Prediction of hemorrhagic transformation via pre-treatment CT radiomics in acute ischemic stroke patients receiving endovascular therapy.

ABSTRACT

OBJECTIVE: This study aimed to extract radiomics features (RFs) from pre-treatment CT scans in patients with acute ischemic stroke (AIS), and to establish a radiomics model to predict hemorrhagic transformation (HT) after endovascular therapy (EVT). METHODS: A total of 105 patients who were diagnosed with AIS [with occlusion of the M1 segment of the middle cerebral artery (MCA) and/or internal carotid artery] and received EVT were enrolled. They were randomly divided into the development cohort (n = 73) and the validation cohort (n = 32). The clinicoradiological data of all patients, including pre-treatment cranial CT without contrast enhancement, CT perfusion, and CT angiography, were obtained. The MCA territory on pre-treatment CT images was segmented to extract RFs associated with HT after EVT. Then, a CT radiomics model based on the selected RFs was constructed to predict HT after EVT. RESULTS: The sensitivity, specificity, and area under the curve of the CT radiomics model for predicting HT after EVT based on pre-treatment CT RFs was 0.806, 0.649, and 0.781 (95% confidence interval (CI) 0.675-0.886), respectively, in the development cohort. The sensitivity, specificity, and area under the curve in the validation cohort was 0.625, 0.875, and 0.797 (95% CI 0.642-0.951), respectively. CONCLUSION: CT radiomics analysis is a valuable tool for predicting HT in AIS patients receiving EVT. It may guide the selection of patients in practice and improve procedural safety and effectiveness. ADVANCES IN KNOWLEDGE Identification of the importance of pre-treatment CT radiomics in the prediction of HT in AIS patients after EVT.