Radiomics and radiogenomics for precision radiotherapy

• Published in: Journal of radiation research Vol. 59; no. suppl_1; pp. i25 - i31
• Main Authors: Wu, Jia, Tha, Khin Khin, Xing, Lei, Li, Ruijiang
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01.03.2018
• Subjects: Genomics; Humans; Image Processing, Computer-Assisted; Precision Medicine; Radiation; Radiotherapy; Special Issue - Approaches to Select Advanced External Radiotherapy; Supplement Paper; radiotherapy; radiomics; radiogenomics; imaging; biomarkers
• ISSN: 0449-3060; 1349-9157
• DOI: 10.1093/jrr/rrx102

Abstract Imaging plays an important role in the diagnosis and staging of cancer, as well as in radiation treatment planning and evaluation of therapeutic response. Recently, there has been significant interest in extracting quantitative information from clinical standard-of-care images, i.e. radiomics, in order to provide a more comprehensive characterization of image phenotypes of the tumor. A number of studies have demonstrated that a deeper radiomic analysis can reveal novel image features that could provide useful diagnostic, prognostic or predictive information, improving upon currently used imaging metrics such as tumor size and volume. Furthermore, these imaging-derived phenotypes can be linked with genomic data, i.e. radiogenomics, in order to understand their biological underpinnings or further improve the prediction accuracy of clinical outcomes. In this article, we will provide an overview of radiomics and radiogenomics, including their rationale, technical and clinical aspects. We will also present some examples of the current results and some emerging paradigms in radiomics and radiogenomics for clinical oncology, with a focus on potential applications in radiotherapy. Finally, we will highlight the challenges in the field and suggest possible future directions in radiomics to maximize its potential impact on precision radiotherapy.