Abstract
BackgroundWe aimed to construct and validate a nomogram model based on the combination of radiomic features and satellite sign number for predicting intracerebral hematoma expansion.MethodsA total of 129 patients from two institutions were enrolled in this study. The preprocessed initial CT images were used for radiomic feature extraction. The ANOVA-Kruskal–Wallis test and least absolute shrinkage and selection operator regression were applied to identify candidate radiomic features and construct the Radscore. A nomogram model was developed by integrating the Radscore with a satellite sign number. The discrimination performance of the proposed model was evaluated by receiver operating characteristic (ROC) analysis, and the predictive accuracy was assessed via a calibration curve. Decision curve analysis (DCA) and Kaplan–Meier (KM) survival analysis were performed to evaluate the clinical value of the model.ResultsFour optimal features were ultimately selected and contributed to the Radscore construction. A positive correlation was observed between the satellite sign number and Radscore (Pearson’s r: 0.451). The nomogram model showed the best performance with high area under the curves in both training cohort (0.881, sensitivity: 0.973; specificity: 0.787) and external validation cohort (0.857, sensitivity: 0.950; specificity: 0.766). The calibration curve, DCA, and KM analysis indicated the high accuracy and clinical usefulness of the nomogram model for hematoma expansion prediction.ConclusionA nomogram model of integrated radiomic signature and satellite sign number based on noncontrast CT images could serve as a reliable and convenient measurement of hematoma expansion prediction.
Highlights
Intracerebral hemorrhage (ICH) confers a worse prognosis than ischemic stroke, with an overall fatality rate approaching 40% and neurological disability among the survivors (van Asch et al, 2010; Heit et al, 2017)
We investigated a nomogram model combined with radiomics and quantitative satellite sign to improve the diagnostic performance in early hematoma expansion prediction
We established and validated a nomogram model for early ICH expansion prediction, incorporating four robust radiomic features which were extracted from noncontrast CT (NCCT) and proven to be effective for the classification of expanders and nonexpanders and the satellite sign number which was found to be a statistically significant imaging marker for the identification of expanders
Summary
Intracerebral hemorrhage (ICH) confers a worse prognosis than ischemic stroke, with an overall fatality rate approaching 40% and neurological disability among the survivors (van Asch et al, 2010; Heit et al, 2017). The satellite sign, which was easy to recognize and clearly defined, was especially proven to be an independent imaging marker for hematoma expansion prediction (Shimoda et al, 2017; Yu et al, 2017). These imaging predictors make qualitative or semi-quantitative analysis studies only and caused inevitable deviation due to subjectivity. We aimed to construct and validate a nomogram model based on the combination of radiomic features and satellite sign number for predicting intracerebral hematoma expansion
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