The Rise of Radiomics and Implications for Oncologic Management

• Published in: JNCI : Journal of the National Cancer Institute 2017-07, Vol.109 (7)
• Main Authors: Verma, Vivek, Simone, 2nd, Charles B, Krishnan, Sunil, Lin, Steven H, Yang, Jinzhong, Hahn, Stephen M
• Format: Article
• Language: English
• Subjects: Diagnostic Imaging - methods; Humans; Image Processing, Computer-Assisted - methods; Imaging, Three-Dimensional - methods; Magnetic Resonance Imaging - methods; Medical Oncology - methods; Medical Oncology - trends; Neoplasms - diagnostic imaging; Precision Medicine - methods; Precision Medicine - trends; Reproducibility of Results; Sensitivity and Specificity; Tomography, X-Ray Computed - methods
• ISSN: 0027-8874; 1460-2105
• DOI: 10.1093/jnci/djx055

Clinical medicine, particularly oncology, is progressing toward personalized care. Whereas the terms genomics, proteomics, transcriptomics, and metabolomics have dominated personalized medicine for the past couple decades, the concept of radiomics was first described in 2012. This nascent concept has major implications for personalized cancer care and involves extracting hundreds of standardized and quantifiable imaging characteristics from diagnostic computed tomography/magnetic resonance imaging images. The central hypothesis of radiomics is that these libraries of quantitative individual voxel-based variables are more sensitively associated with various clinical endpoints compared with the more qualitative radiologic, histopathologic, and clinical data more commonly utilized today. Because radiomics offers immense potential but has not reached a mainstream oncologic audience, the authors discuss herein the role of radiomics in cancer care in the future.