非小细胞肺癌原发灶18F-FDG PET/CT特征预测淋巴结转移

摘 要] 目的 评价非小细胞肺癌（NSCLC）原发灶18F-FDG PET/CT特征对淋巴结转移的预测价值。方法 收集接受18F-FDG PET/CT检查的NSCLC患者91例，共96个原发灶，根据病理结果将病灶分为不伴淋巴结转移，即LN（－）组（n＝66）及伴淋巴结转移，即LN（＋）组（n＝30）。比较两组原发灶大小、肿瘤消失率（TDR）、最大标准摄取值（SUVmax）和肿瘤代谢体积（MTV）差异，采用多因素二元Logistic回归模型筛选上述指标中预测淋巴结转移的相关因素。结果 LN（－）组和LN（＋）组原发灶大小、TDR、SUVmax、MTV差异均具有统计学意义（P均＜0.05），随原发灶、SUVmax及MTV增大和TDR降低，淋巴结转移比例增高。多因素二元Logistic逐步法回归分析结果表明TDR及MTV纳入回归方程。结论 NSCLC原发灶18F-FDG PET/CT表现特征对淋巴结转移具有预测价值，其中TDR及MTV是主要预测因素。

18F-FDG PET/CT features of primary lesion of non-small cell lung carcinoma in prediction lymph node metastasis

Objective To evaluate the value of ¹⁸F-FDG PET/CT features of primary lesion in predicting lymph node metastasis in non-small cell lung carcinoma (NSCLC). Methods Ninety-one patients (96 lung lesions) with NSCLC underwent ¹⁸F-FDG PET/CT scanning were enrolled. According to the pathology results, the 96 lesions were divided into LN(-) group (n=66) without lymph node metastasis and LN(+) group (n=30) with lymph node metastasis. The tumor size, tumor disappearance rate (TDR), SUV_max and metabolic tumor volume (MTV) of the primary lung lesion were compared between the two groups. The multi-variate binary Logistic regression was performed to select main relevant factors in prediction of lymph node metastasis. Results The tumor size, TDR, SUV_max and MTV of primary lung lesion showed significant differences between the two groups (all P<0.05). With the rising of tumor size, SUV_max, MTV and reducing of TDR, the incidence of lymph node metastasis increased. TDR and MTV were incorporated into the regression equation by multi-variate binary Logistic regression analysis. Conclusion Primary lesions features of NSCLC in ¹⁸F-FDG PET/CT scanning have predictive value for lymph node metastasis, in which TDR and MTV are main predictive factors.