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- W2978073368 abstract "Abstract Background The role of radiomics against clinical and histologic standard has been repeatedly demonstrated, although the integration of high-throughput imaging into a multidimensional prediction model is still in its early dawn. Thus, the aim of the present study was to determine whether CT-derived radiomic features (CT-RFs) might intercept the landscaped arrangement of the tumor immune microenvironment (TIME), offering a novel non-invasive assessment of prognostic factors in NSCLC. Methods A cohort of 100 (70 training and 30 validation) surgically resected NSCLC was investigated. TIME was classified according to PD-L1 and Tumor Infiltrating Lymphocytes (TILs) levels and further defined as hot, intermediate or cold by the relative contribution of effector and suppressor phenotypes. Extracted CT-RFs were correlated to TIME profiles and ROC curves were used to test the accuracy of the radiomic predictor. The impact of integrated radio-immune parameters on clinical outcome was estimated by Kaplan Meier method. Results Patient-specific tissue immune profiles were reflected by a strong correlation between CT-RFs and TIME parameters (U-Mann Whitney Test). Cluster Tendency and GrayLevelNonUniformity were upregulated in PD-L1high and TILs rich tumors (p Conclusions Specific TIME profiles inscribe radiomic features resulting in a radio-immune signature with prognostic impact on NSCLC. Legal entity responsible for the study University of Parma. Funding University of Parma. Disclosure All authors have declared no conflicts of interest." @default.
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- W2978073368 date "2019-10-01" @default.
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- W2978073368 title "Identification of a radio-immune signature with high prognostic value in surgically resected NSCLC" @default.
- W2978073368 doi "https://doi.org/10.1093/annonc/mdz269.001" @default.
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