Chang Ruxi, Luo Liang, Shen Cong, Zhang Weishan, Duan Xiaoyi
PET/CT Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China.
Br J Radiol. 2025 May 1;98(1169):715-720. doi: 10.1093/bjr/tqaf034.
The purpose of this study is to evaluate the effectiveness of using 18F-FDG PET/CT metabolic heterogeneity to assess the programmed cell death ligand (PD-L1) expression in primary tumours.
Data from 103 non-small cell lung cancer (NSCLC) patients undergoing 18F-FDG PET/CT were collected. PD-L1 expression was verified via biopsy or surgical specimens. The coefficient of variation (COV) assessed metabolic heterogeneity of the primary tumour. ROC curves evaluated the predictive potential of metabolic metrics and defined thresholds. Logistic regression examined predictors of PD-L1 expression.
The study included 103 patients (mean age: 63.65 ± 9.28 years), of whom 60 were male. Sixty-four patients had positive PD-L1 expression, while 39 had negative PD-L1 expression. COV was significantly higher in the PD-L1-positive group (Z = -2.529, P = 0.011), while no significant differences were noted in other parameters between the groups (P > 0.05 for all). The optimal cut-off value was proposed as 28.9, with sensitivity and specificity of 46.9% (34.3%-59.8%) and 82.1% (66.5%-92.5%), respectively (AUC: 0.649 (0.549, 0.741)) which can more effectively identify PD-L1-negative patients. Other metabolic parameters are less effective than COV (AUC< 0.6). In addition, COV-defined metabolic heterogeneity outperformed other metabolic parameters in predicting PD-L1 expression (P = 0.049) and emerged as an independent predictor.
Metabolic heterogeneity, described by the COV of the primary lesion, is a marker for predicting PD-L1 expression in NSCLC patients. Therefore, the COV of the primary tumour may complement conventional imaging in providing immunohistochemical information before biopsy.
COV of the primary tumour can predict PD-L1 expression, potentially complementing conventional imaging for immunohistochemical information prior to biopsy.
本研究旨在评估利用18F-FDG PET/CT代谢异质性评估原发性肿瘤中程序性细胞死亡配体（PD-L1）表达的有效性。
收集了103例接受18F-FDG PET/CT检查的非小细胞肺癌（NSCLC）患者的数据。通过活检或手术标本验证PD-L1表达。变异系数（COV）评估原发性肿瘤的代谢异质性。受试者工作特征（ROC）曲线评估代谢指标的预测潜力并确定阈值。逻辑回归分析PD-L1表达的预测因素。
本研究纳入103例患者（平均年龄：63.65±9.28岁），其中60例为男性。64例患者PD-L1表达阳性，39例患者PD-L1表达阴性。PD-L1阳性组的COV显著更高（Z = -2.529，P = 0.011），而两组间其他参数无显著差异（所有P>0.05）。建议的最佳截断值为28.9，敏感性和特异性分别为46.9%（34.3%-59.8%）和82.1%（66.5%-92.5%）（曲线下面积：0.649（0.549，0.741）），其能更有效地识别PD-L1阴性患者。其他代谢参数的有效性低于COV（曲线下面积<0.6）。此外，COV定义的代谢异质性在预测PD-L1表达方面优于其他代谢参数（P = 0.049），并成为一个独立的预测因素。
由原发性病变的COV描述的代谢异质性是预测NSCLC患者PD-L1表达的一个标志物。因此，原发性肿瘤的COV可能在活检前提供免疫组化信息方面补充传统影像学检查。
原发性肿瘤的COV可预测PD-L1表达，可能在活检前为免疫组化信息补充传统影像学检查。
