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Updated: Jan 16, 2026

Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery
Published on: December 6, 2024
Computational simulations of coronary artery bifurcation stenting using realistic plaque distribution and materials
Wei Wu1, Shijia Zhao1, Rakshita Ramesh Bhat1
1Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Leonard M. Miller School of Medicine, University of Miami Health System, University of Miami, 1120 NW 14th Street, Suite 1124, Miami, FL, 33136, USA.
Abstract:
Coronary bifurcation stenting is a technically demanding procedure that benefits from precise preoperative planning. Finite element analysis (FEA) offers a powerful framework for simulating stent deployment, with full-plaque (FP) models representing the most detailed and physiologically realistic approach. In this study, we developed and validated an FP finite element model for coronary bifurcation stenting, aiming to establish a reference standard for future model assessments. High-resolution pre-stenting optical coherence tomography (OCT) data from nine patient cases were used to reconstruct anatomically accurate 3D models, incorporating detailed plaque compositions. Stent deployment was simulated following real clinical procedural steps. Model accuracy was assessed by comparing minimal lumen diameter (MLD) between simulations and post-stenting OCT measurements using Bland-Altman analysis. The FP model reliably reproduced multi-step stenting procedures, capturing vessel remodeling and stent deformation with high fidelity. The analysis showed a mean bias of 0.07 mm (2.1% error) with 95% limits of agreement from - 0.38 mm to 0.51 mm. These results demonstrate the model's high accuracy in replicating real-world stenting outcomes. Beyond validation, the FP model offers broad applications. It can serve as a benchmark for evaluating simplified, faster simulation tools, support patient-specific procedural planning, and enable inverse modeling to extract biomechanical properties of plaques. This study establishes the FP model as a robust and versatile platform with potential for future integration into real-time clinical workflows.
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