M Zhang, L Tam, J Wright, M Mohammadzadeh, M Han, E Chen, M Wagner, J Nemalka, H Lai, A Eghbal, C Y Ho, R M Lober, S H Cheshier, N A Vitanza, G A Grant, L M Prolo, K W Yeom, A Jaju
BACKGROUND AND PURPOSE: Pediatric supratentorial tumors such as embryonal tumors, high-grade gliomas, and ependymomas are difficult to distinguish by histopathology and imaging because of overlapping features. We applied machine learning to uncover MR imaging-based radiomics phenotypes that can differentiate these tumor types. MATERIALS AND METHODS: Our retrospective cohort of 231 patients from 7 participating institutions had 50 embryonal tumors, 127 high-grade gliomas, and 54 ependymomas...
April 2022: AJNR. American Journal of Neuroradiology