Radiomics: extracting more information from medical images using advanced feature analysis

Eur J Cancer. 2012 Mar;48(4):441-6. doi: 10.1016/j.ejca.2011.11.036. Epub 2012 Jan 16.


Solid cancers are spatially and temporally heterogeneous. This limits the use of invasive biopsy based molecular assays but gives huge potential for medical imaging, which has the ability to capture intra-tumoural heterogeneity in a non-invasive way. During the past decades, medical imaging innovations with new hardware, new imaging agents and standardised protocols, allows the field to move towards quantitative imaging. Therefore, also the development of automated and reproducible analysis methodologies to extract more information from image-based features is a requirement. Radiomics--the high-throughput extraction of large amounts of image features from radiographic images--addresses this problem and is one of the approaches that hold great promises but need further validation in multi-centric settings and in the laboratory.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Algorithms
  • Diagnostic Imaging* / methods
  • Diagnostic Imaging* / statistics & numerical data
  • Diagnostic Imaging* / trends
  • Genomics / methods
  • High-Throughput Screening Assays / methods*
  • Humans
  • Image Processing, Computer-Assisted* / methods
  • Image Processing, Computer-Assisted* / statistics & numerical data
  • Models, Biological
  • Pattern Recognition, Automated / methods
  • Proteomics / methods
  • Radioactive Tracers*
  • Radiometry / methods
  • Radiometry / statistics & numerical data*


  • Radioactive Tracers