318 Campus Drive
Despina Kontos, PhD
Matthew J. Wilson Professor of Research Radiology II
Associate Vice-Chair for Research, Department of Radiology
Perelman School of Medicine
University of Pennsylvania
Title: Radiomics and Radiogenomics: The Role of Imaging, Machine Learning, and AI, as a Biomarker for Cancer Prognostication and Therapy Response Evaluation
Abstract: Cancer is a heterogeneous disease, with known inter-tumor and intra-tumor heterogeneity in solid tumors. Established histopathologic prognostic biomarkers generally acquired from a tumor biopsy may be limited by sampling variation. Radiomics is an emerging field with the potential to leverage the whole tumor via non-invasive sampling afforded by medical imaging to extract high throughput, quantitative features for personalized tumor characterization. Identifying imaging phenotypes via radiomics analysis and understanding their relationship with prognostic markers and patient outcomes can allow for a non-invasive assessment of tumor heterogeneity. Recent studies have shown that intrinsic radiomic phenotypes of tumor heterogeneity for cancer may have independent prognostic value when predicting disease aggressiveness and recurrence. The independent prognostic value of imaging heterogeneity phenotypes suggests that radiogenomic phenotypes can provide a non-invasive characterization of tumor heterogeneity to augment genomic assays in precision prognosis and treatment.