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Cook MP, Dhahri W, Laflamme MA, Ghugre NR, Wright GA. Using Diffusion Tensor Imaging to Depict Changes After Matured Pluripotent Stem Cell-Derived Cardiomyocytes Transplantation. J Cardiovasc Magn Reson 2024:101045. [PMID: 38795790 DOI: 10.1016/j.jocmr.2024.101045] [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: 01/05/2024] [Revised: 05/10/2024] [Accepted: 05/17/2024] [Indexed: 05/28/2024] Open
Abstract
BACKGROUND Novel treatment strategies are needed to improve the structure and function in the myocardium post infarction. In vitro-matured pluripotent stem cell-derived cardiomyocytes (PSC-CMs), have been shown to be a promising regenerative strategy. We hypothesized that mature PSC-CMs will have anisotropic structure and improved cell alignment when compared to immature PSC-CMs using magnetic resonance imaging (MRI) in a guinea pig model of cardiac injury. METHODS Guinea pigs (n=16) were cryoinjured on day -10, followed by transplantation of either 108 polydimethylsiloxane-matured PSC-CMs (PDMS, n=6) or 108 immature tissue culture plastic-generated PSC-CMs (TCP, n=6) on day 0. Vehicle (sham-treated) subjects were injected with a pro-survival cocktail devoid of cells (n=4), while healthy controls (n=4) did not undergo cryoinjury or treatment. Animals were sacrificed on either day +14 or day +28 post transplantation. Animals were imaged ex vivo on a 7T Bruker MRI. A 3D Diffusion Tensor Imaging sequence was used to quantify structure via fractional anisotropy (FA), mean diffusivity (MD) and myocyte alignment measured by the standard deviation of the transverse angle (TA). RESULTS MD and FA of mature PDMS grafts demonstrated anisotropy that were not significantly different than the healthy control hearts (MD=1.1 ± 0.12 ×10-3 mm2/s vs. 0.93 ± 0.01 ×10-3 mm2/s, p=0.4 and FA=0.22±0.05 vs. 0.26±0.001, p=0.5). Immature TCP grafts exhibited significantly higher MD than the healthy control (1.3 ± 0.08 ×10-3 mm2/s, p<0.05) and significantly lower FA than the control (0.12±0.02, p< 0.05) but were not different from mature PDMS grafts in this small cohort. TA of healthy controls showed low variability and were not significantly different than mature PDMS grafts (p=0.4) while immature TCP grafts were significantly different (p<0.001). DISCUSSION DTI parameters of mature graft tissue trended towards that of the healthy myocardium, indicating the grafted cardiomyocytes may have a similar phenotype to healthy tissue. Contrast-enhanced MR images corresponded well to histological staining, demonstrating a non-invasive method of localizing the repopulated cardiomyocytes within the scar. CONCLUSIONS The DTI measures within graft tissue were indicative of anisotropic structure, and showed greater myocyte organization compared to the scarred territory. These findings show that MRI is a valuable tool to assess structural impacts of regenerative therapies.
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Affiliation(s)
- Moses P Cook
- Department of Medical Biophysics - University of Toronto, Toronto, ON, Canada.
| | - Wahiba Dhahri
- McEwen Centre for Regenerative Medicine, University Health Network, Toronto, ON, Canada; Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada.
| | - Michael A Laflamme
- McEwen Centre for Regenerative Medicine, University Health Network, Toronto, ON, Canada; Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada.
| | - Nilesh R Ghugre
- Department of Medical Biophysics - University of Toronto, Toronto, ON, Canada; Schulich Heart Research Program, Sunnybrook Research Institute, Toronto, ON, Canada; Physical Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada.
| | - Graham A Wright
- Department of Medical Biophysics - University of Toronto, Toronto, ON, Canada; Schulich Heart Research Program, Sunnybrook Research Institute, Toronto, ON, Canada; Physical Sciences Platform, Sunnybrook Research Institute, Toronto, ON, Canada.
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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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Atkins PR, Morris A, Elhabian SY, Anderson AE. A Correspondence-Based Network Approach for Groupwise Analysis of Patient-Specific Spatiotemporal Data. Ann Biomed Eng 2023; 51:2289-2300. [PMID: 37357248 PMCID: PMC11047278 DOI: 10.1007/s10439-023-03270-6] [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: 02/17/2023] [Accepted: 06/01/2023] [Indexed: 06/27/2023]
Abstract
Methods for statistically analyzing patient-specific data that vary both spatially and over time are currently either limited to summary statistics or require elaborate surface registration. We propose a new method, called correspondence-based network analysis, which leverages particle-based shape modeling to establish correspondence across a population and preserve patient-specific measurements and predictions through statistical analysis. Herein, we evaluated this method using three published datasets of the hip describing cortical bone thickness of the proximal femur, cartilage contact stress, and dynamic joint space between control and patient cohorts to evaluate activity- and group-based differences, as applicable, using traditional statistical parametric mapping (SPM) and our proposed spatially considerate correspondence-based network analysis approach. The network approach was insensitive to correspondence density, while the traditional application of SPM showed decreasing area of the region of significance with increasing correspondence density. In comparison to SPM, the network approach identified broader and more connected regions of significance for all three datasets. The correspondence-based network analysis approach identified differences between groups and activities without loss of subject and spatial specificity which could improve clinical interpretation of results.
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Affiliation(s)
- Penny R Atkins
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA
- Department of Orthopaedics, University of Utah, Salt Lake City, UT, USA
| | - Alan Morris
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA
| | - Shireen Y Elhabian
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA
- School of Computing, University of Utah, Salt Lake City, UT, USA
| | - Andrew E Anderson
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA.
- Department of Orthopaedics, University of Utah, Salt Lake City, UT, USA.
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA.
- Department of Physical Therapy, University of Utah, Salt Lake City, UT, USA.
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Pan J, Ng SM, Neubauer S, Rider OJ. Phenotyping heart failure by cardiac magnetic resonance imaging of cardiac macro- and microscopic structure: state of the art review. Eur Heart J Cardiovasc Imaging 2023; 24:1302-1317. [PMID: 37267310 PMCID: PMC10531211 DOI: 10.1093/ehjci/jead124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 05/26/2023] [Indexed: 06/04/2023] Open
Abstract
Heart failure demographics have evolved in past decades with the development of improved diagnostics, therapies, and prevention. Cardiac magnetic resonance (CMR) has developed in a similar timeframe to become the gold-standard non-invasive imaging modality for characterizing diseases causing heart failure. CMR techniques to assess cardiac morphology and function have progressed since their first use in the 1980s. Increasingly efficient acquisition protocols generate high spatial and temporal resolution images in less time. This has enabled new methods of characterizing cardiac systolic and diastolic function such as strain analysis, exercise real-time cine imaging and four-dimensional flow. A key strength of CMR is its ability to non-invasively interrogate the myocardial tissue composition. Gadolinium contrast agents revolutionized non-invasive cardiac imaging with the late gadolinium enhancement technique. Further advances enabled quantitative parametric mapping to increase sensitivity at detecting diffuse pathology. Novel methods such as diffusion tensor imaging and artificial intelligence-enhanced image generation are on the horizon. Magnetic resonance spectroscopy (MRS) provides a window into the molecular environment of the myocardium. Phosphorus (31P) spectroscopy can inform the status of cardiac energetics in health and disease. Proton (1H) spectroscopy complements this by measuring creatine and intramyocardial lipids. Hyperpolarized carbon (13C) spectroscopy is a novel method that could further our understanding of dynamic cardiac metabolism. CMR of other organs such as the lungs may add further depth into phenotypes of heart failure. The vast capabilities of CMR should be deployed and interpreted in context of current heart failure challenges.
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Affiliation(s)
- Jiliu Pan
- Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Level 0, John Radcliffe Hospital, Oxford, OX3 9DU, United Kingdom
| | - Sher May Ng
- Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Level 0, John Radcliffe Hospital, Oxford, OX3 9DU, United Kingdom
| | - Stefan Neubauer
- Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Level 0, John Radcliffe Hospital, Oxford, OX3 9DU, United Kingdom
| | - Oliver J Rider
- Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Level 0, John Radcliffe Hospital, Oxford, OX3 9DU, United Kingdom
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5
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Joy G, Kelly CI, Webber M, Pierce I, Teh I, McGrath L, Velazquez P, Hughes RK, Kotwal H, Das A, Chan F, Bakalakos A, Lorenzini M, Savvatis K, Mohiddin SA, Macfarlane PW, Orini M, Manisty C, Kellman P, Davies RH, Lambiase PD, Nguyen C, Schneider JE, Tome M, Captur G, Dall’Armellina E, Moon JC, Lopes LR. Microstructural and Microvascular Phenotype of Sarcomere Mutation Carriers and Overt Hypertrophic Cardiomyopathy. Circulation 2023; 148:808-818. [PMID: 37463608 PMCID: PMC10473031 DOI: 10.1161/circulationaha.123.063835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 06/19/2023] [Indexed: 07/20/2023]
Abstract
BACKGROUND In hypertrophic cardiomyopathy (HCM), myocyte disarray and microvascular disease (MVD) have been implicated in adverse events, and recent evidence suggests that these may occur early. As novel therapy provides promise for disease modification, detection of phenotype development is an emerging priority. To evaluate their utility as early and disease-specific biomarkers, we measured myocardial microstructure and MVD in 3 HCM groups-overt, either genotype-positive (G+LVH+) or genotype-negative (G-LVH+), and subclinical (G+LVH-) HCM-exploring relationships with electrical changes and genetic substrate. METHODS This was a multicenter collaboration to study 206 subjects: 101 patients with overt HCM (51 G+LVH+ and 50 G-LVH+), 77 patients with G+LVH-, and 28 matched healthy volunteers. All underwent 12-lead ECG, quantitative perfusion cardiac magnetic resonance imaging (measuring myocardial blood flow, myocardial perfusion reserve, and perfusion defects), and cardiac diffusion tensor imaging measuring fractional anisotropy (lower values expected with more disarray), mean diffusivity (reflecting myocyte packing/interstitial expansion), and second eigenvector angle (measuring sheetlet orientation). RESULTS Compared with healthy volunteers, patients with overt HCM had evidence of altered microstructure (lower fractional anisotropy, higher mean diffusivity, and higher second eigenvector angle; all P<0.001) and MVD (lower stress myocardial blood flow and myocardial perfusion reserve; both P<0.001). Patients with G-LVH+ were similar to those with G+LVH+ but had elevated second eigenvector angle (P<0.001 after adjustment for left ventricular hypertrophy and fibrosis). In overt disease, perfusion defects were found in all G+ but not all G- patients (100% [51/51] versus 82% [41/50]; P=0.001). Patients with G+LVH- compared with healthy volunteers similarly had altered microstructure, although to a lesser extent (all diffusion tensor imaging parameters; P<0.001), and MVD (reduced stress myocardial blood flow [P=0.015] with perfusion defects in 28% versus 0 healthy volunteers [P=0.002]). Disarray and MVD were independently associated with pathological electrocardiographic abnormalities in both overt and subclinical disease after adjustment for fibrosis and left ventricular hypertrophy (overt: fractional anisotropy: odds ratio for an abnormal ECG, 3.3, P=0.01; stress myocardial blood flow: odds ratio, 2.8, P=0.015; subclinical: fractional anisotropy odds ratio, 4.0, P=0.001; myocardial perfusion reserve odds ratio, 2.2, P=0.049). CONCLUSIONS Microstructural alteration and MVD occur in overt HCM and are different in G+ and G- patients. Both also occur in the absence of hypertrophy in sarcomeric mutation carriers, in whom changes are associated with electrocardiographic abnormalities. Measurable changes in myocardial microstructure and microvascular function are early-phenotype biomarkers in the emerging era of disease-modifying therapy.
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Affiliation(s)
- George Joy
- Barts Heart Centre, Barts Health NHS Trust, London, UK (G.J., I.P., P.V., R.K.H., H.K., A.B., M.L., K.S., S.A.M., M.O., C.M., R.H.D., P.D.L., J.C.M., L.R.L.)
- Institute of Cardiovascular Science (G.J.. M.W., I.P., R.K.H., F.C., A.B., M.L., K.S., M.O., C.M., R.H.D., P.D.L., G.C., J.C.M., L.R.L.), University College London, UK
| | - Christopher I. Kelly
- Biomedical Imaging Sciences Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, UK (C.I.L., I.T., A.D., J.E.S., E.D.)
| | - Matthew Webber
- Institute of Cardiovascular Science (G.J.. M.W., I.P., R.K.H., F.C., A.B., M.L., K.S., M.O., C.M., R.H.D., P.D.L., G.C., J.C.M., L.R.L.), University College London, UK
- Medical Research Council Unit for Lifelong Health and Ageing (M.W., I.P., F.C., R.H.D., G.C.), University College London, UK
- Centre for Inherited Heart Muscle Conditions, Department of Cardiology, Royal Free London NHS Foundation Trust, UK (M.W., F.C., G.C.)
| | - Iain Pierce
- Barts Heart Centre, Barts Health NHS Trust, London, UK (G.J., I.P., P.V., R.K.H., H.K., A.B., M.L., K.S., S.A.M., M.O., C.M., R.H.D., P.D.L., J.C.M., L.R.L.)
- Institute of Cardiovascular Science (G.J.. M.W., I.P., R.K.H., F.C., A.B., M.L., K.S., M.O., C.M., R.H.D., P.D.L., G.C., J.C.M., L.R.L.), University College London, UK
- Medical Research Council Unit for Lifelong Health and Ageing (M.W., I.P., F.C., R.H.D., G.C.), University College London, UK
| | - Irvin Teh
- Biomedical Imaging Sciences Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, UK (C.I.L., I.T., A.D., J.E.S., E.D.)
| | - Louise McGrath
- Imaging Department, Royal Brompton & Harefield Hospitals, London, UK (L.M.)
| | - Paula Velazquez
- Barts Heart Centre, Barts Health NHS Trust, London, UK (G.J., I.P., P.V., R.K.H., H.K., A.B., M.L., K.S., S.A.M., M.O., C.M., R.H.D., P.D.L., J.C.M., L.R.L.)
- Cardiology Clinical and Academic Group, St. Georges University of London and St. Georges University Hospitals NHS Foundation Trust, UK (P.V., M.T.)
| | - Rebecca K. Hughes
- Barts Heart Centre, Barts Health NHS Trust, London, UK (G.J., I.P., P.V., R.K.H., H.K., A.B., M.L., K.S., S.A.M., M.O., C.M., R.H.D., P.D.L., J.C.M., L.R.L.)
- Institute of Cardiovascular Science (G.J.. M.W., I.P., R.K.H., F.C., A.B., M.L., K.S., M.O., C.M., R.H.D., P.D.L., G.C., J.C.M., L.R.L.), University College London, UK
| | - Huafrin Kotwal
- Barts Heart Centre, Barts Health NHS Trust, London, UK (G.J., I.P., P.V., R.K.H., H.K., A.B., M.L., K.S., S.A.M., M.O., C.M., R.H.D., P.D.L., J.C.M., L.R.L.)
| | - Arka Das
- Biomedical Imaging Sciences Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, UK (C.I.L., I.T., A.D., J.E.S., E.D.)
| | - Fiona Chan
- Institute of Cardiovascular Science (G.J.. M.W., I.P., R.K.H., F.C., A.B., M.L., K.S., M.O., C.M., R.H.D., P.D.L., G.C., J.C.M., L.R.L.), University College London, UK
- Medical Research Council Unit for Lifelong Health and Ageing (M.W., I.P., F.C., R.H.D., G.C.), University College London, UK
- Centre for Inherited Heart Muscle Conditions, Department of Cardiology, Royal Free London NHS Foundation Trust, UK (M.W., F.C., G.C.)
| | - Athanasios Bakalakos
- Barts Heart Centre, Barts Health NHS Trust, London, UK (G.J., I.P., P.V., R.K.H., H.K., A.B., M.L., K.S., S.A.M., M.O., C.M., R.H.D., P.D.L., J.C.M., L.R.L.)
- Institute of Cardiovascular Science (G.J.. M.W., I.P., R.K.H., F.C., A.B., M.L., K.S., M.O., C.M., R.H.D., P.D.L., G.C., J.C.M., L.R.L.), University College London, UK
| | - Massimiliano Lorenzini
- Barts Heart Centre, Barts Health NHS Trust, London, UK (G.J., I.P., P.V., R.K.H., H.K., A.B., M.L., K.S., S.A.M., M.O., C.M., R.H.D., P.D.L., J.C.M., L.R.L.)
- Institute of Cardiovascular Science (G.J.. M.W., I.P., R.K.H., F.C., A.B., M.L., K.S., M.O., C.M., R.H.D., P.D.L., G.C., J.C.M., L.R.L.), University College London, UK
| | - Konstantinos Savvatis
- Barts Heart Centre, Barts Health NHS Trust, London, UK (G.J., I.P., P.V., R.K.H., H.K., A.B., M.L., K.S., S.A.M., M.O., C.M., R.H.D., P.D.L., J.C.M., L.R.L.)
- Institute of Cardiovascular Science (G.J.. M.W., I.P., R.K.H., F.C., A.B., M.L., K.S., M.O., C.M., R.H.D., P.D.L., G.C., J.C.M., L.R.L.), University College London, UK
- William Harvey Research Institute, Queen Mary University London, UK (K.S., S.A.M.)
| | - Saidi A. Mohiddin
- Barts Heart Centre, Barts Health NHS Trust, London, UK (G.J., I.P., P.V., R.K.H., H.K., A.B., M.L., K.S., S.A.M., M.O., C.M., R.H.D., P.D.L., J.C.M., L.R.L.)
- William Harvey Research Institute, Queen Mary University London, UK (K.S., S.A.M.)
| | - Peter W. Macfarlane
- Electrocardiology Section, School of Health and Wellbeing, University of Glasgow, UK (P.W.M.)
| | - Michele Orini
- Barts Heart Centre, Barts Health NHS Trust, London, UK (G.J., I.P., P.V., R.K.H., H.K., A.B., M.L., K.S., S.A.M., M.O., C.M., R.H.D., P.D.L., J.C.M., L.R.L.)
- Institute of Cardiovascular Science (G.J.. M.W., I.P., R.K.H., F.C., A.B., M.L., K.S., M.O., C.M., R.H.D., P.D.L., G.C., J.C.M., L.R.L.), University College London, UK
| | - Charlotte Manisty
- Barts Heart Centre, Barts Health NHS Trust, London, UK (G.J., I.P., P.V., R.K.H., H.K., A.B., M.L., K.S., S.A.M., M.O., C.M., R.H.D., P.D.L., J.C.M., L.R.L.)
- Institute of Cardiovascular Science (G.J.. M.W., I.P., R.K.H., F.C., A.B., M.L., K.S., M.O., C.M., R.H.D., P.D.L., G.C., J.C.M., L.R.L.), University College London, UK
| | - Peter Kellman
- National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, Bethesda, MD (P.K.)
| | - Rhodri H. Davies
- Barts Heart Centre, Barts Health NHS Trust, London, UK (G.J., I.P., P.V., R.K.H., H.K., A.B., M.L., K.S., S.A.M., M.O., C.M., R.H.D., P.D.L., J.C.M., L.R.L.)
- Institute of Cardiovascular Science (G.J.. M.W., I.P., R.K.H., F.C., A.B., M.L., K.S., M.O., C.M., R.H.D., P.D.L., G.C., J.C.M., L.R.L.), University College London, UK
- Medical Research Council Unit for Lifelong Health and Ageing (M.W., I.P., F.C., R.H.D., G.C.), University College London, UK
| | - Pier D. Lambiase
- Barts Heart Centre, Barts Health NHS Trust, London, UK (G.J., I.P., P.V., R.K.H., H.K., A.B., M.L., K.S., S.A.M., M.O., C.M., R.H.D., P.D.L., J.C.M., L.R.L.)
- Institute of Cardiovascular Science (G.J.. M.W., I.P., R.K.H., F.C., A.B., M.L., K.S., M.O., C.M., R.H.D., P.D.L., G.C., J.C.M., L.R.L.), University College London, UK
| | - Christopher Nguyen
- Cardiovascular Innovation Research Centre, HVTI, Cleveland Clinic, OH (C.N.)
| | - Jurgen E. Schneider
- Biomedical Imaging Sciences Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, UK (C.I.L., I.T., A.D., J.E.S., E.D.)
| | - Maite Tome
- Cardiology Clinical and Academic Group, St. Georges University of London and St. Georges University Hospitals NHS Foundation Trust, UK (P.V., M.T.)
| | - Gabriella Captur
- Institute of Cardiovascular Science (G.J.. M.W., I.P., R.K.H., F.C., A.B., M.L., K.S., M.O., C.M., R.H.D., P.D.L., G.C., J.C.M., L.R.L.), University College London, UK
- Medical Research Council Unit for Lifelong Health and Ageing (M.W., I.P., F.C., R.H.D., G.C.), University College London, UK
- Centre for Inherited Heart Muscle Conditions, Department of Cardiology, Royal Free London NHS Foundation Trust, UK (M.W., F.C., G.C.)
| | - Erica Dall’Armellina
- Biomedical Imaging Sciences Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, UK (C.I.L., I.T., A.D., J.E.S., E.D.)
| | - James C. Moon
- Barts Heart Centre, Barts Health NHS Trust, London, UK (G.J., I.P., P.V., R.K.H., H.K., A.B., M.L., K.S., S.A.M., M.O., C.M., R.H.D., P.D.L., J.C.M., L.R.L.)
- Institute of Cardiovascular Science (G.J.. M.W., I.P., R.K.H., F.C., A.B., M.L., K.S., M.O., C.M., R.H.D., P.D.L., G.C., J.C.M., L.R.L.), University College London, UK
| | - Luis R. Lopes
- Barts Heart Centre, Barts Health NHS Trust, London, UK (G.J., I.P., P.V., R.K.H., H.K., A.B., M.L., K.S., S.A.M., M.O., C.M., R.H.D., P.D.L., J.C.M., L.R.L.)
- Institute of Cardiovascular Science (G.J.. M.W., I.P., R.K.H., F.C., A.B., M.L., K.S., M.O., C.M., R.H.D., P.D.L., G.C., J.C.M., L.R.L.), University College London, UK
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6
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Ayers MP, Kramer CM. Imaging Myofibrillar Disarray and Microvascular Dysfunction in Hypertrophic Cardiomyopathy: Novel Imaging Biomarkers for a New Era in Therapeutics. Circulation 2023; 148:819-821. [PMID: 37669360 PMCID: PMC10491427 DOI: 10.1161/circulationaha.123.065789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/07/2023]
Affiliation(s)
| | - Christopher M. Kramer
- Cardiovascular Division, Department of Medicine
- Department of Radiology and Medical Imaging
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7
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Guan D, Zhuan X, Luo X, Gao H. An updated Lagrangian constrained mixture model of pathological cardiac growth and remodelling. Acta Biomater 2023; 166:375-399. [PMID: 37201740 DOI: 10.1016/j.actbio.2023.05.022] [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: 12/14/2022] [Revised: 05/03/2023] [Accepted: 05/10/2023] [Indexed: 05/20/2023]
Abstract
Progressive left ventricular (LV) growth and remodelling (G&R) is often induced by volume and pressure overload, characterized by structural and functional adaptation through myocyte hypertrophy and extracellular matrix remodelling, which are dynamically regulated by biomechanical factors, inflammation, neurohormonal pathways, etc. When prolonged, it can eventually lead to irreversible heart failure. In this study, we have developed a new framework for modelling pathological cardiac G&R based on constrained mixture theory using an updated reference configuration, which is triggered by altered biomechanical factors to restore biomechanical homeostasis. Eccentric and concentric growth, and their combination have been explored in a patient-specific human LV model under volume and pressure overload. Eccentric growth is triggered by overstretching of myofibres due to volume overload, i.e. mitral regurgitation, whilst concentric growth is driven by excessive contractile stress due to pressure overload, i.e. aortic stenosis. Different biological constituent's adaptations under pathological conditions are integrated together, which are the ground matrix, myofibres and collagen network. We have shown that this constrained mixture-motivated G&R model can capture different phenotypes of maladaptive LV G&R, such as chamber dilation and wall thinning under volume overload, wall thickening under pressure overload, and more complex patterns under both pressure and volume overload. We have further demonstrated how collagen G&R would affect LV structural and functional adaption by providing mechanistic insight on anti-fibrotic interventions. This updated Lagrangian constrained mixture based myocardial G&R model has the potential to understand the turnover processes of myocytes and collagen due to altered local mechanical stimuli in heart diseases, and in providing mechanistic links between biomechanical factors and biological adaption at both the organ and cellular levels. Once calibrated with patient data, it can be used for assessing heart failure risk and designing optimal treatment therapies. STATEMENT OF SIGNIFICANCE: Computational modelling of cardiac G&R has shown high promise to provide insight into heart disease management when mechanistic understandings are quantified between biomechanical factors and underlying cellular adaptation processes. The kinematic growth theory has been dominantly used to phenomenologically describe the biological G&R process but neglecting underlying cellular mechanisms. We have developed a constrained mixture based G&R model with updated reference by taking into account different mechanobiological processes in the ground matrix, myocytes and collagen fibres. This G&R model can serve as a basis for developing more advanced myocardial G&R models further informed by patient data to assess heart failure risk, predict disease progression, select the optimal treatment by hypothesis testing, and eventually towards a truly precision cardiology using in-silico models.
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Affiliation(s)
- Debao Guan
- School of Mathematics and Statistics, University of Glasgow, Glasgow G12 8QQ, UK
| | - Xin Zhuan
- School of Mathematics and Statistics, University of Glasgow, Glasgow G12 8QQ, UK
| | - Xiaoyu Luo
- School of Mathematics and Statistics, University of Glasgow, Glasgow G12 8QQ, UK
| | - Hao Gao
- School of Mathematics and Statistics, University of Glasgow, Glasgow G12 8QQ, UK.
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8
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Usman M, Mendiola EA, Mukherjee T, Mehdi RR, Ohayon J, Alluri PG, Sadayappan S, Choudhary G, Avazmohammadi R. On the possibility of estimating myocardial fiber architecture from cardiac strains. FUNCTIONAL IMAGING AND MODELING OF THE HEART : ... INTERNATIONAL WORKSHOP, FIMH ..., PROCEEDINGS. FIMH 2023; 13958:74-83. [PMID: 37671365 PMCID: PMC10478796 DOI: 10.1007/978-3-031-35302-4_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/07/2023]
Abstract
The myocardium is composed of a complex network of contractile myofibers that are organized in such a way as to produce efficient contraction and relaxation of the heart. The myofiber architecture in the myocardium is a key determinant of cardiac motion and the global or organ-level function of the heart. Reports of architectural remodeling in cardiac diseases, such as pulmonary hypertension and myocardial infarction, potentially contributing to cardiac dysfunction call for the inclusion of an architectural marker for an improved assessment of cardiac function. However, the in-vivo quantification of three-dimensional myo-architecture has proven challenging. In this work, we examine the sensitivity of cardiac strains to varying myofiber orientation using a multiscale finite-element model of the LV. Additionally, we present an inverse modeling approach to predict the myocardium fiber structure from cardiac strains. Our results indicate a strong correlation between fiber orientation and LV kinematics, corroborating that the fiber structure is a principal determinant of LV contractile behavior. Our inverse model was capable of accurately predicting the myocardial fiber range and regional fiber angles from strain measures. A concrete understanding of the link between LV myofiber structure and motion, and the development of non-invasive and feasible means of characterizing the myocardium architecture is expected to lead to advanced LV functional metrics and improved prognostic assessment of structural heart disease.
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Affiliation(s)
- Muhammad Usman
- Department of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA
| | - Emilio A Mendiola
- Department of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA
| | - Tanmay Mukherjee
- Department of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA
| | - Rana Raza Mehdi
- Department of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA
| | - Jacques Ohayon
- Savoie Mont-Blanc University, Polytech Annecy-Chambéry, Le Bourget du Lac, France
- Department of Cardiovascular Sciences, Houston Methodist Academic Institute, Houston, TX 77030, USA
| | - Prasanna G Alluri
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Sakthivel Sadayappan
- Department of Internal Medicine, Division of Cardiovascular Health and Disease, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Gaurav Choudhary
- Department of Medicine, Alpert Medical School of Brown University, Providence, RI 02903, USA
| | - Reza Avazmohammadi
- Department of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA
- Department of Cardiovascular Sciences, Houston Methodist Academic Institute, Houston, TX 77030, USA
- J. Mike Walker '66 Department of Mechanical Engineering, Texas A&M University, College Station, TX, USA
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9
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Zheng Y, Chan WX, Nielles-Vallespin S, Scott AD, Ferreira PF, Leo HL, Yap CH. Effects of myocardial sheetlet sliding on left ventricular function. Biomech Model Mechanobiol 2023:10.1007/s10237-023-01721-6. [PMID: 37148404 PMCID: PMC10366046 DOI: 10.1007/s10237-023-01721-6] [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: 10/24/2022] [Accepted: 04/09/2023] [Indexed: 05/08/2023]
Abstract
Left ventricle myocardium has a complex micro-architecture, which was revealed to consist of myocyte bundles arranged in a series of laminar sheetlets. Recent imaging studies demonstrated that these sheetlets re-orientated and likely slided over each other during the deformations between systole and diastole, and that sheetlet dynamics were altered during cardiomyopathy. However, the biomechanical effect of sheetlet sliding is not well-understood, which is the focus here. We conducted finite element simulations of the left ventricle (LV) coupled with a windkessel lumped parameter model to study sheetlet sliding, based on cardiac MRI of a healthy human subject, and modifications to account for hypertrophic and dilated geometric changes during cardiomyopathy remodeling. We modeled sheetlet sliding as a reduced shear stiffness in the sheet-normal direction and observed that (1) the diastolic sheetlet orientations must depart from alignment with the LV wall plane in order for sheetlet sliding to have an effect on cardiac function, that (2) sheetlet sliding modestly aided cardiac function of the healthy and dilated hearts, in terms of ejection fraction, stroke volume, and systolic pressure generation, but its effects were amplified during hypertrophic cardiomyopathy and diminished during dilated cardiomyopathy due to both sheetlet angle configuration and geometry, and that (3) where sheetlet sliding aided cardiac function, it increased tissue stresses, particularly in the myofibre direction. We speculate that sheetlet sliding is a tissue architectural adaptation to allow easier deformations of the LV walls so that LV wall stiffness will not hinder function, and to provide a balance between function and tissue stresses. A limitation here is that sheetlet sliding is modeled as a simple reduction in shear stiffness, without consideration of micro-scale sheetlet mechanics and dynamics.
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Affiliation(s)
- Yu Zheng
- Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
| | - Wei Xuan Chan
- Department of Bioengineering, Imperial College London, London, UK
- British Heart Foundation Centre of Research Excellence, Imperial College London, London, UK
| | - Sonia Nielles-Vallespin
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Andrew D Scott
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Pedro F Ferreira
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Hwa Liang Leo
- Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
| | - Choon Hwai Yap
- Department of Bioengineering, Imperial College London, London, UK.
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10
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Lim E, Shi Y, Leo HL, Al Abed A. Editorial: Data assimilation in cardiovascular medicine: Merging experimental measurements with physics-based computational models. Front Physiol 2023; 14:1153861. [PMID: 36846318 PMCID: PMC9948236 DOI: 10.3389/fphys.2023.1153861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 02/01/2023] [Indexed: 02/11/2023] Open
Affiliation(s)
- E. Lim
- University of Malaya, Kuala Lumpur, Malaysia,*Correspondence: E. Lim,
| | - Y. Shi
- Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, China
| | - H. L. Leo
- National University of Singapore, Singapore, Singapore
| | - A. Al Abed
- University of New South Wales, Kensington, NSW, Australia
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11
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On the structural origin of the anisotropy in the myocardium: Multiscale modeling and analysis. J Mech Behav Biomed Mater 2023; 138:105600. [PMID: 36525875 DOI: 10.1016/j.jmbbm.2022.105600] [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: 02/16/2022] [Revised: 08/23/2022] [Accepted: 11/24/2022] [Indexed: 12/14/2022]
Abstract
Due to structural heterogeneities within the tissue, the myocardium displays an orthotropic material behavior. However, the link between the microstructure and the macroscopic mechanical properties is still not fully established. In particular, if it is admitted that the cardiomyocyte organization induces a transversely isotropic symmetry, the relative role in the observed orthotropic symmetry of cardiomyocyte orientation variation and perimysium collagen "sheetlet" structure, two mechanisms occurring at different scales, is still a matter of debate. In order to shed light on this question, we designed a multiscale model of the myocardium, bridging the cell, sheetlet and tissue scales. More precisely, we compared the macroscopic anisotropy obtained by homogenization of different mesostructures consisting in cardiomyocytes and extracellular collageneous layers, also taking into account the variation of cardiomyocyte and sheetlet orientations on the macroscale, to available experimental data. This study confirms the importance of sheetlets layers in assuring the tissue's anisotropic response, as cardiomyocytes-only mesostructures cannot reproduce the observed anisotropy. Moreover, our model shows the existence of a size effect in the myocardial tissue shear properties, which will require further experimental analysis.
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12
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Li X, Chen R, Xu X, Xiao Z, Wei X, Yang Y, Zhang Z, Wu Z, Zhu Y, Liu H. The comparison of diffusion tensor imaging in human hearts between 1.5 T and 3.0 T. BMC Med Imaging 2023; 23:14. [PMID: 36698134 PMCID: PMC9875455 DOI: 10.1186/s12880-023-00969-9] [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: 01/20/2022] [Accepted: 01/16/2023] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND The aim was to compare the diffusion tensor imaging (DTI) indices derived from human hearts between 1.5 T and 3.0 T scanners. Additionally, the reproducibility of DTI indices was assessed between 1.5 T and 3.0 T scanners. METHODS A total of 18 ex-vivo hearts were derived from patients who underwent heart transplantation. The DTI schemes were performed at 1.5 T and 3.0 T, respectively. Then, the same slices from each ex-vivo heart were selected for image analysis. The student's t-test or Wilcoxon-rank test was used to compare the statistical differences. The agreement of DTI indices was mainly reported as the interclass correlation coefficient (ICC). RESULTS No significant differences (all P > 0.05) were found in the DTI indices between 1.5 T and 3.0 T scanners. Interestingly, the ICC of all DTI indices was relatively lower with a low b-value. The reproducibility of the helix angle (HA) was relatively lower when compared to the other DTI indices. CONCLUSION The DTI indices of ex-vivo human hearts between 1.5 T and 3.0 T scanners had no significant differences. The consistency of DTI indices needed caution using a low b-value with different field strengths, and the relatively low reproducibility of HA should be considered.
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Affiliation(s)
- Xiaodan Li
- grid.284723.80000 0000 8877 7471Department of Radiology, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province China
| | - Rui Chen
- grid.284723.80000 0000 8877 7471Department of Radiology, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province China ,grid.79703.3a0000 0004 1764 3838School of Medicine, South China University of Technology, Guangzhou, Guangdong Province China
| | - Xi Xu
- grid.9227.e0000000119573309Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China ,grid.410726.60000 0004 1797 8419Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
| | - Zebin Xiao
- grid.284723.80000 0000 8877 7471Department of Pathology, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province China
| | - Xiaoyu Wei
- grid.284723.80000 0000 8877 7471Department of Radiology, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province China ,grid.79703.3a0000 0004 1764 3838School of Medicine, South China University of Technology, Guangzhou, Guangdong Province China
| | - Yuelong Yang
- grid.284723.80000 0000 8877 7471Department of Radiology, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province China
| | | | - Zhigang Wu
- Philips Healthcare China, Guangzhou, China
| | - Yanjie Zhu
- grid.9227.e0000000119573309Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China ,grid.410726.60000 0004 1797 8419Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
| | - Hui Liu
- grid.284723.80000 0000 8877 7471Department of Radiology, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong Province China ,grid.79703.3a0000 0004 1764 3838School of Medicine, South China University of Technology, Guangzhou, Guangdong Province China ,grid.284723.80000 0000 8877 7471Guangdong 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, China
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13
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Liu S, Liu Y, Xu X, Chen R, Liang D, Jin Q, Liu H, Chen G, Zhu Y. Accelerated cardiac diffusion tensor imaging using deep neural network. Phys Med Biol 2023; 68. [PMID: 36595239 DOI: 10.1088/1361-6560/acaa86] [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: 05/23/2022] [Accepted: 12/09/2022] [Indexed: 12/14/2022]
Abstract
Cardiac diffusion tensor imaging (DTI) is a noninvasive method for measuring the microstructure of the myocardium. However, its long scan time significantly hinders its wide application. In this study, we developed a deep learning framework to obtain high-quality DTI parameter maps from six diffusion-weighted images (DWIs) by combining deep-learning-based image generation and tensor fitting, and named the new framework FG-Net. In contrast to frameworks explored in previous deep-learning-based fast DTI studies, FG-Net generates inter-directional DWIs from six input DWIs to supplement the loss information and improve estimation accuracy for DTI parameters. FG-Net was evaluated using two datasets ofex vivohuman hearts. The results showed that FG-Net can generate fractional anisotropy, mean diffusivity maps, and helix angle maps from only six raw DWIs, with a quantification error of less than 5%. FG-Net outperformed conventional tensor fitting and black-box network fitting in both qualitative and quantitative metrics. We also demonstrated that the proposed FG-Net can achieve highly accurate fractional anisotropy and helix angle maps in DWIs with differentb-values.
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Affiliation(s)
- Shaonan Liu
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, People's Republic of China.,Department of Computer Science, Inner Mongolia University, Hohhot, People's Republic of China
| | - Yuanyuan Liu
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, People's Republic of China
| | - Xi Xu
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, People's Republic of China
| | - Rui Chen
- Department of Radiology, Guangdong Provincial People's Hospital Guangdong Academy of Medical Sciences, Guangzhou, People's Republic of China
| | - Dong Liang
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, People's Republic of China
| | - Qiyu Jin
- Department of Mathematical Science, Inner Mongolia University, Hohhot, People's Republic of China
| | - Hui Liu
- Department of Radiology, Guangdong Provincial People's Hospital Guangdong Academy of Medical Sciences, Guangzhou, People's Republic of China
| | - Guoqing Chen
- Department of Mathematical Science, Inner Mongolia University, Hohhot, People's Republic of China
| | - Yanjie Zhu
- Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, People's Republic of China.,National Center for Applied Mathematics Shenzhen, Shenzhen, Guangdong, People's Republic of China
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14
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Raj V, Gowda S, Kothari R. Myocardial tissue characterization by cardiac magnetic resonance: A primer for the clinician. JOURNAL OF THE INDIAN ACADEMY OF ECHOCARDIOGRAPHY & CARDIOVASCULAR IMAGING 2023. [DOI: 10.4103/jiae.jiae_44_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
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15
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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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16
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Role of cardiovascular magnetic resonance in the clinical evaluation of left ventricular hypertrophy: a 360° panorama. Int J Cardiovasc Imaging 2022; 39:793-809. [PMID: 36543912 DOI: 10.1007/s10554-022-02774-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Accepted: 12/04/2022] [Indexed: 12/24/2022]
Abstract
Left ventricular hypertrophy (LVH) is a frequent imaging finding in the general population. In order to identify the precise etiology, a comprehensive diagnostic approach should be adopted, including the prevalence of each entity that may cause LVH, family history, clinical, electrocardiographic and imaging findings. By providing a detailed evaluation of the myocardium, cardiovascular magnetic resonance (CMR) has assumed a central role in the differential diagnosis of left ventricular hypertrophy, with the technique of parametric imaging allowing more refined tissue characterization. This article aims to establish a parallel between pathophysiological features and imaging findings through the broad spectrum of LVH entities, emphasizing the role of CMR in the differential diagnosis.
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17
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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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18
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Sharrack N, Das A, Kelly C, Teh I, Stoeck CT, Kozerke S, Swoboda PP, Greenwood JP, Plein S, Schneider JE, Dall'Armellina E. The relationship between myocardial microstructure and strain in chronic infarction using cardiovascular magnetic resonance diffusion tensor imaging and feature tracking. J Cardiovasc Magn Reson 2022; 24:66. [PMID: 36419059 PMCID: PMC9685947 DOI: 10.1186/s12968-022-00892-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 10/03/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Cardiac diffusion tensor imaging (cDTI) using cardiovascular magnetic resonance (CMR) is a novel technique for the non-invasive assessment of myocardial microstructure. Previous studies have shown myocardial infarction to result in loss of sheetlet angularity, derived by reduced secondary eigenvector (E2A) and reduction in subendocardial cardiomyocytes, evidenced by loss of myocytes with right-handed orientation (RHM) on helix angle (HA) maps. Myocardial strain assessed using feature tracking-CMR (FT-CMR) is a sensitive marker of sub-clinical myocardial dysfunction. We sought to explore the relationship between these two techniques (strain and cDTI) in patients at 3 months following ST-elevation MI (STEMI). METHODS 32 patients (F = 28, 60 ± 10 years) underwent 3T CMR three months after STEMI (mean interval 105 ± 17 days) with second order motion compensated (M2), free-breathing spin echo cDTI, cine gradient echo and late gadolinium enhancement (LGE) imaging. HA maps divided into left-handed HA (LHM, - 90 < HA < - 30), circumferential HA (CM, - 30° < HA < 30°), and right-handed HA (RHM, 30° < HA < 90°) were reported as relative proportions. Global and segmental analysis was undertaken. RESULTS Mean left ventricular ejection fraction (LVEF) was 44 ± 10% with a mean infarct size of 18 ± 12 g and a mean infarct segment LGE enhancement of 66 ± 21%. Mean global radial strain was 19 ± 6, mean global circumferential strain was - 13 ± - 3 and mean global longitudinal strain was - 10 ± - 3. Global and segmental radial strain correlated significantly with E2A in infarcted segments (p = 0.002, p = 0.011). Both global and segmental longitudinal strain correlated with RHM of infarcted segments on HA maps (p < 0.001, p = 0.003). Mean Diffusivity (MD) correlated significantly with the global infarct size (p < 0.008). When patients were categorised according to LVEF (reduced, mid-range and preserved), all cDTI parameters differed significantly between the three groups. CONCLUSION Change in sheetlet orientation assessed using E2A from cDTI correlates with impaired radial strain. Segments with fewer subendocardial cardiomyocytes, evidenced by a lower proportion of myocytes with right-handed orientation on HA maps, show impaired longitudinal strain. Infarct segment enhancement correlates significantly with E2A and RHM. Our data has demonstrated a link between myocardial microstructure and contractility following myocardial infarction, suggesting a potential role for CMR cDTI to clinically relevant functional impact.
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Affiliation(s)
- N Sharrack
- Biomedical Imaging Sciences Department, Leeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - A Das
- Biomedical Imaging Sciences Department, Leeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - C Kelly
- Biomedical Imaging Sciences Department, Leeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - I Teh
- Biomedical Imaging Sciences Department, Leeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - C T Stoeck
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
- Centre for Surgical Research, University of Zurich and University Hospital Zurich, Zurich, Switzerland
| | - S Kozerke
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - P P Swoboda
- Biomedical Imaging Sciences Department, Leeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - J P Greenwood
- Biomedical Imaging Sciences Department, Leeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - S Plein
- Biomedical Imaging Sciences Department, Leeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - J E Schneider
- Biomedical Imaging Sciences Department, Leeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - E Dall'Armellina
- Biomedical Imaging Sciences Department, Leeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK.
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19
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Wilson AJ, Sands GB, LeGrice IJ, Young AA, Ennis DB. Myocardial mesostructure and mesofunction. Am J Physiol Heart Circ Physiol 2022; 323:H257-H275. [PMID: 35657613 PMCID: PMC9273275 DOI: 10.1152/ajpheart.00059.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 05/23/2022] [Accepted: 05/23/2022] [Indexed: 11/22/2022]
Abstract
The complex and highly organized structural arrangement of some five billion cardiomyocytes directs the coordinated electrical activity and mechanical contraction of the human heart. The characteristic transmural change in cardiomyocyte orientation underlies base-to-apex shortening, circumferential shortening, and left ventricular torsion during contraction. Individual cardiomyocytes shorten ∼15% and increase in diameter ∼8%. Remarkably, however, the left ventricular wall thickens by up to 30-40%. To accommodate this, the myocardium must undergo significant structural rearrangement during contraction. At the mesoscale, collections of cardiomyocytes are organized into sheetlets, and sheetlet shear is the fundamental mechanism of rearrangement that produces wall thickening. Herein, we review the histological and physiological studies of myocardial mesostructure that have established the sheetlet shear model of wall thickening. Recent developments in tissue clearing techniques allow for imaging of whole hearts at the cellular scale, whereas magnetic resonance imaging (MRI) and computed tomography (CT) can image the myocardium at the mesoscale (100 µm to 1 mm) to resolve cardiomyocyte orientation and organization. Through histology, cardiac diffusion tensor imaging (DTI), and other modalities, mesostructural sheetlets have been confirmed in both animal and human hearts. Recent in vivo cardiac DTI methods have measured reorientation of sheetlets during the cardiac cycle. We also examine the role of pathological cardiac remodeling on sheetlet organization and reorientation, and the impact this has on ventricular function and dysfunction. We also review the unresolved mesostructural questions and challenges that may direct future work in the field.
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Affiliation(s)
- Alexander J Wilson
- Department of Radiology, Stanford University, Stanford, California
- Stanford Cardiovascular Institute, Stanford University, Stanford, California
| | - Gregory B Sands
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Ian J LeGrice
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Department of Physiology, University of Auckland, Auckland, New Zealand
| | - Alistair A Young
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
- Department of Biomedical Engineering, King's College London, London, United Kingdom
| | - Daniel B Ennis
- Department of Radiology, Stanford University, Stanford, California
- Veterans Administration Palo Alto Health Care System, Palo Alto, California
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20
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Evaluation of Right Ventricular Function and Myocardial Microstructure in Fetal Hypoplastic Left Heart Syndrome. J Clin Med 2022; 11:jcm11154456. [PMID: 35956075 PMCID: PMC9369849 DOI: 10.3390/jcm11154456] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 07/15/2022] [Accepted: 07/22/2022] [Indexed: 02/05/2023] Open
Abstract
Right ventricular (RV) function is one of the critical factors affecting the prognosis of fetuses with hypoplastic left heart syndrome (HLHS). Our study objectives included assessment of cardiac function and comprehensive measurement of cardiac microstructure. We retrospectively studied 42 fetuses diagnosed as HLHS by echocardiography. Myocardial deformation of the right ventricular wall was calculated automatically in offline software. Postmortem cardiac imaging for three control fetal hearts and four HLHS specimens was performed by a 9.4T DTI scanner. Myocardial deformation parameters of the RV (including strain, strain rate, and velocity) were significantly lower in HLHS fetuses (all p < 0.01). FA values increased (0.18 ± 0.01 vs. 0.21 ± 0.02; p < 0.01) in HLHS fetuses, but MD reduced (1.3 ± 0.15 vs. 0.88 ± 0.13; p < 0.001). The HLHS fetuses’ RV lateral base wall (−7.31 ± 51.91 vs. −6.85 ± 31.34; p = 0.25), middle wall (1.71 ± 50.92 vs. −9.38 ± 28.18; p < 0.001), and apical wall (−6.19 ± 46.61 vs. −11.16 ± 29.86, p < 0.001) had HA gradient ascent but HA gradient descent in the anteroseptal wall (p < 0.001) and inferoseptal wall (p < 0.001). RV basal lateral wall HA degrees were correlated with RVGLS (R2 = 0.97, p = 0.02). MD values were positively correlated with RVGLS (R2 = 0.93, p = 0.04). Our study found morphological and functional changes of the RV in HLHS fetuses, and cardiac function was related to the orientation patterns of myocardial fibers. It may provide insight into understanding the underlying mechanisms of impaired RV performance in HLHS.
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21
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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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22
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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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23
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Scott AD, Jackson T, Khalique Z, Gorodezky M, Pardoe B, Begum L, Bruno VD, Chowdhury RA, Ferreira PF, Nielles‐Vallespin S, Roehl M, McCarthy KP, Sarathchandra P, Rose JN, Doorly DJ, Pennell DJ, Ascione R, de Silva R, Firmin DN. Development of a cardiovascular magnetic resonance-compatible large animal isolated heart model for direct comparison of beating and arrested hearts. NMR IN BIOMEDICINE 2022; 35:e4692. [PMID: 35040195 PMCID: PMC9286060 DOI: 10.1002/nbm.4692] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 12/21/2021] [Accepted: 01/07/2022] [Indexed: 06/02/2023]
Abstract
Cardiac motion results in image artefacts and quantification errors in many cardiovascular magnetic resonance (CMR) techniques, including microstructural assessment using diffusion tensor cardiovascular magnetic resonance (DT-CMR). Here, we develop a CMR-compatible isolated perfused porcine heart model that allows comparison of data obtained in beating and arrested states. Ten porcine hearts (8/10 for protocol optimisation) were harvested using a donor heart retrieval protocol and transported to the remote CMR facility. Langendorff perfusion in a 3D-printed chamber and perfusion circuit re-established contraction. Hearts were imaged using cine, parametric mapping and STEAM DT-CMR at cardiac phases with the minimum and maximum wall thickness. High potassium and lithium perfusates were then used to arrest the heart in a slack and contracted state, respectively. Imaging was repeated in both arrested states. After imaging, tissue was removed for subsequent histology in a location matched to the DT-CMR data using fiducial markers. Regular sustained contraction was successfully established in six out of 10 hearts, including the final five hearts. Imaging was performed in four hearts and one underwent the full protocol, including colocalised histology. The image quality was good and there was good agreement between DT-CMR data in equivalent beating and arrested states. Despite the use of autologous blood and dextran within the perfusate, T2 mapping results, DT-CMR measures and an increase in mass were consistent with development of myocardial oedema, resulting in failure to achieve a true diastolic-like state. A contiguous stack of 313 5-μm histological sections at and a 100-μm thick section showing cell morphology on 3D fluorescent confocal microscopy colocalised to DT-CMR data were obtained. A CMR-compatible isolated perfused beating heart setup for large animal hearts allows direct comparisons of beating and arrested heart data with subsequent colocalised histology, without the need for onsite preclinical facilities.
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Affiliation(s)
- Andrew D. Scott
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - Tim Jackson
- Department of PerfusionRoyal Brompton HospitalLondonUK
| | - Zohya Khalique
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - Margarita Gorodezky
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - Ben Pardoe
- Department of PerfusionRoyal Brompton HospitalLondonUK
| | - Lale Begum
- Department of PerfusionRoyal Brompton HospitalLondonUK
| | - V. Domenico Bruno
- Translational Biomedical Research CentreUniversity of BristolBristolUK
- Bristol Heart InstituteUniversity Hospital Bristol NHS Foundation TrustBristolUK
| | - Rasheda A. Chowdhury
- National Heart and Lung InstituteImperial CollegeLondonUK
- Imperial Centre for Cardiac EngineeringImperial CollegeLondonUK
| | - Pedro F. Ferreira
- 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
| | - Malte Roehl
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | | | - Padmini Sarathchandra
- National Heart and Lung InstituteImperial CollegeLondonUK
- Magdi Yacoub Institute, National Heart and Lung InstituteImperial CollegeLondonUK
| | - Jan N. Rose
- Department of AeronauticsImperial CollegeLondonUK
| | | | - Dudley J. Pennell
- Cardiovascular Magnetic Resonance UnitRoyal Brompton HospitalLondonUK
- National Heart and Lung InstituteImperial CollegeLondonUK
| | - Raimondo Ascione
- Translational Biomedical Research CentreUniversity of BristolBristolUK
- Bristol Heart InstituteUniversity Hospital Bristol NHS Foundation TrustBristolUK
| | - Ranil de Silva
- 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
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24
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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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25
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Lohr D, Thiele A, Stahnke M, Braun V, Smeir E, Spranger J, Brachs S, Klopfleisch R, Foryst-Ludwig A, Schreiber LM, Kintscher U, Beyhoff N. Assessment of Myocardial Microstructure in a Murine Model of Obesity-Related Cardiac Dysfunction by Diffusion Tensor Magnetic Resonance Imaging at 7T. Front Cardiovasc Med 2022; 9:839714. [PMID: 35449873 PMCID: PMC9016133 DOI: 10.3389/fcvm.2022.839714] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 02/14/2022] [Indexed: 01/10/2023] Open
Abstract
BackgroundObesity exerts multiple deleterious effects on the heart that may ultimately lead to cardiac failure. This study sought to characterize myocardial microstructure and function in an experimental model of obesity-related cardiac dysfunction.MethodsMale C57BL/6N mice were fed either a high-fat diet (HFD; 60 kcal% fat, n = 12) or standard control diet (9 kcal% fat, n = 10) for 15 weeks. At the end of the study period, cardiac function was assessed by ultra-high frequency echocardiography, and hearts were processed for further analyses. The three-dimensional myocardial microstructure was examined ex vivo at a spatial resolution of 100 × 100 × 100 μm3 by diffusion tensor magnetic resonance imaging (DT-MRI) at 7T. Myocardial deformation, diffusion metrics and fiber tract geometry were analyzed with respect to the different myocardial layers (subendocardium/subepicardium) and segments (base/mid-cavity/apex). Results were correlated with blood sample analyses, histopathology, and gene expression data.ResultsHFD feeding induced significantly increased body weight combined with a pronounced accumulation of visceral fat (body weight 42.3 ± 5.7 vs. 31.5 ± 2.2 g, body weight change 73.7 ± 14.8 vs. 31.1 ± 6.6%, both P < 0.001). Obese mice showed signs of diastolic dysfunction, whereas left-ventricular ejection fraction and fractional shortening remained unchanged (E/e’ 41.6 ± 16.6 vs. 24.8 ± 6.0, P < 0.01; isovolumic relaxation time 19 ± 4 vs. 14 ± 4 ms, P < 0.05). Additionally, global longitudinal strain was reduced in the HFD group (−15.1 ± 3.0 vs. −20.0 ± 4.6%, P = 0.01), which was mainly driven by an impairment in basal segments. However, histopathology and gene expression analyses revealed no myocardial fibrosis or differences in cardiomyocyte morphology. Mean diffusivity and eigenvalues of the diffusion tensor were lower in the basal subepicardium of obese mice as assessed by DT-MRI (P < 0.05). The three-dimensional fiber tract arrangement of the left ventricle (LV) remained preserved.ConclusionFifteen weeks of high-fat diet induced alterations in myocardial diffusion properties in mice, whereas no remodeling of the three-dimensional myofiber arrangement of the LV was observed. Obese mice showed reduced longitudinal strain and lower mean diffusivity predominantly in the left-ventricular base, and further investigation into the significance of this regional pattern is required.
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Affiliation(s)
- David Lohr
- Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure Center (CHFC), University Hospital Wuerzburg, Wuerzburg, Germany
| | - Arne Thiele
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pharmacology, Cardiovascular-Metabolic-Renal Research Center, Berlin, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
| | - Max Stahnke
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pharmacology, Cardiovascular-Metabolic-Renal Research Center, Berlin, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
| | - Vera Braun
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pharmacology, Cardiovascular-Metabolic-Renal Research Center, Berlin, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
| | - Elia Smeir
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pharmacology, Cardiovascular-Metabolic-Renal Research Center, Berlin, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
| | - Joachim Spranger
- German Centre for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Endocrinology and Metabolism, Cardiovascular-Metabolic-Renal Research Center, Berlin, Germany
| | - Sebastian Brachs
- German Centre for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Endocrinology and Metabolism, Cardiovascular-Metabolic-Renal Research Center, Berlin, Germany
| | - Robert Klopfleisch
- Department of Veterinary Pathology, College of Veterinary Medicine, Freie Universität Berlin, Berlin, Germany
| | - Anna Foryst-Ludwig
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pharmacology, Cardiovascular-Metabolic-Renal Research Center, Berlin, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
| | - Laura M. Schreiber
- Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure Center (CHFC), University Hospital Wuerzburg, Wuerzburg, Germany
| | - Ulrich Kintscher
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pharmacology, Cardiovascular-Metabolic-Renal Research Center, Berlin, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
| | - Niklas Beyhoff
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Pharmacology, Cardiovascular-Metabolic-Renal Research Center, Berlin, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Berlin, Berlin, Germany
- Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
- Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Cardiology, Campus Benjamin Franklin, Berlin, Germany
- *Correspondence: Niklas Beyhoff,
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Rahman T, Moulin K, Perotti LE. Cardiac Diffusion Tensor Biomarkers of Chronic Infarction Based on In Vivo Data. APPLIED SCIENCES-BASEL 2022; 12. [PMID: 36032414 PMCID: PMC9408809 DOI: 10.3390/app12073512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
In vivo cardiac diffusion tensor imaging (cDTI) data were acquired in
swine subjects six to ten weeks post-myocardial infarction (MI) to identify
microstructural-based biomarkers of MI. Diffusion tensor invariants, diffusion
tensor eigenvalues, and radial diffusivity (RD) are evaluated in the infarct,
border, and remote myocardium, and compared with extracellular volume fraction
(ECV) and native T1 values. Additionally, to aid the interpretation of the
experimental results, the diffusion of water molecules was numerically simulated
as a function of ECV. Finally, findings based on in vivo measures were confirmed
using higher-resolution and higher signal-to-noise data acquired ex vivo in the
same subjects. Mean diffusivity, diffusion tensor eigenvalues, and RD increased
in the infarct and border regions compared to remote myocardium, while
fractional anisotropy decreased. Secondary (e2) and tertiary
(e3) eigenvalues increased more significantly than the primary
eigenvalue in the infarct and border regions. These findings were confirmed by
the diffusion simulations. Although ECV presented the largest increase in
infarct and border regions, e2, e3, and RD increased the
most among non-contrast-based biomarkers. RD is of special interest as it
summarizes the changes occurring in the radial direction and may be more robust
than e2 or e3 alone.
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Affiliation(s)
- Tanjib Rahman
- Department of Mechanical and Aerospace Engineering,
University of Central Florida, Orlando, FL 32816, USA
| | - Kévin Moulin
- CREATIS Laboratory, Univ. Lyon, UJM-Saint-Etienne, INSA,
CNRS UMR 5520, INSERM, 69100 Villeurbanne, France
- Department of Radiology, University Hospital Saint-Etienne,
42270 Saint-Priest-en-Jarez, France
| | - Luigi E. Perotti
- Department of Mechanical and Aerospace Engineering,
University of Central Florida, Orlando, FL 32816, USA
- Correspondence:
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27
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Connecting macroscopic diffusion metrics of cardiac diffusion tensor imaging and microscopic myocardial structures based on simulation. Med Image Anal 2022; 77:102325. [DOI: 10.1016/j.media.2021.102325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 11/26/2021] [Accepted: 11/29/2021] [Indexed: 11/20/2022]
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28
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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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29
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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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30
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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: 2] [Impact Index Per Article: 0.7] [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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31
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Finocchiaro G, Sheikh N, Leone O, Westaby J, Mazzarotto F, Pantazis A, Ferrantini C, Sacconi L, Papadakis M, Sharma S, Sheppard MN, Olivotto I. Arrhythmogenic potential of myocardial disarray in hypertrophic cardiomyopathy: genetic basis, functional consequences and relation to sudden cardiac death. Europace 2021; 23:985-995. [PMID: 33447843 DOI: 10.1093/europace/euaa348] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Accepted: 10/28/2020] [Indexed: 12/19/2022] Open
Abstract
Myocardial disarray is defined as disorganized cardiomyocyte spatial distribution, with loss of physiological fibre alignment and orientation. Since the first pathological descriptions of hypertrophic cardiomyopathy (HCM), disarray appeared as a typical feature of this condition and sparked vivid debate regarding its specificity to the disease and clinical significance as a diagnostic marker and a risk factor for sudden death. Although much of the controversy surrounding its diagnostic value in HCM persists, it is increasingly recognized that myocardial disarray may be found in physiological contexts and in cardiac conditions different from HCM, raising the possibility that central focus should be placed on its quantity and distribution, rather than a mere presence. While further studies are needed to establish what amount of disarray should be considered as a hallmark of the disease, novel experimental approaches and emerging imaging techniques for the first time allow ex vivo and in vivo characterization of the myocardium to a molecular level. Such advances hold the promise of filling major gaps in our understanding of the functional consequences of myocardial disarray in HCM and specifically on arrhythmogenic propensity and as a risk factor for sudden death. Ultimately, these studies will clarify whether disarray represents a major determinant of the HCM clinical profile, and a potential therapeutic target, as opposed to an intriguing but largely innocent bystander.
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Affiliation(s)
- Gherardo Finocchiaro
- Cardiothoracic Centre, Guy's and St Thomas' Hospital, London, UK.,King's College London
| | - Nabeel Sheikh
- Cardiothoracic Centre, Guy's and St Thomas' Hospital, London, UK.,King's College London
| | - Ornella Leone
- Cardiovascular and Cardiac Transplant Pathology Unit, Department of Pathology, Sant'Orsola-Malpighi University Hospital, Bologna, Italy
| | - Joe Westaby
- Cardiovascular Pathology Unit and Cardiology Clinical and Academic Group. St George's, University of London, London and St George's University Hospital NHS Foundation Trust, UK
| | - Francesco Mazzarotto
- Cardiomyopathy Unit, Careggi University Hospital, Florence, Italy.,Department of Experimental and Clinical Medicine, University of Florence, Italy.,National Heart and Lung Institute, Imperial College London, UK.,Cardiovascular Research Centre, Royal Brompton and Harefield National Health Service Foundation Trust, London, UK
| | - Antonis Pantazis
- Cardiovascular Research Centre, Royal Brompton and Harefield National Health Service Foundation Trust, London, UK
| | - Cecilia Ferrantini
- University of Florence, Florence, Italy.,European Laboratory for Non-Linear Spectroscopy, Florence, Italy
| | - Leonardo Sacconi
- European Laboratory for Non-Linear Spectroscopy, Florence, Italy.,Institute for Experimental Cardiovascular Medicine, University of Freiburg, Freiburg, Germany
| | - Michael Papadakis
- Cardiovascular Pathology Unit and Cardiology Clinical and Academic Group. St George's, University of London, London and St George's University Hospital NHS Foundation Trust, UK
| | - Sanjay Sharma
- Cardiovascular Pathology Unit and Cardiology Clinical and Academic Group. St George's, University of London, London and St George's University Hospital NHS Foundation Trust, UK
| | - Mary N Sheppard
- Cardiovascular Pathology Unit and Cardiology Clinical and Academic Group. St George's, University of London, London and St George's University Hospital NHS Foundation Trust, UK
| | - Iacopo Olivotto
- Cardiomyopathy Unit, Careggi University Hospital, Florence, Italy
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32
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Lin L, Zhou X, Dekkers IA, Lamb HJ. Cardiorenal Syndrome: Emerging Role of Medical Imaging for Clinical Diagnosis and Management. J Pers Med 2021; 11:734. [PMID: 34442378 PMCID: PMC8400880 DOI: 10.3390/jpm11080734] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2021] [Revised: 07/24/2021] [Accepted: 07/24/2021] [Indexed: 12/16/2022] Open
Abstract
Cardiorenal syndrome (CRS) concerns the interconnection between heart and kidneys in which the dysfunction of one organ leads to abnormalities of the other. The main clinical challenges associated with cardiorenal syndrome are the lack of tools for early diagnosis, prognosis, and evaluation of therapeutic effects. Ultrasound, computed tomography, nuclear medicine, and magnetic resonance imaging are increasingly used for clinical management of cardiovascular and renal diseases. In the last decade, rapid development of imaging techniques provides a number of promising biomarkers for functional evaluation and tissue characterization. This review summarizes the applicability as well as the future technological potential of each imaging modality in the assessment of CRS. Furthermore, opportunities for a comprehensive imaging approach for the evaluation of CRS are defined.
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Affiliation(s)
- Ling Lin
- Cardiovascular Imaging Group (CVIG), Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (L.L.); (I.A.D.); (H.J.L.)
| | - Xuhui Zhou
- Department of Radiology, The Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen 510833, China
| | - Ilona A. Dekkers
- Cardiovascular Imaging Group (CVIG), Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (L.L.); (I.A.D.); (H.J.L.)
| | - Hildo J. Lamb
- Cardiovascular Imaging Group (CVIG), Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands; (L.L.); (I.A.D.); (H.J.L.)
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33
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Zhang XS, Liu EH, Wang XY, Zhou XX, Zhang HX, Zhu YM, Sang XQ, Kuai ZX. Short-Term Repeatability of in Vivo Cardiac Intravoxel Incoherent Motion Tensor Imaging in Healthy Human Volunteers. J Magn Reson Imaging 2021; 55:854-865. [PMID: 34296813 DOI: 10.1002/jmri.27847] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 07/10/2021] [Accepted: 07/12/2021] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Intravoxel incoherent motion (IVIM) tensor imaging is a promising technique for diagnosis and monitoring of cardiovascular diseases. Knowledge about measurement repeatability, however, remains limited. PURPOSE To evaluate short-term repeatability of IVIM tensor imaging in normal in vivo human hearts. STUDY TYPE Prospective. POPULATION Ten healthy subjects without history of heart diseases. FIELD STRENGTH/SEQUENCE Balanced steady-state free-precession cine sequence and single-shot spin-echo echo planar IVIM tensor imaging sequence (9 b-values, 0-400 seconds/mm2 and six diffusion-encoding directions) at 3.0 T. ASSESSMENT Subjects were scanned twice with an interval of 15 minutes, leaving the scanner between studies. The signal-to-noise ratio (SNR) was evaluated in anterior, lateral, septal, and inferior segments of the left ventricle wall. Fractional anisotropy (FA), mean diffusivity (MD), mean fraction (MF), and helix angle (HA) in the four segments were independently measured by five radiologists. STATISTICAL TESTS IVIM tensor indexes were compared between observers using a one-way analysis of variance or between scans using a paired t-test (normal data) or a Wilcoxon rank-sum test (non-normal data). Interobserver agreement and test-retest repeatability were assessed using the intraclass correlation coefficient (ICC), within-subject coefficient of variation (WCV), and Bland-Altman limits of agreements. RESULTS SNR of inferior segment was significantly lower than the other three segments, and inferior segment was therefore excluded from repeatability analysis. Interobserver repeatability was excellent for all IVIM tensor indexes (ICC: 0.886-0.972; WCV: 0.62%-4.22%). Test-retest repeatability was excellent for MD of the self-diffusion tensor (D) and MF of the perfusion fraction tensor (fp ) (ICC: 0.803-0.888; WCV: 1.42%-9.51%) and moderate for FA and MD of the pseudo-diffusion tensor (D* ) (ICC: 0.487-0.532; WCV: 6.98%-10.89%). FA of D and fp and HA of D presented good test-retest repeatability (ICC: 0.732-0.788; WCV: 3.28%-8.71%). DATA CONCLUSION The D and fp indexes exhibited satisfactory repeatability, but further efforts were needed to improve repeatability of D* indexes. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Xiu-Shi Zhang
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China
| | - En-Hui Liu
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China
| | - Xin-Yu Wang
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China
| | - Xin-Xiang Zhou
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China
| | - Hong-Xia Zhang
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China
| | - Yue-Min Zhu
- CREATIS, CNRS UMR 5220-INSERM U1206-University Lyon 1-INSA Lyon-University Jean Monnet Saint-Etienne, Lyon, France
| | - Xi-Qiao Sang
- Division of Respiratory Disease, The Fourth Hospital of Harbin Medical University, Harbin, China
| | - Zi-Xiang Kuai
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, China
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34
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Paddock S, Tsampasian V, Assadi H, Mota BC, Swift AJ, Chowdhary A, Swoboda P, Levelt E, Sammut E, Dastidar A, Broncano Cabrero J, Del Val JR, Malcolm P, Sun J, Ryding A, Sawh C, Greenwood R, Hewson D, Vassiliou V, Garg P. Clinical Translation of Three-Dimensional Scar, Diffusion Tensor Imaging, Four-Dimensional Flow, and Quantitative Perfusion in Cardiac MRI: A Comprehensive Review. Front Cardiovasc Med 2021; 8:682027. [PMID: 34307496 PMCID: PMC8292630 DOI: 10.3389/fcvm.2021.682027] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 06/04/2021] [Indexed: 01/05/2023] Open
Abstract
Cardiovascular magnetic resonance (CMR) imaging is a versatile tool that has established itself as the reference method for functional assessment and tissue characterisation. CMR helps to diagnose, monitor disease course and sub-phenotype disease states. Several emerging CMR methods have the potential to offer a personalised medicine approach to treatment. CMR tissue characterisation is used to assess myocardial oedema, inflammation or thrombus in various disease conditions. CMR derived scar maps have the potential to inform ablation therapy—both in atrial and ventricular arrhythmias. Quantitative CMR is pushing boundaries with motion corrections in tissue characterisation and first-pass perfusion. Advanced tissue characterisation by imaging the myocardial fibre orientation using diffusion tensor imaging (DTI), has also demonstrated novel insights in patients with cardiomyopathies. Enhanced flow assessment using four-dimensional flow (4D flow) CMR, where time is the fourth dimension, allows quantification of transvalvular flow to a high degree of accuracy for all four-valves within the same cardiac cycle. This review discusses these emerging methods and others in detail and gives the reader a foresight of how CMR will evolve into a powerful clinical tool in offering a precision medicine approach to treatment, diagnosis, and detection of disease.
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Affiliation(s)
- Sophie Paddock
- Department of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, United Kingdom.,Department of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom
| | - Vasiliki Tsampasian
- Department of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, United Kingdom
| | - Hosamadin Assadi
- Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom
| | - Bruno Calife Mota
- Department of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom
| | - Andrew J Swift
- Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom
| | - Amrit Chowdhary
- Multidisciplinary Cardiovascular Research Centre & Division of Biomedical Imaging, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Peter Swoboda
- Multidisciplinary Cardiovascular Research Centre & Division of Biomedical Imaging, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Eylem Levelt
- Multidisciplinary Cardiovascular Research Centre & Division of Biomedical Imaging, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Eva Sammut
- Bristol Heart Institute and Translational Biomedical Research Centre, Faculty of Health Science, University of Bristol, Bristol, United Kingdom
| | - Amardeep Dastidar
- Bristol Heart Institute and Translational Biomedical Research Centre, Faculty of Health Science, University of Bristol, Bristol, United Kingdom
| | - Jordi Broncano Cabrero
- Cardiothoracic Imaging Unit, Hospital San Juan De Dios, Ressalta, HT Medica, Córdoba, Spain
| | - Javier Royuela Del Val
- Cardiothoracic Imaging Unit, Hospital San Juan De Dios, Ressalta, HT Medica, Córdoba, Spain
| | - Paul Malcolm
- Department of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, United Kingdom
| | - Julia Sun
- Department of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom
| | - Alisdair Ryding
- Department of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom
| | - Chris Sawh
- Department of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom
| | - Richard Greenwood
- Department of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom
| | - David Hewson
- Department of Cardiology, Norfolk and Norwich University Hospital, Norwich, United Kingdom
| | - Vassilios Vassiliou
- Department of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, United Kingdom
| | - Pankaj Garg
- Department of Cardiovascular and Metabolic Health, Norwich Medical School, University of East Anglia, Norwich, United Kingdom.,Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom
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Bakir AA, Al Abed A, Lovell NH, Dokos S. Multiphysics computational modelling of the cardiac ventricles. IEEE Rev Biomed Eng 2021; 15:309-324. [PMID: 34185649 DOI: 10.1109/rbme.2021.3093042] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Development of cardiac multiphysics models has progressed significantly over the decades and simulations combining multiple physics interactions have become increasingly common. In this review, we summarise the progress in this field focusing on various approaches of integrating ventricular structures. electrophysiological properties, myocardial mechanics, as well as incorporating blood hemodynamics and the circulatory system. Common coupling approaches are discussed and compared, including the advantages and shortcomings of each. Currently used strategies for patient-specific implementations are highlighted and potential future improvements considered.
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Abstract
PURPOSE OF REVIEW The present article serves to review current risk assessment guidelines for sudden cardiac death (SCD) in patients with hypertrophic cardiomyopathy (HCM) and to discuss how these guidelines can be applied to patients with childhood HCM. New diagnostic techniques that could lead to more accurate risk assessment tools are also discussed. RECENT FINDINGS Current guidelines for risk assessment in childhood HCM are extrapolated from adult guidelines and lack background research to validate their use. Continuous variables, such as wall thickness, are converted to binary variables, which is particularly concerning in pediatric patients' where weight gain and linear growth is likely to lead to more significant hemodynamic changes in shorter periods of time. Some studies have even shown that risk factors concerning in adults may actually be protective in pediatric patients. Additionally, large gaps still remain between genotype and phenotype expression in HCM. SUMMARY A better understanding of the relationship between cause, phenotype, and outcomes is needed to truly be able to determine risk for SCD in childhood HCM. Larger studies, including newer technologies and quantitative models, similar to the European HCM Risk-SCD model, which allows for a quantitative risk diagnosis, are needed as well.
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3D MRI of explanted sheep hearts with submillimeter isotropic spatial resolution: comparison between diffusion tensor and structure tensor imaging. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2021; 34:741-755. [PMID: 33638739 PMCID: PMC8421292 DOI: 10.1007/s10334-021-00913-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 01/29/2021] [Accepted: 02/02/2021] [Indexed: 11/04/2022]
Abstract
Objective The aim of the study is to compare structure tensor imaging (STI) with diffusion tensor imaging (DTI) of the sheep heart (approximately the same size as the human heart). Materials and methods MRI acquisition on three sheep ex vivo hearts was performed at 9.4 T/30 cm with a seven-element RF coil. 3D FLASH with an isotropic resolution of 150 µm and 3D spin-echo DTI at 600 µm were performed. Tensor analysis, angles extraction and segments divisions were performed on both volumes. Results A 3D FLASH allows for visualization of the detailed structure of the left and right ventricles. The helix angle determined using DTI and STI exhibited a smooth transmural change from the endocardium to the epicardium. Both the helix and transverse angles were similar between techniques. Sheetlet organization exhibited the same pattern in both acquisitions, but local angle differences were seen and identified in 17 segments representation. Discussion This study demonstrated the feasibility of high-resolution MRI for studying the myocyte and myolaminar architecture of sheep hearts. We presented the results of STI on three whole sheep ex vivo hearts and demonstrated a good correspondence between DTI and STI. Supplementary Information The online version contains supplementary material available at 10.1007/s10334-021-00913-4.
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Moulin K, Croisille P, Viallon M, Verzhbinsky IA, Perotti LE, Ennis DB. Myofiber strain in healthy humans using DENSE and cDTI. Magn Reson Med 2021; 86:277-292. [PMID: 33619807 DOI: 10.1002/mrm.28724] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 12/15/2020] [Accepted: 01/18/2021] [Indexed: 12/13/2022]
Abstract
PURPOSE Myofiber strain, Eff , is a mechanistically relevant metric of cardiac cell shortening and is expected to be spatially uniform in healthy populations, making it a prime candidate for the evaluation of local cardiomyocyte contractility. In this study, a new, efficient pipeline was proposed to combine microstructural cDTI and functional DENSE data in order to estimate Eff in vivo. METHODS Thirty healthy volunteers were scanned with three long-axis (LA) and three short-axis (SA) DENSE slices using 2D displacement encoding and one SA slice of cDTI. The total acquisition time was 11 minutes ± 3 minutes across volunteers. The pipeline first generates 3D SA displacements from all DENSE slices which are then combined with cDTI data to generate a cine of myofiber orientations and compute Eff . The precision of the post-processing pipeline was assessed using a computational phantom study. Transmural myofiber strain was compared to circumferential strain, Ecc , in healthy volunteers using a Wilcoxon sign rank test. RESULTS In vivo, computed Eff was found uniform transmurally compared to Ecc (-0.14[-0.15, -0.12] vs -0.18 [-0.20, -0.16], P < .001, -0.14 [-0.16, -0.12] vs -0.16 [-0.17, -0.13], P < .001 and -0.14 [-0.16, -0.12] vs Ecc_C = -0.14 [-0.15, -0.11], P = .002, Eff_C vs Ecc_C in the endo, mid, and epi layers, respectively). CONCLUSION We demonstrate that it is possible to measure in vivo myofiber strain in a healthy human population in 10 minutes per subject. Myofiber strain was observed to be spatially uniform in healthy volunteers making it a potential biomarker for the evaluation of local cardiomyocyte contractility in assessing cardiovascular dysfunction.
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Affiliation(s)
- Kévin Moulin
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Pierre Croisille
- University of Lyon, UJM-Saint-Etienne, INSA, CNRS UMR 5520, INSERM U1206, CREATIS, Saint-Etienne, France.,Department of Radiology, University Hospital Saint-Etienne, Saint-Etienne, France
| | - Magalie Viallon
- University of Lyon, UJM-Saint-Etienne, INSA, CNRS UMR 5520, INSERM U1206, CREATIS, Saint-Etienne, France.,Department of Radiology, University Hospital Saint-Etienne, Saint-Etienne, France
| | - Ilya A Verzhbinsky
- Medical Scientist Training Program, University of California - San Diego, La Jolla, CA, USA
| | - Luigi E Perotti
- Department of Mechanical and Aerospace Engineering, University of Central Florida, Orlando, FL, USA
| | - Daniel B Ennis
- Department of Radiology, Stanford University, Stanford, CA, USA
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Sharifi Kia D, Fortunato R, Maiti S, Simon MA, Kim K. An exploratory assessment of stretch-induced transmural myocardial fiber kinematics in right ventricular pressure overload. Sci Rep 2021; 11:3587. [PMID: 33574400 PMCID: PMC7878470 DOI: 10.1038/s41598-021-83154-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 01/22/2021] [Indexed: 01/30/2023] Open
Abstract
Right ventricular (RV) remodeling and longitudinal fiber reorientation in the setting of pulmonary hypertension (PH) affects ventricular structure and function, eventually leading to RV failure. Characterizing the kinematics of myocardial fibers helps better understanding the underlying mechanisms of fiber realignment in PH. In the current work, high-frequency ultrasound imaging and structurally-informed finite element (FE) models were employed for an exploratory evaluation of the stretch-induced kinematics of RV fibers. Image-based experimental evaluation of fiber kinematics in porcine myocardium revealed the capability of affine assumptions to effectively approximate myofiber realignment in the RV free wall. The developed imaging framework provides a noninvasive modality to quantify transmural RV myofiber kinematics in large animal models. FE modeling results demonstrated that chronic pressure overload, but not solely an acute rise in pressures, results in kinematic shift of RV fibers towards the longitudinal direction. Additionally, FE simulations suggest a potential protective role for concentric hypertrophy (increased wall thickness) against fiber reorientation, while eccentric hypertrophy (RV dilation) resulted in longitudinal fiber realignment. Our study improves the current understanding of the role of different remodeling events involved in transmural myofiber reorientation in PH. Future experimentations are warranted to test the model-generated hypotheses.
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Affiliation(s)
- Danial Sharifi Kia
- grid.21925.3d0000 0004 1936 9000Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA USA
| | - Ronald Fortunato
- grid.21925.3d0000 0004 1936 9000Department of Mechanical Engineering and Materials Science, University of Pittsburgh, Pittsburgh, PA USA
| | - Spandan Maiti
- grid.21925.3d0000 0004 1936 9000Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA USA ,grid.21925.3d0000 0004 1936 9000Department of Mechanical Engineering and Materials Science, University of Pittsburgh, Pittsburgh, PA USA
| | - Marc A. Simon
- grid.21925.3d0000 0004 1936 9000Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA USA ,grid.21925.3d0000 0004 1936 9000Division of Cardiology, Department of Medicine, University of Pittsburgh School of Medicine, 623A Scaife Hall, 3550 Terrace Street, Pittsburgh, PA 15213 USA ,grid.412689.00000 0001 0650 7433Heart and Vascular Institute, University of Pittsburgh Medical Center (UPMC), Pittsburgh, PA USA ,grid.412689.00000 0001 0650 7433Pittsburgh Heart, Lung, Blood and Vascular Medicine Institute, University of Pittsburgh and University of Pittsburgh Medical Center (UPMC), Pittsburgh, PA USA ,grid.21925.3d0000 0004 1936 9000McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA USA
| | - Kang Kim
- grid.21925.3d0000 0004 1936 9000Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA USA ,grid.21925.3d0000 0004 1936 9000Department of Mechanical Engineering and Materials Science, University of Pittsburgh, Pittsburgh, PA USA ,grid.21925.3d0000 0004 1936 9000Division of Cardiology, Department of Medicine, University of Pittsburgh School of Medicine, 623A Scaife Hall, 3550 Terrace Street, Pittsburgh, PA 15213 USA ,grid.412689.00000 0001 0650 7433Heart and Vascular Institute, University of Pittsburgh Medical Center (UPMC), Pittsburgh, PA USA ,grid.412689.00000 0001 0650 7433Pittsburgh Heart, Lung, Blood and Vascular Medicine Institute, University of Pittsburgh and University of Pittsburgh Medical Center (UPMC), Pittsburgh, PA USA ,grid.21925.3d0000 0004 1936 9000McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA USA ,grid.21925.3d0000 0004 1936 9000Center for Ultrasound Molecular Imaging and Therapeutics, University of Pittsburgh, Pittsburgh, PA USA
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Chowdhary A, Garg P, Das A, Nazir MS, Plein S. Cardiovascular magnetic resonance imaging: emerging techniques and applications. Heart 2021; 107:697-704. [PMID: 33402364 DOI: 10.1136/heartjnl-2019-315669] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 11/02/2020] [Accepted: 11/23/2020] [Indexed: 01/15/2023] Open
Abstract
This review gives examples of emerging cardiovascular magnetic resonance (CMR) techniques and applications that have the potential to transition from research to clinical application in the near future. Four-dimensional flow CMR (4D-flow CMR) allows time-resolved three-directional, three-dimensional (3D) velocity-encoded phase-contrast imaging for 3D visualisation and quantification of valvular or intracavity flow. Acquisition times of under 10 min are achievable for a whole heart multidirectional data set and commercial software packages are now available for data analysis, making 4D-flow CMR feasible for inclusion in clinical imaging protocols. Diffusion tensor imaging (DTI) is based on the measurement of molecular water diffusion and uses contrasting behaviour in the presence and absence of boundaries to infer tissue structure. Cardiac DTI is capable of non-invasively phenotyping the 3D micro-architecture within a few minutes, facilitating transition of the method to clinical protocols. Hybrid positron emission tomography-magnetic resonance (PET-MR) provides quantitative PET measures of biological and pathological processes of the heart combined with anatomical, morphological and functional CMR imaging. Cardiac PET-MR offers opportunities in ischaemic, inflammatory and infiltrative heart disease.
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Affiliation(s)
- Amrit Chowdhary
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, West Yorkshire, UK
| | - Pankaj Garg
- Cardiovascular and Metabolic Medicine Group, University of East Anglia, Norwich, UK
| | - Arka Das
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, West Yorkshire, UK
| | - Muhummad Sohaib Nazir
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Sven Plein
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, West Yorkshire, UK .,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
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Nguyen CT, Christodoulou AG, Coll-Font J, Ma S, Xie Y, Reese TG, Mekkaoui C, Lewis GD, Bi X, Sosnovik DE, Li D. Free-breathing diffusion tensor MRI of the whole left ventricle using second-order motion compensation and multitasking respiratory motion correction. Magn Reson Med 2020; 85:2634-2648. [PMID: 33252140 DOI: 10.1002/mrm.28611] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 11/01/2020] [Accepted: 11/03/2020] [Indexed: 12/17/2022]
Abstract
PURPOSE We aimed to develop a novel free-breathing cardiac diffusion tensor MRI (DT-MRI) approach, M2-MT-MOCO, capable of whole left ventricular coverage that leverages second-order motion compensation (M2) diffusion encoding and multitasking (MT) framework to efficiently correct for respiratory motion (MOCO). METHODS Imaging was performed in 16 healthy volunteers and 3 heart failure patients with symptomatic dyspnea. The healthy volunteers were scanned to compare the accuracy of interleaved multislice coverage of the entire left ventricle with a single-slice acquisition and the accuracy of the free-breathing conventional MOCO and MT-MOCO approaches with reference breath-hold DT-MRI. Mean diffusivity (MD), fractional anisotropy (FA), helix angle transmurality (HAT), and intrascan repeatability were quantified and compared. RESULTS In all subjects, free-breathing M2-MT-MOCO DT-MRI yielded DWI of the entire left ventricle without bulk motion-induced signal loss. No significant differences were seen in the global values of MD, FA, and HAT in the multislice and single-slice acquisitions. Furthermore, global quantification of MD, FA, and HAT were also not significantly different between the MT-MOCO and breath-hold, whereas conventional MOCO yielded significant differences in MD, FA, and HAT with MT-MOCO and FA with breath-hold. In heart failure patients, M2-MT-MOCO DT-MRI was feasible yielding higher MD, lower FA, and lower HAT compared with healthy volunteers. Substantial agreement was found between repeated scans across all subjects for MT-MOCO. CONCLUSION M2-MT-MOCO enables free-breathing DT-MRI of the entire left ventricle in 10 min, while preserving quantification of myocardial microstructure compared to breath-held and single-slice acquisitions and is feasible in heart failure patients.
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Affiliation(s)
- Christopher T Nguyen
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.,A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Anthony G Christodoulou
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California Los Angeles, Los Angeles, California, USA
| | - Jaume Coll-Font
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.,A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Sen Ma
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California Los Angeles, Los Angeles, California, USA
| | - Yibin Xie
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Timothy G Reese
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Choukri Mekkaoui
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Gregory D Lewis
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.,Heart Failure Section, Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Xiaoming Bi
- Siemens Medical Solutions USA, Inc., Los Angeles, California, USA
| | - David E Sosnovik
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.,A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California Los Angeles, Los Angeles, California, USA
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Probing cardiomyocyte mobility with multi-phase cardiac diffusion tensor MRI. PLoS One 2020; 15:e0241996. [PMID: 33180823 PMCID: PMC7660468 DOI: 10.1371/journal.pone.0241996] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Accepted: 10/24/2020] [Indexed: 11/19/2022] Open
Abstract
PURPOSE Cardiomyocyte organization and performance underlie cardiac function, but the in vivo mobility of these cells during contraction and filling remains difficult to probe. Herein, a novel trigger delay (TD) scout sequence was used to acquire high in-plane resolution (1.6 mm) Spin-Echo (SE) cardiac diffusion tensor imaging (cDTI) at three distinct cardiac phases. The objective was to characterize cardiomyocyte organization and mobility throughout the cardiac cycle in healthy volunteers. MATERIALS AND METHODS Nine healthy volunteers were imaged with cDTI at three distinct cardiac phases (early systole, late systole, and diastasis). The sequence used a free-breathing Spin-Echo (SE) cDTI protocol (b-values = 350s/mm2, twelve diffusion encoding directions, eight repetitions) to acquire high-resolution images (1.6x1.6x8mm3) at 3T in ~7 minutes/cardiac phase. Helix Angle (HA), Helix Angle Range (HAR), E2 angle (E2A), Transverse Angle (TA), Mean Diffusivity (MD), diffusion tensor eigenvalues (λ1-2-3), and Fractional Anisotropy (FA) in the left ventricle (LV) were characterized. RESULTS Images from the patient-specific TD scout sequence demonstrated that SE cDTI acquisition was possible at early systole, late systole, and diastasis in 78%, 100% and 67% of the cases, respectively. At the mid-ventricular level, mobility (reported as median [IQR]) was observed in HAR between early systole and late systole (76.9 [72.6, 80.5]° vs 96.6 [85.9, 100.3]°, p<0.001). E2A also changed significantly between early systole, late systole, and diastasis (27.7 [20.8, 35.1]° vs 45.2 [42.1, 49]° vs 20.7 [16.6, 26.4]°, p<0.001). CONCLUSION We demonstrate that it is possible to probe cardiomyocyte mobility using multi-phase and high resolution cDTI. In healthy volunteers, aggregate cardiomyocytes re-orient themselves more longitudinally during contraction, while cardiomyocyte sheetlets tilt radially during wall thickening. These observations provide new insights into the three-dimensional mobility of myocardial microstructure during systolic contraction.
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Agger P, Stephenson RS. Assessing Myocardial Architecture: The Challenges and Controversies. J Cardiovasc Dev Dis 2020; 7:jcdd7040047. [PMID: 33137874 PMCID: PMC7711767 DOI: 10.3390/jcdd7040047] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 10/04/2020] [Accepted: 10/08/2020] [Indexed: 12/16/2022] Open
Abstract
In recent decades, investigators have strived to describe and quantify the orientation of the cardiac myocytes in an attempt to classify their arrangement in healthy and diseased hearts. There are, however, striking differences between the investigations from both a technical and methodological standpoint, thus limiting their comparability and impeding the drawing of appropriate physiological conclusions from the structural assessments. This review aims to elucidate these differences, and to propose guidance to establish methodological consensus in the field. The review outlines the theory behind myocyte orientation analysis, and importantly has identified pronounced differences in the definitions of otherwise widely accepted concepts of myocytic orientation. Based on the findings, recommendations are made for the future design of studies in the field of myocardial morphology. It is emphasised that projection of myocyte orientations, before quantification of their angulation, introduces considerable bias, and that angles should be assessed relative to the epicardial curvature. The transmural orientation of the cardiomyocytes should also not be neglected, as it is an important determinant of cardiac function. Finally, there is considerable disagreement in the literature as to how the orientation of myocardial aggregates should be assessed, but to do so in a mathematically meaningful way, the normal vector of the aggregate plane should be utilised.
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Affiliation(s)
- Peter Agger
- Comparative Medicine Lab, Department of Clinical Medicine, Aarhus University, 8220 Aarhus N, Denmark
- Department of Pediatrics, Randers Regional Hospital, Skovlyvej 15, 8930 Randers NE, Denmark
- Correspondence:
| | - Robert S. Stephenson
- Institute of Clinical Sciences, College of Medical and Dental Sciences, University of Birmingham, Birmingham B15 2TT, UK;
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Abstract
Classification of heart failure is based on the left ventricular ejection fraction (EF): preserved EF, midrange EF, and reduced EF. There remains an unmet need for further heart failure phenotyping of ventricular structure-function relationships. Because of high spatiotemporal resolution, cardiac magnetic resonance (CMR) remains the reference modality for quantification of ventricular contractile function. The authors aim to highlight novel frameworks, including theranostic use of ferumoxytol, to enable more efficient evaluation of ventricular function in heart failure patients who are also frequently anemic, and to discuss emerging quantitative CMR approaches for evaluation of ventricular structure-function relationships in heart failure.
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Le B, Ferreira P, Merchant S, Zheng G, Sutherland MR, Dahl MJ, Albertine KH, Black MJ. Microarchitecture of the hearts in term and former-preterm lambs using diffusion tensor imaging. Anat Rec (Hoboken) 2020; 304:803-817. [PMID: 33015923 DOI: 10.1002/ar.24516] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 05/31/2020] [Accepted: 06/30/2020] [Indexed: 12/13/2022]
Abstract
Diffusion tensor imaging (DTI) is an MRI technique that can be used to map cardiomyocyte tracts and estimate local cardiomyocyte and sheetlet orientation within the heart. DTI measures diffusion distances of water molecules within the myocardium, where water diffusion generally occurs more freely along the long axis of cardiomyocytes and within the extracellular matrix, but is restricted by cell membranes such that transverse diffusion is limited. DTI can be undertaken in fixed hearts and it allows the three-dimensional mapping of the cardiac microarchitecture, including cardiomyocyte organization, within the whole heart. The objective of this study was to use DTI to compare the cardiac microarchitecture and cardiomyocyte organization in archived fixed left ventricles of lambs that were born either preterm (n = 5) or at term (n = 7), at a postnatal timepoint equivalent to about 6 years of age in children. Although the findings support the feasibility of retrospective DTI scanning of fixed hearts, several hearts were excluded from DTI analysis because of poor scan quality, such as ghosting artifacts. The preliminary findings from viable DTI scans (n = 3/group) suggest that the extracellular compartment is altered and that there is an immature microstructural phenotype early in postnatal life in the LV of lambs born preterm. Our findings support a potential time-efficient imaging role for DTI in detecting abnormal changes in the microstructure of fixed hearts of former-preterm neonates, although further investigation into factors that affect scan quality is required.
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Affiliation(s)
- Bianca Le
- Department of Anatomy and Developmental Biology and Biomedicine Discovery Institute, Monash University, Victoria, Australia
| | | | - Samer Merchant
- Department of Bioengineering, University of Utah, Salt Lake City, Utah, USA
| | - Gang Zheng
- Monash Biomedical Imaging, Monash University, Victoria, Australia
| | - Megan R Sutherland
- Department of Anatomy and Developmental Biology and Biomedicine Discovery Institute, Monash University, Victoria, Australia
| | - Mar Janna Dahl
- Department of Pediatrics, University of Utah, Salt Lake City, Utah, USA
| | - Kurt H Albertine
- Department of Pediatrics, University of Utah, Salt Lake City, Utah, USA
| | - Mary Jane Black
- Department of Anatomy and Developmental Biology and Biomedicine Discovery Institute, Monash University, Victoria, Australia
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Lee JM, Suen SKQ, Ng WL, Ma WC, Yeong WY. Bioprinting of Collagen: Considerations, Potentials, and Applications. Macromol Biosci 2020; 21:e2000280. [PMID: 33073537 DOI: 10.1002/mabi.202000280] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 09/21/2020] [Indexed: 12/15/2022]
Abstract
Collagen is the most abundant extracellular matrix protein that is widely used in tissue engineering (TE). There is little research done on printing pure collagen. To understand the bottlenecks in printing pure collagen, it is imperative to understand collagen from a bottom-up approach. Here it is aimed to provide a comprehensive overview of collagen printing, where collagen assembly in vivo and the various sources of collagen available for TE application are first understood. Next, the current printing technologies and strategy for printing collagen-based materials are highlighted. Considerations and key challenges faced in collagen printing are identified. Finally, the key research areas that would enhance the functionality of printed collagen are presented.
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Affiliation(s)
- Jia Min Lee
- Singapore Centre for 3D Printing, School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
| | - Sean Kang Qiang Suen
- Singapore Centre for 3D Printing, School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
| | - Wei Long Ng
- HP-NTU Digital Manufacturing Corporate Lab, 50 Nanyang Avenue, Singapore, 639798, Singapore
| | - Wai Cheung Ma
- Singapore Centre for 3D Printing, School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
| | - Wai Yee Yeong
- Singapore Centre for 3D Printing, School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore.,HP-NTU Digital Manufacturing Corporate Lab, 50 Nanyang Avenue, Singapore, 639798, Singapore
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47
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Dejea H, Bonnin A, Cook AC, Garcia-Canadilla P. Cardiac multi-scale investigation of the right and left ventricle ex vivo: a review. Cardiovasc Diagn Ther 2020; 10:1701-1717. [PMID: 33224784 DOI: 10.21037/cdt-20-269] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The heart is a complex multi-scale system composed of components integrated at the subcellular, cellular, tissue and organ levels. The myocytes, the contractile elements of the heart, form a complex three-dimensional (3D) network which enables propagation of the electrical signal that triggers the contraction to efficiently pump blood towards the whole body. Cardiovascular diseases (CVDs), a major cause of mortality in developed countries, often lead to cardiovascular remodeling affecting cardiac structure and function at all scales, from myocytes and their surrounding collagen matrix to the 3D organization of the whole heart. As yet, there is no consensus as to how the myocytes are arranged and packed within their connective tissue matrix, nor how best to image them at multiple scales. Cardiovascular imaging is routinely used to investigate cardiac structure and function as well as for the evaluation of cardiac remodeling in CVDs. For a complete understanding of the relationship between structural remodeling and cardiac dysfunction in CVDs, multi-scale imaging approaches are necessary to achieve a detailed description of ventricular architecture along with cardiac function. In this context, ventricular architecture has been extensively studied using a wide variety of imaging techniques: ultrasound (US), optical coherence tomography (OCT), microscopy (confocal, episcopic, light sheet, polarized light), magnetic resonance imaging (MRI), micro-computed tomography (micro-CT) and, more recently, synchrotron X-ray phase contrast imaging (SR X-PCI). Each of these techniques have their own set of strengths and weaknesses, relating to sample size, preparation, resolution, 2D/3D capabilities, use of contrast agents and possibility of performing together with in vivo studies. Therefore, the combination of different imaging techniques to investigate the same sample, thus taking advantage of the strengths of each method, could help us to extract the maximum information about ventricular architecture and function. In this review, we provide an overview of available and emerging cardiovascular imaging techniques for assessing myocardial architecture ex vivo and discuss their utility in being able to quantify cardiac remodeling, in CVDs, from myocyte to whole organ.
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Affiliation(s)
- Hector Dejea
- Paul Scherrer Institut, Villigen PSI, Villigen, Switzerland.,Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Anne Bonnin
- Paul Scherrer Institut, Villigen PSI, Villigen, Switzerland
| | - Andrew C Cook
- Institute of Cardiovascular Science, University College London, London, UK
| | - Patricia Garcia-Canadilla
- Institute of Cardiovascular Science, University College London, London, UK.,Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
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Zhang XS, Sang XQ, Kuai ZX, Zhang HX, Lou J, Lu Q, Zhu YM. Investigation of intravoxel incoherent motion tensor imaging for the characterization of the in vivo human heart. Magn Reson Med 2020; 85:1414-1426. [PMID: 32989786 DOI: 10.1002/mrm.28523] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Revised: 08/24/2020] [Accepted: 08/26/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE To investigate intravoxel incoherent motion (IVIM) tensor imaging of the in vivo human heart and elucidate whether the estimation of IVIM tensors is affected by the complexity of pseudo-diffusion components in myocardium. METHODS The cardiac IVIM data of 10 healthy subjects were acquired using a diffusion weighted spin-echo echo-planar imaging sequence along 6 gradient directions with 10 b values (0~400 s/mm2 ). The IVIM data of left ventricle myocardium were fitted to the IVIM tensor model. The complexity of myocardial pseudo-diffusion components was reduced through exclusion of low b values (0 and 5 s/mm2 ) from the IVIM curve-fitting analysis. The fractional anisotropy, mean fraction/mean diffusivity, and Westin measurements of pseudo-diffusion tensors (fp and D*) and self-diffusion tensor (D), as well as the angle between the main eigenvector of fp (or D*) and that of D, were computed and compared before and after excluding low b values. RESULTS The fractional anisotropy values of fp and D* without low b value participation were significantly higher (P < .001) than those with low b value participation, but an opposite trend was found for the mean fraction/diffusivity values. Besides, after removing low b values, the angle between the main eigenvector of fp (or D*) and that of D became small, and both fp and D* tensors presented significant decrease of spherical components and significant increase of linear components. CONCLUSION The presence of multiple pseudo-diffusion components in myocardium indeed influences the estimation of IVIM tensors. The IVIM tensor model needs to be further improved to account for the complexity of myocardial microcirculatory network and blood flow.
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Affiliation(s)
- Xiu-Shi Zhang
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, People's Republic of China
| | - Xi-Qiao Sang
- Division of Respiratory Disease, The Fourth Hospital of Harbin Medical University, Harbin, People's Republic of China
| | - Zi-Xiang Kuai
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, People's Republic of China
| | - Hong-Xia Zhang
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, People's Republic of China
| | - Jie Lou
- Imaging Center, Harbin Medical University Cancer Hospital, Harbin, People's Republic of China
| | - Qing Lu
- Department of Radiology, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Yue-Min Zhu
- Univ Lyon, INSA Lyon, CNRS, Inserm, CREATIS UMR 5220, U1206, F-69621, Lyon, France
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49
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Tous C, Gentles TL, Young AA, Pontré BP. Ex vivo cardiovascular magnetic resonance diffusion weighted imaging in congenital heart disease, an insight into the microstructures of tetralogy of Fallot, biventricular and univentricular systemic right ventricle. J Cardiovasc Magn Reson 2020; 22:69. [PMID: 32951605 PMCID: PMC7504600 DOI: 10.1186/s12968-020-00662-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2020] [Accepted: 08/11/2020] [Indexed: 11/10/2022] Open
Abstract
PURPOSE Common types of congenital heart disease exhibit a variety of structural and functional variations which may be accompanied by changes in the myocardial microstructure. We aimed to compare myocardial architecture from magnetic resonance diffusion tensor imaging (DTI) in preserved pathology specimens. MATERIALS AND METHODS Pathology specimens (n = 24) formalin-fixed for 40.8 ± 7.9 years comprised tetralogy of Fallot (TOF, n = 10), dextro-transposition of great arteries (D-TGA, n = 8) five with ventricular septal defect (VSD), systemic right ventricle (n = 4), situs inversus totalis (SIT, n = 1) and levo-TGA (L-TGA, n = 1). Specimens were imaged using a custom spin-echo sequence and segmented automatically according to tissue volume fraction. In each specimen T1, T2, fractional anisotropy, mean diffusivity, helix angle (HA) and sheet angle (E2A) were quantified. Pathologies were compared according to their HA gradient, HA asymmetry and E2A mean value in each myocardial segment (anterior, posterior, septal and lateral walls). RESULTS TOF and D-TGA with VSD had decreased helix angle gradient by - 0.34°/% and remained symmetric in the septum in comparison to D-TGA without VSD. Helix angle range was decreased by 45°. It was associated with a decreased HA gradient in the right ventricular (RV) wall, i.e. predominant circumferential myocytes. The sheet angle in the septum of TOF was opposing those of the left ventricular (LV) free wall. Univentricular systemic RV had the lowest HA gradient (- 0.43°/%) and the highest HA asymmetry (75%). HA in SIT was linear, asymmetric, and reversed with a sign change at about 70% of the depth at mid-ventricle. In L-TGA with VSD, HA was asymmetric (90%) and its gradients were decreased in the septum, anterior and lateral wall. CONCLUSION The organization of the myocytes as determined by DTI differs between TOF, D-TGA, L-TGA, systemic RV and SIT specimens. These differences in cardiac structure may further enlighten our understanding of cardiac function in these diverse congenital heart diseases.
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Affiliation(s)
- Cyril Tous
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
- Laboratory of Clinical Image Processing Le Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Montréal, Canada
| | - Thomas L Gentles
- Green Lane Paediatric and Congenital Cardiac Service, Starship Children's Hospital, Auckland, New Zealand
| | - Alistair A Young
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand
- Department of Biomedical Engineering, King's College London, London, UK
| | - Beau P Pontré
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand.
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Mekkaoui I, Pousin J, Hesthaven J, Li JR. Apparent diffusion coefficient measured by diffusion MRI of moving and deforming domains. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2020; 318:106809. [PMID: 32862079 DOI: 10.1016/j.jmr.2020.106809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2020] [Revised: 06/19/2020] [Accepted: 08/04/2020] [Indexed: 06/11/2023]
Abstract
The modeling of the diffusion MRI signal from moving and deforming organs such as the heart is challenging due to significant motion and deformation of the imaged medium during the signal acquisition. Recently, a mathematical formulation of the Bloch-Torrey equation, describing the complex transverse magnetization due to diffusion-encoding magnetic field gradients, was developed to account for the motion and deformation. In that work, the motivation was to cancel the effect of the motion and deformation in the MRI image and the space scale of interest spans multiple voxels. In the present work, we adapt the mathematical equation to study the diffusion MRI signal at the much smaller scale of biological cells. We start with the Bloch-Torrey equation defined on a cell that is moving and deforming and linearize the equation around the magnitude of the diffusion-encoding gradient. The result is a second order signal model in which the linear term gives the imaginary part of the diffusion MRI signal and the quadratic term gives the apparent diffusion coefficient (ADC) attributable to the biological cell. We numerically validate this model for a variety of motions and deformations.
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Affiliation(s)
- Imen Mekkaoui
- INRIA Saclay, Equipe DEFI, CMAP, Ecole Polytechnique, Route de Saclay, 91128 Palaiseau Cedex, France
| | - Jérôme Pousin
- ICJ UMR5208, INSA-Lyon, 20 Av. A. Einstein, 69100 Villeurbanne, France
| | | | - Jing-Rebecca Li
- INRIA Saclay, Equipe DEFI, CMAP, Ecole Polytechnique, Route de Saclay, 91128 Palaiseau Cedex, France.
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