Clinicopathological predictors of the presence of blood circulating tumor DNA in early-stage non-small cell lung cancers.

The implementation of lung cancer screening programs across the world has drawn considerable attention to improve early-stage lung cancer detection and prognostication. Several blood-based assays detecting circulating tumor DNA (ctDNA) recently emerged as non-invasive methods to detect malignancies. However, their limited sensitivity and predictive value remain a hurdle to their clinical use.

Sensitivity of CT-derived radiomic features to extraction libraries and gray-level discretization in the context of immune biomarker discovery.

Objectives: Radiomics can predict patient outcomes by automatically extracting a large number of features from medical images. This study is aimed to investigate the sensitivity of radiomics features extracted from 2 different pipelines, namely, Pyradiomics and RaCat, as well as the impact of gray-level discretization on the discovery of immune checkpoint inhibitors (ICIs) biomarkers.

Methods: A retrospective cohort of 164 non-small cell lung cancer patients administered with ICIs was used in this study.