Impact of Intraventricular Hemorrhage on Classification of Hematoma Expansion and Development of Radiomics Prediction Models

Abstract

Background: To investigate the impact of intraventricular hemorrhage (IVH) on the classification of hematoma expansion (HE), and the development of radiomics models using features extracted from the baseline hematoma to predict HE.Methods: Eighty-four patients with baseline and follow-up non-contrast CT within 4~24 hours were included. The intraparenchymal hemorrhage (IPH) and IVH were separately outlined by an experienced neuroradiologist. HE was defined as an absolute hematoma growth >6 mL or percentage growth >33%. HE was determined based on two criteria, using IPH alone (HEP) or IPH+IVH (HEP+V). The radiomics analysis was performed by using PyRadiomics to extract features, followed by random forest algorithm to select features, and lastly the decision tree to build classification models. Results: The classification of expansion showed 37 (44%) HEP and 47 (56%) non-HEP based on IPH alone, and similar results of 38 (45%) HEP+V and 46 (55%) non-HEP+V based on IPH+IVH. The majority, >94% of HE patients, had a poor outcome (death or mRS>3 at discharge). Three radiomics analysis (RA) models were built. The first model using baseline IPH to predict HEP (RAP-P) showed an accuracy of 80% but loss of correlation with the clinical outcome; the second model using IPH+IVH to predict HEP (RAPV-V) had a slightly higher accuracy of 81% and resumed the poor outcome association with HE; and the third model using IPH+IVH to predict HEP+V (RAPV-PV) had the highest accuracy of 86% with preserved clinical outcome correlation of HE. The sensitivity, specificity, and accuracy of three decision trees (RAP-P, RAPV-P, RAPV-PV) were 0.8/ 0.68/ 0.89; 0.81/ 0.92/ 0.72 and 0.86/ 0.82/ 0.89, respectively.Conclusions: The proposed radiomics approach with additional IVH information could be used to classify the expansion status highly associated with the clinical outcome and provide a robust tool for the enrollment of high-risk ICH cases in the anti-expansion trials.