RESUMO
Radiomics refers to the extraction and analysis of large amounts of advanced quantitative imaging features with high throughput from medical images obtained with CT, MRI and PET, finding disease biomarkers to increase precision in diagnosis, assessment of prognosis and prediction of therapy response. It is well known that cancer treatment is a great challenge; however, early detection and early treatment can greatly increase the survival rate of patients. The change of tumor cells can be monitored by the examination of gene expression. Moreover, it can also be monitored by imaging markers, which makes Radiomics method widely used in cancer treatment, so Radiomics plays a more and more important role in medical imaging and the related fields. This paper firstly summarizes and analyzes the key problems (including multi-modality image acquisition and reconstruction, image segmentation, feature extraction and qualification, and databases, data sharing, informatics analyses and modeling) to be solved in Radiomics. Different challenges are available in each process. Next, the paper describes the application of Radiomics in detection of non-small cell lung cancer, prostate cancer, breast cancer and other cancers. Finally, taking the rapid development of advanced technologies, the paper puts forward several points of future prediction in terms of the development of Radiomics method.