A Radiomic Approach for Evaluating Intra-Subgroup Heterogeneity in SHH and Group 4 Pediatric Medulloblastoma: A Preliminary Multi-Institutional Study
Author:
Ismail Marwa1, Um Hyemin1, Salloum Ralph2, Hollnagel Fauzia3, Ahmed Raheel4, de Blank Peter5ORCID, Tiwari Pallavi16
Affiliation:
1. Department of Radiology, University of Wisconsin-Madison, Madison, WI 53706, USA 2. Nationwide Children’s Hospital, Columbus, OH 43205, USA 3. Department of Medicine, University of Wisconsin-Madison, Madison, WI 53792, USA 4. Department of Neurological Surgery, University of Wisconsin-Madison, Madison, WI 53792, USA 5. Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA 6. Departments of Medical Physics and Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53792, USA
Abstract
Medulloblastoma (MB) is the most frequent malignant brain tumor in children with extensive heterogeneity that results in varied clinical outcomes. Recently, MB was categorized into four molecular subgroups, WNT, SHH, Group 3, and Group 4. While SHH and Group 4 are known for their intermediate prognosis, studies have reported wide disparities in patient outcomes within these subgroups. This study aims to create a radiomic prognostic signature, medulloblastoma radiomics risk (mRRisk), to identify the risk levels within the SHH and Group 4 subgroups, individually, for reliable risk stratification. Our hypothesis is that this signature can comprehensively capture tumor characteristics that enable the accurate identification of the risk level. In total, 70 MB studies (48 Group 4, and 22 SHH) were retrospectively curated from three institutions. For each subgroup, 232 hand-crafted features that capture the entropy, surface changes, and contour characteristics of the tumor were extracted. Features were concatenated and fed into regression models for risk stratification. Contrasted with Chang stratification that did not yield any significant differences within subgroups, significant differences were observed between two risk groups in Group 4 (p = 0.04, Concordance Index (CI) = 0.82) on the cystic core and non-enhancing tumor, and SHH (p = 0.03, CI = 0.74) on the enhancing tumor. Our results indicate that radiomics may serve as a prognostic tool for refining MB risk stratification, towards improved patient care.
Funder
NIH/NCI/ITCR NIH/NCI DOD/PRCRP Career Development Award The Dana Foundation David Mahoney Neuroimaging Program The V Foundation Translational Research Award The Johnson & Johnson WiSTEM2D Award Musella Foundation Grant R&D Pilot Award Departments of Radiology and Medical Physics, University of Wisconsin-Madison WARF Accelerator Oncology Diagnostics Award
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