An Image-Based Computational Framework to Evaluate the Material Stiffness of Arterial Tissue With High-Resolution Magnetic Resonance Imaging.

ABSTRACT: Atherosclerotic plaque rupture is the precipitating event in most acute coronary syndromes. As rupture results from the material failure of arterial tissue under mechanical loading, in vivo image-based techniques that can accurately characterize arterial material stiffness offer potential in risk-stratifying lesions. This study developed and validated a novel magnetic resonance (MR) image-based computational framework to evaluate the material stiffness of vascular tissue. Porcine carotid arteries (n = 4) were subjected to biaxial mechanical testing, followed by MR image acquisition under controlled loading. Best-fit material parameters for an anisotropic material model were estimated via regression analysis on the biaxial data. A deformable image registration technique, termed hyperelastic

SUBMITTER: Wang YFJ 

PROVIDER: S-EPMC12362311 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature