Radiogenomic-based survival risk stratification of tumor habitat on Gd-T1w MRI is associated with biological processes in glioblastoma

Niha Beig, Kaustav Bera, Prateek Prasanna, Jacob Antunes, Ramon Correa, Salendra Singh, Anas Saeed Bamashmos, Marwa Ismail, Nathaniel Braman, Ruchika Verma, Virginia B. Hill, Volodymyr Statsevych, Manmeet S. Ahluwalia, Vinay Varadan, Anant Madabhushi, Pallavi Tiwari*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Purpose: To (i) create a survival risk score using radiomic features from the tumor habitat on routine MRI to predict progressionfree survival (PFS) in glioblastoma and (ii) obtain a biological basis for these prognostic radiomic features, by studying their radiogenomic associations with molecular signaling pathways. Experimental Design: Two hundred three patients with pretreatment Gd-T1w, T2w, T2w-FLAIR MRI were obtained from 3 cohorts: The Cancer Imaging Archive (TCIA; n = 130), Ivy GAP (n = 32), and Cleveland Clinic (n = 41). Gene-expression profiles of corresponding patients were obtained for TCIA cohort. For every study, following expert segmentation of tumor subcompartments (necrotic core, enhancing tumor, peritumoral edema), 936 3D radiomic features were extracted from each subcompartment across all MRI protocols. Using Cox regression model, radiomic risk score (RRS) was developed for every protocol to predict PFS on the training cohort (n = 130) and evaluated on the holdout cohort (n = 73). Further, Gene Ontology and singlesample gene set enrichment analysis were used to identify specific molecular signaling pathway networks associated with RRS features. Results: Twenty-five radiomic features from the tumor habitat yielded the RRS. A combination of RRS with clinical (age and gender) and molecular features (MGMT and IDH status) resulted in a concordance index of 0.81 (P < 0.0001) on training and 0.84 (P = 0.03) on the test set. Radiogenomic analysis revealed associations of RRS features with signaling pathways for cell differentiation, cell adhesion, and angiogenesis, which contribute to chemoresistance in GBM. Conclusions: Our findings suggest that prognostic radiomic features from routine Gd-T1w MRI may also be significantly associated with key biological processes that affect response to chemotherapy in GBM.

Original languageEnglish (US)
Pages (from-to)1866-1876
Number of pages11
JournalClinical Cancer Research
Volume26
Issue number8
DOIs
StatePublished - Apr 15 2020

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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