RCA FAI and PFD are independent predictors of cerebral ischaemic events, with Model 5 achieving an AUC of 0.821, sensitivity of 0.788, and specificity of 0.827.
Does a combined radiomics model of multimodal adipose tissue improve risk stratification for transient ischaemic attacks and ischaemic stroke in patients with coronary artery disease?
Integrating clinical characteristics with coronary and cervical CTA parameters and radiomics significantly enhances risk stratification for ischaemic stroke and TIA in patients with coronary artery disease.
Absolute Event Rate: 0% vs 0%
Background/Objectives: Patients with combined cardiovascular and cerebrovascular disease face poorer prognoses. Early, accurate assessment of the risk of cerebral ischaemic events (including transient ischaemic attacks (TIAs) and ischaemic strokes (ISs)) in patients with coronary artery disease (CAD) is therefore vital for clinical guidance. This study aims to develop a comprehensive risk assessment model for early warning in this population. Methods: In this study, we conducted a retrospective multicentre recruitment of CAD patients undergoing concurrent coronary CTA and cervical CTA (n = 326), with follow-up to observe the occurrence of cerebral ischaemic events. We performed an analysis of high-risk plaque (HRP) characteristics and subcomponent plaque in coronary and cervical arteries, measured the pericoronary fat attenuation index (FAI) and cervical perivascular fat density (PFD), and extracted corresponding radiomic features. Five models were constructed to identify the CAD patients who developed IS/TIA, respectively: Model 1—clinical characteristics; Model 2—coronary CTA parameters + Radscorecoronary; Model 3—cervical CTA parameters + Radscorecervical; Model 4—Model 1 + Model 2; Model 5—Model 1 + Model 2 + Model 3. Results: In the cerebral ischaemia group, the prevalence of coronary and/or cervical HRP was higher than in the non-ischaemia group (28.0% vs. 26.1%, 57.0% vs. 44.0%, p = 0.02). Multivariate logistic regression confirmed that RCA FAI and PFD remained significant independent risk factors for IS/TIA (all p < 0.05). The model prediction results showed that progressively incorporating coronary and cerebral vascular risk factors into the clinical features gradually improved model performance (Model 4 vs. Model 5, AUC: 0.711 0.645–0.777 vs. 0.821 0.769–0.873). Model 5 achieved a sensitivity of 0.788 0.485–0.909 and specificity of 0.827 0.385–0.923, demonstrating the best overall clinical benefit. Conclusions: RCA FAI and PFD are independent predictors of cerebral ischaemic events. By integrating clinical characteristics, coronary CTA and cervical CTA parameters, combined with Radscorecoronary and Radscorecervical, the risk stratification capability for IS/TIA in CAD patients can be significantly enhanced.
Li et al. (Thu,) reported a other. RCA FAI and PFD are independent predictors of cerebral ischaemic events, with Model 5 achieving an AUC of 0.821, sensitivity of 0.788, and specificity of 0.827.
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