Abstract
MRI-driven computational modeling is increasingly used to simulate in vivo cardiac mechanical behavior and estimate subject-specific myocardial stiffness. However, in vivo validation of these estimates is exceedingly difficult due to the lack of a known ground-truth in vivo myocardial stiffness. We have developed 3D-printed heart phantoms of known myocardium-mimicking stiffness and MRI relaxation properties and incorporated the heart phantoms within a highly controlled MRI-compatible setup to simulate in vivo diastolic filling. The setup enables the acquisition of experimental data needed to evaluate myocardial stiffness using computational constitutive modeling: phantom geometry, loading pressures, boundary conditions, and filling strains. The pressure-volume relationship obtained from the phantom setup was used to calibrate an in silico model of the heart phantom undergoing simulated diastolic filling. The model estimated stiffness was compared to a ground-truth stiffness obtained from uniaxial tensile testing. Ultimately, the setup is designed to enable extensive validation of MRI and FEM-based myocardial stiffness estimation frameworks.
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This work was supported by NIH R01 HL131823 to DBE.
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Kolawole, F.O. et al. (2021). A Framework for Evaluating Myocardial Stiffness Using 3D-Printed Heart Phantoms. In: Ennis, D.B., Perotti, L.E., Wang, V.Y. (eds) Functional Imaging and Modeling of the Heart. FIMH 2021. Lecture Notes in Computer Science(), vol 12738. Springer, Cham. https://doi.org/10.1007/978-3-030-78710-3_30
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DOI: https://doi.org/10.1007/978-3-030-78710-3_30
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