Exploratory Radiomics for Predicting Adaptive Radiotherapy in Non-Small Cell Lung Cancer

The possibility of planning a therapy minimizing side effects and optimizing efficacy of cancer treatments is one of the main challenges tackled by precision medicine research in oncology. In this context, radiomics is revealing itself as a promising path for better understanding the correct approach to personalized cures. Its primary aim is to go beyond basic medical images analysis, which only leverages on direct measurements on the tumor mass, i.e. dimension and shape. On the contrary, radiomics approach is oriented to the extraction of heterogeneous and quantitative data from the images to characterize the disease from a wider perspective, in order to provide the physician a valid support for the therapy decision and survival prediction. This manuscript presents an application of radiomics to Non-Small Cell Lung Cancer, dealing with the novel task of predicting the possibility to carry out an adaptive therapy. We achieved promising performance, reporting a radiomics signature for predicting tumor reduction during therapy.