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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