The application of radiomics in predicting gene mutations in cancer

Yana Qi1, Tingting Zhao1, Mingyong Han2

  • 1Cancer Therapy and Research Center, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, 324 Jingwuweiqi Road, Jinan, 250021, Shandong, China.

European Radiology
|January 20, 2022
PubMed

Insights

Radiogenomics uses medical imaging to predict cancer gene mutations, offering a noninvasive alternative to costly genetic testing. This field shows promise for personalized cancer therapy but requires further development to overcome current limitations.

Area of Science:

  • Oncology
  • Radiology
  • Genomics

Background:

  • Molecular targeted therapy is crucial for precision cancer treatment, driven by advances in genetic testing.
  • Genetic testing is often expensive, invasive, and time-consuming, limiting its accessibility for all cancer patients.
  • Radiogenomics emerges as a potential solution by linking imaging features to genomic characteristics.

Purpose of the Study:

  • To review the current applications of radiogenomics in predicting gene mutations across various cancers.
  • To highlight radiogenomics as a noninvasive tool for cancer genetic profiling.
  • To discuss the potential and limitations of radiogenomics in clinical practice.

Main Methods:

  • Correlation of imaging characteristics with gene expression patterns and mutations.
  • Analysis of radiogenomic data in brain, lung, colorectal, breast, and kidney tumors.
  • Review of existing literature on radiogenomics and its predictive capabilities.

Main Results:

  • Radiogenomics demonstrates potential in predicting gene mutations noninvasively.
  • Imaging biomarkers can be derived to infer genomic status in tumors.
  • The field is rapidly advancing, showing promise for personalized medicine.

Conclusions:

  • Radiogenomics offers a promising, noninvasive approach to complement or substitute traditional genetic testing in oncology.
  • Accurate imaging biomarkers are key to advancing radiogenomics for precision cancer therapy.
  • Further research is needed to address limitations and fully integrate radiogenomics into clinical workflows.