Evaluation of Shape and Textural Features from CT as Prognostic Biomarkers in Non-small Cell Lung Cancer.

BACKGROUND/AIM: We retrospectively investigated the prognostic potential (correlation with overall survival) of 9 shape and 21 textural features from non-contrast-enhanced computed tomography (CT) in patients with non-small-cell lung cancer.

MATERIALS AND METHODS: We considered a public dataset of 203 individuals with inoperable, histologically- or cytologically-confirmed NSCLC. Three-dimensional shape and textural features from CT were computed using proprietary code and their prognostic potential evaluated through four different statistical protocols.

RESULTS: Volume and grey-level run length matrix (GLRLM) run length non-uniformity were the only two features to pass all four protocols. Both features correlated negatively with overall survival. The results also showed a strong dependence on the evaluation protocol used.

CONCLUSION: Tumour volume and GLRLM run-length non-uniformity from CT were the best predictor of survival in patients with non-small-cell lung cancer. We did not find enough evidence to claim a relationship with survival for the other features.