The role of plaque morphology and composition in vulnerability assessment: Computational analysis using CT images and elastography

Objective This study seeks to assess the influence of using patient-specific data from different imaging methods on evaluating carotid plaque vulnerability via finite element analysis (FEA) instead of using data derived from the literature. Methods 54 patients were considered in this analysis, who preoperatively underwent computed tomography angiography (CTA) and ultrasound (US) imaging evaluations. The composition (i.e. calcific, lipidic and mixed) and vulnerability (i.e. stable or vulnerable) of their plaques were evaluated by macroscopic and histologic assessment post-endarterectomy. In particular, the plaques of these 54 patients were classified as mixed. 3D reconstructions of the carotid artery were generated from CTA scans, and computational analyses were performed using two different simulation settings for material properties and loads: a) the material properties of the plaque components were set as an average of values available in the literature (LIT-based); b) the material property of the plaque fibrous content was modified using stiffness data derived from US shear-wave elastography imaging (SWE-based). Statistical analyses were conducted to compare stress parameters obtained from the different simulations within groups of vulnerable and stable plaques. Results Comparisons between LIT-based and SWE-based FEA revealed notable differences in stress parameters associated with plaque vulnerability. In particular, the stress values derived from SWE-based simulations provided distinct stratification of vulnerable versus stable plaques, whereas LIT-based models showed limited differentiation. Significant variations in von Mises ( p = 0.015, p = 0.037) and maximum principal stress ( p = 0.014) distributions were observed in SWE-based FEA. Conclusions Patient-specific modelling and computational analysis integrating CTA-derived morphological with US-derived biomechanical data could improve the assessment of plaque vulnerability in mixed-composition carotid plaques.