A 3D personalized cardiac myocyte aggregate orientation model using MRI data-driven low-rank basis functions

摘要: Abstract Cardiac myocyte aggregate orientation has a strong impact on cardiac electrophysiology and mechanics. Studying the link between structural characteristics, strain, stresses over cycle function requires full volumetric representation of microstructure. In this work, we exploit similarity across hearts to extract low-rank predominant in left ventricle from high-resolution magnetic resonance ex-vivo diffusion tensor imaging (cDTI) porcine hearts. We compared two reduction methods, Proper Generalized Decomposition combined with Singular Value Orthogonal Decomposition. demonstrate existence general set basis functions aggregated which defines data-driven, personalizable, parametric model featuring higher flexibility than existing atlas rule-based approaches. A more detailed microstructure matching available patient data can improve accuracy personalized computational models. Additionally, approximate one human heart feasibility transferring humans.