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PET/CT相关参数与非小细胞肺癌PD-L1表达的相关性研究 被引量:2

Correlation between PET/CT Related Parameters and PD-L1 Expression in Nonsmall Cell Lung Cancer
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摘要 目的 探讨PET/CT相关参数在非小细胞肺癌患者PD-L1表达状态中应用及诊断效能。方法 回顾性分析2018年3月至2021年3月共62例N SCLC患者的临床及影像学资料。采用免疫组织化学染色检测所选病例组织标本中PD-L1的表达情况。患者术前行18F-FDG PET/CT检查,测定最大标准化摄取值(SUVmax),使用Research Omni-Kinetics (Version V2.1.0-2017.11.16)软件进行放射组学参数提取。利用统计学方法获得有代表性的参数,通过受试者工作特征(ROC)曲线评估各特征参数判断PD-L1表达状态的能力。结果 62例NSCL患者肿瘤分化程度、PET/CT参数SUVmax、GLN、Sphericity在两组间差异有统计学意义。其中GLN参数显示出优于其他参数值的鉴别效能,其AUC为0.873。结论 PET/CT参数可以用来预测NSCLC患者PD-L1的表达状态,用于指导NSCLC患者的治疗。 Objective To investigate the value of PET/CT related parameters in predicting the expression of PD-L1 in non-small cell lung cancer patients.Methods Retrospective analysis of the clinical and radiomic data of 62 patients with NSCLC from March 2018 to March 2021.The PD-L1 expression of selected tissue specimens was measured by immunohistochemical staining.The patients underwent 18F-FDG PET/CT examination before the operation to determine the maximum standardized uptake value(SUVmax),and extract the radiomic parameters using Research Omni-Kinetics(Version V2.1.0-2017.11.16)software.Representative parameters were obtained via statistical methods,the receiver operating characteristic(ROC)curve was used to evaluate the judging ability of each characteristic parameter within the expression of PD-L1.Results There existed statistically significant difference in the degree of tumor differentiation,SUVmax,GLN,Sphericity of the two groups within the 62 NSCLC patients.The average value and GreyLevelNonuniformity showed better discrimination efficiency than the other parameter values,and the corresponding AUC were 0.880 and 0.858.Conclusion The parameters of PET/CT texture analysis can be used to predict the expression of PD-L1 in NSCLC patients,so as to guide the therapy of NSCLC patients.
作者 段梦月 胡春峰 鲍慧新 DUAN Meng-yue;HU Chun-feng;BAO Hui-xin(Department of Medical Imaging,Affiliated Hospital of Xuzhou Medical University,Xuzhou 221006,Jiangsu Province,China)
出处 《中国CT和MRI杂志》 2023年第5期28-30,共3页 Chinese Journal of CT and MRI
关键词 非小细胞肺癌 PD-L1 正电子发射断层成像 纹理分析 Non-small Cell Lung Cancer PD-L1 Positron Emission Tomography Texture Analysis
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