Delta-Radiomics Signature For Prediction Of Survival In Advanced Nsclc Patients Treated With Immunotherapy

Lung cancer is the leading cause of cancer death in Europe with an approximate 5-years survival rate of 13% from diagnosis. The potential of computational image analysis to provide decision support in oncology and the importance of identifying predictive and non-invasive biomarkers of disease progression and response to therapy has led to Radiomics. The objective of this study was to develop a delta-radiomics signature to predict survival and treatment response in patients with advanced non-small cell lung cancer (NSCLC) undergoing immunotherapy. Pre-treatment and first follow-up CT images and intra-nodular and peri-nodular regions from 88 patients have been used to calculate delta-features. The delta-radiomics signature significantly stratified high- and low-risk patients $(\mathrm{p}=0.018)$, it was significantly associated with Overall Survival $(\mathrm{p}=0.03)$ and it predicted responders with an area under the receiver operating characteristic curve (ROC-AUC) of 0.76 in an independent test set. The results demonstrate the potential of delta-radiomics to be an early biomarker of immunotherapy response.