title: Radiomics: Images Are More than Pictures, They Are Data.
abstract: In the past decade, the field of medical image analysis has grown exponentially, with an increased number of pattern recognition tools and an increase in data set sizes. These advances have facilitated the development of processes for high-throughput extraction of quantitative features that result in the conversion of images into mineable data and the subsequent analysis of these data for decision support; this practice is termed radiomics. This is in contrast to the traditional practice of treating medical images as pictures intended solely for visual interpretation. Radiomic data contain first-, second-, and higher-order statistics. These data are combined with other patient data and are mined with sophisticated bioinformatics tools to develop models that may potentially improve diagnostic, prognostic, and predictive accuracy. Because radiomics analyses are intended to be conducted with standard of care images, it is conceivable that conversion of digital images to mineable data will eventually become routine practice. This report describes the process of radiomics, its challenges, and its potential power to facilitate better clinical decision making, particularly in the care of patients with cancer.
authors.affiliation: From the Department of Cancer Imaging, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Dr, Tampa, FL 33612 (R.J.G.); Department of Radiology, University of Washington, Seattle, Wash (P.E.K.); and Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York NY 10065 (H.H.).
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Gillies
authors.affiliation: From the Department of Cancer Imaging, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Dr, Tampa, FL 33612 (R.J.G.); Department of Radiology, University of Washington, Seattle, Wash (P.E.K.); and Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York NY 10065 (H.H.).
authors.forename: Paul E
authors.initials: PE
authors.lastname: Kinahan
authors.affiliation: From the Department of Cancer Imaging, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Dr, Tampa, FL 33612 (R.J.G.); Department of Radiology, University of Washington, Seattle, Wash (P.E.K.); and Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York NY 10065 (H.H.).
authors.forename: Hedvig
authors.initials: H
authors.lastname: Hricak
mesh_terms: D000465:Algorithms; D001706:Biopsy; D057225:Data Mining; D003657:Decision Making; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D003952:Diagnostic Imaging; D023281:Genomics; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008490:Medical Informatics; D009369:Neoplasms / Q000175:diagnosis* / Q000473:pathology; D011379:Prognosis; D011873:Radiology Information Systems