Functional outcome prediction across multiple timescales intracerebral hemorrhage using a radiomics model.

Objectives: To discover a model for accurate risk stratification of intracerebral hemorrhage (ICH) patient outcomes across multiple time windows. Materials and methods: This retrospective study enrolled ICH patients with onset-to-imaging time (OIT) < 72 h. Patients were divided into three groups, 1-3: OIT< 6 h, 6-24 h, 24-72 h. Group 1 patients with preoperative reimaging within 72 h formed Group 4. The 90-day mRS score served as the endpoint (0-3: favorable prognosis; 4-6: poor prognosis). Binary logistic regression was used to build prognostic models for each group. The generalizability of the Group 1 model was validated across other subgroups. Results: A total of 2136 patients with ICH were included in the study. In the training， internal and external validation set, the AUC values achieved when the Group 1 radiomics model was assessed in Group 2 patients were 0.773, 0.759 and 0.706. The AUC values observed when the Group 1 combined model was evaluated in Group 3 patients were 0.811, 0.847 and 0.944. In the training set, the AUC obtained when the Group 1 radiomics model was tested in Group 4 patients was 0.779. The AUC of the radiomics model constructed by combining the key radiomic features of Groups 1 and 4 was 0.788. The AUC of the independent radiomics model for Group 4 was 0.815. Conclusion: Prognostic models for ICH patients with OIT < 6 h may also be generalizable to those with OIT < 72 h, enabling reliable early outcome assessment across different time windows.