Combinations of Clinical Factors, CT Signs, Radiomics for Differentiating High-density Areas After Mechanical Thrombectomy in Patients with Acute Ischemic Stroke

BACKGROUND AND PURPOSE: Clinically, hemorrhagic transformation (HT) after mechanical thrombectomy (MT) is a common complication. This study is aim to investigate the value of clinical factors, CT signs, and radiomics in the differential diagnosis of high-density areas (HDAs) in the brain after MT in patients with acute ischemic stroke with large vessel occlusion (AIS-LVO).

MATERIALS AND METHODS: A total of 156 eligible patients with AIS-LVO in Center Ⅰ from December 2015 to June 2023 were retrospectively enrolled and randomly divided into training (n=109) and internal validation (n=47) sets at a ratio of 7:3. The data of 63 patients in Center Ⅱ were collected as an external validation set. According to the diagnostic criteria, the patients in the three datasets were divided into a HT group and a non-HT group. The clinical and imaging data from Centers Ⅰ and Ⅱ were used to construct a clinical factor and CT-sign model, a radiomic model and a combined model by logistic regression (LR). Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic efficacy of each model in the three datasets.

RESULTS: Clinical blood glucose (Glu) and the maximum cross-sectional area (Area_max) on CT were associated with the nature of the HDA according to multivariate LR analyses (P < 0.05). Among the three models, the combined model had the highest diagnostic efficiency, with area under the curve (AUC) values of 0.895, 0.882, and 0.820 in the three datasets, which were significantly greater than the AUC values of the radiomic model (0.887, 0.898, 0.798) and clinical factor and CT sign model (0.831, 0.744, 0.684).

CONCLUSIONS: The combined model based on radiomics had the best performance, indicating that radiomic features can be used as imaging biomarkers to aid in the clinical judgment of the nature of HDA after MT.

ABBREVIATIONS: HDA =high-density area; HT =hemorrhagic transformation; MT =mechanical thrombectomy; AIS-LVO =acute ischemic stroke with large vessel occlusion; LR =logistic regression; AUC =area under the curve; ICE =iodine contrast extravasation; DECT =dual energy CT; IOM =iodine overlay map; VNC =virtual noncontrast; Glu =glucose; LASSO =least absolute shrinkage and selection operator; ICC =intraclass correlation coefficient; ROC =receiver operating characteristic; DCA =decision curve analysis