A clinical-radiomics nomogram may provide a personalized 90-day functional outcome assessment for spontaneous intracerebral hemorrhage

Objectives To develop and validate a noncontrast computed tomography (NCCT)-based clinical-radiomics nomogram to identify spontaneous intracerebral hemorrhage (sICH) patients with a poor 90-day prognosis on admission. Methods In this double-center retrospective study, data from 435 patients with sICH (training cohort: n = 244; internal validation cohort: n = 104; external validation cohort: n = 87) were reviewed. The radiomics score (Rad-score) was calculated based on the coefficients of the selected radiomics features. A clinical-radiomics nomogram was developed by using independent predictors of poor outcome at 90 days through multivariate logistic regression analysis in the training cohort and was validated in the internal and external cohorts. Results At 90 days, 200 of 435 (46.0%) patients had a poor prognosis. The clinical-radiomics nomogram was developed by six independent predictors namely midline shift, NCCT time from sICH onset, Glasgow Coma Scale score, serum glucose, uric acid, and Rad-score. In identifying patients with poor prognosis, the clinical-radiomics nomogram showed an area under the receiver operating characteristic curve (AUC) of 0.81 in the training cohort, an AUC of 0.78 in the internal validation cohort, and an AUC of 0.73 in the external validation cohort. The calibration curve revealed that the clinical-radiomics nomogram showed satisfactory calibration in the training and internal validation cohorts (both p > 0.05), but slightly poor agreement in the external validation cohort (p < 0.05). Conclusions The clinical-radiomics nomogram is a valid computer-aided tool that may provide personalized risk assessment of 90-day functional outcome for sICH patients.

Automated summary

This study developed and validated a clinical-radiomics nomogram based on NCCT to identify sICH patients with poor 90-day prognosis. The nomogram, consisting of six independent predictors, showed good predictive performance in different cohorts, providing accurate risk assessment for sICH patients.