TY - JOUR T1 - Evaluation of Shape and Textural Features from CT as Prognostic Biomarkers in Non-small Cell Lung Cancer JF - Anticancer Research JO - Anticancer Res SP - 2155 LP - 2160 VL - 38 IS - 4 AU - FRANCESCO BIANCONI AU - MARIO LUCA FRAVOLINI AU - RAQUEL BELLO-CEREZO AU - MATTEO MINESTRINI AU - MICHELE SCIALPI AU - BARBARA PALUMBO Y1 - 2018/04/01 UR - http://ar.iiarjournals.org/content/38/4/2155.abstract N2 - 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. ER -