Radiologically Defined Tumor-habitat Adjacency as a Prognostic Biomarker in Glioblastoma

Intratumor heterogeneity in glioblastoma (GBM) has been linked to adverse clinical outcomes including poor survival and sub-optimal response to therapies. Different techniques, such as radiomics, have been used to characterize GBM phenotype. However, the spatial diversity and the interaction between different sub-regions within the tumor (habitats) and its microenvironment has been relatively unexplored. Besides, existing approaches have mainly focused on the radiomic analysis within globally defined regions without considering local heterogeneity. In this paper, we developed a 3D spatial co-localization descriptor based on the adjacency of habitats to quantify the diversity of physiologically similar sub-regions on multi-protocol magnetic resonance imaging. We demonstrated the utility of this spatial phenotype descriptor in predicting overall patient survival. Our experimental results on N=236 treatment-naïve MRI scans suggest that the co-localization features in conjunction with traditional clinical measures, such as age and tumor volume, outperform texture based radiomic features. The presented descriptor provides a tool for more complete characterization of intratumor heterogeneity in solid cancers.