:1022-1034. [PMID: 38650395 DOI: 10.1002/mrm.30118] [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: 12/31/2023] [Revised: 02/27/2024] [Accepted: 04/01/2024] [Indexed: 04/25/2024]
Abstract
PURPOSE This work reports for the first time on the implementation and application of cardiac diffusion-weighted MRI on a Connectom MR scanner with a maximum gradient strength of 300 mT/m. It evaluates the benefits of the increased gradient performance for the investigation of the myocardial microstructure. METHODS Cardiac diffusion-weighted imaging (DWI) experiments were performed on 10 healthy volunteers using a spin-echo sequence with up to second- and third-order motion compensation (M 2 $$ {M}_2 $$ andM 3 $$ {M}_3 $$ ) andb = 100 , 450 $$ b=100,450 $$ , and 1000s / m m 2 $$ \mathrm{s}/\mathrm{m}{\mathrm{m}}^2 $$ (twice theb max $$ {b}_{\mathrm{max}} $$ commonly used on clinical scanners). Mean diffusivity (MD), fractional anisotropy (FA), helix angle (HA), and secondary eigenvector angle (E2A) were calculated for b = [100, 450]s / m m 2 $$ \mathrm{s}/\mathrm{m}{\mathrm{m}}^2 $$ and b = [100, 1000]s / m m 2 $$ \mathrm{s}/\mathrm{m}{\mathrm{m}}^2 $$ for bothM 2 $$ {M}_2 $$ andM 3 $$ {M}_3 $$ . RESULTS The MD values withM 3 $$ {M}_3 $$ are slightly higher than withM 2 $$ {M}_2 $$ withΔ MD = 0 . 05 ± 0 . 05 [ × 1 0 - 3 mm 2 / s ] ( p = 4 e - 5 ) $$ \Delta \mathrm{MD}=0.05\pm 0.05\kern0.3em \left[\times 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=4e-5\right) $$ forb max = 450 s / mm 2 $$ {b}_{\mathrm{max}}=450\kern0.3em \mathrm{s}/{\mathrm{mm}}^2 $$ andΔ MD = 0 . 03 ± 0 . 03 [ × 1 0 - 3 mm 2 / s ] ( p = 4 e - 4 ) $$ \Delta \mathrm{MD}=0.03\pm 0.03\kern0.3em \left[\times \kern0.3em 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=4e-4\right) $$ forb max = 1000 s / mm 2 $$ {b}_{\mathrm{max}}=1000\kern0.3em \mathrm{s}/{\mathrm{mm}}^2 $$ . A reduction in MD is observed by increasing theb max $$ {b}_{\mathrm{max}} $$ from 450 to 1000s / mm 2 $$ \mathrm{s}/{\mathrm{mm}}^2 $$ (Δ MD = 0 . 06 ± 0 . 04 [ × 1 0 - 3 mm 2 / s ] ( p = 1 . 6 e - 9 ) $$ \Delta \mathrm{MD}=0.06\pm 0.04\kern0.3em \left[\times \kern0.3em 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=1.6e-9\right) $$ forM 2 $$ {M}_2 $$ andΔ MD = 0 . 08 ± 0 . 05 [ × 1 0 - 3 mm 2 / s ] ( p = 1 e - 9 ) $$ \Delta \mathrm{MD}=0.08\pm 0.05\kern0.3em \left[\times \kern0.3em 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=1e-9\right) $$ forM 3 $$ {M}_3 $$ ). The difference between FA, E2A, and HA was not significant in different schemes (p > 0 . 05 $$ p>0.05 $$ ). CONCLUSION This work demonstrates cardiac DWI in vivo with higher b-value and higher order of motion compensated diffusion gradient waveforms than is commonly used. Increasing the motion compensation order fromM 2 $$ {M}_2 $$ toM 3 $$ {M}_3 $$ and the maximum b-value from 450 to 1000 s / mm 2 $$ \mathrm{s}/{\mathrm{mm}}^2 $$ affected the MD values but FA and the angular metrics (HA and E2A) remained unchanged. Our work paves the way for cardiac DWI on the next-generation MR scanners with high-performance gradient systems.
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Affiliation(s)
- Maryam Afzali
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Lars Mueller
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Sam Coveney
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Fabrizio Fasano
- Siemens Healthcare Ltd, Camberly, UK
- Siemens Healthcare GmbH, Erlangen, Germany
| | - Christopher John Evans
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Maria Engel
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | | | - Irvin Teh
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Erica Dall'Armellina
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Jürgen E Schneider
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
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Scott AD, Wen K, Luo Y, Huang J, Gover S, Soundarajan R, Ferreira PF, Pennell DJ, Nielles-Vallespin S. The effects of field strength on stimulated echo and motion compensated spin echo diffusion tensor cardiovascular magnetic resonance sequences. J Cardiovasc Magn Reson 2024:101052. [PMID: 38936803 DOI: 10.1016/j.jocmr.2024.101052] [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: 12/22/2023] [Revised: 04/03/2024] [Accepted: 06/19/2024] [Indexed: 06/29/2024] Open
Abstract
BACKGROUND In-vivo diffusion tensor CMR (DT-CMR) is an emerging technique for microstructural tissue characterisation in the myocardium. Most studies are performed at 3T, where higher signal to noise ratio (SNR) should benefit this signal starved method. However, a few studies have suggested that DT-CMR is possible at 1.5T, where EPI artefacts may be less severe and 1.5T hardware is more widely available. METHODS We recruited 20 healthy volunteers and performed mid-ventricular short axis DT-CMR at 1.5 T and 3 T. Acquisitions were performed at peak systole and end-diastole using both stimulated echo acquisition mode (STEAM) and motion compensated spin-echo (MCSE) sequences at matched spatial resolutions. DT-CMR parameters were averaged over the LV and compared between 1.5 T and 3 T sequences using both datasets with and without the blow reference data included. RESULTS Eleven (1.5T) and 12 (3T) diastolic MCSE acquisitions were rejected as the helix angle (HA) demonstrated <50% normal appearance circumferentially or the acquisition was abandoned due to poor image quality; a maximum of one acquisition was rejected for other datasets. Subjective HA map quality was significantly better at 3T than 1.5T for STEAM (p<0.05), but not for MCSE and other DT-CMR quality measures were consistent with improvements in STEAM at 3T over 1.5T. When blow data was excluded, no significant differences in mean diffusivity were observed between field strengths, but fractional anisotropy was significantly higher at 1.5T than 3T for STEAM systole (p<0.05). Absolute second eigenvector orientation (E2A, sheetlet angle) was significantly higher at 1.5T than 3T for MCSE systole and STEAM diastole, but significantly lower for STEAM systole (all p<0.05). Transmural HA distribution was less steep at 1.5T than 3T for STEAM diastole data (p<0.05). SNR in the blow images was higher at 3T than 1.5T for all acquisitions (p<0.05). CONCLUSION While 3T provides benefits in terms of SNR, both STEAM and MCSE can be performed at 1.5T. However, MCSE is unreliable in diastole at both field strengths and STEAM benefits from the improved SNR at 3T over 1.5T. Future clinical research studies may be able to leverage the wider availability of 1.5T CMR hardware where MCSE acquisitions are desirable.
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Affiliation(s)
- Andrew D Scott
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, Guy's and St Thomas' NHS Foundation Trust, Sydney Street, London, UK, SW3 6NP; National Heart and Lung Institute, Imperial College, Dovehouse Street, London, UK, SW3 6LY.
| | - Ke Wen
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, Guy's and St Thomas' NHS Foundation Trust, Sydney Street, London, UK, SW3 6NP; National Heart and Lung Institute, Imperial College, Dovehouse Street, London, UK, SW3 6LY; EPSRC Centre for Doctoral Training in Smart Medical Imaging. King's College London and Imperial College London, 5th Floor Beckett House, 1 Lambeth Palace Road, London, UK, SE1 7EU
| | - Yaqing Luo
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, Guy's and St Thomas' NHS Foundation Trust, Sydney Street, London, UK, SW3 6NP; National Heart and Lung Institute, Imperial College, Dovehouse Street, London, UK, SW3 6LY; EPSRC Centre for Doctoral Training in Smart Medical Imaging. King's College London and Imperial College London, 5th Floor Beckett House, 1 Lambeth Palace Road, London, UK, SE1 7EU
| | - Jiahao Huang
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, Guy's and St Thomas' NHS Foundation Trust, Sydney Street, London, UK, SW3 6NP; Department of Bioengineering, Imperial College London, Royal School of Mines, Exhibition Road, London, UK SW7 2AZ
| | - Simon Gover
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, Guy's and St Thomas' NHS Foundation Trust, Sydney Street, London, UK, SW3 6NP
| | - Rajkumar Soundarajan
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, Guy's and St Thomas' NHS Foundation Trust, Sydney Street, London, UK, SW3 6NP
| | - Pedro F Ferreira
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, Guy's and St Thomas' NHS Foundation Trust, Sydney Street, London, UK, SW3 6NP; National Heart and Lung Institute, Imperial College, Dovehouse Street, London, UK, SW3 6LY
| | - Dudley J Pennell
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, Guy's and St Thomas' NHS Foundation Trust, Sydney Street, London, UK, SW3 6NP; National Heart and Lung Institute, Imperial College, Dovehouse Street, London, UK, SW3 6LY
| | - Sonia Nielles-Vallespin
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, Guy's and St Thomas' NHS Foundation Trust, Sydney Street, London, UK, SW3 6NP; National Heart and Lung Institute, Imperial College, Dovehouse Street, London, UK, SW3 6LY
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Sadighi M, Kara D, Mai D, Nguyen K, Chen S, Kwon D, Nguyen C. Cardiac DTI using short-axis PROPELLER: A feasibility study. Magn Reson Med 2024; 91:2546-2558. [PMID: 38376096 PMCID: PMC11102807 DOI: 10.1002/mrm.30020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 12/06/2023] [Accepted: 01/08/2024] [Indexed: 02/21/2024]
Abstract
PURPOSE We aimed to develop a free-breathing (FB) cardiac DTI (cDTI) method based on short-axis PROPELLER (SAP) and M2 motion compensated spin-echo EPI (SAP-M2-EPI) to mitigate geometric distortion and eliminate aliasing in acquired diffusion-weighted (DW) images, particularly in patients with a higher body mass index (BMI). THEORY AND METHODS The study involved 10 healthy volunteers whose BMI values fell into specific categories: BMI <25 (4 volunteers), 25< BMI <28 (5 volunteers), and BMI >30 (1 volunteer). We compared DTI parameters, including fractional anisotropy (FA), mean diffusivity (MD), and helix angle transmurality (HAT), between SAP-M2-EPI and M2-ssEPI. To evaluate the performance of SAP-M2-EPI in reducing geometric distortions in the left ventricle (LV) compared to CINE and M2-ssEPI, we utilized the DICE similarity coefficient (DSC) and assessed misregistration area. RESULTS In all volunteers, SAP-M2-EPI yielded high-quality LV DWIs without aliasing, demonstrating significantly reduced geometric distortion (with an average DSC of 0.92 and average misregistration area of 90 mm2) and diminished signal loss due to bulk motion when compared to M2-ssEPI. DTI parameter maps exhibited consistent patterns across slices without motion related artifacts. CONCLUSION SAP-M2-EPI facilitates free-breathing cDTI of the entire LV, effectively eliminating aliasing and minimizing geometric distortion compared to M2-ssEPI. Furthermore, it preserves accurate quantification of myocardial microstructure.
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Affiliation(s)
- Mehdi Sadighi
- Cardiovascular Innovation Research Center (CIRC), Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Danielle Kara
- Cardiovascular Innovation Research Center (CIRC), Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Dingheng Mai
- Cardiovascular Innovation Research Center (CIRC), Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio, USA
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Case Western Reserve University, Cleveland, Ohio, USA
| | - Khoi Nguyen
- Cardiovascular Innovation Research Center (CIRC), Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Shi Chen
- Cardiovascular Innovation Research Center (CIRC), Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Deborah Kwon
- Cardiovascular Innovation Research Center (CIRC), Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio, USA
- Imaging Institute,Cleveland Clinic, Cleveland, Ohio, USA
| | - Christopher Nguyen
- Cardiovascular Innovation Research Center (CIRC), Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio, USA
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Case Western Reserve University, Cleveland, Ohio, USA
- Imaging Institute,Cleveland Clinic, Cleveland, Ohio, USA
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Rock CA, Chen YI, Wang R, Philip AL, Keil B, Weiner RB, Elmariah S, Mekkaoui C, Nguyen CT, Sosnovik DE. Diffusion Tensor Phenomapping of the Healthy and Pressure-Overloaded Human Heart. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.03.24306781. [PMID: 38746173 PMCID: PMC11092740 DOI: 10.1101/2024.05.03.24306781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Current techniques to image the microstructure of the heart with diffusion tensor MRI (DTI) are highly under-resolved. We present a technique to improve the spatial resolution of cardiac DTI by almost 10-fold and leverage this to measure local gradients in cardiomyocyte alignment or helix angle (HA). We further introduce a phenomapping approach based on voxel-wise hierarchical clustering of these gradients to identify distinct microstructural microenvironments in the heart. Initial development was performed in healthy volunteers (n=8). Thereader, subjects with severe but well-compensated aortic stenosis (AS, n=10) were compared to age-matched controls (CTL, n=10). Radial HA gradient was significantly reduced in AS (8.0±0.8°/mm vs. 10.2±1.8°/mm, p=0.001) but the other HA gradients did not change significantly. Four distinct microstructural clusters could be idenJfied in both the CTL and AS subjects and did not differ significantly in their properties or distribution. Despite marked hypertrophy, our data suggest that the myocardium in well-compensated AS can maintain its microstructural coherence. The described phenomapping approach can be used to characterize microstructural plasticity and perturbation in any organ system and disease.
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Kara D, Koenig K, Lowe M, Nguyen C, Sakaie K. Facilitating diffusion tensor imaging of the brain during continuous gross head motion with first and second order motion compensating diffusion gradients. Magn Reson Med 2024; 91:1556-1566. [PMID: 38073070 PMCID: PMC10872734 DOI: 10.1002/mrm.29924] [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: 06/08/2023] [Revised: 10/19/2023] [Accepted: 10/24/2023] [Indexed: 01/26/2024]
Abstract
PURPOSE To demonstrate the feasibility of motion compensating diffusion gradient schemes in the acquisition of quality diffusion tensor images (DTI) of the brain during continuous gross head motion. METHODS Five healthy subjects were scanned using a clinical 3 T MRI with and without continuous head motion. For one volunteer, DTI data was acquired using standard (M0) diffusion-weighted (DW) gradients, and first (M1) and second (M2) order gradient schemes that were previously developed for use in cardiac DTI. In four additional volunteers, DTI data was acquired with M0 and M2 gradients. DTI parameters were calculated and compared with established retrospective motion corrections. RESULTS In the absence of motion, DTI parameters calculated from M0, M1, and M2 data were consistent. In the presence of motion, up to 44% of DW images acquired with M0 gradients were corrupted by signal dropout, compared to 0% of the M2 images. In voxelwise comparisons, DTI parameters calculated using motion-M0 data were elevated compared to reference data. Retrospective corrections for extreme motion applied to motion-M0 data did not improve consistency with reference data in cases where motion corrupted >15% of DW images. In contrast, DTI parameters calculated with motion-M2 data were consistent with reference data. CONCLUSION This proof-of-principle study demonstrates that motion compensating diffusion gradients can mitigate artifacts because of continuous motion in DTI of the brain and offers promise for improved DTI accessibility. Further study will be necessary to determine the robustness of the approach in patient populations with high susceptibility to head motion.
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Affiliation(s)
- Danielle Kara
- Cardiovascular Innovation Research Center, Heart, Vascular, and Thoracic Institute, Cleveland Clinic
| | | | - Mark Lowe
- Imaging Sciences, Imaging Institute, Cleveland Clinic
| | - Christopher Nguyen
- Cardiovascular Innovation Research Center, Heart, Vascular, and Thoracic Institute, Cleveland Clinic
- Imaging Sciences, Imaging Institute, Cleveland Clinic
- Biomedical Engineering, Lerner Research Institute, Cleveland Clinic and Case Western Reserve University
| | - Ken Sakaie
- Imaging Sciences, Imaging Institute, Cleveland Clinic
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Christodoulou AG, Cruz G, Arami A, Weingärtner S, Artico J, Peters D, Seiberlich N. The future of cardiovascular magnetic resonance: All-in-one vs. real-time (Part 1). J Cardiovasc Magn Reson 2024; 26:100997. [PMID: 38237900 PMCID: PMC11211239 DOI: 10.1016/j.jocmr.2024.100997] [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: 12/21/2023] [Accepted: 01/10/2024] [Indexed: 02/26/2024] Open
Abstract
Cardiovascular magnetic resonance (CMR) protocols can be lengthy and complex, which has driven the research community to develop new technologies to make these protocols more efficient and patient-friendly. Two different approaches to improving CMR have been proposed, specifically "all-in-one" CMR, where several contrasts and/or motion states are acquired simultaneously, and "real-time" CMR, in which the examination is accelerated to avoid the need for breathholding and/or cardiac gating. The goal of this two-part manuscript is to describe these two different types of emerging rapid CMR. To this end, the vision of each is described, along with techniques which have been devised and tested along the pathway of clinical implementation. The pros and cons of the different methods are presented, and the remaining open needs of each are detailed. Part 1 will tackle the "all-in-one" approaches, and Part 2 the "real-time" approaches along with an overall summary of these emerging methods.
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Affiliation(s)
- Anthony G Christodoulou
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Gastao Cruz
- Michigan Institute for Imaging Technology and Translation, Department of Radiology, University of Michigan, Ann Arbor, MI, USA
| | - Ayda Arami
- Department of Imaging Physics, Delft University of Technology, Delft, the Netherlands; Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Sebastian Weingärtner
- Department of Imaging Physics, Delft University of Technology, Delft, the Netherlands
| | | | - Dana Peters
- Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Nicole Seiberlich
- Michigan Institute for Imaging Technology and Translation, Department of Radiology, University of Michigan, Ann Arbor, MI, USA.
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Bonner BP, Yurista SR, Coll‐Font J, Chen S, Eder RA, Foster AN, Nguyen KD, Caravan P, Gale EM, Nguyen C. Contrast-Enhanced Cardiac Magnetic Resonance Imaging With a Manganese-Based Alternative to Gadolinium for Tissue Characterization of Acute Myocardial Infarction. J Am Heart Assoc 2023; 12:e026923. [PMID: 37042259 PMCID: PMC10227253 DOI: 10.1161/jaha.122.026923] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 01/05/2023] [Indexed: 04/13/2023]
Abstract
Background Late gadolinium enhancement cardiac magnetic resonance imaging is an effective and reproducible method for characterizing myocardial infarction. However, gadolinium-based contrast agents are contraindicated in patients with acute and chronic renal insufficiency. In addition, several recent studies have noted tissue deposition of free gadolinium in patients who have undergone serial contrast-enhanced magnetic resonance imaging. There is a clinical need for alternative forms of magnetic resonance imaging contrast agents that are acceptable in the setting of renal insufficiency. Methods and Results Three days after 80 minutes of ischemia/reperfusion of the left anterior descending coronary artery, cardiac magnetic resonance imaging was performed to assess myocardial lesion burden using both contrast agents. Late gadolinium enhancement cardiac magnetic resonance imaging was examined 10 and 15 minutes after contrast injection. Contrast agents were administered in alternating manner with a 2- to 3-hour washout period between contrast agent injections. Lesion evaluation and image processing were performed using Segment Medviso software. Mean infarct size and transmurality, measured using RVP-001, were not different compared with those measured using late gadolinium enhancement images. Bland-Altman analysis demonstrated a nominal bias of 0.13 mL (<1% of average total lesion volume) for RVP-001 in terms of gross infarct size measurement. Conclusions The experimental manganese-based contrast agent RVP-001 appears to be an effective agent for assessment of myocardial infarction location, size, and transmurality, and it may be useful as an alternative to gadolinium-based agents.
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Affiliation(s)
- Benjamin P. Bonner
- Cardiovascular Research CenterMassachusetts General HospitalBostonMA
- Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General HospitalBostonMA
- Louisiana State University Health Sciences CenterNew OrleansLA
| | - Salva R. Yurista
- Cardiovascular Research CenterMassachusetts General HospitalBostonMA
- Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General HospitalBostonMA
- Harvard Medical SchoolBostonMA
| | - Jaume Coll‐Font
- Cardiovascular Research CenterMassachusetts General HospitalBostonMA
- Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General HospitalBostonMA
- Harvard Medical SchoolBostonMA
| | - Shi Chen
- Cardiovascular Research CenterMassachusetts General HospitalBostonMA
- Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General HospitalBostonMA
| | - Robert A. Eder
- Cardiovascular Research CenterMassachusetts General HospitalBostonMA
- Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General HospitalBostonMA
| | - Anna N. Foster
- Cardiovascular Research CenterMassachusetts General HospitalBostonMA
- Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General HospitalBostonMA
| | - Khoi D. Nguyen
- Cardiovascular Research CenterMassachusetts General HospitalBostonMA
- Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General HospitalBostonMA
- Harvard Medical SchoolBostonMA
| | - Peter Caravan
- Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General HospitalBostonMA
- Harvard Medical SchoolBostonMA
| | - Eric M. Gale
- Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General HospitalBostonMA
- Harvard Medical SchoolBostonMA
| | - Christopher Nguyen
- Cardiovascular Research CenterMassachusetts General HospitalBostonMA
- Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General HospitalBostonMA
- Harvard Medical SchoolBostonMA
- Division of Health Science TechnologyHarvard–Massachusetts Institute of TechnologyCambridgeMA
- Cardiovascular Innovation Research CenterHeart, Vascular, and Thoracic Institute, Cleveland ClinicClevelandOH
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Dejea H, Schlepütz CM, Méndez-Carmona N, Arnold M, Garcia-Canadilla P, Longnus SL, Stampanoni M, Bijnens B, Bonnin A. A tomographic microscopy-compatible Langendorff system for the dynamic structural characterization of the cardiac cycle. Front Cardiovasc Med 2022; 9:1023483. [PMID: 36620622 PMCID: PMC9815149 DOI: 10.3389/fcvm.2022.1023483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 12/07/2022] [Indexed: 12/24/2022] Open
Abstract
Introduction Cardiac architecture has been extensively investigated ex vivo using a broad spectrum of imaging techniques. Nevertheless, the heart is a dynamic system and the structural mechanisms governing the cardiac cycle can only be unveiled when investigating it as such. Methods This work presents the customization of an isolated, perfused heart system compatible with synchrotron-based X-ray phase contrast imaging (X-PCI). Results Thanks to the capabilities of the developed setup, it was possible to visualize a beating isolated, perfused rat heart for the very first time in 4D at an unprecedented 2.75 μm pixel size (10.6 μm spatial resolution), and 1 ms temporal resolution. Discussion The customized setup allows high-spatial resolution studies of heart architecture along the cardiac cycle and has thus the potential to serve as a tool for the characterization of the structural dynamics of the heart, including the effects of drugs and other substances able to modify the cardiac cycle.
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Affiliation(s)
- Hector Dejea
- Paul Scherrer Institute, Villigen, Switzerland,Institute for Biomedical Engineering, University and ETH Zürich, Zurich, Switzerland,*Correspondence: Hector Dejea ✉
| | | | - Natalia Méndez-Carmona
- Department of Cardiac Surgery, Inselspital, Bern University Hospital, Bern, Switzerland,Department for BioMedical Research, University of Bern, Bern, Switzerland
| | - Maria Arnold
- Department of Cardiac Surgery, Inselspital, Bern University Hospital, Bern, Switzerland,Department for BioMedical Research, University of Bern, Bern, Switzerland
| | - Patricia Garcia-Canadilla
- BCNatal-Barcelona Center for Maternal-Fetal and Neonatal Medicine, Hospital Sant Joan de Déu and Hospital Clínic, University of Barcelona, Barcelona, Spain,Cardiovascular Diseases and Child Development, Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Spain
| | - Sarah L. Longnus
- Department of Cardiac Surgery, Inselspital, Bern University Hospital, Bern, Switzerland,Department for BioMedical Research, University of Bern, Bern, Switzerland
| | - Marco Stampanoni
- Paul Scherrer Institute, Villigen, Switzerland,Institute for Biomedical Engineering, University and ETH Zürich, Zurich, Switzerland
| | - Bart Bijnens
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain,Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Anne Bonnin
- Paul Scherrer Institute, Villigen, Switzerland
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Ferreira PF, Banerjee A, Scott AD, Khalique Z, Yang G, Rajakulasingam R, Dwornik M, De Silva R, Pennell DJ, Firmin DN, Nielles‐Vallespin S. Accelerating Cardiac Diffusion Tensor Imaging With a U-Net Based Model: Toward Single Breath-Hold. J Magn Reson Imaging 2022; 56:1691-1704. [PMID: 35460138 PMCID: PMC9790699 DOI: 10.1002/jmri.28199] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 04/04/2022] [Accepted: 04/04/2022] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND In vivo cardiac diffusion tensor imaging (cDTI) characterizes myocardial microstructure. Despite its potential clinical impact, considerable technical challenges exist due to the inherent low signal-to-noise ratio. PURPOSE To reduce scan time toward one breath-hold by reconstructing diffusion tensors for in vivo cDTI with a fitting-free deep learning approach. STUDY TYPE Retrospective. POPULATION A total of 197 healthy controls, 547 cardiac patients. FIELD STRENGTH/SEQUENCE A 3 T, diffusion-weighted stimulated echo acquisition mode single-shot echo-planar imaging sequence. ASSESSMENT A U-Net was trained to reconstruct the diffusion tensor elements of the reference results from reduced datasets that could be acquired in 5, 3 or 1 breath-hold(s) (BH) per slice. Fractional anisotropy (FA), mean diffusivity (MD), helix angle (HA), and sheetlet angle (E2A) were calculated and compared to the same measures when using a conventional linear-least-square (LLS) tensor fit with the same reduced datasets. A conventional LLS tensor fit with all available data (12 ± 2.0 [mean ± sd] breath-holds) was used as the reference baseline. STATISTICAL TESTS Wilcoxon signed rank/rank sum and Kruskal-Wallis tests. Statistical significance threshold was set at P = 0.05. Intersubject measures are quoted as median [interquartile range]. RESULTS For global mean or median results, both the LLS and U-Net methods with reduced datasets present a bias for some of the results. For both LLS and U-Net, there is a small but significant difference from the reference results except for LLS: MD 5BH (P = 0.38) and MD 3BH (P = 0.09). When considering direct pixel-wise errors the U-Net model outperformed significantly the LLS tensor fit for reduced datasets that can be acquired in three or just one breath-hold for all parameters. DATA CONCLUSION Diffusion tensor prediction with a trained U-Net is a promising approach to minimize the number of breath-holds needed in clinical cDTI studies. EVIDENCE LEVEL 4 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Pedro F. Ferreira
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | | | - Andrew D. Scott
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - Zohya Khalique
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - Guang Yang
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - Ramyah Rajakulasingam
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - Maria Dwornik
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - Ranil De Silva
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - Dudley J. Pennell
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - David N. Firmin
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - Sonia Nielles‐Vallespin
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
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10
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Magat J, Yon M, Bihan-Poudec Y, Ozenne V. A groupwise registration and tractography framework for cardiac myofiber architecture description by diffusion MRI: An application to the ventricular junctions. PLoS One 2022; 17:e0271279. [PMID: 35849598 PMCID: PMC9292118 DOI: 10.1371/journal.pone.0271279] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 06/27/2022] [Indexed: 11/19/2022] Open
Abstract
Background Knowledge of the normal myocardial–myocyte orientation could theoretically allow the definition of relevant quantitative biomarkers in clinical routine to diagnose heart pathologies. A whole heart diffusion tensor template representative of the global myofiber organization over species is therefore crucial for comparisons across populations. In this study, we developed a groupwise registration and tractography framework to resolve the global myofiber arrangement of large mammalian sheep hearts. To demonstrate the potential application of the proposed method, a novel description of sub-regions in the intraventricular septum is presented. Methods Three explanted sheep (ovine) hearts (size ~12×8×6 cm3, heart weight ~ 150 g) were perfused with contrast agent and fixative and imaged in a 9.4T magnet. A group-wise registration of high-resolution anatomical and diffusion-weighted images were performed to generate anatomical and diffusion tensor templates. Diffusion tensor metrics (eigenvalues, eigenvectors, fractional anisotropy …) were computed to provide a quantitative and spatially-resolved analysis of cardiac microstructure. Then tractography was performed using deterministic and probabilistic algorithms and used for different purposes: i) Visualization of myofiber architecture, ii) Segmentation of sub-area depicting the same fiber organization, iii) Seeding and Tract Editing. Finally, dissection was performed to confirm the existence of macroscopic structures identified in the diffusion tensor template. Results The template creation takes advantage of high-resolution anatomical and diffusion-weighted images obtained at an isotropic resolution of 150 μm and 600 μm respectively, covering ventricles and atria and providing information on the normal myocardial architecture. The diffusion metric distributions from the template were found close to the one of the individual samples validating the registration procedure. Small new sub-regions exhibiting spatially sharp variations in fiber orientation close to the junctions of the septum and ventricles were identified. Each substructure was defined and represented using streamlines. The existence of a fiber-bundles in the posterior junction was validated by anatomical dissection. A complex structural organization of the anterior junction in comparison to the posterior junction was evidenced by the high-resolution acquisition. Conclusions A new framework combining cardiac template generation and tractography was applied on the whole sheep heart. The framework can be used for anatomical investigation, characterization of microstructure and visualization of myofiber orientation across samples. Finally, a novel description of the ventricular junction in large mammalian sheep hearts was proposed.
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Affiliation(s)
- Julie Magat
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Foundation Bordeaux Université, Bordeaux, France
- Centre de recherche Cardio-Thoracique de Bordeaux, Univ. Bordeaux, U1045, Bordeaux, France
- INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, U1045, Bordeaux, France
| | - Maxime Yon
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Foundation Bordeaux Université, Bordeaux, France
- Centre de recherche Cardio-Thoracique de Bordeaux, Univ. Bordeaux, U1045, Bordeaux, France
- INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, U1045, Bordeaux, France
| | - Yann Bihan-Poudec
- Institut des Sciences Cognitives Marc Jeannerod, CNRS UMR 5229, Université Claude Bernard Lyon I, Bron, France
| | - Valéry Ozenne
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Foundation Bordeaux Université, Bordeaux, France
- Centre de recherche Cardio-Thoracique de Bordeaux, Univ. Bordeaux, U1045, Bordeaux, France
- INSERM, Centre de recherche Cardio-Thoracique de Bordeaux, U1045, Bordeaux, France
- Centre de Résonance Magnétique des Systèmes Biologiques, UMR 5536, CNRS/Université de Bordeaux, Bordeaux, France
- * E-mail:
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11
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Eder RA, van den Boomen M, Yurista SR, Rodriguez-Aviles YG, Islam MR, Chen YCI, Trager L, Coll-Font J, Cheng L, Li H, Rosenzweig A, Wrann CD, Nguyen CT. Exercise-induced CITED4 expression is necessary for regional remodeling of cardiac microstructural tissue helicity. Commun Biol 2022; 5:656. [PMID: 35787681 PMCID: PMC9253017 DOI: 10.1038/s42003-022-03635-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 06/23/2022] [Indexed: 11/10/2022] Open
Abstract
Both exercise-induced molecular mechanisms and physiological cardiac remodeling have been previously studied on a whole heart level. However, the regional microstructural tissue effects of these molecular mechanisms in the heart have yet to be spatially linked and further elucidated. We show in exercised mice that the expression of CITED4, a transcriptional co-regulator necessary for cardioprotection, is regionally heterogenous in the heart with preferential significant increases in the lateral wall compared with sedentary mice. Concordantly in this same region, the heart’s local microstructural tissue helicity is also selectively increased in exercised mice. Quantification of CITED4 expression and microstructural tissue helicity reveals a significant correlation across both sedentary and exercise mouse cohorts. Furthermore, genetic deletion of CITED4 in the heart prohibits regional exercise-induced microstructural helicity remodeling. Taken together, CITED4 expression is necessary for exercise-induced regional remodeling of the heart’s microstructural helicity revealing how a key molecular regulator of cardiac remodeling manifests into downstream local tissue-level changes. Expression of transcription factor CITED4 is necessary for exercise-induced regional remodeling of the heart’s microstructural helicity, revealing how a key molecular regulator of cardiac remodeling mediates local tissue-level changes.
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Affiliation(s)
- Robert A Eder
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA, 02129, USA
| | - Maaike van den Boomen
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA, 02129, USA.,Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA.,Department of Radiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands.,Harvard Medical School, Boston, MA, 02129, USA
| | - Salva R Yurista
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA, 02129, USA.,Harvard Medical School, Boston, MA, 02129, USA
| | - Yaiel G Rodriguez-Aviles
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA, 02129, USA.,Ponce Health Sciences University, School of Medicine, Ponce, PR, 00716, USA
| | - Mohammad Rashedul Islam
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA, 02129, USA.,Harvard Medical School, Boston, MA, 02129, USA
| | - Yin-Ching Iris Chen
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA.,Harvard Medical School, Boston, MA, 02129, USA
| | - Lena Trager
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA, 02129, USA
| | - Jaume Coll-Font
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA, 02129, USA.,Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA.,Harvard Medical School, Boston, MA, 02129, USA
| | - Leo Cheng
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA.,Harvard Medical School, Boston, MA, 02129, USA
| | - Haobo Li
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA, 02129, USA.,Harvard Medical School, Boston, MA, 02129, USA
| | - Anthony Rosenzweig
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA, 02129, USA.,Harvard Medical School, Boston, MA, 02129, USA.,Massachusetts General Hospital, Cardiology Division and Corrigan Minehan Heart Center, Boston, MA, 02114, USA
| | - Christiane D Wrann
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA, 02129, USA. .,Harvard Medical School, Boston, MA, 02129, USA. .,McCance Center for Brain Health, Massachusetts General Hospital, Boston, MA, 02114, USA.
| | - Christopher T Nguyen
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA, 02129, USA. .,Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA. .,Harvard Medical School, Boston, MA, 02129, USA. .,Division of Health Sciences and Technology, Harvard-Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. .,Cardiovascular Innovation Research Center, Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio, 44195, USA.
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12
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Biochemical and Structural Imaging of Remodeled Myocardium. CURRENT OPINION IN PHYSIOLOGY 2022. [DOI: 10.1016/j.cophys.2022.100570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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13
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Stimm J, Guenthner C, Kozerke S, Stoeck CT. Comparison of interpolation methods of predominant cardiomyocyte orientation from in vivo and ex vivo cardiac diffusion tensor imaging data. NMR IN BIOMEDICINE 2022; 35:e4667. [PMID: 34964179 PMCID: PMC9285076 DOI: 10.1002/nbm.4667] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 11/25/2021] [Accepted: 11/26/2021] [Indexed: 06/14/2023]
Abstract
Cardiac electrophysiology and cardiac mechanics both depend on the average cardiomyocyte long-axis orientation. In the realm of personalized medicine, knowledge of the patient-specific changes in cardiac microstructure plays a crucial role. Patient-specific computational modelling has emerged as a tool to better understand disease progression. In vivo cardiac diffusion tensor imaging (cDTI) is a vital tool to non-destructively measure the average cardiomyocyte long-axis orientation in the heart. However, cDTI suffers from long scan times, rendering volumetric, high-resolution acquisitions challenging. Consequently, interpolation techniques are needed to populate bio-mechanical models with patient-specific average cardiomyocyte long-axis orientations. In this work, we compare five interpolation techniques applied to in vivo and ex vivo porcine input data. We compare two tensor interpolation approaches, one rule-based approximation, and two data-driven, low-rank models. We demonstrate the advantage of tensor interpolation techniques, resulting in lower interpolation errors than do low-rank models and rule-based methods adapted to cDTI data. In an ex vivo comparison, we study the influence of three imaging parameters that can be traded off against acquisition time: in-plane resolution, signal to noise ratio, and number of acquired short-axis imaging slices.
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Affiliation(s)
- Johanna Stimm
- Institute for Biomedical EngineeringUniversity and ETH ZurichZurichSwitzerland
| | - Christian Guenthner
- Institute for Biomedical EngineeringUniversity and ETH ZurichZurichSwitzerland
| | - Sebastian Kozerke
- Institute for Biomedical EngineeringUniversity and ETH ZurichZurichSwitzerland
| | - Christian T. Stoeck
- Institute for Biomedical EngineeringUniversity and ETH ZurichZurichSwitzerland
- Division of Surgical ResearchUniversity Hospital ZurichUniversity ZurichSwitzerland
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14
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Weine J, van Gorkum RJH, Stoeck CT, Vishnevskiy V, Kozerke S. Synthetically Trained Convolutional Neural Networks for Improved Tensor Estimation from Free-Breathing Cardiac DTI. Comput Med Imaging Graph 2022; 99:102075. [DOI: 10.1016/j.compmedimag.2022.102075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 03/15/2022] [Accepted: 05/05/2022] [Indexed: 10/18/2022]
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15
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Stimm J, Nordsletten DA, Jilberto J, Miller R, Berberoğlu E, Kozerke S, Stoeck CT. Personalization of biomechanical simulations of the left ventricle by in-vivo cardiac DTI data: Impact of fiber interpolation methods. Front Physiol 2022; 13:1042537. [PMID: 36518106 PMCID: PMC9742433 DOI: 10.3389/fphys.2022.1042537] [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: 09/12/2022] [Accepted: 11/14/2022] [Indexed: 11/29/2022] Open
Abstract
Simulations of cardiac electrophysiology and mechanics have been reported to be sensitive to the microstructural anisotropy of the myocardium. Consequently, a personalized representation of cardiac microstructure is a crucial component of accurate, personalized cardiac biomechanical models. In-vivo cardiac Diffusion Tensor Imaging (cDTI) is a non-invasive magnetic resonance imaging technique capable of probing the heart's microstructure. Being a rather novel technique, issues such as low resolution, signal-to noise ratio, and spatial coverage are currently limiting factors. We outline four interpolation techniques with varying degrees of data fidelity, different amounts of smoothing strength, and varying representation error to bridge the gap between the sparse in-vivo data and the model, requiring a 3D representation of microstructure across the myocardium. We provide a workflow to incorporate in-vivo myofiber orientation into a left ventricular model and demonstrate that personalized modelling based on fiber orientations from in-vivo cDTI data is feasible. The interpolation error is correlated with a trend in personalized parameters and simulated physiological parameters, strains, and ventricular twist. This trend in simulation results is consistent across material parameter settings and therefore corresponds to a bias introduced by the interpolation method. This study suggests that using a tensor interpolation approach to personalize microstructure with in-vivo cDTI data, reduces the fiber uncertainty and thereby the bias in the simulation results.
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Affiliation(s)
- Johanna Stimm
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - David A Nordsletten
- Department of Biomedical Engineering and Cardiac Surgery, University of Michigan, Ann Arbor, MI, United States.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Javiera Jilberto
- Department of Biomedical Engineering and Cardiac Surgery, University of Michigan, Ann Arbor, MI, United States
| | - Renee Miller
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Ezgi Berberoğlu
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Christian T Stoeck
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.,Division of Surgical Research, University Hospital Zurich, University Zurich, Zurich, Switzerland
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16
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Coll-Font J, Chen S, Eder R, Fang Y, Han QJ, van den Boomen M, Sosnovik DE, Mekkaoui C, Nguyen CT. Manifold-based respiratory phase estimation enables motion and distortion correction of free-breathing cardiac diffusion tensor MRI. Magn Reson Med 2022; 87:474-487. [PMID: 34390021 PMCID: PMC8616783 DOI: 10.1002/mrm.28972] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 07/22/2021] [Accepted: 07/25/2021] [Indexed: 01/03/2023]
Abstract
PURPOSE For in vivo cardiac DTI, breathing motion and B0 field inhomogeneities produce misalignment and geometric distortion in diffusion-weighted (DW) images acquired with conventional single-shot EPI. We propose using a dimensionality reduction method to retrospectively estimate the respiratory phase of DW images and facilitate both distortion correction (DisCo) and motion compensation. METHODS Free-breathing electrocardiogram-triggered whole left-ventricular cardiac DTI using a second-order motion-compensated spin echo EPI sequence and alternating directionality of phase encoding blips was performed on 11 healthy volunteers. The respiratory phase of each DW image was estimated after projecting the DW images into a 2D space with Laplacian eigenmaps. DisCo and motion compensation were applied to the respiratory sorted DW images. The results were compared against conventional breath-held T2 half-Fourier single shot turbo spin echo. Cardiac DTI parameters including fractional anisotropy, mean diffusivity, and helix angle transmurality were compared with and without DisCo. RESULTS The left-ventricular geometries after DisCo and motion compensation resulted in significantly improved alignment of DW images with T2 reference. DisCo reduced the distance between the left-ventricular contours by 13.2% ± 19.2%, P < .05 (2.0 ± 0.4 for DisCo and 2.4 ± 0.5 mm for uncorrected). DisCo DTI parameter maps yielded no significant differences (mean diffusivity: 1.55 ± 0.13 × 10-3 mm2 /s and 1.53 ± 0.13 × 10-3 mm2 /s, P = .09; fractional anisotropy: 0.375 ± 0.041 and 0.379 ± 0.045, P = .11; helix angle transmurality: 1.00% ± 0.10°/% and 0.99% ± 0.12°/%, P = .44), although the orientation of individual tensors differed. CONCLUSION Retrospective respiratory phase estimation with LE-based DisCo and motion compensation in free-breathing cardiac DTI resulting in significantly reduced geometric distortion and improved alignment within and across slices.
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Affiliation(s)
- Jaume Coll-Font
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (MA), USA,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston (MA), USA,Harvard Medical School, Boston (MA), USA
| | - Shi Chen
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (MA), USA
| | - Robert Eder
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (MA), USA
| | - Yiling Fang
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (MA), USA,Institute of Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, (MA), USA
| | - Qiao Joyce Han
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (MA), USA,Harvard Medical School, Boston (MA), USA
| | - Maaike van den Boomen
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (MA), USA,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston (MA), USA,Harvard Medical School, Boston (MA), USA,Department of Radiology, University Medical Center Groningen, Groningen, Netherlands
| | - David E. Sosnovik
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (MA), USA,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston (MA), USA,Harvard Medical School, Boston (MA), USA
| | - Choukri Mekkaoui
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (MA), USA,Harvard Medical School, Boston (MA), USA
| | - Christopher T. Nguyen
- Cardiovascular Research Center, Massachusetts General Hospital, Boston (MA), USA,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston (MA), USA,Harvard Medical School, Boston (MA), USA
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17
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Das A, Kelly C, Teh I, Nguyen C, Brown LAE, Chowdhary A, Jex N, Thirunavukarasu S, Sharrack N, Gorecka M, Swoboda PP, Greenwood JP, Kellman P, Moon JC, Davies RH, Lopes LR, Joy G, Plein S, Schneider JE, Dall'Armellina E. Phenotyping hypertrophic cardiomyopathy using cardiac diffusion magnetic resonance imaging: the relationship between microvascular dysfunction and microstructural changes. Eur Heart J Cardiovasc Imaging 2021; 23:352-362. [PMID: 34694365 PMCID: PMC8863073 DOI: 10.1093/ehjci/jeab210] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 10/16/2021] [Indexed: 01/05/2023] Open
Abstract
Aims Microvascular dysfunction in hypertrophic cardiomyopathy (HCM) is predictive of clinical decline, however underlying mechanisms remain unclear. Cardiac diffusion tensor imaging (cDTI) allows in vivo characterization of myocardial microstructure by quantifying mean diffusivity (MD), fractional anisotropy (FA) of diffusion, and secondary eigenvector angle (E2A). In this cardiac magnetic resonance (CMR) study, we examine associations between perfusion and cDTI parameters to understand the sequence of pathophysiology and the interrelation between vascular function and underlying microstructure. Methods and results Twenty HCM patients underwent 3.0T CMR which included: spin-echo cDTI, adenosine stress and rest perfusion mapping, cine-imaging, and late gadolinium enhancement (LGE). Ten controls underwent cDTI. Myocardial perfusion reserve (MPR), MD, FA, E2A, and wall thickness were calculated per segment and further divided into subendocardial (inner 50%) and subepicardial (outer 50%) regions. Segments with wall thickness ≤11 mm, MPR ≥2.2, and no visual LGE were classified as ‘normal’. Compared to controls, ‘normal’ HCM segments had increased MD (1.61 ± 0.09 vs. 1.46 ± 0.07 × 10−3 mm2/s, P = 0.02), increased E2A (60 ± 9° vs. 38 ± 12°, P < 0.001), and decreased FA (0.29 ± 0.04 vs. 0.35 ± 0.02, P = 0.002). Across all HCM segments, subendocardial regions had higher MD and lower MPR than subepicardial (MDendo 1.61 ± 0.08 × 10−3 mm2/s vs. MDepi 1.56 ± 0.18 × 10−3 mm2/s, P = 0.003, MPRendo 1.85 ± 0.83, MPRepi 2.28 ± 0.87, P < 0.0001). Conclusion In HCM patients, even in segments with normal wall thickness, normal perfusion, and no scar, diffusion is more isotropic than in controls, suggesting the presence of underlying cardiomyocyte disarray. Increased E2A suggests the myocardial sheetlets adopt hypercontracted angulation in systole. Increased MD, most notably in the subendocardium, is suggestive of regional remodelling which may explain the reduced subendocardial blood flow.
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Affiliation(s)
- Arka Das
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Christopher Kelly
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Irvin Teh
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Christopher Nguyen
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, 55 Fruit St, Boston, MA 02114, USA.,A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, 55 Fruit St, Boston, MA 02114, USA.,Department of Medicine, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA.,Biomedical Imaging Research Institute, Cedars-Sinai Medical Centre, 116 N Robertson Blvd, Los Angeles, CA 90048, USA
| | - Louise A E Brown
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Amrit Chowdhary
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Nicholas Jex
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Sharmaine Thirunavukarasu
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Noor Sharrack
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Miroslawa Gorecka
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Peter P Swoboda
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - John P Greenwood
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Peter Kellman
- National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, 31 Center Dr, Bethesda, MD 20892, USA
| | - James C Moon
- Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London EC1A 7BE, UK
| | - Rhodri H Davies
- Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London EC1A 7BE, UK
| | - Luis R Lopes
- Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London EC1A 7BE, UK.,Centre for Heart Muscle Disease, Institute of Cardiovascular Science, University College London, Gower St, London WC1E 6BT, UK
| | - George Joy
- Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London EC1A 7BE, UK
| | - Sven Plein
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Jürgen E Schneider
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Erica Dall'Armellina
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, 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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