Using 18F-FDG PET/CT to Predict PD-L1 Expression in NSCLC via Metabolic Tumor Heterogeneity.

IF 1.8 4区 医学 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Ruxi Chang, Liang Luo, Cong Shen, Weishan Zhang, Xiaoyi Duan
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引用次数: 0

Abstract

Objectives: The purpose of this study is to evaluate the effectiveness of using F-18 FDG PET/CT metabolic heterogeneity to assess the PD-L1 expression in primary tumors.

Methods: Data from 103 NSCLC patients undergoing F-18 FDG PET/CT was collected. PD-L1 expression was verified via biopsy or surgical specimens. The coefficient of variation (COV) assessed metabolic heterogeneity of the primary tumor. ROC curves evaluated the predictive potential of metabolic metrics and defined thresholds. Logistic regression examined predictors of PD-L1 expression.

Results: The study included 103 patients (mean age: 63.65 ± 9.28 years), of whom 60 were male. 64 patients were PD-L1 expression positive, while 39 were negative. COV was significantly higher in the PD-L1 positive group (Z = -2.529, P = 0.011),while no significant differences noted in otherparameters between the groups (P > 0.05 for all). The optimal cutoff 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)) whichcan more effectively identify PD-L1 negative patients. Other metabolic parameters are less effective than COV.(AUV < 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.

Conclusion: 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 tumor may complement conventional imaging in providing immunohistochemical information before biopsy.

Advances in knowledge: COV of the primary tumor can predict PD-L1 expression, potentially complementing conventional imaging for immunohistochemical information prior to biopsy.

利用18F-FDG PET/CT通过代谢性肿瘤异质性预测非小细胞肺癌中PD-L1的表达
目的:本研究的目的是评估使用F-18 FDG PET/CT代谢异质性评估原发性肿瘤中PD-L1表达的有效性。方法:收集103例接受F-18 FDG PET/CT检查的NSCLC患者的数据。PD-L1表达通过活检或手术标本进行验证。变异系数(COV)评估原发肿瘤的代谢异质性。ROC曲线评估代谢指标的预测潜力并定义阈值。Logistic回归检验PD-L1表达的预测因子。结果:纳入103例患者,平均年龄63.65±9.28岁,其中男性60例。PD-L1阳性64例,阴性39例。PD-L1阳性组COV明显升高(Z = -2.529, P = 0.011),其他参数组间差异无统计学意义(P < 0.05)。最佳临界值为28.9,敏感性46.9%(34.3% ~ 59.8%),特异性82.1%(66.5% ~ 92.5%)(AUC: 0.649(0.549, 0.741)),能更有效地识别PD-L1阴性患者。其他代谢参数不如冠状病毒有效。结论:由原发病变的COV描述的代谢异质性是预测非小细胞肺癌患者PD-L1表达的一个标志。因此,原发肿瘤的冠状病毒可以补充常规影像学,在活检前提供免疫组织化学信息。知识进展:原发肿瘤的冠状病毒可以预测PD-L1的表达,潜在地补充了活检前的常规免疫组织化学成像信息。
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来源期刊
British Journal of Radiology
British Journal of Radiology 医学-核医学
CiteScore
5.30
自引率
3.80%
发文量
330
审稿时长
2-4 weeks
期刊介绍: BJR is the international research journal of the British Institute of Radiology and is the oldest scientific journal in the field of radiology and related sciences. Dating back to 1896, BJR’s history is radiology’s history, and the journal has featured some landmark papers such as the first description of Computed Tomography "Computerized transverse axial tomography" by Godfrey Hounsfield in 1973. A valuable historical resource, the complete BJR archive has been digitized from 1896. Quick Facts: - 2015 Impact Factor – 1.840 - Receipt to first decision – average of 6 weeks - Acceptance to online publication – average of 3 weeks - ISSN: 0007-1285 - eISSN: 1748-880X Open Access option
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