Radiogenomics and IR

J Vasc Interv Radiol. 2018 May;29(5):706-713. doi: 10.1016/j.jvir.2017.11.021. Epub 2018 Mar 15.

Abstract

Radiogenomics involves the integration of mineable data from imaging phenotypes with genomic and clinical data to establish predictive models using machine learning. As a noninvasive surrogate for a tumor's in vivo genetic profile, radiogenomics may potentially provide data for patient treatment stratification. Radiogenomics may also supersede the shortcomings associated with genomic research, such as the limited availability of high-quality tissue and restricted sampling of tumoral subpopulations. Interventional radiologists are well suited to circumvent these obstacles through advancements in image-guided tissue biopsies and intraprocedural imaging. Comprehensive understanding of the radiogenomic process is crucial for interventional radiologists to contribute to this evolving field.

Publication types

  • Review

MeSH terms

  • Biomarkers, Tumor / genetics
  • Data Mining
  • Genetic Markers
  • Genetic Predisposition to Disease
  • Genomics / methods*
  • Humans
  • Machine Learning
  • Neoplasms / genetics*
  • Neoplasms / radiotherapy*
  • Phenotype
  • Radiography, Interventional*

Substances

  • Biomarkers, Tumor
  • Genetic Markers