SDPS-40 MEDULLOBLASTOMA MOLECULAR SUBTYPE PREDICTION USING PATHOMIC FEATURE ANALYSIS - Mahtabfar, Aria; Familiar, Ariana; Kazerooni, Anahita Fathi; Kiani, Mahsa; Khanna, Omaditya; Viswanathan, Karthik; Resnick, Adam; Storm, Phillip; Viaene, Angela; Nabavizadeh, Ali (Neuro-oncology advances, 2023)
Abstract The clinical course of pediatric medulloblastoma patients exhibits wide variability based on molecular subtype. The ability to predict medulloblastoma molecular subtypes (Group 3/4, WNT, SHH) based on histopathologic features alone has immense utility by providing clinicians insight into the molecular and biological underpinnings of the tumor. Although the use of computational pathology (“pathomics”) is expanding in multiple disciplines, its application in pediatric neuro-oncology has been limited. Our preliminary analysis highlights the potential for application in medulloblastoma and pediatric brain tumor research. Using the Children’s Brain Tumor Network database, pediatric patients with available clinical data, whole-slide images (WSI) and molecular subtyping were evaluated for inclusion. Regions-of-interest (ROI) on each H&E-stained WSI were selected for pathomic analysis, and features were extracted using a digital pathology software package (Qupath). 25 pathomic features capturing cellular and nuclear-level intensity and morphology properties were included. Subsequently, a histogram gradient boosting classifier was used to perform binary classification of Group 3/4 vs. SHH/WNT with leave-one-subject-out cross validation. A total of 68 subjects, with median age at diagnosis of 8.19 years (range 0.29-18.69), and median overall survival (OS) of 56 months (range 0.76-258.37) were identified. Our cohort included 44 and 24 subjects in Group 3/4 and SHH/WNT, respectively. Pathomic features classified subjects into Group 3/4 or SHH/WNT with a classification accuracy of 71% (SEM=0.06). A t-test against stratified chance accuracy (57%) showed significantly above-chance testing performance (p=.019). Inspection of the confusion matrix indicated better discrimination of Group 3/4 compared to SHH/WNT subjects, likely due to the larger number of these subjects in the dataset. Our preliminary analysis shows acceptable testing accuracy in distinguishing Group 3/4 from SHH/WNT medulloblastoma, and highlights the possibility of gaining molecular insight purely from histopathologic images. The potential of pathomic features should be considered an untapped resource.