Standardized 18F-FDG PET/CT radiomic features provide information on PD-L1 expression status in treatment-naive patients with non-small cell lung cancer

Zhang R, Hohenforst-Schmidt W, Steppert C, Sziklavari Z, Schmidkonz C, Atzinger A, Kuwert T, Klink T, Sterlacci W, Hartmann A, Vieth M, Foerster S (2022)

Publication Type: Journal article

Publication year: 2022

Journal

Nuklearmedizin-Nuclear Medicine Schattauer

DOI: 10.1055/a-1816-6950

Abstract

Purpose To study the relationship between standardized 18F-FDG PET/CT radiomic features and clinicopathological variables and programmed death ligand-1 (PD-L1) expression status in non-small cell lung cancer (NSCLC) patients. Methods 58 NSCLC patients with preoperative 18F-FDG PET/CT scans and postoperative results of PD-L1 expression were retrospectively analysed. A standardized, open-source software was used to extract 86 radiomic features from PET and low-dose CT images. Univariate analysis and multivariate logistic regression were used to find independent predictors of PD-L1 expression. The Area Under the Curve (AUC) of receiver operating characteristic (ROC) curve was used to compare the ability of variables and their combination in predicting PD-L1 expression. Results Multivariate logistic regression resulted in the PET radiomic feature GLRLM_LGRE (Odds Rate (OR): 0.300 vs 0.114, 95% confidence interval (CI): 0.096-0.931 vs 0.021-0.616, in NSCLC and adenocarcinoma respectively) and the CT radiomic feature GLZLM_SZE (OR: 3.338 vs 7.504, 95%CI: 1.074-10.375 vs 1.382-40.755, in NSCLC and adenocarcinoma respectively), being independent predictors of PD-L1 status. In NSCLC group, after adjusting for gender and histology, the PET radiomic feature GLRLM_LGRE (OR: 0.282, 95%CI: 0.085-0.936) remained an independent predictor for PD-L1 status. In the adenocarcinoma group, when adjusting for gender the PET radiomic feature GLRLM_LGRE (OR: 0.115, 95%CI: 0.021-0.631) and the CT radiomic feature GLZLM_SZE (OR: 7.343, 95%CI: 1.285-41.965) remained associated with PD-L1 expression. Conclusion NSCLC and adenocarcinoma with PD-L1 expression show higher tumour heterogeneity. Heterogeneity-related 18F-FDG PET and CT radiomic features showed good ability to non-invasively predict PD-L1 expression.

Authors with CRIS profile

Ruiyun Zhang Lehrstuhl für Allgemeine Pathologie und Pathologische Anatomie Christian Schmidkonz Medizinische Fakultät Armin Atzinger Department of Nuclear Medicine Torsten Kuwert Lehrstuhl für Klinische Nuklearmedizin William Sterlacci Medizinische Fakultät Arndt Hartmann Lehrstuhl für Allgemeine Pathologie und Pathologische Anatomie Michael Vieth Professur für Allgemeine Pathologie

Involved external institutions

Klinikum Coburg DE Germany (DE) Universitätsklinikum Würzburg DE Germany (DE) Klinikum Bayreuth DE Germany (DE) Sana Klinikum Hof ​​ DE Germany (DE)

How to cite

APA:

Zhang, R., Hohenforst-Schmidt, W., Steppert, C., Sziklavari, Z., Schmidkonz, C., Atzinger, A.,... Foerster, S. (2022). Standardized 18F-FDG PET/CT radiomic features provide information on PD-L1 expression status in treatment-naive patients with non-small cell lung cancer. Nuklearmedizin-Nuclear Medicine. https://dx.doi.org/10.1055/a-1816-6950

MLA:

Zhang, Ruiyun, et al. "Standardized 18F-FDG PET/CT radiomic features provide information on PD-L1 expression status in treatment-naive patients with non-small cell lung cancer." Nuklearmedizin-Nuclear Medicine (2022).

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