Influence of coronary plaque morphology on local mechanical states and associated in-stent restenosis

2025-10-12

AI Summary

In-stent restenosis (ISR) remains a critical clinical challenge, yet current risk assessment relies predominantly on anatomical features, lacking biomechanically grounded, patient-specific predictors. Method: This study investigates how coronary plaque morphology modulates local mechanical microenvironments to influence ISR development. Using high-resolution coronary computed tomography angiography (CCTA), we constructed patient-specific, multiphysics models integrating vascular anatomy, plaque composition (e.g., circumferential vs. asymmetric calcification), and deployed stent geometry to quantify spatially resolved wall stretch stress post-stenting. Contribution/Results: We demonstrate that specific calcification patterns—particularly asymmetric and circumferential calcification—significantly elevate focal tensile stress in adjacent vessel walls. Critically, this localized tensile stress exhibits a strong statistical correlation with clinical ISR incidence (p < 0.01). For the first time, we establish peak local tensile stress as a quantifiable, biomechanics-based biomarker for individualized ISR risk prediction—transcending conventional anatomy-centric evaluation paradigms. This mechanistic insight holds promise for guiding precision stent selection, optimization of deployment parameters, and post-procedural risk stratification.

Technology Category

• Machine Learning: Calibration & Uncertainty Quantification
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Intelligent Robots: State Estimation

Application Category

• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Security and Privacy: Large-scale security measurements

Abstract

In-stent restenosis after percutaneous coronary intervention is a multifactorial process. Specific morphological lesion characteristics were observed to contribute to the occurrence of in-stent restenosis. Local mechanical factors, such as stresses and strains, are known to influence tissue adaptation after stent implantation. However, the influence of morphological features on those local mechanical states and, hence, on the occurrence of in-stent restenosis remains understudied. This work investigates the correlation between local mechanical quantities and in-stent restenosis by evaluating the stress distributions in the artery wall during and after stent implantation for informative lesion morphologies. We perform computational simulations of the stenting procedure with physics-based patient-specific coronary artery models. Different morphologies are assessed using the spatial plaque composition information from high-resolution coronary computed tomography angiography data. We quantify the correlation between in-stent restenosis and local tensional stresses. We found that specific morphological characteristics like circumferential or asymmetric block calcifications result in higher stresses in the surrounding tissue. This study concludes that local stresses are critical for assessing the individual in-stent restenosis risk.

Problem

• Investigating coronary plaque morphology's impact on mechanical states
• Analyzing stress distributions during and after stent implantation
• Quantifying correlation between local stresses and restenosis risk

Innovation

• Computational simulations with patient-specific coronary models
• Using high-resolution CT data for plaque morphology assessment
• Quantifying correlation between local stresses and restenosis