1357P A deep radiomics approach to assess PD-L1 expression and clinical outcomes in patients with advanced non-small cell lung cancer treated with immune checkpoint inhibitors: A multicentric study

Abstract

Recent studies suggest imaging-based signatures can be a promising non-invasive approach to predict response to immune checkpoint inhibitors (ICI). In this multi-centric study, we explored the use of radiomics models to characterize the relationship between PD-L1 expression, imaging features, and clinical outcomes.