CRESTomics: Analyzing Carotid Plaques in the CREST-2 Trial with a New Additive Classification Model

2026-03-04

AI Summary

This study addresses the critical need for accurate stroke risk assessment of carotid plaques by proposing a novel kernel additive classification model. Leveraging 500 ultrasound images from the multicenter CREST-2 trial, the method integrates coherence loss with group sparsity regularization to simultaneously preserve nonlinear classification performance and enhance model interpretability. Feature group effects are visualized via partial dependence plots, revealing a strong association between plaque texture characteristics and clinically high-risk status. The approach achieves a favorable balance between predictive accuracy and interpretability, offering a reliable tool for carotid plaque risk stratification in clinical practice.

Technology Category

• Machine Learning: Kernel Methods
• Computer Vision: Interpretability, Explainability, and Transparency
• Reasoning under Uncertainty: Graphical Models

Application Category

• User Modeling, Personalization and Recommendation: Explainable and interpretable methods for personalization
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• Web Mining and Content Analysis: Normalization, clustering, classification, and summarization of Web text

Abstract

Accurate characterization of carotid plaques is critical for stroke prevention in patients with carotid stenosis. We analyze 500 plaques from CREST-2, a multi-center clinical trial, to identify radiomics-based markers from B-mode ultrasound images linked with high-risk. We propose a new kernel-based additive model, combining coherence loss with group-sparse regularization for nonlinear classification. Group-wise additive effects of each feature group are visualized using partial dependence plots. Results indicate our method accurately and interpretably assesses plaques, revealing a strong association between plaque texture and clinical risk.

Problem

• carotid plaques
• stroke prevention
• radiomics
• carotid stenosis
• B-mode ultrasound

Innovation

• additive model
• coherence loss
• group-sparse regularization
• radiomics
• carotid plaque