Shape-based Tumor Microenvironment Analysis to Differentiate Non-Small Cell Lung Cancer Subtypes: a Radio-Pathomic Study

Shaped-based descriptors from Computed Tomography (CT) scans and whole slide digital pathology images were used to differentiate the two major histopathological subtypes of non-small-cell lung cancer (NSCLC). Our two hypotheses are 1) Encoding information on local heterogeneity will augment the model's classification capabilities 2) Shape-based biomarkers from radiology and pathology can complement each other. Shape features were extracted from the tumor map from pathology and radiology images. In pathology, tumor-microenvironment features were encoded by clustering the tumor map into phenotype maps. These features performed better than the features from whole tumor map. Integration of radio-pathomics performed best, achieving 0.802 AUC.