Institute of Pathology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Pathology, Klinikum Bayreuth GmbH, Bayreuth, Germany.
Nuklearmedizin. 2022 Oct;61(5):385-393. doi: 10.1055/a-1816-6950. Epub 2022 Jun 29.
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.
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.
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.
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.
研究非小细胞肺癌(NSCLC)患者标准化 18F-FDG PET/CT 放射组学特征与临床病理变量和程序性死亡配体-1(PD-L1)表达状态之间的关系。
回顾性分析 58 例 NSCLC 患者术前 18F-FDG PET/CT 扫描和术后 PD-L1 表达结果。使用标准化、开源软件从 PET 和低剂量 CT 图像中提取 86 个放射组学特征。采用单因素分析和多变量逻辑回归分析寻找 PD-L1 表达的独立预测因子。采用受试者工作特征(ROC)曲线下面积(AUC)比较变量及其组合预测 PD-L1 表达的能力。
多变量逻辑回归显示,PET 放射组学特征 GLRLM_LGRE(比值比(OR):0.300 与 0.114,95%置信区间(CI):0.096-0.931 与 0.021-0.616,分别在 NSCLC 和腺癌中)和 CT 放射组学特征 GLZLM_SZE(OR:3.338 与 7.504,95%CI:1.074-10.375 与 1.382-40.755,分别在 NSCLC 和腺癌中)是 PD-L1 状态的独立预测因子。在 NSCLC 组中,在校正性别和组织学后,PET 放射组学特征 GLRLM_LGRE(OR:0.282,95%CI:0.085-0.936)仍然是 PD-L1 状态的独立预测因子。在腺癌组中,在校正性别后,PET 放射组学特征 GLRLM_LGRE(OR:0.115,95%CI:0.021-0.631)和 CT 放射组学特征 GLZLM_SZE(OR:7.343,95%CI:1.285-41.965)仍与 PD-L1 表达相关。
PD-L1 表达的 NSCLC 和腺癌表现出更高的肿瘤异质性。与异质性相关的 18F-FDG PET 和 CT 放射组学特征具有良好的无创预测 PD-L1 表达的能力。