ArticleIEEE transactions on medical imaging2020
Estimating Aggregate Cardiomyocyte Strain Using In Vivo Diffusion and Displacement Encoded MRI.
Article in IEEE transactions on medical imaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Automated cardiac strain estimation from short-axis DENSE and Cine MR images.Biomechanics and modeling in mechanobiology · 2026Article
- MR perfusion source mapping depicts venous territories and reveals perfusion modulation during neural activation.Nature communications · 2025Article
- Strain mapping using compressed sensing accelerated 4D flow MRI-Potential for detecting coactivation in thigh muscles.Frontiers in physiology · 2025Article
- In-silico heart model phantom to validate cardiac strain imaging.Computers in biology and medicine · 2024Article
- In-silico heart model phantom to validate cardiac strain imaging.bioRxiv : the preprint server for biology · 2024Article
- Myocardial mesostructure and mesofunction.American journal of physiology. Heart and circulatory physiology · 2022Review
- Comparison of interpolation methods of predominant cardiomyocyte orientation from in vivo and ex vivo cardiac diffusion tensor imaging data.NMR in biomedicine · 2022Article
- Reproducibility of global and segmental myocardial strain using cine DENSE at 3 T: a multicenter cardiovascular magnetic resonance study in healthy subjects and patients with heart disease.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2022Article
- Cardiac Diffusion Tensor Biomarkers of Chronic Infarction Based on In Vivo Data.Applied sciences (Basel, Switzerland) · 2022Article
- Personalization of biomechanical simulations of the left ventricle by in-vivo cardiac DTI data: Impact of fiber interpolation methods.Frontiers in physiology · 2022Article
- Using synthetic data generation to train a cardiac motion tag tracking neural network.Medical image analysis · 2021Article
- Myofiber strain in healthy humans using DENSE and cDTI.Magnetic resonance in medicine · 2021Article
- Arbitrary Point Tracking with Machine Learning to Measure Cardiac Strains in Tagged MRI.Functional imaging and modeling of the heart : ... International Workshop, FIMH ..., proceedings. FIMH (Conference) · 2021Article
- Fully-automated global and segmental strain analysis of DENSE cardiovascular magnetic resonance using deep learning for segmentation and phase unwrapping.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2021Article
- Estimating cardiomyofiber strain in vivo by solving a computational model.Medical image analysis · 2021Article
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6 authors.
Funding
Abstract
Changes in left ventricular (LV) aggregate cardiomyocyte orientation and deformation underlie cardiac function and dysfunction. As such, in vivo aggregate cardiomyocyte "myofiber" strain ( [Formula: see text]) has mechanistic significance, but currently there exists no established technique to measure in vivo [Formula: see text]. The objective of this work is to describe and validate a pipeline to compute in vivo [Formula: see text] from magnetic resonance imaging (MRI) data. Our pipeline integrates LV motion from multi-slice Displacement ENcoding with Stimulated Echoes (DENSE) MRI with in vivo LV microstructure from cardiac Diffusion Tensor Imaging (cDTI) data. The proposed pipeline is validated using an analytical deforming heart-like phantom. The phantom is used to evaluate 3D cardiac strains computed from a widely available, open-source DENSE Image Analysis Tool. Phantom evaluation showed that a DENSE MRI signal-to-noise ratio (SNR) ≥20 is required to compute [Formula: see text] with near-zero median strain bias and within a strain tolerance of 0.06. Circumferential and longitudinal strains are also accurately measured under the same SNR requirements, however, radial strain exhibits a median epicardial bias of -0.10 even in noise-free DENSE data. The validated framework is applied to experimental DENSE MRI and cDTI data acquired in eight ( N=8 ) healthy swine. The experimental study demonstrated that [Formula: see text] has decreased transmural variability compared to radial and circumferential strains. The spatial uniformity and mechanistic significance of in vivo [Formula: see text] make it a compelling candidate for characterization and early detection of cardiac dysfunction.
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