Quantitative contrast enhancement volume on immediate post-thrombectomy CT predicts symptomatic intracranial hemorrhage and functional outcomes in acute large vessel occlusion stroke - Huang, Ziyang; Xiong, Zhiyu; Gong, Chen; Jiang, Shuyu; Huang, Liping; Wang, You; Yuan, Jinxian; Gao, Yuan; Ban, Yuenan; Chen, Yangmei; Xu, Tao (Frontiers in Neurology, 2025)
ObjectivesSymptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) for acute ischemic stroke due to anterior circulation large vessel occlusion (AIS-LVO) significantly impacts clinical outcomes. Contrast enhancement (CE) on immediate post-EVT non-contrast CT (NCCT) may reflect blood–brain barrier disruption, but its volumetric correlation with sICH and functional independence remains underexplored.MethodsWe performed a retrospective screening on consecutive AIS-LVO patients who had CE on NCCT immediately within 2 h after EVT. The quantitative volume of CE was calculated by using 3D Slicer software. Multivariable logistic regression was performed to achieve the risk factors of sICH and functional independence. The discrimination and calibration of the multivariable models were assessed using the area under the receiver operator characteristic curve, fivefold cross-validation, calibration curve, and decision curve analysis.ResultsIn this study, 111 patients were enrolled in the final analysis. According to the restricted cubic spline, 10.6 mL was the optimal threshold of CE volume dichotomization for patients with AIS-LVO. In multivariate regression analysis, the CE+ group (CE volume beyond 10.6 mL) was significantly associated with sICH (aOR: 5.24, 95% CI: 1.45–18.99, p = 0.012) and functional independence (10.9% vs. 51.8%; aOR 0.05, 95% CI: 0.01–0.28, p < 0.001). The multivariable models demonstrated good discrimination and calibration in this cohort, as well as the fivefold cross-validation.ConclusionVolumetric quantification of CE on immediate post-EVT NCCT serves as a novel biomarker for early sICH risk stratification and functional prognosis in AIS-LVO. Incorporating CE volume into predictive models enhances clinical utility, enabling timely diagnosis and intervention.