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Denise Madeddu

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    Mini Oral session III (ID 65)

    • Event: ELCC 2019
    • Type: Mini Oral session
    • Track:
    • Presentations: 1
    • Moderators:
    • Coordinates: 4/12/2019, 17:45 - 18:45, Room C
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      2O - Differentially regulated high-throughput CT imaging features correlate to distinct tumor immune contextures portraying a radiomic signature with prognostic impact on surgically resected NSCLC (ID 507)

      17:45 - 18:45  |  Author(s): Denise Madeddu

      • Abstract
      • Presentation
      • Slides


      The ground-breaking advent of immunotherapy in the oncologic arena still leaves uncovered the identification of valid prognostic and predictive biomarkers. To this aim, we advanced the hypothesis that intersecting the tumor immune microenvironment (TIME) with high-throughput extracted radiomic features may identify NSCLC patients with distinct clinical outcome.

      a9ded1e5ce5d75814730bb4caaf49419 Methods

      We enrolled 60 surgically resected NSCLC patients. TIME was assessed by the quantitative evaluation of PD-L1 levels and an extensive morphometric analysis of Tumor Infiltrating Lymphocytes (TILs). From each CT scan, in addition to semantic characteristics, 841 radiomic features were extracted through an open-source (3d Slicer) software. Radiomic variables were subjected to statistical analysis to test their correlation with tissue immune profiles and survival outcome.

      20c51b5f4e9aeb5334c90ff072e6f928 Results

      A cluster of 3 patients (A) displaying oppositely regulated radiomic features was identified by an unsupervised hierarchical model. Compared to the remaining cases, cluster A had a significantly reduced (p < 0.01) OS (13 vs 33 mos.) and DFS (11 vs 25 mos.) and shared similar semantic imaging characteristics (no effect on parenchyma and subsolid texture) and a desertic TIME (PD-L1low and TILslow). Radiomic variables from cluster A were then compared to those extracted from patients matched for both desertic TIME and qualitative CT parameters but with favorable survival outcome (cluster B). By applying signal-to-noise ratio and T-test, the most significant oppositely regulated wavelet features (p < 0.0001) in the two clusters were Large Dependence Emphasis, Busyness, Cluster-Tendency and Gray Level Variance. The detailed analysis of corresponding TIME revealed that PD-1-to-CD8 ratio was the only immunophenotypic parameter differentially expressed by the two prognostic classes.

      fd69c5cf902969e6fb71d043085ddee6 Conclusions

      Higher order radiomic features associated with specific TILs phenotype may enclose a radiologic signature with prognostic impact on NSCLC.

      b651e8a99c4375feb982b7c2cad376e9 Legal entity responsible for the study

      University Hospital of Parma.

      213f68309caaa4ccc14d5f99789640ad Funding

      Has not received any funding.

      682889d0a1d3b50267a69346a750433d Disclosure

      All authors have declared no conflicts of interest.


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