1251P Exploring quantitative biomarkers from different tumour volumes for radiomics in lung cancer

Abstract

Recent advances in medical imaging technology allow the use of advanced image analysis methods by the extraction of quantitative features from medical images to characterize tumor biology in order to provide informations that may be useful to guide therapies and predict survival. In our previous experience, a radiomics signature mixing semantic and image-based features was able to predict the reduction of the target volume during chemoradiation in LA-NSCLC. The aim of this study is to investigate which 3D ROI contain more quantitative information that can be exploit for a radiomic approach in lung cancer.