モヤモヤ病に対する直接バイパス術後の脳高灌流症候群の術前局所血行動態予測:ASPECTSトポグラフィーに基づく定量的CT灌流画像研究
Jiatong Zhang1,2, Lu Wang2,3, Yi Wang1,2
1Department of Neurosurgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu Province, China.
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), p = 0.018), and lower PCA Tmax (OR (95% CI), 0.03 (0.00-0.69), p = 0.029) as independent predictors. ROC analysis demonstrated that combining Suzuki stage and PCA Tmax achieved an AUC of 0.83 (cut-off value = 0.060), indicating good discriminative performance for predicting postoperative CHS.
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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