TY - GEN
T1 - Does EDPVR Represent Myocardial Tissue Stiffness? Toward a Better Definition
AU - Mehdi, Rana Raza
AU - Mendiola, Emilio A.
AU - Naeini, Vahid
AU - Choudhary, Gaurav
AU - Avazmohammadi, Reza
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - EDPVR
KW - FE simulations
KW - LV diastolic stiffness
KW - myocardial material model
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U2 - 10.1109/EMBC53108.2024.10782464
DO - 10.1109/EMBC53108.2024.10782464
M3 - Conference contribution
AN - SCOPUS:85214974305
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
BT - 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024
Y2 - 15 July 2024 through 19 July 2024
ER -