Abstract
BackgroundThe 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. MethodsA 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. ResultsPatient-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<0.01), while Skewness and Coarseness were correlated to PD-L1low and TILs poor (p<005) samples, respectively. Among 13 CT extracted features distinctive of hot TIME (hCT-RFs), the most significantly upregulated were Energy, Busyness, and Entropy (p<0.01), underlining the heterogeneous nature of inflamed NSCLC. Conversely, cold TIME-related features (cCT-RFs) showed a restricted variability being essentially confined to LowGrayLevelEmphasis (p<0.001). When hCT-RFs and cCT-RFs were entered together in a multivariate logistic regression model, a highly specific and sensitive radiomic predictor of hot (1.00 AUC, p<0.001) and cold (0.92 AUC, p=0.001) TIME was revealed. Strikingly, a progressive decrease in OS and DFS (Kaplan Meier, p<0.001) was documented, respectively, in hot, intermediate and cold NSCLC as defined by the radio-immune model. ConclusionsSpecific TIME profiles inscribe radiomic features resulting in a radio-immune signature with prognostic impact on NSCLC. Legal entity responsible for the studyUniversity of Parma. FundingUniversity of Parma. DisclosureAll authors have declared no conflicts of interest.
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