Radiomics of Early Detection


 

 

Project Summary:

“Radiomics” is the process of extracting structured and mineable data from biomedical images, and then using these data to provide more power for cancer diagnosis and prognosis, as well as prediction and monitoring response to anti-cancer therapies (1).  Lung “nodules” are commonly observed in chest CT scans, which are coherent structures that may or may not be cancerous. These can be observed in a screening setting (for those at high risk defined by the US Preventive Service as Adults 55-80 with a history of smoking), or they can be detected incidentally (during a CT scan for another concern). In either case, there is a significant problem of over-detection and over-diagnosis, as 96% of indeterminate screening nodules and over 60% of incidental nodules are not cancers, but nonetheless require follow up. Radiomics has shown exceptional power in being able to better define the future progression of these nodules and will eventually reduce the burden of over-detection and over-diagnosis (2-5).

Radiomics features distinguish cancer from non-cancer in incidentally detected IPNs

Hawkins et al., JTO, 2016


References:

  1. Gillies RJ, Kinahan PE, Hricak H. Radiomics: Images Are More than Pictures, They Are Data. Radiology 2016;278(2):563-77.
  2. Liu Y, Wang H, Li Q, McGettigan MJ, Balagurunathan Y, Garcia A, et al. Radiologic Features of Small Pulmonary Nodules and Lung Cancer Risk in the National Lung Screening Trial: A Nested Case-Control Study. Radiology 2017;(in press).
  3. Schabath MB, Massion PP, Thompson ZJ, Eschrich SA, Balagurunathan Y, Goldof D, et al. Differences in Patient Outcomes of Prevalence, Interval, and Screen-Detected Lung Cancers in the CT Arm of the National Lung Screening Trial. PloS one 2016;11(8):e0159880.
  4. Hawkins S, Wang H, Liu Y, Garcia A, Stringfield O, Krewer H, et al. Predicting malignant nodules from screening CTs. Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer 2016.
  5. Schabath MB, Gillies RJ. Noninvasive Quantitative Imaging-based Biomarkers and Lung Cancer Screening. American journal of respiratory and critical care medicine 2015;192(6):654-6.

 

Project Members


 

Robert J Gillies, PhD

PI, Chair of Department