The Added Value of Intraventricular Hemorrhage on the Radiomics Analysis for the Prediction of Hematoma Expansion of Spontaneous Intracerebral Hemorrhage

Te-Chang Wu; Yan-Lin Liu; Jeon-Hor Chen; Yang Zhang; Tai-Yuan Chen; Ching-Chung Ko; Min-Ying Su

doi:10.3390/diagnostics12112755

The Added Value of Intraventricular Hemorrhage on the Radiomics Analysis for the Prediction of Hematoma Expansion of Spontaneous Intracerebral Hemorrhage

Diagnostics (Basel). 2022 Nov 10;12(11):2755. doi: 10.3390/diagnostics12112755.

Authors

Te-Chang Wu^{1

2}, Yan-Lin Liu³, Jeon-Hor Chen^{3

4}, Yang Zhang^{3

5}, Tai-Yuan Chen^{1

6}, Ching-Chung Ko^{1

7}, Min-Ying Su³

Affiliations

¹ Department of Medical Imaging, Chi-Mei Medical Center, Tainan 71004, Taiwan.
² Department of Medical Sciences Industry, Chang Jung Christian University, Tainan 71101, Taiwan.
³ Department of Radiological Sciences, University of California, Irvine, CA 92521, USA.
⁴ Department of Radiology, E-DA Hospital, I-Shou University, Kaohsiung 84001, Taiwan.
⁵ Department of Radiation Oncology, Rutgers-Cancer Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, NJ 08901, USA.
⁶ Graduate Institute of Medical Sciences, Chang Jung Christian University, Tainan 71101, Taiwan.
⁷ Center of General Education, Chia Nan University of Pharmacy and Science, Tainan 71710, Taiwan.

Abstract

Background: Among patients undergoing head computed tomography (CT) scans within 3 h of spontaneous intracerebral hemorrhage (sICH), 28% to 38% have hematoma expansion (HE) on follow-up CT. This study aimed to predict HE using radiomics analysis and investigate the impact of intraventricular hemorrhage (IVH) compared with the conventional approach based on intraparenchymal hemorrhage (IPH) alone. Methods: This retrospective study enrolled 127 patients with baseline and follow-up non-contrast CT (NCCT) within 4~72 h of sICH. IPH and IVH were outlined separately for performing radiomics analysis. HE was defined as an absolute hematoma growth > 6 mL or percentage growth > 33% of either IPH (HEP) or a combination of IPH and IVH (HEP+V) at follow-up. Radiomic features were extracted using PyRadiomics, and then the support vector machine (SVM) was used to build the classification model. For each case, a radiomics score was generated to indicate the probability of HE. Results: There were 57 (44.9%) HEP and 70 (55.1%) non-HEP based on IPH alone, and 58 (45.7%) HEP+V and 69 (54.3%) non-HEP+V based on IPH + IVH. The majority (>94%) of HE patients had poor early outcomes (death or modified Rankin Scale > 3 at discharge). The radiomics model built using baseline IPH to predict HEP (RMP) showed 76.4% accuracy and 0.73 area under the ROC curve (AUC). The other model using IPH + IVH to predict HEP+V (RMP+V) had higher accuracy (81.9%) with AUC = 0.80, and this model could predict poor outcomes. The sensitivity/specificity of RMP and RMP+V for HE prediction were 71.9%/80.0% and 79.3%/84.1%, respectively. Conclusion: The proposed radiomics approach with additional IVH information can improve the accuracy in prediction of HE, which is associated with poor clinical outcomes. A reliable radiomics model may provide a robust tool to help manage ICH patients and to enroll high-risk ICH cases into anti-expansion or neuroprotection drug trials.

Keywords: hematoma expansion; intraventricular hemorrhage; prediction; radiomics; spontaneous intracerebral hemorrhage.

Grants and funding

This research received no external funding.