Abstract
Image-based computational models have been introduced to calculate plaque stress/strain conditions and investigate their association with plaque progression and rupture [Tang, Yang, Zheng, et al. (2004)]. However, the accuracy of the computational results is heavily dependent on the data and assumptions used by those models. Patient-specific vessel material properties are in general lacking in image-based computational models, limiting the accuracy of their stress/strain calculations. A noninvasive approach of combining in vivo 3D multi-contrast and Cine magnetic resonance imaging (MRI) and computational modeling was used to quantify patient-specific carotid plaque material properties for potential plaque model improvements [Wang, Canton, Guo, et al. (2017)]. The stress-based plaque vulnerability index (SPVI) was proposed to combine mechanical analysis, plaque morphology and composition for more complete carotid plaque vulnerability assessment.
Highlights
Image-based computational models have been introduced to calculate plaque stress/strain conditions and investigate their association with plaque progression and rupture [Tang, Yang, Zheng et al (2004)]
A simple numerical code was used to determine five stress intervals [0, a), [a, 2a), [2a, 3a), [3a, 4a), and [4a, +∞) corresponding to stress-based plaque vulnerability index (SPVI) values 0-4 to reach the best agreement between SPVI and MPSI
The five intervals [0, 46.8), [46.8, 80), [80, 92), [92, 103), and [103, +∞) from in vivo material models were used for SPVI values of 0, 1, 2, 3 and 4, respectively
Summary
Image-based computational models have been introduced to calculate plaque stress/strain conditions and investigate their association with plaque progression and rupture [Tang, Yang, Zheng et al (2004)]. School of Biological Science and Medical Engineering, Southeast University, Nanjing, 201196, China. Mathematical Sciences Department, Worcester Polytechnic Institute, Worcester, MA, 01609, USA.
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