Prediction of collateral circulation grading and functional outcomes in acute ischemic stroke using FLAIR vascular hyperintensity combined with multimodal CT parameters

利用FLAIR血管高信号结合多模态CT参数预测急性缺血性卒中侧支循环分级和功能预后

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Abstract

BACKGROUND/OBJECTIVES: The variability in acute ischemic stroke (AIS) outcomes is closely associated with collateral circulation status. While fluid-attenuated inversion recovery vascular hyperintensity (FVH) and multimodal CT parameters (e.g., rLMC score, rCBV) were associated with 90-day functional outcomes in AIS patients, their combined predictive value and clinical utility warrant further investigation. This study investigates the combined predictive value of FVH and multimodal CT parameters for collateral assessment and prognosis in AIS. METHODS: We retrospectively and consecutively enrolled AIS patients with internal carotid artery or middle cerebral artery stenosis/occlusion who did not receive intravenous thrombolysis or mechanical thrombectomy. All patients underwent one-stop CT angiography-CT perfusion and multimodal MRI within 72 h of symptom onset. Evaluations included FVH scores (based on modified ASPECTS regions), rLMC scores, Maas scores, and ASITN/SIR collateral grading. Spearman analysis assessed correlations between FVH and CTA collateral scores. Univariate and multivariate logistic regression indicated the independent predictors of a 90-day functional outcome [favorable (mRS 0-2) vs. poor (mRS 3-6)], with receiver operating characteristic (ROC) curves evaluating predictive performance. RESULTS: The cohort comprised 112 patients (70 favorable outcomes, 42 poor outcomes). FVH scores showed a negative correlation with ASITN/SIR collateral grades (r = -0.432, p < 0.001). Compared to the favorable outcome group, the poor outcome group exhibited higher baseline National Institute of Health Stroke Scale (NIHSS) scores, elevated FVH scores, reduced rLMC scores, and lower rCBV values (all p < 0.05). Multivariate analysis indicated that NIHSS score, FVH score, rLMC score, and rCBV were independent predictors of poor outcomes. ROC analysis demonstrated strong predictive performance for rLMC score (AUC = 0.848, 95%CI 0.778-0.919), FVH score (AUC = 0.662, 95%CI 0.550-0.774), and rCBV (AUC = 0.727, 95%CI 0.631-0.822). CONCLUSION: Multimodal CT combined with MRI facilitates early AIS diagnosis and collateral assessment. The integration of FVH with CT parameters (rLMC score and rCBV) was associated with the prediction of functional outcomes in AIS patients.

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