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Abstract #2388

Gradient-entropy based radiomic features to predict molecular sub-types of pediatric Medulloblastoma on Gadolinium-enhanced T1w MRI

Sukanya Iyer1, Marwa Ismail1, Benita Tamrazi2, Ashley Margol3, Ramon Correa1, Prateek Prasanna1, Niha Beig1, Ruchika Verma1, Volodymyr Statsevyc4, Anant Madabhushi1, and Pallavi Tiwari1

1Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, 2Radiology, Children's Hospital Los Angels, Los Angels, CA, United States, 3Hematology, Children's Hospital Los Angels, Los Angels, CA, United States, 4Diagnostic Radiology, Cleveland Clinic Foundation, Cleveland, OH, United States

Genomic Characterization of Medulloblastoma (MB) has recently identified 4 distinct molecular subgroups: Sonic Hedgehog (SHH), wingless (WNT), Group 3, and Group 4. These subgroups have shown different clinical behaviours and benefits to subgroup-specific treatments. We explored the feasibility of a new gradient-entropy radiomic feature, CoLlAGe, to distinguish molecular sub-types of MB on Gd-T1w MRI. Our results using multi-class comparison via one way ANOVA and post-hoc comparison showed significant differences in CoLlAGe features obtained across molecular sub-types. Our feasibility results suggest that the CoLlAGe features in different tumor regions observed on routine Gd-T1w MRI may potentially serve as surrogate markers to non-invasively characterize molecular sub-types of pediatric MB.

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