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Updated: May 6, 2026

A Magnetic Resonance Imaging Protocol for Stroke Onset Time Estimation in Permanent Cerebral Ischemia
Published on: September 16, 2017
Predicting early severe midline shift in acute ischemic stroke Within 24 h of endovascular thrombectomy
Nannan Han1, Xiaobo Zhang1, Yu Zhang2
1Department of Neurology, The Affiliated Hospital of Northwest University, Xi'an No.3 Hospital, Xi'an, China.
Purpose:
Early and severe (ES) midline shift (MLS ≥ 10 mm) simultaneously occurring within 24 h after endovascular thrombectomy (EVT) is a life-threatening emergency that requires immediate intervention. This study aims to describe ES-MLS and develop a predictive model in patients with anterior circulation occlusion who have undergone EVT.
Methods:
This retrospective cohort study utilized data from a prospective registry. Functional outcome was defined as a modified Rankin Scale score of 0-2. Radiomic features extracted from pre-EVT diffusion-weighted imaging were subjected to LASSO regression with fourfold cross-validation. Clinical features were selected via multivariable regression and integrated into a nomogram, with performance evaluated through receiver operating characteristic curve analysis in both training and validation datasets.
Results:
A total of 481 patients (median age 68 [IQR 58-76], 39.7% female) were included in this study, which consisted of a training dataset (n = 361) and a validation dataset (n = 120). In the ES-MLS group, 85.7% had died and none had a functional outcome at the 90-day follow-up. Recanalization, NIHSS score, and two radiomic features were identified as factors associated with ES-MLS in the nomogram. The predictive model exhibited an area under the curve (AUC) of 0.844 (95% confidence interval [CI], 0.803-0.880) in the training dataset and 0.823 (95% CI, 0.743-0.887) in the validation dataset.
Conclusion:
This is the initial structured overview of ES-MLS after EVT, featuring a model designed for personalized prediction of ES-MLS. The tool may enhance patient selection before EVT and refine the aggressive monitoring strategy after EVT.

