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Area of Science:

  • Integrative biology
  • Medical imaging
  • Genomics

Background:

  • Radiogenomics combines radiomics (imaging features) with genomics (molecular data) to overcome single-omic limitations.
  • Radiomics offers noninvasive tissue characterization, while genomics reveals molecular underpinnings.
  • The core hypothesis links imaging phenotypes to genetic/molecular processes, reflecting biological activity.

Purpose of the Study:

  • To review the principles of radiogenomic analysis, including image and gene analysis.
  • To cover advanced techniques for integrating imaging and genomic data.
  • To summarize current research and achievements in radiogenomics across diseases.

Main Methods:

  • Review of fundamental principles in radiomics and genomics.
  • Discussion of analytical techniques for data integration.
  • Synthesis of recent research findings in oncology and non-oncology.

Main Results:

  • Radiogenomics has potential for elucidating disease mechanisms, noninvasive genomic variation detection, and improved prognosis.
  • Current research highlights achievements in understanding disease biology through integrated data.
  • Significant potential exists for clinical applications in diagnosis and treatment planning.

Conclusions:

  • Radiogenomics offers a powerful, noninvasive approach to link imaging phenotypes with molecular mechanisms.
  • Clinical implementation faces challenges including data scarcity, analytical standardization, and translational barriers.
  • Future research must focus on data quality, analytical platforms, and validation through clinical trials and animal models.