Radiogenomics provide a large-scale data analytical framework that aims to understand the broad multiscale relationships between the complex information encoded in medical images (including computational, quantitative, and semantic image features) and their underlying clinical, therapeutic, and biological associations. As such it is a powerful and increasingly important tool for both clinicians and researchers involved in the imaging, evaluation, understanding, and management of lung cancers. Herein we provide an overview of the growing field of lung cancer radiogenomics and its applications.
*Department of Diagnostic Radiology, University of Hong Kong, Hong Kong
†Department of Computer and Electrical Engineering, National Chiao Tung University, HsinChu, Taiwan
‡Departments of Radiological Sciences and Pathology, David Geffen School of Medicine at UCLA, Los Angeles, CA
The authors declare no conflicts of interest.
Correspondence to: Michael D. Kuo, MD, Departments of Radiological Sciences and Pathology, David Geffen School of Medicine at UCLA, 10833 LeConte Ave., Box 951721, CHS 17-135, Los Angeles, CA 90095-1721 (e-mail: firstname.lastname@example.org).