Prediction of short-term prognosis of patients with hypertensive intracerebral hemorrhage by radiomic-clinical nomogram

Abstract

Hypertensive intracerebral hemorrhage (HICH) is the most common type of spontaneous intracerebral hemorrhage in China which is associated with high mortality and disability. We sought to develop and validate a noncontrast computed tomography (NCCT)-based nomogram model to achieve short-term prognostic prediction for patients with HICH. We retrospectively studied 292 patients with HICH from two medical centers, and they were divided into training (n = 151), validation (n = 66), and testing cohorts (n = 75). Based on radiomics, univariate and multivariate, and logistic regression analyses, four models (black hole sign, clinical, radiomics score, and combined models) were established to predict the prognosis of patients with HICH 30 days after the onset. The results suggested that the combined model had the best predictive performance with the area under the receiver operating characteristic curve (AUC) of 0.821, 0.816, and 0.815 in the training, validation, and testing cohorts, respectively. In addition, a radiomics-clinical (R-C) nomogram was visualized. A calibration curve analysis showed that the R-C nomogram had satisfactory calibration in the three cohorts. A decision curve analysis demonstrated that the R-C nomogram was clinically valuable. Our results suggest that the R-C nomogram can accurately and reliably predict the short-term prognosis of patients with HICH and provide a useful evaluation for making individualized treatment plans.