Cerebrovascular CTA radiomics for objective collateral grading in acute ischemic stroke

Objective Collateral circulation is a key determinant of functional outcome after large vessel occlusion (LVO) and informs thrombectomy decisions. However, collateral grading is rater-dependent and error-prone. We developed an automated cerebrovascular radiomics pipeline to establish objective collateral scoring on computed tomography angiography (CTA). Materials and methods We retrospectively analyzed admission CTAs from 343 LVO patients in the MR CLEAN trial, split into training/validation (n = 274) and testing (n = 69) sets. Vessel regions of interest were segmented using nnU-Net models trained on 40 arterial tree CTAs and 125 multiclass circle of Willis (CoW) cases. Radiomics features were extracted from vascular regions. Predictive features were identified, and a random forest classifier was trained to distinguish sufficient (> 50%) from insufficient (<= 50%) collateral status according to the Tan score system. Performance was compared to the atlas-based middle cerebral artery (MCA) mask model and validated on an external cohort of 140 acute LVO patients. Results Segmentation models accurately annotated cerebral arteries (95th percentile Hausdorff distance 4.49, Dice similarity coefficient 0.83) and CoW segments (2.27 and 0.81, respectively). After feature selection, 6 top features were identified for vessel-tree radiomics, 98 for MCA mask-based radiomics, and 32 for a combined vessel-tree/CoW model. Vessel-tree outperformed MCA mask model on both internal (area under the receiver operating characteristic curve (AUROC): 0.88 versus 0.82) and external (AUROC: 0.83 versus 0.66) test sets. Adding CoW features further improved performance, achieving 0.87 AUROC. Conclusion We presented a fully automated generalizable CTA radiomics approach for objective collateral scoring in acute LVO. Relevance statement This study introduces a fully automated CTA cerebrovascular radiomics pipeline that objectively assesses collateral status in patients with acute ischemic stroke. Combining vessel-tree and circle of Willis features improved collateral score prediction accuracy and generalizability, supporting more reliable, data-driven decision-making in acute large vessel occlusion management.