Prostate Cancer Aggressiveness Prediction Using CT Images
pca is mostly asymptomatic at an early stage and often painless requiring active surveillance screening. trus is the principal method to diagnose pca following a histological examination by observing cell pattern irregularities and assigning the gs according to the recommended guidelines. This procedure presents sampling errors and, being invasive may cause complications to the patients. ebrt is presented as curative option for localised and locally advanced disease, as a palliative option for metastatic low-volume disease or after prostatectomy for prostate bed and pelvic nodes salvage. In the ebrt worflow a ct scan is performed as the basis for dose calculations and volume delineations. In this work, we evaluated the use of data-characterization algorithms (radiomics) from ct images for pca aggressiveness assessment. The fundamental motivation relies on the wide availability of ct images and the need to provide tools to assess ebrt effectiveness. We used Pyradiomics and lifex to extract features and search for a radiomic signature within ct images. Finnaly, when applying pcan to the features, we were able to show promising results.