The value of venous outflow assessment based on multiphase CTA in predicting the prognosis of endovascular therapy for acute ischemic stroke patients
摘要
To investigate the predictive value of venous outflow (VO) assessment based on multiphase computed tomography angiography (mCTA) for the prognosis of acute ischemic stroke (AIS) patients with large vessel occlusion (LVO) undergoing endovascular therapy (EVT).
MethodsThis retrospective study included patients with AIS due to angiographically confirmed anterior circulation large vessel occlusion. Eligible patients were those who underwent multiphase CTA, CTP, and subsequent EVT between 2021 and 2024. VO was assessed using the cortical vein opacification score (COVES) across arterial, venous, and late venous phases, with scores of 3–6 defining good VO. The primary outcome was a dichotomized functional outcome at 90 days, assessed using the modified Rankin Scale (mRS) and categorized as good (mRS score 0–2) or poor (mRS score 3–6).Multivariate logistic regression analysis was used to identify independent predictors, and a predictive model was constructed. The predictive performance was evaluated using receiver operating characteristic (ROC) curve analysis.
ResultsA total of 106 patients were ultimately included in the analysis. Sixty-four (60.4%) patients achieved good functional outcomes. Multivariate logistic regression analysis showed that good VO in the peak venous phase (OR = 6.448,; 95%CI, 1.799–23.109; P = 0.004) and lower △Tmax (OR = 0.814; 95%CI,0.702–0.944; P = 0.006) were independently associated with a favorable outcome. The predictive model combining good VO in the peak venous phase and lower △Tmax demonstrated improved performance compared to either parameter alone (AUC = 0.787 ; 95%CI, 0.701–0.874).
ConclusionVO assessment based on mCTA, particularly the COVES score in the peak venous phase, serves as an independent predictor of 90-day functional outcome in AIS patients with anterior circulation large vessel occlusion after EVT, offering potential imaging evidence for clinical decision-making.