2024/07/21 by Rana Raza Mehdi, Mehdi, Rana Raza, Emilio A. Mendiola +7
Engineering · Medicine · #Cardiac Imaging and Diagnostics #Cardiovascular Function and Risk Factors #Elasticity and Material Modeling #FOS: Biological sciences #FOS: Physical sciences #Medical Physics (physics.med-ph) #Tissues and Organs (q-bio.TO)
paper · pdf · doi:10.48550/arxiv.2407.15254
openalex publication_date 2024/07/21 · openalex created_date 2025/01/05 · openalex updated_date 2026/07/28
Accurate assessment of myocardial tissue stiffness is pivotal for the diagnosis and prognosis of heart diseases. Left ventricular diastolic stiffness (β) obtained from the end-diastolic pressure-volume relationship (EDPVR) has conventionally been utilized as a representative metric of myocardial stiffness. The EDPVR can be employed to estimate the intrinsic stiffness of myocardial tissues through image-based in-silico inverse optimization. However, whether β, as an organ-level metric, accurately represents the tissue-level myocardial tissue stiffness in healthy and diseased myocardium remains elusive. We developed a modeling-based approach utilizing a two-parameter material model for the myocardium (denoted by af and bf) in image-based in-silico biventricular heart models to generate EDPVRs for different material parameters. Our results indicated a variable relationship between β and the material parameters depending on the range of the parameters. Interestingly, β showed a very low sensitivity to af, once averaged across several LV geometries, and even a negative correlation with af for small values of af. These findings call for a critical assessment of the reliability and confoundedness of EDPVR-derived metrics to represent tissue-level myocardial stiffness. Our results also underscore the necessity to explore image-based in-silico frameworks, promising to provide a high-fidelity and potentially non-invasive assessment of myocardial stiffness.