Frontiers in human neuroscience · 2026
Combined assessment of FLAIR vascular hyperintensities and cortical venous outflow for outcome prediction in acute middle cerebral artery occlusion.
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Yang Ping, Xu Lingjia, Zhou Feng
Аннотация
BACKGROUND: Fluid-attenuated inversion recovery vascular hyperintensities (FVHs) are an imaging marker of leptomeningeal collateral compensation, but their prognostic value in stroke remains controversial. Venous outflow (VO) dysfunction may offset collateral benefits, suggesting that VO status could modulate the prognostic effect of FVHs. In this study, we combined the assessment of FVHs and VO in patients with acute middle cerebral artery (MCA) occlusion who did not receive reperfusion treatment, to determine whether the arteriovenous coupling state predicts 90-day good outcome.
METHODS: A total of 152 patients were enrolled and divided into four groups based on FVHs and VO status: Type I (good coupling), Type II (arteriovenous mismatch), Type III (hypoperfusion), and Type IV (arteriovenous failure). G02 was a binary indicator of arteriovenous mismatch (Type II vs. non-Type II), derived from the four-group classification. Multivariable logistic regression was used to analyze the independent association between the four groups and 90-day good outcome. A prediction model was constructed with a baseline model including National Institutes of Health Stroke Scale (NIHSS) score, diffusion-weighted imaging (DWI) volume, and age, and a full model adding G02 to the baseline model. Model performance was evaluated using 5-fold cross-validation with AUC, calibration curves, and decision curves.
RESULTS: Of the 152 patients, 28 (18.4%) were classified as Type II, which was independently associated with reduced odds of good 90-day outcome (OR = 0.041, 95%CI 0.003 ~ 0.506). Adding G02 to the baseline model (NIHSS + DWI volume + age) improved the AUC from 0.759 to 0.780 (NRI = 0.0305, IDI = 0.0348), and the full model showed greater net benefit on decision curve analysis.
CONCLUSION: Our findings suggest that impaired VO may offset the favorable effect of collateral compensation reflected by FVHs. In non-reperfused acute MCA occlusion, arteriovenous mismatch independently predicts poor prognosis. Adding this marker to conventional clinical variables modestly improves prognostic performance and provides greater net clinical benefit, supporting combined arterial and venous assessment for stroke risk stratification.
METHODS: A total of 152 patients were enrolled and divided into four groups based on FVHs and VO status: Type I (good coupling), Type II (arteriovenous mismatch), Type III (hypoperfusion), and Type IV (arteriovenous failure). G02 was a binary indicator of arteriovenous mismatch (Type II vs. non-Type II), derived from the four-group classification. Multivariable logistic regression was used to analyze the independent association between the four groups and 90-day good outcome. A prediction model was constructed with a baseline model including National Institutes of Health Stroke Scale (NIHSS) score, diffusion-weighted imaging (DWI) volume, and age, and a full model adding G02 to the baseline model. Model performance was evaluated using 5-fold cross-validation with AUC, calibration curves, and decision curves.
RESULTS: Of the 152 patients, 28 (18.4%) were classified as Type II, which was independently associated with reduced odds of good 90-day outcome (OR = 0.041, 95%CI 0.003 ~ 0.506). Adding G02 to the baseline model (NIHSS + DWI volume + age) improved the AUC from 0.759 to 0.780 (NRI = 0.0305, IDI = 0.0348), and the full model showed greater net benefit on decision curve analysis.
CONCLUSION: Our findings suggest that impaired VO may offset the favorable effect of collateral compensation reflected by FVHs. In non-reperfused acute MCA occlusion, arteriovenous mismatch independently predicts poor prognosis. Adding this marker to conventional clinical variables modestly improves prognostic performance and provides greater net clinical benefit, supporting combined arterial and venous assessment for stroke risk stratification.