ArticleFrontiers in neurology2025
Preoperative local hemodynamics predict cerebral hyperperfusion syndrome after direct bypass for moyamoya disease: a quantitative CTP study based on ASPECT topography.
Article in Frontiers in neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Advances in cerebrovascular reserve function assessment for moyamoya disease.BMJ neurology open · 2026Review
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6 authors.
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Abstract
Background and objective: Postoperative cerebral hyperperfusion syndrome (CHS) remains a common and serious complication after extracranial-intracranial (EC-IC) bypass for moyamoya disease (MMD). This study aimed to identify preoperative hemodynamic predictors of CHS using quantitative whole-brain CT perfusion (WB-CTP) analysis. Methods: The author retrospectively analyzed 103 hemispheres from 89 MMD patients who underwent direct bypass from January 2024 to December 2024. Preoperative WB-CTP scans based on the Alberta Stroke Program Early CT score (ASPECTS) topography were processed to quantify cerebral blood flow (CBF) and time to peak (Tmax) across various brain regions, with the cerebellum serving as the reference. CHS was diagnosed based on clinical and radiological criteria. Univariable and multivariable logistic regression analyses were performed to identify independent predictors, and receiver operating characteristic (ROC) analysis was used to evaluate predictive performance. Results: Postoperative CHS occurred in 11.7% (12/103) of the included cases. Univariable analysis revealed Suzuki stage, moyamoya vessel density, and Tmax values in the thalamus (THAL) and posterior cerebral artery (PCA) regions as significant factors. Multivariable analysis confirmed advanced Suzuki stage (OR (95% CI), 8.87(1.44-54.45), Conclusion: Advanced Suzuki stage and reduced PCA Tmax are independent risk factors for postoperative CHS after direct bypass in MMD patients. Preoperative ASPECTS-based quantitative CTP analysis can effectively stratify CHS risk and support individualized surgical planning and perioperative management.
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