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Sadighi M, Kara D, Mai D, Nguyen K, Chen S, Kwon D, Nguyen C. Cardiac DTI using short-axis PROPELLER: A feasibility study. Magn Reson Med 2024; 91:2546-2558. [PMID: 38376096 PMCID: PMC11102807 DOI: 10.1002/mrm.30020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 12/06/2023] [Accepted: 01/08/2024] [Indexed: 02/21/2024]
Abstract
PURPOSE We aimed to develop a free-breathing (FB) cardiac DTI (cDTI) method based on short-axis PROPELLER (SAP) and M2 motion compensated spin-echo EPI (SAP-M2-EPI) to mitigate geometric distortion and eliminate aliasing in acquired diffusion-weighted (DW) images, particularly in patients with a higher body mass index (BMI). THEORY AND METHODS The study involved 10 healthy volunteers whose BMI values fell into specific categories: BMI <25 (4 volunteers), 25< BMI <28 (5 volunteers), and BMI >30 (1 volunteer). We compared DTI parameters, including fractional anisotropy (FA), mean diffusivity (MD), and helix angle transmurality (HAT), between SAP-M2-EPI and M2-ssEPI. To evaluate the performance of SAP-M2-EPI in reducing geometric distortions in the left ventricle (LV) compared to CINE and M2-ssEPI, we utilized the DICE similarity coefficient (DSC) and assessed misregistration area. RESULTS In all volunteers, SAP-M2-EPI yielded high-quality LV DWIs without aliasing, demonstrating significantly reduced geometric distortion (with an average DSC of 0.92 and average misregistration area of 90 mm2) and diminished signal loss due to bulk motion when compared to M2-ssEPI. DTI parameter maps exhibited consistent patterns across slices without motion related artifacts. CONCLUSION SAP-M2-EPI facilitates free-breathing cDTI of the entire LV, effectively eliminating aliasing and minimizing geometric distortion compared to M2-ssEPI. Furthermore, it preserves accurate quantification of myocardial microstructure.
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Affiliation(s)
- Mehdi Sadighi
- Cardiovascular Innovation Research Center (CIRC), Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Danielle Kara
- Cardiovascular Innovation Research Center (CIRC), Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Dingheng Mai
- Cardiovascular Innovation Research Center (CIRC), Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio, USA
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Case Western Reserve University, Cleveland, Ohio, USA
| | - Khoi Nguyen
- Cardiovascular Innovation Research Center (CIRC), Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Shi Chen
- Cardiovascular Innovation Research Center (CIRC), Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Deborah Kwon
- Cardiovascular Innovation Research Center (CIRC), Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio, USA
- Imaging Institute,Cleveland Clinic, Cleveland, Ohio, USA
| | - Christopher Nguyen
- Cardiovascular Innovation Research Center (CIRC), Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio, USA
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Case Western Reserve University, Cleveland, Ohio, USA
- Imaging Institute,Cleveland Clinic, Cleveland, Ohio, USA
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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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Comprehensive assessment of myocardial remodeling in ischemic heart disease by synchrotron propagation based X-ray phase contrast imaging. Sci Rep 2021; 11:14020. [PMID: 34234175 PMCID: PMC8263575 DOI: 10.1038/s41598-021-93054-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 06/16/2021] [Indexed: 02/06/2023] Open
Abstract
Cardiovascular research is in an ongoing quest for a superior imaging method to integrate gross-anatomical information with microanatomy, combined with quantifiable parameters of cardiac structure. In recent years, synchrotron radiation-based X-ray Phase Contrast Imaging (X-PCI) has been extensively used to characterize soft tissue in detail. The objective was to use X-PCI to comprehensively quantify ischemic remodeling of different myocardial structures, from cell to organ level, in a rat model of myocardial infarction. Myocardial infarction-induced remodeling was recreated in a well-established rodent model. Ex vivo rodent hearts were imaged by propagation based X-PCI using two configurations resulting in 5.8 µm and 0.65 µm effective pixel size images. The acquired datasets were used for a comprehensive assessment of macrostructural changes including the whole heart and vascular tree morphology, and quantification of left ventricular myocardial thickness, mass, volume, and organization. On the meso-scale, tissue characteristics were explored and compared with histopathological methods, while microstructural changes were quantified by segmentation of cardiomyocytes and calculation of cross-sectional areas. Propagation based X-PCI provides detailed visualization and quantification of morphological changes on whole organ, tissue, vascular as well as individual cellular level of the ex vivo heart, with a single, non-destructive 3D imaging modality.
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Nguyen CT, Christodoulou AG, Coll-Font J, Ma S, Xie Y, Reese TG, Mekkaoui C, Lewis GD, Bi X, Sosnovik DE, Li D. Free-breathing diffusion tensor MRI of the whole left ventricle using second-order motion compensation and multitasking respiratory motion correction. Magn Reson Med 2021; 85:2634-2648. [PMID: 33252140 PMCID: PMC7902339 DOI: 10.1002/mrm.28611] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 11/01/2020] [Accepted: 11/03/2020] [Indexed: 12/17/2022]
Abstract
PURPOSE We aimed to develop a novel free-breathing cardiac diffusion tensor MRI (DT-MRI) approach, M2-MT-MOCO, capable of whole left ventricular coverage that leverages second-order motion compensation (M2) diffusion encoding and multitasking (MT) framework to efficiently correct for respiratory motion (MOCO). METHODS Imaging was performed in 16 healthy volunteers and 3 heart failure patients with symptomatic dyspnea. The healthy volunteers were scanned to compare the accuracy of interleaved multislice coverage of the entire left ventricle with a single-slice acquisition and the accuracy of the free-breathing conventional MOCO and MT-MOCO approaches with reference breath-hold DT-MRI. Mean diffusivity (MD), fractional anisotropy (FA), helix angle transmurality (HAT), and intrascan repeatability were quantified and compared. RESULTS In all subjects, free-breathing M2-MT-MOCO DT-MRI yielded DWI of the entire left ventricle without bulk motion-induced signal loss. No significant differences were seen in the global values of MD, FA, and HAT in the multislice and single-slice acquisitions. Furthermore, global quantification of MD, FA, and HAT were also not significantly different between the MT-MOCO and breath-hold, whereas conventional MOCO yielded significant differences in MD, FA, and HAT with MT-MOCO and FA with breath-hold. In heart failure patients, M2-MT-MOCO DT-MRI was feasible yielding higher MD, lower FA, and lower HAT compared with healthy volunteers. Substantial agreement was found between repeated scans across all subjects for MT-MOCO. CONCLUSION M2-MT-MOCO enables free-breathing DT-MRI of the entire left ventricle in 10 min, while preserving quantification of myocardial microstructure compared to breath-held and single-slice acquisitions and is feasible in heart failure patients.
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Affiliation(s)
- Christopher T. Nguyen
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA
| | - Anthony G. Christodoulou
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA
| | - Jaume Coll-Font
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA
| | - Sen Ma
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA
| | - Yibin Xie
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Timothy G. Reese
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA
- Department of Radiology, Harvard Medical School, Boston, MA
| | - Choukri Mekkaoui
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA
- Department of Radiology, Harvard Medical School, Boston, MA
| | - Gregory D. Lewis
- Department of Medicine, Harvard Medical School, Boston, MA
- Heart Failure Section, Cardiology Division, Massachusetts General Hospital, Boston, MA
| | - Xiaoming Bi
- Siemens Medical Solutions USA, Inc., Los Angeles, CA
| | - David E. Sosnovik
- Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA
| | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA
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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: 3.3] [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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Huang J, Wang L, Chu C, Liu W, Zhu Y. Accelerating cardiac diffusion tensor imaging combining local low-rank and 3D TV constraint. MAGMA (NEW YORK, N.Y.) 2019; 32:407-422. [PMID: 30903326 DOI: 10.1007/s10334-019-00747-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2018] [Revised: 03/08/2019] [Accepted: 03/11/2019] [Indexed: 06/09/2023]
Abstract
OBJECTIVE Diffusion tensor magnetic resonance imaging (DT-MRI, or DTI) is a promising technique for invasively probing biological tissue structures. However, DTI is known to suffer from much longer acquisition time with respect to conventional MRI and the problem is worsened when dealing with in vivo acquisitions. Therefore, faster DTI for both ex vivo and in vivo scans is highly desired. MATERIALS AND METHODS This paper proposes a new compressed sensing (CS) reconstruction method that employs local low-rank (LLR) model and three-dimensional (3D) total variation (TV) constraint to reconstruct cardiac diffusion-weighted (DW) images from highly undersampled k-space data. The LLR model takes the set of DW images corresponding to different diffusion gradient directions as a 3D image volume and decomposes the latter into overlapping 3D blocks. Then, the 3D blocks are stacked as two-dimensional (2D) matrix. Finally, low-rank property is applied to each block matrix and the 3D TV constraint to the 3D image volume. The underlying constrained optimization problem is finally solved using the first-order fast method. The proposed method is evaluated on real ex vivo cardiac DTI data as a prerequisite to in vivo cardiac DTI applications. RESULTS The results on real human ex vivo cardiac DTI images demonstrate that the proposed method exhibits lower reconstruction errors for DTI indices, including fractional anisotropy (FA), mean diffusivities (MD), transverse angle (TA), and helix angle (HA), compared to existing CS-based DTI image reconstruction techniques. CONCLUSION The proposed method provides better reconstruction quality and more accurate DTI indices in comparison with the state-of-the-art CS-based DW image reconstruction methods.
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Affiliation(s)
- Jianping Huang
- College of Mechanical and Electrical Engineering, Northeast Forestry University, Heilongjiang, 150040, Harbin, China.
- Metislab, LIA CNRS, Harbin Institute of Technology, Heilongjiang, 150001, Harbin, China.
- CREATIS, CNRS UMR5220, Inserm U1206, INSA Lyon, University of Lyon, Lyon, France.
| | - Lihui Wang
- Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province, School of Computer Science and Technology, Guizhou University, Guiyang, China
| | - Chunyu Chu
- College of Engineering, Bohai University, Jinzhou, 121013, China
| | - Wanyu Liu
- Metislab, LIA CNRS, Harbin Institute of Technology, Heilongjiang, 150001, Harbin, China
| | - Yuemin Zhu
- Metislab, LIA CNRS, Harbin Institute of Technology, Heilongjiang, 150001, Harbin, China
- CREATIS, CNRS UMR5220, Inserm U1206, INSA Lyon, University of Lyon, Lyon, France
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7
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Nguyen CT, Buckberg G, Li D. Magnetic Resonance Diffusion Tensor Imaging Provides New Insights Into the Microstructural Alterations in Dilated Cardiomyopathy. Circ Cardiovasc Imaging 2018; 9:CIRCIMAGING.116.005593. [PMID: 27729369 DOI: 10.1161/circimaging.116.005593] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Christopher T Nguyen
- From the Department of Biomedical Sciences, Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA (C.T.N., D.L.); Departments of Cardiac Surgery (G.B.) and Medicine (D.L.), David Geffen School of Medicine at University of California, Los Angeles; and Department of Bioengineering, University of California, Los Angeles (D.L.)
| | - Gerald Buckberg
- From the Department of Biomedical Sciences, Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA (C.T.N., D.L.); Departments of Cardiac Surgery (G.B.) and Medicine (D.L.), David Geffen School of Medicine at University of California, Los Angeles; and Department of Bioengineering, University of California, Los Angeles (D.L.)
| | - Debiao Li
- From the Department of Biomedical Sciences, Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA (C.T.N., D.L.); Departments of Cardiac Surgery (G.B.) and Medicine (D.L.), David Geffen School of Medicine at University of California, Los Angeles; and Department of Bioengineering, University of California, Los Angeles (D.L.).
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8
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Funck C, Laun FB, Wetscherek A. Characterization of the diffusion coefficient of blood. Magn Reson Med 2018; 79:2752-2758. [PMID: 28940621 PMCID: PMC5836916 DOI: 10.1002/mrm.26919] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2017] [Revised: 07/27/2017] [Accepted: 08/22/2017] [Indexed: 12/13/2022]
Abstract
PURPOSE To characterize the diffusion coefficient of human blood for accurate results in intravoxel incoherent motion imaging. METHODS Diffusion-weighted MRI of blood samples from 10 healthy volunteers was acquired with a single-shot echo-planar-imaging sequence at body temperature. Effects of gradient profile (monopolar or flow-compensated), diffusion time (40-100 ms), and echo time (60-200 ms) were investigated. RESULTS Although measured apparent diffusion coefficients of blood were larger for flow-compensated than for monopolar gradients, no dependence of the apparent diffusion coefficient on the diffusion time was found. Large differences between individual samples were observed, with results ranging from 1.26 to 1.66 µm2 /ms for flow-compensated and 0.94 to 1.52 µm2 /ms for monopolar gradients. Statistical analysis indicates correlations of the flow-compensated apparent diffusion coefficient with hematocrit (P = 0.007) and hemoglobin (P = 0.017), but not with mean corpuscular volume (P = 0.64). Results of Monte-Carlo simulations support the experimental observations. CONCLUSIONS Measured blood apparent diffusion coefficient values depend on hematocrit/hemoglobin concentration and applied gradient profile due to non-Gaussian diffusion. Because in vivo measurement is delicate, an estimation based on blood count results could be an alternative. For intravoxel incoherent motion modeling, the use of a blood self-diffusion constant Db = 1.54 ± 0.12 µm2 /ms for flow-compensated and Db = 1.30 ± 0.18 µm2 /ms for monopolar encoding is suggested. Magn Reson Med 79:2752-2758, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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Affiliation(s)
- Carsten Funck
- Medical Physics in Radiology, German Cancer Research Center (DKFZ)HeidelbergGermany
| | - Frederik Bernd Laun
- Medical Physics in Radiology, German Cancer Research Center (DKFZ)HeidelbergGermany
- Institute of RadiologyUniversity Hospital ErlangenErlangenGermany
| | - Andreas Wetscherek
- Medical Physics in Radiology, German Cancer Research Center (DKFZ)HeidelbergGermany
- Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation TrustLondonUnited Kingdom
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Nielles-Vallespin S, Khalique Z, Ferreira PF, de Silva R, Scott AD, Kilner P, McGill LA, Giannakidis A, Gatehouse PD, Ennis D, Aliotta E, Al-Khalil M, Kellman P, Mazilu D, Balaban RS, Firmin DN, Arai AE, Pennell DJ. Assessment of Myocardial Microstructural Dynamics by In Vivo Diffusion Tensor Cardiac Magnetic Resonance. J Am Coll Cardiol 2017; 69:661-676. [PMID: 28183509 PMCID: PMC8672367 DOI: 10.1016/j.jacc.2016.11.051] [Citation(s) in RCA: 162] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2016] [Revised: 10/29/2016] [Accepted: 11/07/2016] [Indexed: 01/23/2023]
Abstract
BACKGROUND Cardiomyocytes are organized in microstructures termed sheetlets that reorientate during left ventricular thickening. Diffusion tensor cardiac magnetic resonance (DT-CMR) may enable noninvasive interrogation of in vivo cardiac microstructural dynamics. Dilated cardiomyopathy (DCM) is a condition of abnormal myocardium with unknown sheetlet function. OBJECTIVES This study sought to validate in vivo DT-CMR measures of cardiac microstructure against histology, characterize microstructural dynamics during left ventricular wall thickening, and apply the technique in hypertrophic cardiomyopathy (HCM) and DCM. METHODS In vivo DT-CMR was acquired throughout the cardiac cycle in healthy swine, followed by in situ and ex vivo DT-CMR, then validated against histology. In vivo DT-CMR was performed in 19 control subjects, 19 DCM, and 13 HCM patients. RESULTS In swine, a DT-CMR index of sheetlet reorientation (E2A) changed substantially (E2A mobility ~46°). E2A changes correlated with wall thickness changes (in vivo r2 = 0.75; in situ r2 = 0.89), were consistently observed under all experimental conditions, and accorded closely with histological analyses in both relaxed and contracted states. The potential contribution of cyclical strain effects to in vivo E2A was ~17%. In healthy human control subjects, E2A increased from diastole (18°) to systole (65°; p < 0.001; E2A mobility = 45°). HCM patients showed significantly greater E2A in diastole than control subjects did (48 ; p < 0.001) with impaired E2A mobility (23°; p < 0.001). In DCM, E2A was similar to control subjects in diastole, but systolic values were markedly lower (40° ; p < 0.001) with impaired E2A mobility (20°; p < 0.001). CONCLUSIONS Myocardial microstructure dynamics can be characterized by in vivo DT-CMR. Sheetlet function was abnormal in DCM with altered systolic conformation and reduced mobility, contrasting with HCM, which showed reduced mobility with altered diastolic conformation. These novel insights significantly improve understanding of contractile dysfunction at a level of noninvasive interrogation not previously available in humans. (J Am Coll Cardiol 2017;69:661–76) Published by Elsevier on behalf of the American College of Cardiology Foundation.
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Affiliation(s)
- Sonia Nielles-Vallespin
- National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland; Cardiovascular Magnetic Resonance Unit, Royal Brompton and Harefield National Health Service Foundation Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom.
| | - Zohya Khalique
- Cardiovascular Magnetic Resonance Unit, Royal Brompton and Harefield National Health Service Foundation Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom; National Institute for Health Research Cardiovascular Biomedical Research Unit, Royal Brompton and Harefield National Health Service Foundation Trust, and Imperial College London, London, United Kingdom
| | - Pedro F Ferreira
- Cardiovascular Magnetic Resonance Unit, Royal Brompton and Harefield National Health Service Foundation Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom; National Institute for Health Research Cardiovascular Biomedical Research Unit, Royal Brompton and Harefield National Health Service Foundation Trust, and Imperial College London, London, United Kingdom
| | - Ranil de Silva
- Cardiovascular Magnetic Resonance Unit, Royal Brompton and Harefield National Health Service Foundation Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom; National Institute for Health Research Cardiovascular Biomedical Research Unit, Royal Brompton and Harefield National Health Service Foundation Trust, and Imperial College London, London, United Kingdom
| | - Andrew D Scott
- Cardiovascular Magnetic Resonance Unit, Royal Brompton and Harefield National Health Service Foundation Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom; National Institute for Health Research Cardiovascular Biomedical Research Unit, Royal Brompton and Harefield National Health Service Foundation Trust, and Imperial College London, London, United Kingdom
| | - Philip Kilner
- Cardiovascular Magnetic Resonance Unit, Royal Brompton and Harefield National Health Service Foundation Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom; National Institute for Health Research Cardiovascular Biomedical Research Unit, Royal Brompton and Harefield National Health Service Foundation Trust, and Imperial College London, London, United Kingdom
| | - Laura-Ann McGill
- Cardiovascular Magnetic Resonance Unit, Royal Brompton and Harefield National Health Service Foundation Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Archontis Giannakidis
- Cardiovascular Magnetic Resonance Unit, Royal Brompton and Harefield National Health Service Foundation Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Peter D Gatehouse
- Cardiovascular Magnetic Resonance Unit, Royal Brompton and Harefield National Health Service Foundation Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Daniel Ennis
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Eric Aliotta
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Majid Al-Khalil
- Cardiovascular Magnetic Resonance Unit, Royal Brompton and Harefield National Health Service Foundation Trust, London, United Kingdom
| | - Peter Kellman
- National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland
| | - Dumitru Mazilu
- National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland
| | - Robert S Balaban
- National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland
| | - David N Firmin
- Cardiovascular Magnetic Resonance Unit, Royal Brompton and Harefield National Health Service Foundation Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom; National Institute for Health Research Cardiovascular Biomedical Research Unit, Royal Brompton and Harefield National Health Service Foundation Trust, and Imperial College London, London, United Kingdom
| | - Andrew E Arai
- National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland
| | - Dudley J Pennell
- Cardiovascular Magnetic Resonance Unit, Royal Brompton and Harefield National Health Service Foundation Trust, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom; National Institute for Health Research Cardiovascular Biomedical Research Unit, Royal Brompton and Harefield National Health Service Foundation Trust, and Imperial College London, London, United Kingdom
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Nguyen C, Fan Z, Xie Y, Pang J, Speier P, Bi X, Kobashigawa J, Li D. In vivo diffusion-tensor MRI of the human heart on a 3 tesla clinical scanner: An optimized second order (M2) motion compensated diffusion-preparation approach. Magn Reson Med 2016; 76:1354-1363. [PMID: 27550078 PMCID: PMC5067209 DOI: 10.1002/mrm.26380] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2016] [Revised: 06/23/2016] [Accepted: 07/22/2016] [Indexed: 12/13/2022]
Abstract
PURPOSE To optimize a diffusion-prepared balanced steady-state free precession cardiac MRI (CMR) technique to perform diffusion-tensor CMR (DT-CMR) in humans on a 3 Tesla clinical scanner METHODS: A previously developed second order motion compensated (M2) diffusion-preparation scheme was significantly shortened (40%) yielding sufficient signal-to-noise ratio for DT-CMR imaging. In 20 healthy volunteers and 3 heart failure (HF) patients, DT-CMR was performed comparing no motion compensation (M0), first order motion compensation (M1), and the optimized M2. Mean diffusivity (MD), fractional anisotropy (FA), helix angle (HA), and HA transmural slope (HATS) were calculated. Reproducibility and success rate (SR) were investigated. RESULTS M2-derived left ventricular (LV) MD, FA, and HATS (1.4 ± 0.2 μm2 /ms, 0.28 ± 0.06, -1.0 ± 0.2 °/%trans) were significantly (P < 0.001) less than M1 (1.8 ± 0.3 μm2 /ms, 0.46 ± 0.14, -0.1 ± 0.3 °/%trans) and M0 (4.8 ± 1.0 μm2 /ms, 0.70 ± 0.14, 0.1 ± 0.3 °/%trans) indicating less motion corruption and yielding values more consistent with previous literature. M2-derived DT-CMR parameters had higher reproducible (ICC > 0.85) and SR (82%) than M1 (ICC = 0.20-0.85; SR = 37%) and M0 (ICC = 0.20-0.30; SR = 11%). M2 DT-CMR was able to yield HA maps with smooth transmural transition from endocardium to epicardium. CONCLUSION The proposed M2 DT-CMR reproducibly yielded bulk motion robust estimations of mean LV MD, FA, HA, and HATS on a 3T clinical scanner. Magn Reson Med 76:1354-1363, 2016. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Christopher Nguyen
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Zhaoyang Fan
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Yibin Xie
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Jianing Pang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | | | - Xiaoming Bi
- Siemens Healthcare, Los Angeles, California, USA
| | - Jon Kobashigawa
- Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
- Department of Bioengineering, University of California Los Angeles, Los Angeles, California, USA.
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von Deuster C, Stoeck CT, Genet M, Atkinson D, Kozerke S. Spin echo versus stimulated echo diffusion tensor imaging of the in vivo human heart. Magn Reson Med 2015; 76:862-72. [PMID: 26445426 PMCID: PMC4989478 DOI: 10.1002/mrm.25998] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2015] [Revised: 07/29/2015] [Accepted: 09/01/2015] [Indexed: 12/13/2022]
Abstract
Purpose To compare signal‐to‐noise ratio (SNR) efficiency and diffusion tensor metrics of cardiac diffusion tensor mapping using acceleration‐compensated spin‐echo (SE) and stimulated echo acquisition mode (STEAM) imaging. Methods Diffusion weighted SE and STEAM sequences were implemented on a clinical 1.5 Tesla MR system. The SNR efficiency of SE and STEAM was measured (b = 50–450 s/mm2) in isotropic agar, anisotropic diffusion phantoms and the in vivo human heart. Diffusion tensor analysis was performed on mean diffusivity, fractional anisotropy, helix and transverse angles. Results In the isotropic phantom, the ratio of SNR efficiency for SE versus STEAM, SNRt(SE/STEAM), was 2.84 ± 0.08 for all tested b‐values. In the anisotropic diffusion phantom the ratio decreased from 2.75 ± 0.05 to 2.20 ± 0.13 with increasing b‐value, similar to the in vivo decrease from 2.91 ± 0.43 to 2.30 ± 0.30. Diffusion tensor analysis revealed reduced deviation of helix angles from a linear transmural model and reduced transverse angle standard deviation for SE compared with STEAM. Mean diffusivity and fractional anisotropy were measured to be statistically different (P < 0.001) between SE and STEAM. Conclusion Cardiac DTI using motion‐compensated SE yields a 2.3–2.9× increase in SNR efficiency relative to STEAM and improved accuracy of tensor metrics. The SE method hence presents an attractive alternative to STEAM based approaches. Magn Reson Med 76:862–872, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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Affiliation(s)
- Constantin von Deuster
- Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.,Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Christian T Stoeck
- Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.,Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Martin Genet
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - David Atkinson
- Centre for Medical Imaging, University College London, London, United Kingdom
| | - Sebastian Kozerke
- Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.,Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
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Stoeck CT, von Deuster C, Genet M, Atkinson D, Kozerke S. Second-order motion-compensated spin echo diffusion tensor imaging of the human heart. Magn Reson Med 2015; 75:1669-76. [PMID: 26033456 DOI: 10.1002/mrm.25784] [Citation(s) in RCA: 84] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2014] [Revised: 04/21/2015] [Accepted: 05/01/2015] [Indexed: 12/13/2022]
Abstract
PURPOSE Myocardial microstructure has been challenging to probe in vivo. Spin echo-based diffusion-weighted sequences allow for single-shot acquisitions but are highly sensitive to cardiac motion. In this study, the use of second-order motion-compensated diffusion encoding was compared with first-order motion-compensated diffusion-weighted imaging during systolic contraction of the heart. METHODS First- and second-order motion-compensated diffusion encoding gradients were incorporated into a triggered single-shot spin echo sequence. The effect of contractile motion on the apparent diffusion coefficients and tensor orientations was investigated in vivo from basal to apical level of the heart. RESULTS Second-order motion compensation was found to increase the range of systolic trigger delays from 30%-55% to 15%-77% peak systole at the apex and from 25%-50% to 15%-79% peak systole at the base. Diffusion tensor analysis yielded more physiological transmural distributions when using second-order motion-compensated diffusion tensor imaging. CONCLUSION Higher-order motion-compensated diffusion encoding decreases the sensitivity to cardiac motion, thereby enabling cardiac DTI over a wider range of time points during systolic contraction of the heart.
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Affiliation(s)
- Christian T Stoeck
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Constantin von Deuster
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.,Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Martin Genet
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - David Atkinson
- Centre for Medical Imaging, University College London, London, United Kingdom
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.,Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
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