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CT Radiomics Features for Evaluation of PD-L1, CD8+TILs and Foxp3+TILs Expression Status in Patients with Stage I NSCLC
Q Wen*, X Meng , J Zhu , Y Yin , J Yu , Shandong Cancer Hospital Affiliated to Shandong University, Jinan, Shandong
Presentations
SU-H4-GePD-J(B)-3 (Sunday, July 30, 2017) 4:30 PM - 5:00 PM Room: Joint Imaging-Therapy ePoster Lounge - B
Purpose: Radiomics can quantify tumor phenotypic characteristics non-invasively and apply features algorithms to computed tomography (CT). In this study, we retrospectively investigated the association between CT-based radiomics features and programmed death-ligand 1 (PD-L1), CD8+ tumor-infiltrating lymphocytes (TILs) and forkhead box protein 3+ (FOXP3+) TILs expression in patients with surgically resected stage I non-small cell lung cancer (NSCLC).
Methods: A total of 96 patients with surgically resected NSCLC were included in the institutional review board-approved retrospective study and performed immunohistochemistry of PD-L1, CD8+TILs and FOXP3+ TILs. Clinical and demographic factors were obtained from medical records. 127 radiomics features coming from 5 different feature categories (tumor shape, intensity histogram, gray-level co-occurrence matrix, run length matrix, wavelet texture) were extracted from segmented volumes of each tumor. 48 out of 127 were considered as independent features and were performed in this analysis.
Results: In our univariate analysis, PD-L1 expression was significantly correlated with male sex (P = 0.003), squamous carcinoma (P < 0.001), never smoking (P = 0.015). And 8 radiomics features was detected a statistically significant difference between positive PD-L1 expression group and negative PD-L1 expression group in univariate analysis. A multiple logistic regression model illustrated that adding radiomics features to clinical factors might improve the predictive value, due to the AUC increasing from 0.628 to 0.714 (P < 0.001). In addition, there was no radiomics features and clinical variables had significant correlated with CD8+ TILs and FOXP3+ TILs expression.
Conclusion: Radiomics features based on computed tomography of NSCLC could provide useful information regarding tumor phenotype, and the model made up of radiomics features and clinical data could predict the expression of PD-L1 non-invasively.
Funding Support, Disclosures, and Conflict of Interest: This study was supported by the National Natural Science Foundation of China (Grant No. 81671785), the special foundation for Scientific Research in Public Interest of China (Grant No. 201402011)
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