ArticleFunctional imaging and modeling of the heart : ... International Workshop, FIMH ..., proceedings. FIMH (Conference)2021
An image registration framework to estimate 3D myocardial strains from cine cardiac MRI in mice.
Article in Functional imaging and modeling of the heart : ... International Workshop, FIMH ..., proceedings. FIMH (Conference), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Computational modeling of left ventricular flow using PC-CMR-derived four-dimensional wall motion.International journal of engineering science · 2026Article
- Advancing cardiac motion estimation with emerging AI techniques for enhanced echocardiographic image registration.MethodsX · 2025Article
- Physics-Informed In-Silico Dynamic Computed Tomography of Human Lungs: Generation, Evaluation, and Refinement.Journal of biomechanical engineering · 2025Article
- Principal Strain Analysis for Early Detection of Radiation-Induced Cardiotoxicity in a Mouse Model.International journal of radiation oncology, biology, physics · 2025Article
- Complete spatiotemporal quantification of cardiac motion in mice through multi-view magnetic resonance imaging and super-resolution reconstruction.Scientific reports · 2025Article
- Non-Invasive Diagnosis of Chronic Myocardial Infarction via Composite In-Silico-Human Data Learning.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- FEBio FINESSE: An Open-Source Finite Element Simulation Approach to Estimate In Vivo Heart Valve Strains Using Shape Enforcement.Annals of biomedical engineering · 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
- Article
- Multi-Modality Deep Infarct: Non-invasive identification of infarcted myocardium using composite in-silico-human data learning.Research square · 2024Article
- Multi-Modality Deep Infarct: Non-invasive identification of infarcted myocardium using composite in-silico-human data learning.bioRxiv : the preprint server for biology · 2024Article
- In-silico CT lung phantom generated from finite-element mesh.Proceedings of SPIE--the International Society for Optical Engineering · 2024Article
- On the possibility of estimating myocardial fiber architecture from cardiac strains.Functional imaging and modeling of the heart : ... International Workshop, FIMH ..., proceedings. FIMH (Conference) · 2023Article
- Contractile Adaptation of the Left Ventricle Post-myocardial Infarction: Predictions by Rodent-Specific Computational Modeling.Annals of biomedical engineering · 2023Article
- Improved right ventricular strain estimation in rats using anisotropic diffusion filtering.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
- Volumetric versus distortional deformation in rat lungs.Proceedings of SPIE--the International Society for Optical Engineering · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Accurate and efficient quantification of cardiac motion offers promising biomarkers for non-invasive diagnosis and prognosis of structural heart diseases. Cine cardiac magnetic resonance imaging remains one of the most advanced imaging tools to provide image acquisitions needed to assess and quantify in-vivo heart kinematics. The majority of cardiac motion studies are focused on human data, and there remains a need to develop and implement an image-registration pipeline to quantify full three-dimensional (3D) cardiac motion in mice where ideal image acquisition is challenged by the subject size and heart rate and the possibility of traditional tagged imaging is hampered. In this study, we used diffeomorphic image registration to estimate strains in the left ventricular wall in two wild-type mice and one diabetic mouse. Our pipeline resulted in a continuous and fully 3D strain map over one cardiac cycle. The estimation of 3D regional and transmural variations of strains is a critical step towards identifying mechanistic biomarkers for improved diagnosis and phenotyping of structural left heart diseases including heart failure with reduced or preserved ejection fraction.
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