Clinical Multimodal Integration for Stratification of Glioblastoma Patients

Glioblastoma is globally the most common malignant adult brain tumor, with heterogeneous morphological and molecular profiles, and a grim prognosis (median overall survival (OS)=14 months) that gets further augmented by socio-economic health determinants. In India, as many as 38% of brain tumor cases are reported to be glioblastoma. Clinical research and developments in routine radiologic, histopathologic, and molecular assessment of glioblastoma, over the last 18 years, have only yielded minimal OS improvements and have mostly focused on WEIRD (western, educated, industrialized, rich & democratic) country contexts.

This project focuses on novel integrative computational (AI) analyses of routinely acquired multi-modal clinical data to develop new insights on glioblastoma morphological patterns associated with shorter and longer OS, with a specific lens on patients in India, allowing clinical neuropathologists to provide additional prognostic information gleaned during microscopic assessment to the treating team and suggest avenues of biological investigation for understanding and treating glioblastoma.