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Updated: Sep 18, 2026

Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery
Published on: December 6, 2024
Material characterization of heterogenous atherosclerotic arteries with the Virtual Fields Method
Yanjing Liu1, Ronald D van den Berg2, Frank J H Gijsen3
1Department of Cardiology, Biomedical Engineering, Cardiovascular Institute, Thorax Center, Erasmus MC, Dr. Molewaterplein 40, Rotterdam, 3015GD, The Netherlands.
Background And Objective:
Rupture of an atherosclerotic plaque in an artery is the primary cause of life-threatening cardiovascular events. Plaque rupture is closely associated with elevated mechanical stresses within the plaque. Stress analysis of plaques, which are structurally heterogeneous due to their multi-component composition, holds significant potential to improve the rupture risk assessment of plaques, guiding clinical decision making and surgical planning. A major challenge, however, lies in the efficient and accurate characterization of plaque-specific mechanical properties.
Methods:
In this study, we introduce a novel framework based on the Virtual Fields Method (VFM) to identify the heterogeneous material properties of atherosclerotic plaques. We further propose a systematic strategy to generate virtual displacement fields (VDFs) tailored for pressurized tubular structures, such as the specific application of arteries, and determine the optimal number of VDFs for carotid artery plaques from ultrasound-derived measurements.
Results:
The proposed framework achieved high accuracy in estimating the mechanical properties of individual plaque components, even when realistic levels of noise in the ultrasound data were considered. The computation time was 11 ± 2.5 s for pre-clinical ultrasound resolution and 8.6 ± 2.3 s for clinical ultrasound resolution.
Conclusion:
This work presents the first implementation of VFM for the material characterization of heterogeneous atherosclerotic plaques. The robustness and computational efficiency of the framework provide a methodological basis for future studies toward in vivo plaque characterization.

