Abstract #4457

Framework for Characterizing in vivo Passive Myocardial Stiffness using in vivo MRI

Fikunwa O Kolawole^1,2,3, Tyler E Cork^1,2,4, Michael Loecher^1,2, Vicky Y Wang^1,2, Ellen Kuhl³, and Daniel B Ennis^1,2

¹Radiology, Stanford University, Stanford, CA, United States, ²Radiology, Veterans Administration Health Care System, Palo Alto, CA, United States, ³Mechanical Engineering, Stanford University, Stanford, CA, United States, ⁴Bioengineering, Stanford University, Stanford, CA, United States

Synopsis

Keywords: Myocardium, In Silico, computational modeling; inverse finite element modeling

As increased passive myocardial stiffness is implicated in the etiology of many cardiac diseases, its in vivo estimation can improve management of heart disease. MRI-driven computational constitutive modeling can be used to obtain subject-specific passive myocardial stiffness. We present a method for building an in silico model to estimate subject-specific passive myocardial stiffness by combining LV geometric data derived from cine bSSFP, regional kinematics extracted from tagged MRI, and myocardial microstructure measured using in vivo cDTI. This project aims to develop a clinically translatable in vivo passive myocardial stiffness evaluation framework by integrating cardiac MRI and computational modeling.

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