AUTHOR=Meier Raphael , Pahud de Mortanges Aurélie , Wiest Roland , Knecht Urspeter TITLE=Exploratory Analysis of Qualitative MR Imaging Features for the Differentiation of Glioblastoma and Brain Metastases JOURNAL=Frontiers in Oncology VOLUME=Volume 10 - 2020 YEAR=2020 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2020.581037 DOI=10.3389/fonc.2020.581037 ISSN=2234-943X ABSTRACT=Objectives: To identify qualitative VASARI Magnetic Resonance (MR) Imaging features for differentiation of glioblastoma (GBM) and brain metastases (BMs) of different primary tumors. Materials and Methods: T1-weighted pre- and post-contrast, T2-weighted, and T2-weighted, fluid attenuated inversion recovery (FLAIR) MR images of a total of 239 lesions from 109 patients with either GBM or BM (mammacarcinoma, non-small cell (NSCLC) adenocarcinoma, NSCLC squamous cell carcinoma, small-cell lung cancer (SCLC)) were included. A set of adapted, qualitative VASARI MR features describing tumor appearance and location were scored (binary; 1=presence of feature, 0=absence of feature). Exploratory data analysis was performed on binary scores using a combination of descriptive statistics (proportions with 95% binomial confidence intervals), unsupervised methods and supervised methods including multivariate feature ranking using either repeated fitting or recursive feature elimination with Support Vector Machines (SVMs). Results: GBMs were found to involve all lobes of the cerebrum with a fronto-occipital gradient, often affected the corpus callosum (32.4%, 95% CI 19.1–49.2), and showed a strong preference for the right hemisphere (79.4%, 95% CI 63.2–89.7). BMs occurred most frequently in the frontal lobe (35.1%, 95% CI 28.9–41.9) and cerebellum (28.3%, 95% CI 22.6–34.8). The appearance of GBMs was characterized by preference for well-defined non-enhancing tumor margin (100%, 89.8–100), ependymal extension (52.9%, 36.7–68.5) and substantially less enhancing foci than BMs (44.1%, 28.9–60.6 vs. 75.1 %, 68.8–80.5). Unsupervised and supervised analyses showed that GBMs are distinctively different from BMs and that this difference is driven by definition of non-enhancing tumor margin, ependymal extension and features describing laterality. Differentiation of histological subtypes of BMs was driven by presence of well-defined enhancing and non-enhancing tumor margins and localization in the vision center. SVM models with optimal hyperparameters led to weighted F1-score of 0.865 for differentiation of GBMs from BMs and weighted F1-score of 0.326 for differentiation of BM subtypes. Conclusion: VASARI MR imaging features related to definition of non-enhancing margin, ependymal extension and tumor localization may serve as potential imaging biomarkers to differentiate GBMs from BMs.