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Wang S, Li Z, Yuan F, Varray F. Use of the intrusion angle to describe the radial orientation of local cardiomyocytes in the left ventricle. J Morphol 2023; 284:e21650. [PMID: 37990764 DOI: 10.1002/jmor.21650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 09/20/2023] [Accepted: 09/24/2023] [Indexed: 11/23/2023]
Abstract
The projected transverse angle and the nonprojected intrusion angle can be used to describe the radial orientation of local cardiomyocytes in the left ventricle wall, although to date their descriptive relevance has not been demonstrated. This paper compares the evolution of the transverse angle and the intrusion angle in five left ventricle wall samples, and investigates in more detail their respective behaviors when the nonprojected helical angle varies. We show that the intrusion angle avoids the "projection" effect, and contrary to the transverse angle, it remains stable whatever the values taken by the nonprojected helical angle, even when this approaches 90°. The intrusion angle is the better choice, rather than the transverse angle, in describing the radial orientation of local cardiomyocytes. Furthermore, the oscillation of the intrusion angle in the samples is assessed, whose results indicate that the intrusion angle's oscillation amplitude and period are regional and related to the local tissue architecture.
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Affiliation(s)
- Shunli Wang
- School of Instrumentation Science and Engineering, Harbin Institute of Technology, Precision Instrument Research Institute, Harbin, China
| | - Zhaorui Li
- School of Instrumentation Science and Engineering, Harbin Institute of Technology, Precision Instrument Research Institute, Harbin, China
| | - Feng Yuan
- School of Instrumentation Science and Engineering, Harbin Institute of Technology, Precision Instrument Research Institute, Harbin, China
| | - François Varray
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, CNRS, Inserm, CREATIS UMR 5220 U1294, CREATIS (Centre de Researche en Acquisition et Traitement de I'Image pour la Santé), Lyon, France
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Farzi M, Coveney S, Afzali M, Zdora M, Lygate CA, Rau C, Frangi AF, Dall'Armellina E, Teh I, Schneider JE. Measuring cardiomyocyte cellular characteristics in cardiac hypertrophy using diffusion-weighted MRI. Magn Reson Med 2023; 90:2144-2157. [PMID: 37345727 PMCID: PMC10962572 DOI: 10.1002/mrm.29775] [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: 01/23/2023] [Revised: 05/05/2023] [Accepted: 06/02/2023] [Indexed: 06/23/2023]
Abstract
PURPOSE This paper presents a hierarchical modeling approach for estimating cardiomyocyte major and minor diameters and intracellular volume fraction (ICV) using diffusion-weighted MRI (DWI) data in ex vivo mouse hearts. METHODS DWI data were acquired on two healthy controls and two hearts 3 weeks post transverse aortic constriction (TAC) using a bespoke diffusion scheme with multiple diffusion times (Δ $$ \Delta $$ ), q-shells and diffusion encoding directions. Firstly, a bi-exponential tensor model was fitted separately at each diffusion time to disentangle the dependence on diffusion times from diffusion weightings, that is, b-values. The slow-diffusing component was attributed to the restricted diffusion inside cardiomyocytes. ICV was then extrapolated atΔ = 0 $$ \Delta =0 $$ using linear regression. Secondly, given the secondary and the tertiary diffusion eigenvalue measurements for the slow-diffusing component obtained at different diffusion times, major and minor diameters were estimated assuming a cylinder model with an elliptical cross-section (ECS). High-resolution three-dimensional synchrotron X-ray imaging (SRI) data from the same specimen was utilized to evaluate the biophysical parameters. RESULTS Estimated parameters using DWI data were (control 1/control 2 vs. TAC 1/TAC 2): major diameter-17.4μ $$ \mu $$ m/18.0μ $$ \mu $$ m versus 19.2μ $$ \mu $$ m/19.0μ $$ \mu $$ m; minor diameter-10.2μ $$ \mu $$ m/9.4μ $$ \mu $$ m versus 12.8μ $$ \mu $$ m/13.4μ $$ \mu $$ m; and ICV-62%/62% versus 68%/47%. These findings were consistent with SRI measurements. CONCLUSION The proposed method allowed for accurate estimation of biophysical parameters suggesting cardiomyocyte diameters as sensitive biomarkers of hypertrophy in the heart.
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Affiliation(s)
- Mohsen Farzi
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic MedicineUniversity of LeedsLeedsUK
| | - Sam Coveney
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic MedicineUniversity of LeedsLeedsUK
| | - Maryam Afzali
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic MedicineUniversity of LeedsLeedsUK
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of PsychologyCardiff UniversityCardiffUK
| | - Marie‐Christine Zdora
- Diamond Light Source Ltd.Harwell Science and Innovation CampusDidcotUK
- Department of Physics & AstronomyUniversity College LondonLondonUK
| | - Craig A. Lygate
- Division of Cardiovascular Medicine, Radcliffe Department of MedicineUniversity of OxfordOxfordUK
| | - Christoph Rau
- Diamond Light Source Ltd.Harwell Science and Innovation CampusDidcotUK
| | - Alejandro F. Frangi
- Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of ComputingUniversity of LeedsLeedsUK
| | - Erica Dall'Armellina
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic MedicineUniversity of LeedsLeedsUK
| | - Irvin Teh
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic MedicineUniversity of LeedsLeedsUK
| | - Jürgen E. Schneider
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic MedicineUniversity of LeedsLeedsUK
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3
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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: 12] [Impact Index Per Article: 12.0] [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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Teh I, Shelley D, Boyle JH, Zhou F, Poenar A, Sharrack N, Foster RJ, Yuldasheva NY, Parker GJM, Dall'Armellina E, Plein S, Schneider JE, Szczepankiewicz F. Cardiac q-space trajectory imaging by motion-compensated tensor-valued diffusion encoding in human heart in vivo. Magn Reson Med 2023; 90:150-165. [PMID: 36941736 PMCID: PMC10952623 DOI: 10.1002/mrm.29637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 01/25/2023] [Accepted: 02/23/2023] [Indexed: 03/23/2023]
Abstract
PURPOSE Tensor-valued diffusion encoding can probe more specific features of tissue microstructure than what is available by conventional diffusion weighting. In this work, we investigate the technical feasibility of tensor-valued diffusion encoding at high b-values with q-space trajectory imaging (QTI) analysis, in the human heart in vivo. METHODS Ten healthy volunteers were scanned on a 3T scanner. We designed time-optimal gradient waveforms for tensor-valued diffusion encoding (linear and planar) with second-order motion compensation. Data were analyzed with QTI. Normal values and repeatability were investigated for the mean diffusivity (MD), fractional anisotropy (FA), microscopic FA (μFA), isotropic, anisotropic and total mean kurtosis (MKi, MKa, and MKt), and orientation coherence (Cc ). A phantom, consisting of two fiber blocks at adjustable angles, was used to evaluate sensitivity of parameters to orientation dispersion and diffusion time. RESULTS QTI data in the left ventricular myocardium were MD = 1.62 ± 0.07 μm2 /ms, FA = 0.31 ± 0.03, μFA = 0.43 ± 0.07, MKa = 0.20 ± 0.07, MKi = 0.13 ± 0.03, MKt = 0.33 ± 0.09, and Cc = 0.56 ± 0.22 (mean ± SD across subjects). Phantom experiments showed that FA depends on orientation dispersion, whereas μFA was insensitive to this effect. CONCLUSION We demonstrated the first tensor-valued diffusion encoding and QTI analysis in the heart in vivo, along with first measurements of myocardial μFA, MKi, MKa, and Cc . The methodology is technically feasible and provides promising novel biomarkers for myocardial tissue characterization.
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Affiliation(s)
- Irvin Teh
- Leeds Institute of Cardiovascular and Metabolic MedicineUniversity of LeedsLeedsUK
| | - David Shelley
- Leeds Institute of Cardiovascular and Metabolic MedicineUniversity of LeedsLeedsUK
- Leeds Teaching Hospitals TrustLeedsUK
| | - Jordan H. Boyle
- Faculty of Industrial Design EngineeringDelft University of TechnologyDelftNetherlands
| | - Fenglei Zhou
- Center for Medical Image Computing, Department of Medical Physics & Biomedical Engineering and Department of NeuroinflammationUniversity College LondonLondonUK
- Astrea BioseparationCombertonUK
| | - Ana‐Maria Poenar
- Leeds Institute of Cardiovascular and Metabolic MedicineUniversity of LeedsLeedsUK
| | - Noor Sharrack
- Leeds Institute of Cardiovascular and Metabolic MedicineUniversity of LeedsLeedsUK
| | - Richard J. Foster
- Leeds Institute of Cardiovascular and Metabolic MedicineUniversity of LeedsLeedsUK
| | - Nadira Y. Yuldasheva
- Leeds Institute of Cardiovascular and Metabolic MedicineUniversity of LeedsLeedsUK
| | - Geoff J. M. Parker
- Center for Medical Image Computing, Department of Medical Physics & Biomedical Engineering and Department of NeuroinflammationUniversity College LondonLondonUK
- Bioxydyn LimitedManchesterUK
| | - Erica Dall'Armellina
- Leeds Institute of Cardiovascular and Metabolic MedicineUniversity of LeedsLeedsUK
| | - Sven Plein
- Leeds Institute of Cardiovascular and Metabolic MedicineUniversity of LeedsLeedsUK
| | - Jürgen E. Schneider
- Leeds Institute of Cardiovascular and Metabolic MedicineUniversity of LeedsLeedsUK
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Xu X, Hu J, Zheng Y, Liu Y, Cui Z, Liang D, Zhu Y. Slice-specific tracking for free-breathing diffusion tensor cardiac MRI. NMR IN BIOMEDICINE 2023:e4922. [PMID: 36914257 DOI: 10.1002/nbm.4922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 02/20/2023] [Accepted: 02/22/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Diffusion tensor cardiac magnetic resonance (DT-CMR) imaging has great potential to characterize myocardial microarchitecture. However, its accuracy is limited by respiratory and cardiac motion and long scan times. Here, we develop and evaluate a slice-specific tracking method to improve the efficiency and accuracy of DT-CMR acquisition during free breathing. METHODS Coronal images were obtained along with signals from a diaphragmatic navigator. Respiratory and slice displacements were obtained from the navigator signals and coronal images, respectively, and these displacements were fitted with a linear model to obtain the slice-specific tracking factors. This method was evaluated in DT-CMR examinations of 17 healthy subjects, and the results were compared with those obtained using a fixed tracking factor of 0.6. DT-CMR with breath-holding was used for reference. Quantitative and qualitative evaluation methods were used to analyze the performance of the slice-specific tracking method and the consistency between the obtained diffusion parameters. RESULTS In the study, the slice-specific tracking factors showed an upward trend from the basal to the apical slice. Residual in-plane movements were lower in slice-specific tracking than in fixed-factor tracking (RMSE: 2.748 ± 1.171 versus 5.983 ± 2.623, P < 0.001). The diffusion parameters obtained using slice-specific tracking were not significantly different from those obtained from breath-holding acquisition (P > 0.05). CONCLUSION In free-breathing DT-CMR imaging, the slice-specific tracking method reduced misalignment of the acquired slices. The diffusion parameters obtained using this approach were consistent with those obtained with the breath-holding technique.
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Affiliation(s)
- Xi Xu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
| | - Junpu Hu
- United Imaging Healthcare, Shanghai, China
| | - Yijia Zheng
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Yuanyuan Liu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Zhuoxu Cui
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Dong Liang
- Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China
- Research Center for Medical AI, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Yanjie Zhu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
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6
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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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7
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Garcia-Canadilla P, Mohun TJ, Bijnens B, Cook AC. Detailed quantification of cardiac ventricular myocardial architecture in the embryonic and fetal mouse heart by application of structure tensor analysis to high resolution episcopic microscopic data. Front Cell Dev Biol 2022; 10:1000684. [DOI: 10.3389/fcell.2022.1000684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 10/31/2022] [Indexed: 11/18/2022] Open
Abstract
The mammalian heart, which is one of the first organs to form and function during embryogenesis, develops from a simple tube into a complex organ able to efficiently pump blood towards the rest of the body. The progressive growth of the compact myocardium during embryonic development is accompanied by changes in its structural complexity and organisation. However, how myocardial myoarchitecture develops during embryogenesis remain poorly understood. To date, analysis of heart development has focused mainly on qualitative descriptions using selected 2D histological sections. High resolution episcopic microscopy (HREM) is a novel microscopic imaging technique that enables to obtain high-resolution three-dimensional images of the heart and perform detailed quantitative analyses of heart development. In this work, we performed a detailed characterization of the development of myocardial architecture in wildtype mice, from E14.5 to E18.5, by means of structure tensor analysis applied to HREM images of the heart. Our results shows that even at E14.5, myocytes are already aligned, showing a gradual change in their helical angle from positive angulation in the endocardium towards negative angulation in the epicardium. Moreover, there is gradual increase in the degree of myocardial organisation concomitant with myocardial growth. However, the development of the myoarchitecture is heterogeneous showing regional differences between ventricles, ventricular walls as well as between myocardial layers, with different growth patterning between the endocardium and epicardium. We also found that the percentage of circumferentially arranged myocytes within the LV significantly increases with gestational age. Finally, we found that fractional anisotropy (FA) within the LV gradually increases with gestational age, while the FA within RV remains unchanged.
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8
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Lashgari M, Ravikumar N, Teh I, Li JR, Buckley DL, Schneider JE, Frangi AF. Three-dimensional micro-structurally informed in silico myocardium-Towards virtual imaging trials in cardiac diffusion weighted MRI. Med Image Anal 2022; 82:102592. [PMID: 36095906 DOI: 10.1016/j.media.2022.102592] [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: 08/27/2021] [Revised: 08/14/2022] [Accepted: 08/18/2022] [Indexed: 11/24/2022]
Abstract
In silico tissue models (viz. numerical phantoms) provide a mechanism for evaluating quantitative models of magnetic resonance imaging. This includes the validation and sensitivity analysis of imaging biomarkers and tissue microstructure parameters. This study proposes a novel method to generate a realistic numerical phantom of myocardial microstructure. The proposed method extends previous studies by accounting for the variability of the cardiomyocyte shape, water exchange between the cardiomyocytes (intercalated discs), disorder class of myocardial microstructure, and four sheetlet orientations. In the first stage of the method, cardiomyocytes and sheetlets are generated by considering the shape variability and intercalated discs in cardiomyocyte-cardiomyocyte connections. Sheetlets are then aggregated and oriented in the directions of interest. The morphometric study demonstrates no significant difference (p>0.01) between the distribution of volume, length, and primary and secondary axes of the numerical and real (literature) cardiomyocyte data. Moreover, structural correlation analysis validates that the in-silico tissue is in the same class of disorderliness as the real tissue. Additionally, the absolute angle differences between the simulated helical angle (HA) and input HA (reference value) of the cardiomyocytes (4.3°±3.1°) demonstrate a good agreement with the absolute angle difference between the measured HA using experimental cardiac diffusion tensor imaging (cDTI) and histology (reference value) reported by (Holmes et al., 2000) (3.7°±6.4°) and (Scollan et al. 1998) (4.9°±14.6°). Furthermore, the angular distance between eigenvectors and sheetlet angles of the input and simulated cDTI is much smaller than those between measured angles using structural tensor imaging (as a gold standard) and experimental cDTI. Combined with the qualitative results, these results confirm that the proposed method can generate richer numerical phantoms for the myocardium than previous studies.
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Affiliation(s)
- Mojtaba Lashgari
- Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, UK; Biomedical Imaging Science Department, Leeds Institute for Cardiovascular and Metabolic Medicine (LICAMM), School of Medicine, University of Leeds, Leeds, UK.
| | - Nishant Ravikumar
- Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, UK; Biomedical Imaging Science Department, Leeds Institute for Cardiovascular and Metabolic Medicine (LICAMM), School of Medicine, University of Leeds, Leeds, UK
| | - Irvin Teh
- Biomedical Imaging Science Department, Leeds Institute for Cardiovascular and Metabolic Medicine (LICAMM), School of Medicine, University of Leeds, Leeds, UK
| | - Jing-Rebecca Li
- INRIA Saclay, Equipe DEFI, CMAP, Ecole Polytechnique, Route de Saclay, 91128 Palaiseau Cedex, France
| | - David L Buckley
- Biomedical Imaging Science Department, Leeds Institute for Cardiovascular and Metabolic Medicine (LICAMM), School of Medicine, University of Leeds, Leeds, UK
| | - Jurgen E Schneider
- Biomedical Imaging Science Department, Leeds Institute for Cardiovascular and Metabolic Medicine (LICAMM), School of Medicine, University of Leeds, Leeds, UK
| | - Alejandro F Frangi
- Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), School of Computing, University of Leeds, Leeds, UK; Biomedical Imaging Science Department, Leeds Institute for Cardiovascular and Metabolic Medicine (LICAMM), School of Medicine, University of Leeds, Leeds, UK; INRIA Saclay, Equipe DEFI, CMAP, Ecole Polytechnique, Route de Saclay, 91128 Palaiseau Cedex, France; Medical Imaging Research Center (MIRC), Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium; Medical Imaging Research Center (MIRC), Department of Electrical Engineering, KU Leuven, Leuven, Belgium; Alan Turing Institute, London, UK.
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9
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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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10
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Abstract
Major advances in biomedical imaging have occurred over the last 2 decades and now allow many physiological, cellular, and molecular processes to be imaged noninvasively in small animal models of cardiovascular disease. Many of these techniques can be also used in humans, providing pathophysiological context and helping to define the clinical relevance of the model. Ultrasound remains the most widely used approach, and dedicated high-frequency systems can obtain extremely detailed images in mice. Likewise, dedicated small animal tomographic systems have been developed for magnetic resonance, positron emission tomography, fluorescence imaging, and computed tomography in mice. In this article, we review the use of ultrasound and positron emission tomography in small animal models, as well as emerging contrast mechanisms in magnetic resonance such as diffusion tensor imaging, hyperpolarized magnetic resonance, chemical exchange saturation transfer imaging, magnetic resonance elastography and strain, arterial spin labeling, and molecular imaging.
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Affiliation(s)
- David E Sosnovik
- Cardiology Division, Cardiovascular Research Center (D.E.S.), Massachusetts General Hospital and Harvard Medical School, Boston.,A.A. Martinos Center for Biomedical Imaging (D.E.S.), Massachusetts General Hospital and Harvard Medical School, Boston.,Harvard-MIT Program in Health Sciences and Technology, Harvard Medical School and Massachusetts Institute of Technology, Cambridge (D.E.S.)
| | - Marielle Scherrer-Crosbie
- Cardiology Division, Hospital of the University of Pennsylvania and Perelman School of Medicine, Philadelphia (M.S.-C)
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11
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Farzi M, Mcclymont D, Whittington H, Zdora MC, Khazin L, Lygate CA, Rau C, Dall'Armellina E, Teh I, Schneider JE. Assessing Myocardial Microstructure With Biophysical Models of Diffusion MRI. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:3775-3786. [PMID: 34270420 DOI: 10.1109/tmi.2021.3097907] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Biophysical models are a promising means for interpreting diffusion weighted magnetic resonance imaging (DW-MRI) data, as they can provide estimates of physiologically relevant parameters of microstructure including cell size, volume fraction, or dispersion. However, their application in cardiac microstructure mapping (CMM) has been limited. This study proposes seven new two-compartment models with combination of restricted cylinder models and a diffusion tensor to represent intra- and extracellular spaces, respectively. Three extended versions of the cylinder model are studied here: cylinder with elliptical cross section (ECS), cylinder with Gamma distributed radii (GDR), and cylinder with Bingham distributed axes (BDA). The proposed models were applied to data in two fixed mouse hearts, acquired with multiple diffusion times, q-shells and diffusion encoding directions. The cylinderGDR-pancake model provided the best performance in terms of root mean squared error (RMSE) reducing it by 25% compared to diffusion tensor imaging (DTI). The cylinderBDA-pancake model represented anatomical findings closest as it also allows for modelling dispersion. High-resolution 3D synchrotron X-ray imaging (SRI) data from the same specimen was utilized to evaluate the biophysical models. A novel tensor-based registration method is proposed to align SRI structure tensors to the MR diffusion tensors. The consistency between SRI and DW-MRI parameters demonstrates the potential of compartment models in assessing physiologically relevant parameters.
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12
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Exploring arterial tissue microstructural organization using non-Gaussian diffusion magnetic resonance schemes. Sci Rep 2021; 11:22247. [PMID: 34782651 PMCID: PMC8593063 DOI: 10.1038/s41598-021-01476-z] [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: 04/08/2021] [Accepted: 10/13/2021] [Indexed: 12/02/2022] Open
Abstract
The purpose of this study was to characterize the alterations in microstructural organization of arterial tissue using higher-order diffusion magnetic resonance schemes. Three porcine carotid artery models namely; native, collagenase treated and decellularized, were used to estimate the contribution of collagen and smooth muscle cells (SMC) on diffusion signal attenuation using gaussian and non-gaussian schemes. The samples were imaged in a 7 T preclinical scanner. High spatial and angular resolution diffusion weighted images (DWIs) were acquired using two multi-shell (max b-value = 3000 s/mm2) acquisition protocols. The processed DWIs were fitted using monoexponential, stretched-exponential, kurtosis and bi-exponential schemes. Directionally variant and invariant microstructural parametric maps of the three artery models were obtained from the diffusion schemes. The parametric maps were used to assess the sensitivity of each diffusion scheme to collagen and SMC composition in arterial microstructural environment. The inter-model comparison showed significant differences across the considered models. The bi-exponential scheme based slow diffusion compartment (Ds) was highest in the absence of collagen, compared to native and decellularized microenvironments. In intra-model comparison, kurtosis along the radial direction was the highest. Overall, the results of this study demonstrate the efficacy of higher order dMRI schemes in mapping constituent specific alterations in arterial microstructure.
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13
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Huang SY, Witzel T, Keil B, Scholz A, Davids M, Dietz P, Rummert E, Ramb R, Kirsch JE, Yendiki A, Fan Q, Tian Q, Ramos-Llordén G, Lee HH, Nummenmaa A, Bilgic B, Setsompop K, Wang F, Avram AV, Komlosh M, Benjamini D, Magdoom KN, Pathak S, Schneider W, Novikov DS, Fieremans E, Tounekti S, Mekkaoui C, Augustinack J, Berger D, Shapson-Coe A, Lichtman J, Basser PJ, Wald LL, Rosen BR. Connectome 2.0: Developing the next-generation ultra-high gradient strength human MRI scanner for bridging studies of the micro-, meso- and macro-connectome. Neuroimage 2021; 243:118530. [PMID: 34464739 PMCID: PMC8863543 DOI: 10.1016/j.neuroimage.2021.118530] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 08/10/2021] [Accepted: 08/27/2021] [Indexed: 11/26/2022] Open
Abstract
The first phase of the Human Connectome Project pioneered advances in MRI technology for mapping the macroscopic structural connections of the living human brain through the engineering of a whole-body human MRI scanner equipped with maximum gradient strength of 300 mT/m, the highest ever achieved for human imaging. While this instrument has made important contributions to the understanding of macroscale connectional topology, it has also demonstrated the potential of dedicated high-gradient performance scanners to provide unparalleled in vivo assessment of neural tissue microstructure. Building on the initial groundwork laid by the original Connectome scanner, we have now embarked on an international, multi-site effort to build the next-generation human 3T Connectome scanner (Connectome 2.0) optimized for the study of neural tissue microstructure and connectional anatomy across multiple length scales. In order to maximize the resolution of this in vivo microscope for studies of the living human brain, we will push the diffusion resolution limit to unprecedented levels by (1) nearly doubling the current maximum gradient strength from 300 mT/m to 500 mT/m and tripling the maximum slew rate from 200 T/m/s to 600 T/m/s through the design of a one-of-a-kind head gradient coil optimized to minimize peripheral nerve stimulation; (2) developing high-sensitivity multi-channel radiofrequency receive coils for in vivo and ex vivo human brain imaging; (3) incorporating dynamic field monitoring to minimize image distortions and artifacts; (4) developing new pulse sequences to integrate the strongest diffusion encoding and highest spatial resolution ever achieved in the living human brain; and (5) calibrating the measurements obtained from this next-generation instrument through systematic validation of diffusion microstructural metrics in high-fidelity phantoms and ex vivo brain tissue at progressively finer scales with accompanying diffusion simulations in histology-based micro-geometries. We envision creating the ultimate diffusion MRI instrument capable of capturing the complex multi-scale organization of the living human brain - from the microscopic scale needed to probe cellular geometry, heterogeneity and plasticity, to the mesoscopic scale for quantifying the distinctions in cortical structure and connectivity that define cyto- and myeloarchitectonic boundaries, to improvements in estimates of macroscopic connectivity.
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Affiliation(s)
- Susie Y Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | | | - Boris Keil
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany
| | - Alina Scholz
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany
| | - Mathias Davids
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | | | | | - John E Kirsch
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Qiuyun Fan
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Qiyuan Tian
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Gabriel Ramos-Llordén
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Hong-Hsi Lee
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Aapo Nummenmaa
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Kawin Setsompop
- Radiological Sciences Laboratory, Department of Radiology, Stanford University, Stanford, CA, USA
| | - Fuyixue Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Alexandru V Avram
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Michal Komlosh
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Dan Benjamini
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Kulam Najmudeen Magdoom
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Sudhir Pathak
- Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Walter Schneider
- Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Dmitry S Novikov
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY, USA
| | - Els Fieremans
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY, USA
| | - Slimane Tounekti
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Choukri Mekkaoui
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jean Augustinack
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Daniel Berger
- Department of Molecular and Cell Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Alexander Shapson-Coe
- Department of Molecular and Cell Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Jeff Lichtman
- Department of Molecular and Cell Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Peter J Basser
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Bruce R Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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14
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Wang S, Varray F, Liu W, Clarysse P, Magnin IE. Measurement of local orientation of cardiomyocyte aggregates in human left ventricle free wall samples using X-ray phase-contrast microtomography. Med Image Anal 2021; 75:102269. [PMID: 34775279 DOI: 10.1016/j.media.2021.102269] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 10/10/2021] [Accepted: 10/12/2021] [Indexed: 12/27/2022]
Abstract
Most cardiomyocytes in the left ventricle wall are grouped in aggregates of four to five units that are quasi-parallel to each other. When one or more "cardiomyocyte aggregates" are delimited by two cleavage planes, this defines a "sheetlet" that can be considered as a "work unit" that contributes to the thickening of the wall during the cardiac cycle. In this paper, we introduce the skeleton method to measure the local three-dimensional (3D) orientation of cardiomyocyte aggregates in the sheetlets in three steps: data segmentation; extraction of the skeleton of the sheetlets; and calculation of the local orientation of the cardiomyocyte aggregates inside the sheetlets. These data include a series of virtual tissue volumes and five transmural human left ventricle free wall samples, imaged with 3D synchrotron radiation phase-contrast microtomography, and reconstructed with a 3.5×3.5×3.5μm3 voxel size. We computed the local orientation of the cardiomyocyte aggregates inside the sheetlets with a working window of 112×112×112μm3 in size. These data demonstrate that the skeleton method can provide accurate 3D measurements and reliable screening of the 3D evolution of the orientation of cardiomyocyte aggregates within the sheetlets. We showed that in regions that contain one population of quasi-parallel sheetlets, the orientation of the cardiomyocyte aggregates undergo "oscillations" along the perpendicular direction of the sheetlets. In regions that contain two populations of sheetlets with a different angular range, we demonstrate some discontinuity of the helix angle of the cardiomyocyte aggregates at the interface between the two populations.
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Affiliation(s)
- Shunli Wang
- School of Instrumentation Science and Engineering, Harbin Institute of Technology (HIT), Harbin 150001, China; Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, CNRS, Inserm, CREATIS UMR 5220, U1294, F-69621, Lyon, France.
| | - François Varray
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, CNRS, Inserm, CREATIS UMR 5220, U1294, F-69621, Lyon, France.
| | - Wanyu Liu
- Sino European School of Technology, Shanghai University, Shanghai 200444, China.
| | - Patrick Clarysse
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, CNRS, Inserm, CREATIS UMR 5220, U1294, F-69621, Lyon, France.
| | - Isabelle E Magnin
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, CNRS, Inserm, CREATIS UMR 5220, U1294, F-69621, Lyon, France.
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15
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Das A, Kelly C, Teh I, Nguyen C, Brown LAE, Chowdhary A, Jex N, Thirunavukarasu S, Sharrack N, Gorecka M, Swoboda PP, Greenwood JP, Kellman P, Moon JC, Davies RH, Lopes LR, Joy G, Plein S, Schneider JE, Dall'Armellina E. Phenotyping hypertrophic cardiomyopathy using cardiac diffusion magnetic resonance imaging: the relationship between microvascular dysfunction and microstructural changes. Eur Heart J Cardiovasc Imaging 2021; 23:352-362. [PMID: 34694365 PMCID: PMC8863073 DOI: 10.1093/ehjci/jeab210] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 10/16/2021] [Indexed: 01/05/2023] Open
Abstract
Aims Microvascular dysfunction in hypertrophic cardiomyopathy (HCM) is predictive of clinical decline, however underlying mechanisms remain unclear. Cardiac diffusion tensor imaging (cDTI) allows in vivo characterization of myocardial microstructure by quantifying mean diffusivity (MD), fractional anisotropy (FA) of diffusion, and secondary eigenvector angle (E2A). In this cardiac magnetic resonance (CMR) study, we examine associations between perfusion and cDTI parameters to understand the sequence of pathophysiology and the interrelation between vascular function and underlying microstructure. Methods and results Twenty HCM patients underwent 3.0T CMR which included: spin-echo cDTI, adenosine stress and rest perfusion mapping, cine-imaging, and late gadolinium enhancement (LGE). Ten controls underwent cDTI. Myocardial perfusion reserve (MPR), MD, FA, E2A, and wall thickness were calculated per segment and further divided into subendocardial (inner 50%) and subepicardial (outer 50%) regions. Segments with wall thickness ≤11 mm, MPR ≥2.2, and no visual LGE were classified as ‘normal’. Compared to controls, ‘normal’ HCM segments had increased MD (1.61 ± 0.09 vs. 1.46 ± 0.07 × 10−3 mm2/s, P = 0.02), increased E2A (60 ± 9° vs. 38 ± 12°, P < 0.001), and decreased FA (0.29 ± 0.04 vs. 0.35 ± 0.02, P = 0.002). Across all HCM segments, subendocardial regions had higher MD and lower MPR than subepicardial (MDendo 1.61 ± 0.08 × 10−3 mm2/s vs. MDepi 1.56 ± 0.18 × 10−3 mm2/s, P = 0.003, MPRendo 1.85 ± 0.83, MPRepi 2.28 ± 0.87, P < 0.0001). Conclusion In HCM patients, even in segments with normal wall thickness, normal perfusion, and no scar, diffusion is more isotropic than in controls, suggesting the presence of underlying cardiomyocyte disarray. Increased E2A suggests the myocardial sheetlets adopt hypercontracted angulation in systole. Increased MD, most notably in the subendocardium, is suggestive of regional remodelling which may explain the reduced subendocardial blood flow.
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Affiliation(s)
- Arka Das
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Christopher Kelly
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Irvin Teh
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Christopher Nguyen
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, 55 Fruit St, Boston, MA 02114, USA.,A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, 55 Fruit St, Boston, MA 02114, USA.,Department of Medicine, Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA.,Biomedical Imaging Research Institute, Cedars-Sinai Medical Centre, 116 N Robertson Blvd, Los Angeles, CA 90048, USA
| | - Louise A E Brown
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Amrit Chowdhary
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Nicholas Jex
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Sharmaine Thirunavukarasu
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Noor Sharrack
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Miroslawa Gorecka
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Peter P Swoboda
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - John P Greenwood
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Peter Kellman
- National Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, 31 Center Dr, Bethesda, MD 20892, USA
| | - James C Moon
- Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London EC1A 7BE, UK
| | - Rhodri H Davies
- Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London EC1A 7BE, UK
| | - Luis R Lopes
- Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London EC1A 7BE, UK.,Centre for Heart Muscle Disease, Institute of Cardiovascular Science, University College London, Gower St, London WC1E 6BT, UK
| | - George Joy
- Barts Heart Centre, The Cardiovascular Magnetic Resonance Imaging Unit and The Inherited Cardiovascular Diseases Unit, St Bartholomew's Hospital, West Smithfield, London EC1A 7BE, UK
| | - Sven Plein
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Jürgen E Schneider
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
| | - Erica Dall'Armellina
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9JT, UK
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Bi X, Zhang S, Jiang H, Wei Z. A Multi-Scale Computational Model for the Rat Ventricle: Construction, Parallelization, and Applications. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 208:106289. [PMID: 34303152 DOI: 10.1016/j.cmpb.2021.106289] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 07/10/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Cardiovascular diseases are the top killer of human beings. The ventricular arrhythmia, as a type of malignant cardiac arrhythmias, typically leads to death if not treated within minutes. The multi-scale virtual heart provides an idealized tool for exploring the underlying mechanisms, by means of incorporating abundant experimental data at the level of ion channels and analyzing the subsequent pathological changes at organ levels. However, there are few studies on building a virtual heart model for rats-a species most widely used in experiments. OBJECTIVE To build a multi-scale computational model for rats, with detailed methodology for the model construction, computational optimization, and its applications. METHODS First, approaches for building multi-scale models ranging from cellular to 3-D organ levels are introduced, with detailed descriptions of handling the ventricular myocardium heterogeneity, geometry processing, and boundary conditions, etc. Next, for dealing with the expensive computational costs of 3-D models, optimization approaches including an optimized representation and a GPU-based parallelization method are introduced. Finally, methods for reproducing of some key phenomenon (e.g., electrocardiograph, spiral/scroll waves) are demonstrated. RESULTS Three types of heterogeneity, including the transmural heterogeneity, the interventricular heterogeneity, and the base-apex heterogeneity are incorporated into the model. The normal and reentrant excitation waves, as well as the corresponding pseudo-ECGs are reproduced by the constructed ventricle model. In addition, the temporal and spatial vulnerability to reentry arrhythmias are quantified based on the evaluation experiments of vulnerable window and the critical length. CONCLUSIONS The constructed multi-scale rat ventricle model is able to reproduce both the physiological and the pathological phenomenon in different scales. Evaluation experiments suggest that the apex is the most susceptible area to arrhythmias. The model can be a promising tool for the investigation of arrhythmogenesis and the screening of anti-arrhythmic drugs.
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Affiliation(s)
- Xiangpeng Bi
- College of Computer Science and Technology, Ocean University of China, Qingdao 266100, China
| | - Shugang Zhang
- College of Computer Science and Technology, Ocean University of China, Qingdao 266100, China; High Performance Computing Center, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266237, China.
| | - Huasen Jiang
- College of Computer Science and Technology, Ocean University of China, Qingdao 266100, China
| | - Zhiqiang Wei
- College of Computer Science and Technology, Ocean University of China, Qingdao 266100, China; High Performance Computing Center, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266237, China
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Martonová D, Alkassar M, Seufert J, Holz D, Dương MT, Reischl B, Friedrich O, Leyendecker S. Passive mechanical properties in healthy and infarcted rat left ventricle characterised via a mixture model. J Mech Behav Biomed Mater 2021; 119:104430. [PMID: 33780851 DOI: 10.1016/j.jmbbm.2021.104430] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 02/21/2021] [Accepted: 02/22/2021] [Indexed: 11/29/2022]
Abstract
During the cardiac cycle, electrical excitation is coupled with mechanical response of the myocardium. Besides the active contraction, passive mechanics plays an important role, and its behaviour differs in healthy and diseased hearts as well as among different animal species. The aim of this study is the characterisation of passive mechanical properties in healthy and infarcted rat myocardium by means of mechanical testing and subsequent parameter fitting. Elasticity assessments via uniaxial extension tests are performed on healthy and infarcted tissue samples from left ventricular rat myocardium. In order to fully characterise the orthotropic cardiac tissue, our experimental data are combined with other previously published tests in rats - shear tests on healthy myocardium and equibiaxial tests on infarcted tissue. In a first step, we calibrate the Holzapfel-Ogden strain energy function in the healthy case. Sa far, this orthotropic constitutive law for the passive myocardium has been fitted to experimental data in several species, however there is a lack of an appropriate parameter set for the rat. With our determined parameters, a finite element simulation of the end-diastolic filling is performed. In a second step, we propose a model for the infarcted tissue. It is represented as a mixture of intact myocardium and a transversely isotropic scar structure. In our mechanical experiments, the tissue after myocardial infarction shows significantly stiffer behaviour than in the healthy case, and the stiffness correlates with the amount of fibrosis. A similar relationship is observed in the computational simulation of the end-diastolic filling. We conclude that our new proposed material model can capture the behaviour of two kinds of tissues - healthy and infarcted rat myocardium, and its calibration with the fitted parameters represents the experimental data well.
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Affiliation(s)
- Denisa Martonová
- Friedrich-Alexander-Universität Erlangen-Nürnberg, Institute of Applied Dynamics, Immerwahrstraße 1, 91058 Erlangen, Germany.
| | - Muhannad Alkassar
- Friedrich-Alexander-Universität Erlangen-Nürnberg, Pediatric Cardiology, Loschgestraße 15, 91054 Erlangen, Germany
| | - Julia Seufert
- Friedrich-Alexander-Universität Erlangen-Nürnberg, Pediatric Cardiology, Loschgestraße 15, 91054 Erlangen, Germany
| | - David Holz
- Friedrich-Alexander-Universität Erlangen-Nürnberg, Institute of Applied Dynamics, Immerwahrstraße 1, 91058 Erlangen, Germany
| | - Minh Tuấn Dương
- Friedrich-Alexander-Universität Erlangen-Nürnberg, Institute of Applied Dynamics, Immerwahrstraße 1, 91058 Erlangen, Germany; School of Mechanical Engineering, Hanoi University of Science and Technology, 1 DaiCoViet Road, Hanoi, Vietnam
| | - Barbara Reischl
- Friedrich-Alexander-Universität Erlangen-Nürnberg, Institute of Medical Biotechnology, Paul-Gordan-Str. 3, 91052 Erlangen, Germany
| | - Oliver Friedrich
- Friedrich-Alexander-Universität Erlangen-Nürnberg, Institute of Medical Biotechnology, Paul-Gordan-Str. 3, 91052 Erlangen, Germany
| | - Sigrid Leyendecker
- Friedrich-Alexander-Universität Erlangen-Nürnberg, Institute of Applied Dynamics, Immerwahrstraße 1, 91058 Erlangen, Germany
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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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Das A, Kelly C, Teh I, Stoeck CT, Kozerke S, Chowdhary A, Brown LAE, Saunderson CED, Craven TP, Chew PG, Jex N, Swoboda PP, Levelt E, Greenwood JP, Schneider JE, Plein S, Dall'Armellina E. Acute Microstructural Changes after ST-Segment Elevation Myocardial Infarction Assessed with Diffusion Tensor Imaging. Radiology 2021; 299:86-96. [PMID: 33560187 DOI: 10.1148/radiol.2021203208] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Background Cardiac diffusion tensor imaging (cDTI) allows for in vivo characterization of myocardial microstructure. In cDTI, mean diffusivity and fractional anisotropy (FA)-markers of magnitude and anisotropy of diffusion of water molecules-are known to change after myocardial infarction. However, little is known about regional changes in helix angle (HA) and secondary eigenvector angle (E2A), which reflects orientations of laminar sheetlets, and their association with long-term recovery of left ventricular ejection fraction (LVEF). Purpose To assess serial changes in cDTI biomarkers in participants following ST-segment elevation myocardial infarction (STEMI) and to determine their associations with long-term left ventricular remodeling. Materials and Methods In this prospective study, 30 participants underwent cardiac MRI (3 T) after STEMI at 5 days and 3 months after reperfusion (National Institute of Health Research study no. 33963 and Research Ethics no. REC17/YH/0062). Spin-echo cDTI with second-order motion-compensation (approximate duration, 13 minutes; three sections; 18 noncollinear diffusion-weighted scans with b values of 100 sec/mm2 [three acquisitions], 200 sec/mm2 [three acquisitions], and 500 sec/mm2 [12 acquisitions]), functional images, and late gadolinium enhancement images were obtained. Multiple regression analysis was used to assess associations between acute cDTI parameters and 3-month LVEF. Results Acutely infarcted myocardium had reduced FA, E2A, and myocytes with right-handed orientation (RHM) on HA maps compared with remote myocardium (mean remote FA = 0.36 ± 0.02 [standard deviation], mean infarcted FA = 0.25 ± 0.03, P < .001; mean remote E2A = 55° ± 9, mean infarcted E2A = 49° ± 10, P < .001; mean remote RHM = 16% ± 6, mean infarcted RHM = 9% ± 5, P < .001). All three parameters (FA, E2A, and RHM) correlated with 3-month LVEF (r = 0.68, r = 0.59, and r = 0.53, respectively), with acute FA being independently predictive of 3-month LVEF (standardized β = 0.56, P = .008) after multivariable analysis adjusting for factors, including acute LVEF and infarct size. Conclusion After ST-segment elevation myocardial infarction, diffusion becomes more isotropic in acutely infarcted myocardium as reflected by decreased fractional anisotropy. Reductions in secondary eigenvector angle suggest that the myocardial sheetlets are unable to adopt their usual steep orientations in systole, whereas reductions in myocytes with right-handed orientation on helix angle maps are likely reflective of a loss of organization among subendocardial myocytes. Correlations between these parameters and 3-month left ventricular ejection fraction highlight the potential clinical use of cardiac diffusion tensor imaging after myocardial infarction in predicting long-term remodeling. © RSNA, 2021 Online supplemental material is available for this article.
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Affiliation(s)
- Arka Das
- From the Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, and Leeds Teaching Hospitals NHS Trust, Clarendon, Way, Leeds LS2 9JT, England (A.D., C.K., I.T., A.C., L.A.E.B., C.E.D.S., T.P.C., P.G.C., N.J., P.P.S., E.L., J.P.G., J.E.S., S.P., E.D.); and Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland (C.T.S., S.K.)
| | - Christopher Kelly
- From the Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, and Leeds Teaching Hospitals NHS Trust, Clarendon, Way, Leeds LS2 9JT, England (A.D., C.K., I.T., A.C., L.A.E.B., C.E.D.S., T.P.C., P.G.C., N.J., P.P.S., E.L., J.P.G., J.E.S., S.P., E.D.); and Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland (C.T.S., S.K.)
| | - Irvin Teh
- From the Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, and Leeds Teaching Hospitals NHS Trust, Clarendon, Way, Leeds LS2 9JT, England (A.D., C.K., I.T., A.C., L.A.E.B., C.E.D.S., T.P.C., P.G.C., N.J., P.P.S., E.L., J.P.G., J.E.S., S.P., E.D.); and Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland (C.T.S., S.K.)
| | - Christian T Stoeck
- From the Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, and Leeds Teaching Hospitals NHS Trust, Clarendon, Way, Leeds LS2 9JT, England (A.D., C.K., I.T., A.C., L.A.E.B., C.E.D.S., T.P.C., P.G.C., N.J., P.P.S., E.L., J.P.G., J.E.S., S.P., E.D.); and Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland (C.T.S., S.K.)
| | - Sebastian Kozerke
- From the Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, and Leeds Teaching Hospitals NHS Trust, Clarendon, Way, Leeds LS2 9JT, England (A.D., C.K., I.T., A.C., L.A.E.B., C.E.D.S., T.P.C., P.G.C., N.J., P.P.S., E.L., J.P.G., J.E.S., S.P., E.D.); and Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland (C.T.S., S.K.)
| | - Amrit Chowdhary
- From the Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, and Leeds Teaching Hospitals NHS Trust, Clarendon, Way, Leeds LS2 9JT, England (A.D., C.K., I.T., A.C., L.A.E.B., C.E.D.S., T.P.C., P.G.C., N.J., P.P.S., E.L., J.P.G., J.E.S., S.P., E.D.); and Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland (C.T.S., S.K.)
| | - Louise A E Brown
- From the Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, and Leeds Teaching Hospitals NHS Trust, Clarendon, Way, Leeds LS2 9JT, England (A.D., C.K., I.T., A.C., L.A.E.B., C.E.D.S., T.P.C., P.G.C., N.J., P.P.S., E.L., J.P.G., J.E.S., S.P., E.D.); and Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland (C.T.S., S.K.)
| | - Christopher E D Saunderson
- From the Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, and Leeds Teaching Hospitals NHS Trust, Clarendon, Way, Leeds LS2 9JT, England (A.D., C.K., I.T., A.C., L.A.E.B., C.E.D.S., T.P.C., P.G.C., N.J., P.P.S., E.L., J.P.G., J.E.S., S.P., E.D.); and Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland (C.T.S., S.K.)
| | - Thomas P Craven
- From the Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, and Leeds Teaching Hospitals NHS Trust, Clarendon, Way, Leeds LS2 9JT, England (A.D., C.K., I.T., A.C., L.A.E.B., C.E.D.S., T.P.C., P.G.C., N.J., P.P.S., E.L., J.P.G., J.E.S., S.P., E.D.); and Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland (C.T.S., S.K.)
| | - Pei G Chew
- From the Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, and Leeds Teaching Hospitals NHS Trust, Clarendon, Way, Leeds LS2 9JT, England (A.D., C.K., I.T., A.C., L.A.E.B., C.E.D.S., T.P.C., P.G.C., N.J., P.P.S., E.L., J.P.G., J.E.S., S.P., E.D.); and Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland (C.T.S., S.K.)
| | - Nicholas Jex
- From the Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, and Leeds Teaching Hospitals NHS Trust, Clarendon, Way, Leeds LS2 9JT, England (A.D., C.K., I.T., A.C., L.A.E.B., C.E.D.S., T.P.C., P.G.C., N.J., P.P.S., E.L., J.P.G., J.E.S., S.P., E.D.); and Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland (C.T.S., S.K.)
| | - Peter P Swoboda
- From the Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, and Leeds Teaching Hospitals NHS Trust, Clarendon, Way, Leeds LS2 9JT, England (A.D., C.K., I.T., A.C., L.A.E.B., C.E.D.S., T.P.C., P.G.C., N.J., P.P.S., E.L., J.P.G., J.E.S., S.P., E.D.); and Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland (C.T.S., S.K.)
| | - Eylem Levelt
- From the Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, and Leeds Teaching Hospitals NHS Trust, Clarendon, Way, Leeds LS2 9JT, England (A.D., C.K., I.T., A.C., L.A.E.B., C.E.D.S., T.P.C., P.G.C., N.J., P.P.S., E.L., J.P.G., J.E.S., S.P., E.D.); and Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland (C.T.S., S.K.)
| | - John P Greenwood
- From the Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, and Leeds Teaching Hospitals NHS Trust, Clarendon, Way, Leeds LS2 9JT, England (A.D., C.K., I.T., A.C., L.A.E.B., C.E.D.S., T.P.C., P.G.C., N.J., P.P.S., E.L., J.P.G., J.E.S., S.P., E.D.); and Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland (C.T.S., S.K.)
| | - Jurgen E Schneider
- From the Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, and Leeds Teaching Hospitals NHS Trust, Clarendon, Way, Leeds LS2 9JT, England (A.D., C.K., I.T., A.C., L.A.E.B., C.E.D.S., T.P.C., P.G.C., N.J., P.P.S., E.L., J.P.G., J.E.S., S.P., E.D.); and Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland (C.T.S., S.K.)
| | - Sven Plein
- From the Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, and Leeds Teaching Hospitals NHS Trust, Clarendon, Way, Leeds LS2 9JT, England (A.D., C.K., I.T., A.C., L.A.E.B., C.E.D.S., T.P.C., P.G.C., N.J., P.P.S., E.L., J.P.G., J.E.S., S.P., E.D.); and Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland (C.T.S., S.K.)
| | - Erica Dall'Armellina
- From the Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, and Leeds Teaching Hospitals NHS Trust, Clarendon, Way, Leeds LS2 9JT, England (A.D., C.K., I.T., A.C., L.A.E.B., C.E.D.S., T.P.C., P.G.C., N.J., P.P.S., E.L., J.P.G., J.E.S., S.P., E.D.); and Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland (C.T.S., S.K.)
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Espino-Gonzalez E, Tickle PG, Benson AP, Kissane RWP, Askew GN, Egginton S, Bowen TS. Abnormal skeletal muscle blood flow, contractile mechanics and fibre morphology in a rat model of obese-HFpEF. J Physiol 2021; 599:981-1001. [PMID: 33347612 PMCID: PMC7898698 DOI: 10.1113/jp280899] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Accepted: 12/04/2020] [Indexed: 12/18/2022] Open
Abstract
KEY POINTS Heart failure is characterised by limb and respiratory muscle impairments that limit functional capacity and quality of life. However, compared with heart failure with reduced ejection fraction (HFrEF), skeletal muscle alterations induced by heart failure with preserved ejection fraction (HFpEF) remain poorly explored. Here we report that obese-HFpEF induces multiple skeletal muscle alterations in the rat hindlimb, including impaired muscle mechanics related to shortening velocity, fibre atrophy, capillary loss, and an impaired blood flow response to contractions that implies a perfusive oxygen delivery limitation. We also demonstrate that obese-HFpEF is characterised by diaphragmatic alterations similar to those caused by denervation - atrophy in Type IIb/IIx (fast/glycolytic) fibres and hypertrophy in Type I (slow/oxidative) fibres. These findings extend current knowledge in HFpEF skeletal muscle physiology, potentially underlying exercise intolerance, which may facilitate future therapeutic approaches. ABSTRACT Peripheral skeletal muscle and vascular alterations induced by heart failure with preserved ejection fraction (HFpEF) remain poorly identified, with limited therapeutic targets. This study used a cardiometabolic obese-HFpEF rat model to comprehensively phenotype skeletal muscle mechanics, blood flow, microvasculature and fibre atrophy. Lean (n = 8) and obese-HFpEF (n = 8) ZSF1 rats were compared. Skeletal muscles (soleus and diaphragm) were assessed for in vitro contractility (isometric and isotonic properties) alongside indices of fibre-type cross-sectional area, myosin isoform, and capillarity, and estimated muscle PO2 . In situ extensor digitorum longus (EDL) contractility and femoral blood flow were assessed. HFpEF soleus demonstrated lower absolute maximal force by 22%, fibre atrophy by 24%, a fibre-type shift from I to IIa, and a 17% lower capillary-to-fibre ratio despite increased capillary density (all P < 0.05) with preserved muscle PO2 (P = 0.115) and isometric specific force (P > 0.05). Soleus isotonic properties (shortening velocity and power) were impaired by up to 17 and 22%, respectively (P < 0.05), while the magnitude of the exercise hyperaemia was attenuated by 73% (P = 0.012) in line with higher muscle fatigue by 26% (P = 0.079). Diaphragm alterations (P < 0.05) included Type IIx fibre atrophy despite Type I/IIa fibre hypertrophy, with increased indices of capillarity alongside preserved contractile properties during isometric, isotonic, and cyclical contractions. In conclusion, obese-HFpEF rats demonstrated blunted skeletal muscle blood flow during contractions in parallel to microvascular structural remodelling, fibre atrophy, and isotonic contractile dysfunction in the locomotor muscles. In contrast, diaphragm phenotype remained well preserved. This study identifies numerous muscle-specific impairments that could exacerbate exercise intolerance in obese-HFpEF.
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Affiliation(s)
- Ever Espino-Gonzalez
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Peter G Tickle
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Alan P Benson
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Roger W P Kissane
- Department of Musculoskeletal & Ageing Science, University of Liverpool, Liverpool, UK
| | - Graham N Askew
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - Stuart Egginton
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, UK
| | - T Scott Bowen
- School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds, UK
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21
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Das A, Chowdhary A, Kelly C, Teh I, Stoeck CT, Kozerke S, Maxwell N, Craven TP, Jex NJ, Saunderson CED, Brown LAE, Ben-Arzi H, Sengupta A, Page SP, Swoboda PP, Greenwood JP, Schneider JE, Plein S, Dall'Armellina E. Insight Into Myocardial Microstructure of Athletes and Hypertrophic Cardiomyopathy Patients Using Diffusion Tensor Imaging. J Magn Reson Imaging 2021; 53:73-82. [PMID: 32558016 DOI: 10.1002/jmri.27257] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 05/28/2020] [Accepted: 05/28/2020] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Hypertrophic cardiomyopathy (HCM) remains the commonest cause of sudden cardiac death among young athletes. Differentiating between physiologically adaptive left ventricular (LV) hypertrophy observed in athletes' hearts and pathological HCM remains challenging. By quantifying the diffusion of water molecules, diffusion tensor imaging (DTI) MRI allows voxelwise characterization of myocardial microstructure. PURPOSE To explore microstructural differences between healthy volunteers, athletes, and HCM patients using DTI. STUDY TYPE Prospective cohort. POPULATION Twenty healthy volunteers, 20 athletes, and 20 HCM patients. FIELD STRENGTH/SEQUENCE 3T/DTI spin echo. ASSESSMENT In-house MatLab software was used to derive mean diffusivity (MD) and fractional anisotropy (FA) as markers of amplitude and anisotropy of the diffusion of water molecules, and secondary eigenvector angles (E2A)-reflecting the orientations of laminar sheetlets. STATISTICAL TESTS Independent samples t-tests were used to detect statistical significance between any two cohorts. Analysis of variance was utilized for detecting the statistical difference between the three cohorts. Statistical tests were two-tailed. A result was considered statistically significant at P ≤ 0.05. RESULTS DTI markers were significantly different between HCM, athletes, and volunteers. HCM patients had significantly higher global MD and E2A, and significantly lower FA than athletes and volunteers. (MDHCM = 1.52 ± 0.06 × 10-3 mm2 /s, MDAthletes = 1.49 ± 0.03 × 10-3 mm2 /s, MDvolunteers = 1.47 ± 0.02 × 10-3 mm2 /s, P < 0.05; E2AHCM = 58.8 ± 4°, E2Aathletes = 47 ± 5°, E2Avolunteers = 38.5 ± 7°, P < 0.05; FAHCM = 0.30 ± 0.02, FAAthletes = 0.35 ± 0.02, FAvolunteers = 0.36 ± 0.03, P < 0.05). HCM patients had significantly higher E2A in their thickest segments compared to the remote (E2Athickest = 66.8 ± 7, E2Aremote = 51.2 ± 9, P < 0.05). DATA CONCLUSION DTI depicts an increase in amplitude and isotropy of diffusion in the myocardium of HCM compared to athletes and volunteers as reflected by increased MD and decreased FA values. While significantly higher E2A values in HCM and athletes reflect steeper configurations of the myocardial sheetlets than in volunteers, HCM patients demonstrated an eccentric rise in E2A in their thickest segments, while athletes demonstrated a concentric rise. Further studies are required to determine the diagnostic capabilities of DTI. EVIDENCE LEVEL 1 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Arka Das
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Amrit Chowdhary
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Chris Kelly
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Irvin Teh
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Christian T Stoeck
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Nicholas Maxwell
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Thomas P Craven
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Nicholas J Jex
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Christopher E D Saunderson
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Louise A E Brown
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Hadar Ben-Arzi
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Anshuman Sengupta
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Stephen P Page
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Peter P Swoboda
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - John P Greenwood
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Jurgen E Schneider
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Sven Plein
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Erica Dall'Armellina
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, Leeds Teaching Hospitals NHS Trust, Leeds, UK
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22
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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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23
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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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24
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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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25
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Carruth ED, Teh I, Schneider JE, McCulloch AD, Omens JH, Frank LR. Regional variations in ex-vivo diffusion tensor anisotropy are associated with cardiomyocyte remodeling in rats after left ventricular pressure overload. J Cardiovasc Magn Reson 2020; 22:21. [PMID: 32241289 PMCID: PMC7114814 DOI: 10.1186/s12968-020-00615-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 03/05/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Pressure overload left ventricular (LV) hypertrophy is characterized by increased cardiomyocyte width and ventricle wall thickness, however the regional variation of this remodeling is unclear. Cardiovascular magnetic resonance (CMR) diffusion tensor imaging (DTI) may provide a non-invasive, comprehensive, and geometrically accurate method to detect regional differences in structural remodeling in hypertrophy. We hypothesized that DTI parameters, such as fractional and planar anisotropy, would reflect myocyte remodeling due to pressure overload in a regionally-dependent manner. METHODS We investigated the regional distributions of myocyte remodeling in rats with or without transverse aortic constriction (TAC) via direct measurement of myocyte dimensions with confocal imaging of thick tissue sections, and correlated myocyte cross-sectional area and other geometric features with parameters of diffusivity from ex-vivo DTI in the same regions of the same hearts. RESULTS We observed regional differences in several parameters from DTI between TAC hearts and SHAM controls. Consistent with previous studies, helix angles from DTI correlated strongly with those measured directly from histological sections (p < 0.001, R2 = 0.71). There was a transmural gradient in myocyte cross-sectional area in SHAM hearts that was diminished in the TAC group. We also found several regions of significantly altered DTI parameters in TAC LV compared to SHAM, especially in myocyte sheet angle dispersion and planar anisotropy. Among others, these parameters correlated significantly with directly measured myocyte aspect ratios. CONCLUSIONS These results show that structural remodeling in pressure overload LV hypertrophy is regionally heterogeneous, especially transmurally, with a greater degree of remodeling in the sub-endocardium compared to the sub-epicardium. Additionally, several parameters derived from DTI correlated significantly with measurements of myocyte geometry from direct measurement in histological sections. We suggest that DTI may provide a non-invasive, comprehensive method to detect regional structural myocyte LV remodeling during disease.
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Affiliation(s)
- Eric D Carruth
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
| | - Irvin Teh
- Leeds Institute of Cardiovascular & Metabolic Medicine, University of Leeds, Leeds, UK
| | - Jurgen E Schneider
- Leeds Institute of Cardiovascular & Metabolic Medicine, University of Leeds, Leeds, UK
| | - Andrew D McCulloch
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
| | - Jeffrey H Omens
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA.
- Department of Medicine, University of California San Diego, La Jolla, California, USA.
| | - Lawrence R Frank
- Department of Radiology, University of California San Diego, La Jolla, California, USA
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26
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Giannakidis A, Gullberg GT. Transmural Remodeling of Cardiac Microstructure in Aged Spontaneously Hypertensive Rats by Diffusion Tensor MRI. Front Physiol 2020; 11:265. [PMID: 32296341 PMCID: PMC7136532 DOI: 10.3389/fphys.2020.00265] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Accepted: 03/09/2020] [Indexed: 11/16/2022] Open
Abstract
The long-standing high blood pressure (also known as hypertension) overworks the heart. Microstructural remodeling is a key factor of hypertensive heart disease progression. Diffusion tensor magnetic resonance imaging (DT-MRI) is a powerful tool for the rapid noninvasive nondestructive delineation of the cardiomyocyte organization. The spontaneously hypertensive rat (SHR) is a well-established model of genetic hypertension. The goal of this study was to employ high-resolution DT-MRI and the SHR animal model to assess the transmural layer-specific remodeling of myocardial microstructure associated with hypertension. Ex vivo experiments were performed on excised formalin-fixed hearts of aged SHRs (n = 4) and age-matched controls (n = 4). The DT-MRI-derived fractional anisotropy (FA), longitudinal diffusivity (λL), transversal diffusivity (λT), and mean diffusivity (MD) served as the readout parameters investigated at three transmural zones (i.e., endocardium, mesocardium, and epicardium). The helix angles (HAs) of the aggregated cardiomyocytes and the orientation of laminar sheetlets were also studied. Compared with controls, the SHRs exhibited decreased epicardial FA, while FA changes in the other two transmural regions were insignificant. No substantial differences were observed in the diffusivity parameters and the transmural course of HAs between the two groups. A consistent distribution pattern of laminar sheetlet orientation was not identified for either group. Our findings are in line with the known cellular microstructure from early painstaking histological studies. Biophysical explanations of the study outcomes are provided. In conclusion, our experimental findings indicate that the epicardial microstructure is more vulnerable to high blood pressure leading to more pronounced changes in this region during remodeling. DT-MRI is well-suited for elucidating these alterations. The revealed transmural nonuniformity of myocardial reorganization may shed light on the mechanisms of the microstructure-function relationship in hypertension progression. Our results provide insights into the management of patients with systemic arterial hypertension, thus prevent the progression toward heart failure. The findings of this study should be acknowledged by electromechanical models of the heart that simulate the specific cardiac pathology.
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Affiliation(s)
- Archontis Giannakidis
- School of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom.,Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States.,National Heart & Lung Institute, Imperial College London, London, United Kingdom
| | - Grant T Gullberg
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States.,Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
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27
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Teh I, McClymont D, Carruth E, Omens J, McCulloch A, Schneider JE. Improved compressed sensing and super-resolution of cardiac diffusion MRI with structure-guided total variation. Magn Reson Med 2020; 84:1868-1880. [PMID: 32125040 PMCID: PMC8629124 DOI: 10.1002/mrm.28245] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 02/12/2020] [Accepted: 02/13/2020] [Indexed: 12/14/2022]
Abstract
Purpose Structure‐guided total variation is a recently introduced prior that allows reconstruction of images using knowledge of the location and orientation of edges in a reference image. In this work, we demonstrate the advantages of a variant of structure‐guided total variation known as directional total variation (DTV), over traditional total variation (TV), in the context of compressed‐sensing reconstruction and super‐resolution. Methods We compared TV and DTV in retrospectively undersampled ex vivo diffusion tensor imaging and diffusion spectrum imaging data from healthy, sham, and hypertrophic rat hearts. Results In compressed sensing at an undersampling factor of 8, the RMS error of mean diffusivity and fractional anisotropy relative to the fully sampled ground truth were 44% and 20% lower in DTV compared with TV. In super‐resolution, these values were 29% and 14%, respectively. Similarly, we observed improvements in helix angle, transverse angle, sheetlet elevation, and sheetlet azimuth. The RMS error of the diffusion kurtosis in the undersampled data relative to the ground truth was uniformly lower (22% on average) with DTV compared to TV. Conclusion Acquiring one fully sampled non‐diffusion‐weighted image and 10 diffusion‐weighted images at 8× undersampling would result in an 80% net reduction in data needed. We demonstrate efficacy of the DTV algorithm over TV in reducing data sampling requirements, which can be translated into higher apparent resolution and potentially shorter scan times. This method would be equally applicable in diffusion MRI applications outside the heart.
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Affiliation(s)
- Irvin Teh
- Leeds Institute of Cardiovascular & Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | | | | | - Jeffrey Omens
- Department of Medicine, University of California San Diego, La Jolla, California
| | - Andrew McCulloch
- Department of Medicine, University of California San Diego, La Jolla, California.,Department of Bioengineering, University of California San Diego, La Jolla, California
| | - Jürgen E Schneider
- Leeds Institute of Cardiovascular & Metabolic Medicine, University of Leeds, Leeds, United Kingdom
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28
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Investigation of the Role of Myocyte Orientations in Cardiac Arrhythmia Using Image-Based Models. Biophys J 2019; 117:2396-2408. [PMID: 31679763 PMCID: PMC6990390 DOI: 10.1016/j.bpj.2019.09.041] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Revised: 09/13/2019] [Accepted: 09/23/2019] [Indexed: 11/24/2022] Open
Abstract
Cardiac electrical excitation-propagation is influenced by myocyte orientations (cellular organization). Quantitatively understanding this relationship presents a significant research challenge, especially during arrhythmias in which excitation patterns become complex. Tissue-scale simulations of cardiac electrophysiology, incorporating both dynamic action potential behavior and image-based myocardial architecture, provide an approach to investigate three-dimensional (3D) propagation of excitation waves in the heart. In this study, we aimed to assess the importance of natural variation in myocyte orientations on cardiac arrhythmogenesis using 3D tissue electrophysiology simulations. Three anatomical models (i.e., describing myocyte orientations) of healthy rat ventricles—obtained using diffusion tensor imaging at 100 μm resolution—were registered to a single biventricular geometry (i.e., a single cardiac shape), in which the myocyte orientations could be represented by each of the diffusion tensor imaging data sets or by an idealized rule-based description. The Fenton-Karma cellular excitation model was modified to reproduce rat ventricular action potential duration restitution to create reaction-diffusion cardiac electrophysiology models. Over 250 3D simulations were performed to investigate the effects of myocyte orientations on the following: 1) ventricular activation, 2) location-dependent arrhythmia induction via rapid pacing, and 3) dynamics of re-entry averaged over multiple episodes. It was shown that 1) myocyte orientation differences manifested themselves in local activation times, but the influence on total activation time was small; 2) differences in myocyte orientations could critically affect the inducibility and persistence of arrhythmias for specific stimulus-location/cycle-length combinations; and 3) myocyte orientations alone could be an important determinant of scroll wave break, although no significant differences were observed in averaged arrhythmia dynamics between the four myocyte orientation scenarios considered. Our results show that myocyte orientations are an important determinant of arrhythmia inducibility, persistence, and scroll wave break. These findings suggest that where specificity is desired (for example, when predicting location-dependent, patient-specific arrhythmia inducibility), subject-specific myocyte orientations may be important.
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29
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Nielles-Vallespin S, Scott A, Ferreira P, Khalique Z, Pennell D, Firmin D. Cardiac Diffusion: Technique and Practical Applications. J Magn Reson Imaging 2019; 52:348-368. [PMID: 31482620 DOI: 10.1002/jmri.26912] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Revised: 08/13/2019] [Accepted: 08/14/2019] [Indexed: 12/12/2022] Open
Abstract
The 3D microarchitecture of the cardiac muscle underlies the mechanical and electrical properties of the heart. Cardiomyocytes are arranged helically through the depth of the wall, and their shortening leads to macroscopic torsion, twist, and shortening during cardiac contraction. Furthermore, cardiomyocytes are organized in sheetlets separated by shear layers, which reorientate, slip, and shear during macroscopic left ventricle (LV) wall thickening. Cardiac diffusion provides a means for noninvasive interrogation of the 3D microarchitecture of the myocardium. The fundamental principle of MR diffusion is that an MRI signal is attenuated by the self-diffusion of water in the presence of large diffusion-encoding gradients. Since water molecules are constrained by the boundaries in biological tissue (cell membranes, collagen layers, etc.), depicting their diffusion behavior elucidates the shape of the myocardial microarchitecture they are embedded in. Cardiac diffusion therefore provides a noninvasive means to understand not only the dynamic changes in cardiac microstructure of healthy myocardium during cardiac contraction but also the pathophysiological changes in the presence of disease. This unique and innovative technology offers tremendous potential to enable improved clinical diagnosis through novel microstructural and functional assessment. in vivo cardiac diffusion methods are immediately translatable to patients, opening new avenues for diagnostic investigation and treatment evaluation in a range of clinically important cardiac pathologies. This review article describes the 3D microstructure of the LV, explains in vivo and ex vivo cardiac MR diffusion acquisition and postprocessing techniques, as well as clinical applications to date. Level of Evidence: 1 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019. J. Magn. Reson. Imaging 2020;52:348-368.
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Affiliation(s)
- Sonia Nielles-Vallespin
- Cardiovascular MR Unit, Royal Brompton And Harefield NHS Foundation Trust, London, UK.,NHLI, Imperial College of Science, Technology and Medicine, London, UK
| | - Andrew Scott
- Cardiovascular MR Unit, Royal Brompton And Harefield NHS Foundation Trust, London, UK.,NHLI, Imperial College of Science, Technology and Medicine, London, UK
| | - Pedro Ferreira
- Cardiovascular MR Unit, Royal Brompton And Harefield NHS Foundation Trust, London, UK.,NHLI, Imperial College of Science, Technology and Medicine, London, UK
| | - Zohya Khalique
- Cardiovascular MR Unit, Royal Brompton And Harefield NHS Foundation Trust, London, UK.,NHLI, Imperial College of Science, Technology and Medicine, London, UK
| | - Dudley Pennell
- Cardiovascular MR Unit, Royal Brompton And Harefield NHS Foundation Trust, London, UK.,NHLI, Imperial College of Science, Technology and Medicine, London, UK
| | - David Firmin
- Cardiovascular MR Unit, Royal Brompton And Harefield NHS Foundation Trust, London, UK.,NHLI, Imperial College of Science, Technology and Medicine, London, UK
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30
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Fan Y, Ronan W, Teh I, Schneider JE, Varela CE, Whyte W, McHugh P, Leen S, Roche E. A comparison of two quasi-static computational models for assessment of intra-myocardial injection as a therapeutic strategy for heart failure. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2019; 35:e3213. [PMID: 31062508 DOI: 10.1002/cnm.3213] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Revised: 05/02/2019] [Accepted: 05/03/2019] [Indexed: 06/09/2023]
Abstract
Myocardial infarction, or heart attack, is the leading cause of mortality globally. Although the treatment of myocardial infarct has improved significantly, scar tissue that persists can often lead to increased stress and adverse remodeling of surrounding tissue and ultimately to heart failure. Intra-myocardial injection of biomaterials represents a potential treatment to attenuate remodeling, mitigate degeneration, and reverse the disease process in the tissue. In vivo experiments on animal models have shown functional benefits of this therapeutic strategy. However, a poor understanding of the optimal injection pattern, volume, and material properties has acted as a barrier to its widespread clinical adoption. In this study, we developed two quasistatic finite element simulations of the left ventricle to investigate the mechanical effect of intra-myocardial injection. The first model employed an idealized left ventricular geometry with rule-based cardiomyocyte orientation. The second model employed a subject-specific left ventricular geometry with cardiomyocyte orientation from diffusion tensor magnetic resonance imaging. Both models predicted cardiac parameters including ejection fraction, systolic wall thickening, and ventricular twist that matched experimentally reported values. All injection simulations showed cardiomyocyte stress attenuation, offering an explanation for the mechanical reinforcement benefit associated with injection. The study also enabled a comparison of injection location and the corresponding effect on cardiac performance at different stages of the cardiac cycle. While the idealized model has lower fidelity, it predicts cardiac function and differentiates the effects of injection location. Both models represent versatile in silico tools to guide optimal strategy in terms of injection number, volume, site, and material properties.
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Affiliation(s)
- Yiling Fan
- Mechanical Engineering, College of Engineering and Informatics, National University of Ireland Galway, Galway, Ireland
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - William Ronan
- Biomechanics Research Centre, Biomedical Engineering, College of Engineering and Informatics, National University of Ireland Galway, Galway, Ireland
| | - Irvin Teh
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Jurgen E Schneider
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Claudia E Varela
- Institute for Medical Engineering Science, Massachusetts Institute of Technology, Cambridge, Massachusetts
- Harvard-MIT Program in Health Sciences and Technology, Cambridge, Massachusetts
| | - William Whyte
- Tissue Engineering Research Group, Department of Anatomy, Royal College of Surgeons in Ireland (RCSI), Dublin, 2, Ireland
- Trinity Centre for Bioengineering, Trinity College Dublin (TCD), College Green, Dublin, 2, Ireland
- Advanced Materials and BioEngineering Research (AMBER) Centre, RCSI, NUIG & TCD, Dublin, 2, Ireland
- John A Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, Massachusetts
| | - Peter McHugh
- Biomechanics Research Centre, Biomedical Engineering, College of Engineering and Informatics, National University of Ireland Galway, Galway, Ireland
| | - Sean Leen
- Mechanical Engineering, College of Engineering and Informatics, National University of Ireland Galway, Galway, Ireland
| | - Ellen Roche
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts
- Institute for Medical Engineering Science, Massachusetts Institute of Technology, Cambridge, Massachusetts
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31
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Garcia-Canadilla P, Cook AC, Mohun TJ, Oji O, Schlossarek S, Carrier L, McKenna WJ, Moon JC, Captur G. Myoarchitectural disarray of hypertrophic cardiomyopathy begins pre-birth. J Anat 2019; 235:962-976. [PMID: 31347708 PMCID: PMC6794206 DOI: 10.1111/joa.13058] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/17/2019] [Indexed: 01/24/2023] Open
Abstract
Myoarchitectural disarray – the multiscalar disorganisation of myocytes, is a recognised histopathological hallmark of adult human hypertrophic cardiomyopathy (HCM). It occurs before the establishment of left ventricular hypertrophy (LVH) but its early origins and evolution around the time of birth are unknown. Our aim is to investigate whether myoarchitectural abnormalities in HCM are present in the fetal heart. We used wild‐type, heterozygous and homozygous hearts (n = 56) from a Mybpc3‐targeted knock‐out HCM mouse model and imaged the 3D micro‐structure by high‐resolution episcopic microscopy. We developed a novel structure tensor approach to extract, display and quantify myocyte orientation and its local angular uniformity by helical angle, angle of intrusion and myoarchitectural disarray index, respectively, immediately before and after birth. In wild‐type, we demonstrate uniformity of orientation of cardiomyocytes with smooth transitions of helical angle transmurally both before and after birth but with traces of disarray at the septal insertion points of the right ventricle. In comparison, heterozygous mice free of LVH, and homozygous mice showed not only loss of the normal linear helical angulation transmural profiles observed in wild‐type but also fewer circumferentially arranged myocytes at birth. Heterozygous and homozygous showed more disarray with a wider distribution than in wild‐type before birth. In heterozygous mice, disarray was seen in the anterior, septal and inferior walls irrespective of stage, whereas in homozygous mice it extended to the whole LV circumference including the lateral wall. In conclusion, myoarchitectural disarray is detectable in the fetal heart of an HCM mouse model before the development of LVH.
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Affiliation(s)
| | - Andrew C Cook
- Institute of Cardiovascular Science, University College London, London, UK
| | | | - Onyedikachi Oji
- Institute of Cardiovascular Science, University College London, London, UK
| | - Saskia Schlossarek
- Cardiovascular Research Centre, Institute of Experimental Pharmacology and Toxicology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,DZHK (German Center for Cardiovascular Research), partner site Hamburg/Kiel/Lübeck, Hamburg, Germany
| | - Lucie Carrier
- Cardiovascular Research Centre, Institute of Experimental Pharmacology and Toxicology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,DZHK (German Center for Cardiovascular Research), partner site Hamburg/Kiel/Lübeck, Hamburg, Germany
| | - William J McKenna
- Institute of Cardiovascular Science, University College London, London, UK
| | - James C Moon
- Institute of Cardiovascular Science, University College London, London, UK.,The Cardiovascular Magnetic Resonance Imaging Unit, Barts Heart Centre, St Bartholomew's Hospital, London, UK
| | - Gabriella Captur
- Institute of Cardiovascular Science, University College London, London, UK
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32
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Cork TE, Perotti LE, Verzhbinsky IA, Loecher M, Ennis DB. High-Resolution Ex Vivo Microstructural MRI After Restoring Ventricular Geometry via 3D Printing. FUNCTIONAL IMAGING AND MODELING OF THE HEART : ... INTERNATIONAL WORKSHOP, FIMH ..., PROCEEDINGS. FIMH 2019; 11504:177-186. [PMID: 31432042 DOI: 10.1007/978-3-030-21949-9_20] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Computational modeling of the heart requires accurately incorporating both gross anatomical detail and local microstructural information. Together, these provide the necessary data to build 3D meshes for simulation of cardiac mechanics and electrophysiology. Recent MRI advances make it possible to measure detailed heart motion in vivo, but in vivo microstructural imaging of the heart remains challenging. Consequently, the most detailed measurements of microstructural organization and microanatomical infarct details are obtained ex vivo. The objective of this work was to develop and evaluate a new method for restoring ex vivo ventricular geometry to match the in vivo configuration. This approach aids the integration of high-resolution ex vivo microstructural information with in vivo motion measurements. The method uses in vivo cine imaging to generate surface meshes, then creates a 3D printed left ventricular (LV) blood pool cast and a pericardial mold to restore the ex vivo cardiac geometry to a mid-diastasis reference configuration. The method was evaluated in healthy (N = 7) and infarcted (N = 3) swine. Dice similarity coefficients were calculated between in vivo and ex vivo images for the LV cavity (0.93 ± 0.01), right ventricle (RV) cavity (0.80 ± 0.05), and the myocardium (0.72 ± 0.04). The R 2 coefficient between in vivo and ex vivo LV and RV cavity volumes were 0.95 and 0.91, respectively. These results suggest that this method adequately restores ex vivo geometry to match in vivo geometry. This approach permits a more precise incorporation of high-resolution ex vivo anatomical and microstructural data into computational models that use in vivo data for simulation of cardiac mechanics and electrophysiology.
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Affiliation(s)
- Tyler E Cork
- Department of Radiology, Stanford University, Stanford, CA 94305, USA.,Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Luigi E Perotti
- Department of Mechanical and Aerospace Engineering, University of Central Florida, Orlando, FL 32816, USA
| | | | - Michael Loecher
- Department of Radiology, Stanford University, Stanford, CA 94305, USA
| | - Daniel B Ennis
- Department of Radiology, Stanford University, Stanford, CA 94305, USA
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33
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Dejea H, Garcia-Canadilla P, Cook AC, Guasch E, Zamora M, Crispi F, Stampanoni M, Bijnens B, Bonnin A. Comprehensive Analysis of Animal Models of Cardiovascular Disease using Multiscale X-Ray Phase Contrast Tomography. Sci Rep 2019; 9:6996. [PMID: 31061429 PMCID: PMC6502928 DOI: 10.1038/s41598-019-43407-z] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Accepted: 04/23/2019] [Indexed: 01/02/2023] Open
Abstract
Cardiovascular diseases (CVDs) affect the myocardium and vasculature, inducing remodelling of the heart from cellular to whole organ level. To assess their impact at micro and macroscopic level, multi-resolution imaging techniques that provide high quality images without sample alteration and in 3D are necessary: requirements not fulfilled by most of current methods. In this paper, we take advantage of the non-destructive time-efficient 3D multiscale capabilities of synchrotron Propagation-based X-Ray Phase Contrast Imaging (PB-X-PCI) to study a wide range of cardiac tissue characteristics in one healthy and three different diseased rat models. With a dedicated image processing pipeline, PB-X-PCI images are analysed in order to show its capability to assess different cardiac tissue components at both macroscopic and microscopic levels. The presented technique evaluates in detail the overall cardiac morphology, myocyte aggregate orientation, vasculature changes, fibrosis formation and nearly single cell arrangement. Our results agree with conventional histology and literature. This study demonstrates that synchrotron PB-X-PCI, combined with image processing tools, is a powerful technique for multi-resolution structural investigation of the heart ex-vivo. Therefore, the proposed approach can improve the understanding of the multiscale remodelling processes occurring in CVDs, and the comprehensive and fast assessment of future interventional approaches.
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Affiliation(s)
- Hector Dejea
- Paul Scherrer Institut, Villigen PSI, Switzerland.
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.
| | - Patricia Garcia-Canadilla
- PhySense, DTIC, Universitat Pompeu Fabra, Barcelona, Spain
- Institute of Cardiovascular Science, University College London, London, UK
| | - Andrew C Cook
- Institute of Cardiovascular Science, University College London, London, UK
| | - Eduard Guasch
- Arrhythmia Unit, Department of Cardiology, Hospital Clínic de Barcelona, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Centro de Investigación Biomédica en Red - Cardiovascular (CIBER-CV), Madrid, Spain
| | - Monica Zamora
- BCNatal, Hospital Clínic and Hospital Sant Joan de Déu, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Fatima Crispi
- BCNatal, Hospital Clínic and Hospital Sant Joan de Déu, Barcelona, Spain
- Centre for Biomedical Research on Rare Diseases (CIBER-ER), Hospital Clínic, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Marco Stampanoni
- Paul Scherrer Institut, Villigen PSI, Switzerland
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Bart Bijnens
- PhySense, DTIC, Universitat Pompeu Fabra, Barcelona, Spain
- ICREA, Barcelona, Spain
| | - Anne Bonnin
- Paul Scherrer Institut, Villigen PSI, Switzerland
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34
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Doste R, Soto-Iglesias D, Bernardino G, Alcaine A, Sebastian R, Giffard-Roisin S, Sermesant M, Berruezo A, Sanchez-Quintana D, Camara O. A rule-based method to model myocardial fiber orientation in cardiac biventricular geometries with outflow tracts. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2019; 35:e3185. [PMID: 30721579 DOI: 10.1002/cnm.3185] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Revised: 10/23/2018] [Accepted: 01/05/2019] [Indexed: 06/09/2023]
Abstract
Rule-based methods are often used for assigning fiber orientation to cardiac anatomical models. However, existing methods have been developed using data mostly from the left ventricle. As a consequence, fiber information obtained from rule-based methods often does not match histological data in other areas of the heart such as the right ventricle, having a negative impact in cardiac simulations beyond the left ventricle. In this work, we present a rule-based method where fiber orientation is separately modeled in each ventricle following observations from histology. This allows to create detailed fiber orientation in specific regions such as the endocardium of the right ventricle, the interventricular septum, and the outflow tracts. We also carried out electrophysiological simulations involving these structures and with different fiber configurations. In particular, we built a modeling pipeline for creating patient-specific volumetric meshes of biventricular geometries, including the outflow tracts, and subsequently simulate the electrical wavefront propagation in outflow tract ventricular arrhythmias with different origins for the ectopic focus. The resulting simulations with the proposed rule-based method showed a very good agreement with clinical parameters such as the 10 ms isochrone ratio in a cohort of nine patients suffering from this type of arrhythmia. The developed modeling pipeline confirms its potential for an in silico identification of the site of origin in outflow tract ventricular arrhythmias before clinical intervention.
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Affiliation(s)
- Ruben Doste
- Physense, ETIC, Universitat Pompeu Fabra, Barcelona, Spain
| | | | | | | | - Rafael Sebastian
- Computational Multiscale Simulation Lab (CoMMLab), Department of Computer Science, Universitat de Valencia, Valencia, Spain
| | | | | | - Antonio Berruezo
- Arrhythmia Section, Cardiology Department, Thorax Institute, Hospital Clinic, Universitat de Barcelona, Barcelona, Spain
| | - Damian Sanchez-Quintana
- Department of Anatomy and Cell Biology, Faculty of Medicine, University of Extremadura, Badajoz, Spain
| | - Oscar Camara
- Physense, ETIC, Universitat Pompeu Fabra, Barcelona, Spain
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35
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Gonzalez-Tendero A, Zhang C, Balicevic V, Cárdenes R, Loncaric S, Butakoff C, Paun B, Bonnin A, Garcia-Cañadilla P, Muñoz-Moreno E, Gratacós E, Crispi F, Bijnens B. Whole heart detailed and quantitative anatomy, myofibre structure and vasculature from X-ray phase-contrast synchrotron radiation-based micro computed tomography. Eur Heart J Cardiovasc Imaging 2018; 18:732-741. [PMID: 28329054 DOI: 10.1093/ehjci/jew314] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2016] [Accepted: 11/28/2016] [Indexed: 11/13/2022] Open
Abstract
Background While individual cardiac myocytes only have a limited ability to shorten, the heart efficiently pumps a large volume-fraction thanks to a cell organization in a complex 3D fibre structure. Subclinical subtle cardiac structural remodelling is often present before symptoms arise. Understanding and early detection of these subtle changes is crucial for diagnosis and prevention. Additionally, personalized computational modelling requires knowledge on the multi-scale structure of the whole heart and vessels. Methods and Results We developed a rapid acquisition together with visualization and quantification methods of the integrated microstructure of whole in-vitro rodents hearts using synchrotron based X-ray phase-contrast tomography. These images are formed not only by X-ray absorption by the tissue but also by wave propagation phenomena, enhancing structural information, thus allowing to raise tissue contrast to an unprecedented level. We used a (ex-vivo) normal rat heart and fetal rabbit hearts suffering intrauterine growth restriction as a model of subclinical cardiac remodelling to illustrate the strengths and potential of the technique. For comparison, histology and diffusion tensor magnetic resonance imaging was performed. Conclusions We have developed a novel, high resolution, image acquisition, and quantification approach to study a whole in-vitro heart at myofibre resolution, providing integrated 3D structural information at microscopic level without any need of tissue slicing and processing. This superior imaging approach opens up new possibilities for a systems approach towards analysing cardiac structure and function, providing rapid acquisition of quantitative microstructure of the heart in a near native state.
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Affiliation(s)
- Anna Gonzalez-Tendero
- Fetal i+D Fetal Medicine Research Center, BCNatal-Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain
| | - Chong Zhang
- PhySense, DTIC, Universitat Pompeu Fabra, Barcelona, Spain.,CellNetworks, Heidelberg, Germany
| | - Vedrana Balicevic
- Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia
| | - Rubén Cárdenes
- Fetal i+D Fetal Medicine Research Center, BCNatal-Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain.,PhySense, DTIC, Universitat Pompeu Fabra, Barcelona, Spain
| | - Sven Loncaric
- Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia
| | | | - Bruno Paun
- PhySense, DTIC, Universitat Pompeu Fabra, Barcelona, Spain
| | - Anne Bonnin
- European Synchrotron Radiation Facility, Grenoble, France.,Paul Scherrer Institut, Villigen, Switzerland
| | | | - Emma Muñoz-Moreno
- Fetal i+D Fetal Medicine Research Center, BCNatal-Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain
| | - Eduard Gratacós
- Fetal i+D Fetal Medicine Research Center, BCNatal-Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain
| | - Fatima Crispi
- Fetal i+D Fetal Medicine Research Center, BCNatal-Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), IDIBAPS, University of Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain
| | - Bart Bijnens
- PhySense, DTIC, Universitat Pompeu Fabra, Barcelona, Spain.,ICREA, Barcelona, Spain
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36
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Hoffman JIE. Will the real ventricular architecture please stand up? Physiol Rep 2018; 5:5/18/e13404. [PMID: 28947592 PMCID: PMC5617926 DOI: 10.14814/phy2.13404] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2017] [Accepted: 07/23/2017] [Indexed: 12/28/2022] Open
Abstract
Ventricular twisting, essential for cardiac function, is attributed to the contraction of myocardial helical fibers. The exact relationship between ventricular anatomy and function remains to be determined, but one commonly used explanatory model is the helical ventricular myocardial band (HVMB) model of Torrent‐Guasp. This model has been successful in explaining many aspects of ventricular function, (Torrent‐Guasp et al. Eur. J. Cardiothorac. Surg., 25, 376, 2004; Buckberg et al. Eur. J. Cardiothorac. Surg., 47, 587, 2015; Buckberg et al. Eur. J. Cardiothorac. Surg. 47, 778, 2015) but the model ignores important aspects of ventricular anatomy and should probably be replaced. The purpose of this review is to compare the HVMB model with a different model (nested layers). A complication when interpreting experimental observations that relate anatomy to function is that, in the myocardium, shortening does not always imply activation and lengthening does not always imply inactivation.
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Affiliation(s)
- Julien I E Hoffman
- Department of Pediatrics, University of California, San Francisco, California
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37
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Aliotta E, Moulin K, Magrath P, Ennis DB. Quantifying precision in cardiac diffusion tensor imaging with second-order motion-compensated convex optimized diffusion encoding. Magn Reson Med 2018; 80:1074-1087. [PMID: 29427349 DOI: 10.1002/mrm.27107] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Revised: 01/04/2018] [Accepted: 01/05/2018] [Indexed: 12/13/2022]
Affiliation(s)
- Eric Aliotta
- Department of Radiological Sciences, University of California, Los Angeles, California.,Biomedical Physics Interdepartmental Program, University of California, Los Angeles, California
| | - Kévin Moulin
- Department of Radiological Sciences, University of California, Los Angeles, California
| | - Patrick Magrath
- Department of Bioengineering, University of California, Los Angeles, California
| | - Daniel B Ennis
- Department of Radiological Sciences, University of California, Los Angeles, California.,Biomedical Physics Interdepartmental Program, University of California, Los Angeles, California.,Department of Bioengineering, University of California, Los Angeles, California
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38
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McClymont D, Teh I, Schneider JE. The impact of signal-to-noise ratio, diffusion-weighted directions and image resolution in cardiac diffusion tensor imaging - insights from the ex-vivo rat heart. J Cardiovasc Magn Reson 2017; 19:90. [PMID: 29157268 PMCID: PMC5695094 DOI: 10.1186/s12968-017-0395-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2017] [Accepted: 10/09/2017] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Cardiac diffusion tensor imaging (DTI) is limited by scan time and signal-to-noise (SNR) restrictions. This invariably leads to a trade-off between the number of averages, diffusion-weighted directions (ND), and image resolution. Systematic evaluation of these parameters is therefore important for adoption of cardiac DTI in clinical routine where time is a key constraint. METHODS High quality reference DTI data were acquired in five ex-vivo rat hearts. We then retrospectively set 2 ≤ SNR ≤ 97, 7 ≤ ND ≤ 61, varied the voxel volume by up to 192-fold and investigated the impact on the accuracy and precision of commonly derived parameters. RESULTS For maximal scan efficiency, the accuracy and precision of the mean diffusivity is optimised when SNR is maximised at the expense of ND. With typical parameter settings used clinically, we estimate that fractional anisotropy may be overestimated by up to 13% with an uncertainty of ±30%, while the precision of the sheetlet angles may be as poor as ±31°. Although the helix angle has better precision of ±14°, the transmural range of helix angles may be under-estimated by up to 30° in apical and basal slices, due to partial volume and tapering myocardial geometry. CONCLUSIONS These findings inform a baseline of understanding upon which further issues inherent to in-vivo cardiac DTI, such as motion, strain and perfusion, can be considered. Furthermore, the reported bias and reproducibility provides a context in which to assess cardiac DTI biomarkers.
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Affiliation(s)
- Darryl McClymont
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Irvin Teh
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Leeds Institute of Cardiovascular & Metabolic Medicine, University of Leeds, Leeds, UK
| | - Jürgen E. Schneider
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Leeds Institute of Cardiovascular & Metabolic Medicine, University of Leeds, Leeds, UK
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39
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Bates J, Teh I, McClymont D, Kohl P, Schneider JE, Grau V. Monte Carlo Simulations of Diffusion Weighted MRI in Myocardium: Validation and Sensitivity Analysis. IEEE TRANSACTIONS ON MEDICAL IMAGING 2017; 36:1316-1325. [PMID: 28328501 DOI: 10.1109/tmi.2017.2679809] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
A model of cardiac microstructure and diffusion MRI is presented, and compared with experimental data from ex vivo rat hearts. The model includes a simplified representation of individual cells, with physiologically correct cell size and orientation, as well as intra- to extracellular volume ratio. Diffusion MRI is simulated using a Monte Carlo model and realistic MRI sequences. The results show good correspondence between the simulated and experimental MRI signals. Similar patterns are observed in the eigenvalues of the diffusion tensor, the mean diffusivity (MD), and the fractional anisotropy (FA). A sensitivity analysis shows that the diffusivity is the dominant influence on all three eigenvalues of the diffusion tensor, the MD, and the FA. The area and aspect ratio of the cell cross-section affect the secondary and tertiary eigenvalues, and hence the FA. Within biological norms, the cell length, volume fraction of cells, and rate of change of helix angle play a relatively small role in influencing tissue diffusion. Results suggest that the model could be used to improve understanding of the relationship between cardiac microstructure and diffusion MRI measurements, as well as in testing and refinement of cardiac diffusion MRI protocols.
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40
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Teh I, McClymont D, Zdora MC, Whittington HJ, Davidoiu V, Lee J, Lygate CA, Rau C, Zanette I, Schneider JE. Validation of diffusion tensor MRI measurements of cardiac microstructure with structure tensor synchrotron radiation imaging. J Cardiovasc Magn Reson 2017; 19:31. [PMID: 28279178 PMCID: PMC5345150 DOI: 10.1186/s12968-017-0342-x] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2016] [Accepted: 02/16/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Diffusion tensor imaging (DTI) is widely used to assess tissue microstructure non-invasively. Cardiac DTI enables inference of cell and sheetlet orientations, which are altered under pathological conditions. However, DTI is affected by many factors, therefore robust validation is critical. Existing histological validation is intrinsically flawed, since it requires further tissue processing leading to sample distortion, is routinely limited in field-of-view and requires reconstruction of three-dimensional volumes from two-dimensional images. In contrast, synchrotron radiation imaging (SRI) data enables imaging of the heart in 3D without further preparation following DTI. The objective of the study was to validate DTI measurements based on structure tensor analysis of SRI data. METHODS One isolated, fixed rat heart was imaged ex vivo with DTI and X-ray phase contrast SRI, and reconstructed at 100 μm and 3.6 μm isotropic resolution respectively. Structure tensors were determined from the SRI data and registered to the DTI data. RESULTS Excellent agreement in helix angles (HA) and transverse angles (TA) was observed between the DTI and structure tensor synchrotron radiation imaging (STSRI) data, where HADTI-STSRI = -1.4° ± 23.2° and TADTI-STSRI = -1.4° ± 35.0° (mean ± 1.96 standard deviation across all voxels in the left ventricle). STSRI confirmed that the primary eigenvector of the diffusion tensor corresponds with the cardiomyocyte long-axis across the whole myocardium. CONCLUSIONS We have used STSRI as a novel and high-resolution gold standard for the validation of DTI, allowing like-with-like comparison of three-dimensional tissue structures in the same intact heart free of distortion. This represents a critical step forward in independently verifying the structural basis and informing the interpretation of cardiac DTI data, thereby supporting the further development and adoption of DTI in structure-based electro-mechanical modelling and routine clinical applications.
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Affiliation(s)
- Irvin Teh
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Leeds Institute of Cardiovascular & Metabolic Medicine, University of Leeds, Leeds, UK
| | - Darryl McClymont
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Marie-Christine Zdora
- Diamond Light Source, Didcot, UK
- Department of Physics and Astronomy, University College London, London, UK
| | - Hannah J. Whittington
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Valentina Davidoiu
- Division of Imaging Sciences and Biomedical Engineering, King’s College London, London, UK
| | - Jack Lee
- Division of Imaging Sciences and Biomedical Engineering, King’s College London, London, UK
| | - Craig A. Lygate
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Christoph Rau
- Diamond Light Source, Didcot, UK
- University of Manchester, Manchester, UK
- Feinberg School of Medicine, Northwestern University, Chicago, USA
| | | | - Jürgen E. Schneider
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Leeds Institute of Cardiovascular & Metabolic Medicine, University of Leeds, Leeds, UK
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McClymont D, Teh I, Carruth E, Omens J, McCulloch A, Whittington HJ, Kohl P, Grau V, Schneider JE. Evaluation of non-Gaussian diffusion in cardiac MRI. Magn Reson Med 2016; 78:1174-1186. [PMID: 27670633 PMCID: PMC5366286 DOI: 10.1002/mrm.26466] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2016] [Revised: 08/18/2016] [Accepted: 08/23/2016] [Indexed: 12/20/2022]
Abstract
PURPOSE The diffusion tensor model assumes Gaussian diffusion and is widely applied in cardiac diffusion MRI. However, diffusion in biological tissue deviates from a Gaussian profile as a result of hindrance and restriction from cell and tissue microstructure, and may be quantified better by non-Gaussian modeling. The aim of this study was to investigate non-Gaussian diffusion in healthy and hypertrophic hearts. METHODS Thirteen rat hearts (five healthy, four sham, four hypertrophic) were imaged ex vivo. Diffusion-weighted images were acquired at b-values up to 10,000 s/mm2 . Models of diffusion were fit to the data and ranked based on the Akaike information criterion. RESULTS The diffusion tensor was ranked best at b-values up to 2000 s/mm2 but reflected the signal poorly in the high b-value regime, in which the best model was a non-Gaussian "beta distribution" model. Although there was considerable overlap in apparent diffusivities between the healthy, sham, and hypertrophic hearts, diffusion kurtosis and skewness in the hypertrophic hearts were more than 20% higher in the sheetlet and sheetlet-normal directions. CONCLUSION Non-Gaussian diffusion models have a higher sensitivity for the detection of hypertrophy compared with the Gaussian model. In particular, diffusion kurtosis may serve as a useful biomarker for characterization of disease and remodeling in the heart. Magn Reson Med 78:1174-1186, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Darryl McClymont
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Irvin Teh
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Eric Carruth
- Department of Bioengineering, University of California-San Diego, La Jolla, California, USA
| | - Jeffrey Omens
- Department of Bioengineering, University of California-San Diego, La Jolla, California, USA.,Department of Medicine, University of California-San Diego, La Jolla, California, USA
| | - Andrew McCulloch
- Department of Bioengineering, University of California-San Diego, La Jolla, California, USA
| | - Hannah J Whittington
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Peter Kohl
- National Heart and Lung Institute, Imperial College London, London, United Kingdom.,Institute for Experimental Cardiovascular Medicine, University Heart Centre Freiburg, Bad Krozingen, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Vicente Grau
- Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Jürgen E Schneider
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
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