Improving Risk Stratification for Transient Ischaemic Attacks and Ischaemic Stroke in Patients with Coronary Artery
Na Li1, Shuting Wang1, Hong Pan1
1Department of Radiology, Fourth Affiliated Hospital of Harbin Medical University, Harbin 150001, China.
Insights
Coronary artery disease patients with high-risk plaque, identified by coronary artery and cervical artery imaging, face increased risk of cerebral ischaemic events. A comprehensive model integrating clinical data and imaging features significantly enhances risk prediction for these events.
Area of Science:
- Cardiovascular Medicine
- Neurology
- Radiology
Background:
- Patients with combined cardiovascular and cerebrovascular disease have poorer prognoses.
- Early, accurate risk assessment for cerebral ischaemic events is crucial for patients with coronary artery disease (CAD).
- This study developed a comprehensive risk assessment model for early warning in CAD patients.
Purpose of the Study:
- To develop and validate a comprehensive risk assessment model for predicting cerebral ischaemic events in CAD patients.
- To identify independent predictors of ischaemic events in CAD patients using imaging features.
- To enhance the risk stratification capability for ischaemic events in CAD patients.
Main Methods:
- Retrospective multicentre study of 326 CAD patients undergoing coronary CTA and cervical CTA.
- Analysis of high-risk plaque (HRP) characteristics, pericoronary fat attenuation index (FAI), and cervical perivascular fat density (PFD).
- Development of five risk prediction models, integrating clinical characteristics, CTA parameters, and radiomic features (Radscore).
Main Results:
- The prevalence of coronary and/or cervical HRP was higher in the cerebral ischaemia group.
- RCA FAI and PFD were confirmed as significant independent risk factors for ischaemic stroke/transient ischaemic attack (IS/TIA).
- The integrated model (Model 5) incorporating clinical data, coronary CTA, and cervical CTA parameters achieved the best performance (AUC: 0.821), with high sensitivity (0.788) and specificity (0.827).
Conclusions:
- Pericoronary fat attenuation index (FAI) and perivascular fat density (PFD) are independent predictors of cerebral ischaemic events in CAD patients.
- Integrating clinical characteristics, coronary CTA, and cervical CTA parameters with radiomic scores significantly enhances risk stratification for IS/TIA.
- The developed comprehensive model offers improved clinical benefit for early warning and management of cerebral ischaemic events in CAD patients.
Abstract:
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.
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