Coroller, ThibaudGrossmann, PatrickHou, YingRios Velazquez, EmmanuelLeijenaar, Ralph T.H.Hermann, GretchenLambin, PhilippeHaibe-Kains, BenjaminMak, RaymondAerts, Hugo2016-11-162015Coroller, Thibaud P., Patrick Grossmann, Ying Hou, Emmanuel Rios Velazquez, Ralph T.H. Leijenaar, Gretchen Hermann, Philippe Lambin, Benjamin Haibe-Kains, Raymond H. Mak, and Hugo J.W.L. Aerts. 2015. “CT-Based Radiomic Signature Predicts Distant Metastasis in Lung Adenocarcinoma.” Radiotherapy and Oncology 114 (3) (March): 345–350. doi:10.1016/j.radonc.2015.02.015.0167-8140http://nrs.harvard.edu/urn-3:HUL.InstRepos:29400926Background and Purpose: Radiomics provides opportunities to quantify the tumor phenotype non-invasively by applying a large number of quantitative imaging features. This study evaluates computed-tomography (CT) radiomic features for their capability to predict distant metastasis (DM) for lung adenocarcinoma patients. Material and Methods: We included two datasets: 98 patients for discovery and 84 for validation. The phenotype of the primary tumor was quantified on pre-treatment CT-scans using 635 radiomic features. Univariate and multivariate analysis was performed to evaluate radiomics performance using the concordance index (CI). Results: Thirty-five radiomic features were found to be prognostic (CI > 0.60, FDR < 5%) for DM and twelve for survival. It is noteworthy that tumor volume was only moderately prognostic for DM (CI=0.55, p-value=2.77 × 10−5) in the discovery cohort. A radiomic-signature had strong power for predicting DM in the independent validation dataset (CI=0.61, p-value=1.79 ×10−17). Adding this radiomic-signature to a clinical model resulted in a significant improvement of predicting DM in the validation dataset (p-value=1.56 × 10−11). Conclusions: Although only basic metrics are routinely quantified, this study shows that radiomic features capturing detailed information of the tumor phenotype can be used as a prognostic biomarker for clinically-relevant factors such as DM. Moreover, the radiomic-signature provided additional information to clinical data.en-USJournal Article2016-11-1610.1016/j.radonc.2015.02.015