^(18)F-氟代脱氧葡萄糖正电子发射断层扫描成像/CT原发灶影像特征对非小细胞肺癌淋巴结转移的预测价值

Value of ^(18)F-FDG PET/CT imaging characteristics of primary lesions in predicting lymph node metastasis of non-small cell lung cancer

目的 基于^(18)F-氟代脱氧葡萄糖(^(18)F-FDG)正电子发射断层扫描成像/CT(PET/CT)探究非小细胞肺癌(NSCLC)淋巴结转移的影响因素,建立Logistic预测模型并分析其预测临床价值。方法 收集我院收治的NSCLC患者156例为观察对象,纳入年限为2019年6月至2021年6月,根据是否合并淋巴结转移分为合并淋巴结转移组47例和未合并淋巴结转移组109例,比较2组临床病理特征,均行^(18)F-FDG PET/CT检查,比较2组患者区域最大标准摄取值(SUVmax)、糖酵解总量(TLG)、代谢体积(MTV)等原发灶影像学特征,并建立Logistic回归方程:P=ExpΣBiXi/1+ExpΣBiXi,建立Logistic预测模型并分析其预测淋巴结转移的灵敏度、特异度和准确度。结果 淋巴结转移组TNM分期Ⅲ期及肿瘤直径≥3 cm比例高于无淋巴结转移组(P<0.05)。淋巴结转移组患者原发灶T-SUVmax、T-TLG、L-SURmax、T-TLGsur、B-SURmax、B-TLGsur指标均高于无淋巴结转移组,差异具有统计学意义(P<0.05)。Logistic回归分析结果提示TNM分期、肿瘤直径、T-SUVmax、T-TLG、L-SURmax、T-TLGsur、B-SURmax、B-TLGsur指标均与NSCLC淋巴结转移有关(P<0.05)。通过Logistic回归模型预测NSCLC发生淋巴结转移的概率P,建立P值的受试者工作特征(ROC)曲线,模型预测概率P的曲线下面积(AUC)为0.796(0.693~0.899),提示该模型具有较高的效用价值。当灵敏度为89.5%,特异度为69.0%,约登指数为0.585,对应的预测概率为-3.258。结论 NSCLC淋巴结转移的原发病灶18FFDG PET/CT影像特征明显异常表达,建立预测模型可进一步提高NSCLC患者淋巴结转移的诊断效能,临床上可以选择更加积极的治疗方案。

Objective To explore the influencing factors of lymph node metastasis in non-small cell lung cancer(NSCLC)based on ^(18)F-fluorodeoxyglucose(^(18)F-FDG)positron emission tomography imaging/computed tomography imaging(PET/CT),to establish a Logistic prediction model and to analyze its predictive clinical value.Methods One hundred and fifty-six patients with NSCLC admitted to our hospital from June 2019 to June 2021 were collected as observation subjects,and they were divided into 47 cases in the combined lymph node metastasis group and 109 cases in the uncomplicated lymph node metastasis group according to whether they had combined lymph node metastasis,the clinicopathological characteristics of the two groups were compared.All of them performed an ^(18)F-FDG PET/CT examination,the imaging characteristics of primary foci such as SUVmax,total glycolysis(TLG),and metabolic volume(MTV)were compared between the two groups and a Logistic regression equation was established:P=ExpΣBiXi/1+ExpΣBiXi,and a Logistic prediction model was established and analyzed for its sensitivity,specificity and accuracy of predicting lymph node metastasis.Results The proportion of TNM stageⅢand tumor diameter≥3 cm was significantly higher in the lymph node metastasis group than that in the no lymph node metastasis group(P<0.05).The indexes of T-SUVmax,T-TLG,L-SURmax,T-TLGsur,B-SURmax,B-TLGsur in the primary foci of patients with lymph node metastasis were higher than those in the group without lymph node metastasis,and the difference was statistically significant(P<0.05).The results of Logistic regression analysis suggested that TNM stage,tumor diameter,T-SUVmax,T TLG,L-SURmax,T-TLGsur,B-SURmax,and B-TLGsur indicators were all associated with lymph node metastasis in NSCLC(P<0.05).The probability P of lymph node metastasis in NSCLC was predicted by a Logistic regression model,and the receiver operator characteristic curve(ROC)of P value was established,and the area under the curve(AUC)of the model predicting the probability P was 0.796(0.693,0.899),suggesting that the model has a high utility value.When the sensitivity was 89.5%,the specificity was 69.0%,and the Jorden index was 0.585,the corresponding predictive probability was-3.258.Conclusion ^(18)F-FDG PET/CT imaging features of the primary lesion of lymph node metastasis in NSCLC are obviously abnormally expressed,and the establishment of predictive model can further improve the diagnostic efficacy of lymph node metastasis in NSCLC patients,which can be clinically selected for more aggressive treatment options.