18F-FDG PET/CT代谢参数在预测非小细胞肺癌患者纵隔淋巴结转移中的临床价值

目的 探讨18F-氟脱氧葡萄糖（FDG） PET/CT代谢参数在预测非小细胞肺癌（NSCLC）患者纵隔淋巴结转移中的临床价值。 方法 回顾性分析2018年1月至2021年3月于安徽省阜阳市人民医院经组织病理学检查确诊为NSCLC的102例患者的临床资料，其中男性59例、女性43例，年龄33~90（66.0±11.2）岁。所有患者术前均行18F-FDG PET/CT显像，分析并计算代谢参数，变异系数（CV）为病灶最大标准化摄取值（SUV_max）的标准差（SD）与SUV_max的比值；LMV为淋巴结SUV_max与纵隔血池平均标准化摄取值（SUV_mean）的比值；病灶葡萄糖酵解总量（TLG）为肿瘤代谢体积（MTV）与SUV_mean的乘积。绘制受试者工作特征（ROC）曲线，确定预测淋巴结转移的最佳临界值，并计算灵敏度和特异度。计数资料采用χ2检验或Fisher确切概率法进行比较；连续性计量资料采用独立样本t检验进行比较。采用单因素及多因素Logistic回归分析筛选淋巴结转移的预测因素。 结果 单因素Logistic回归分析结果显示，当患者肺部原发肿瘤的长径>30.0 mm或淋巴结的短径>10.0 mm时易发生淋巴结转移（61.9%对38.1%、59.5%对40.5%，χ2=9.16、5.20，均P<0.05）；转移组患者的原发肿瘤CV、淋巴结SUV_max和LMV均高于未转移组患者（46.7±6.1对29.4±6.0、5.9±1.9对2.8±1.6、2.2±0.6对1.4±0.3，t=13.81、8.60、3.97，均P<0.05）。多因素Logistic回归分析结果显示，淋巴结SUV_max[OR=2.2，95%可信区间（CI）:1.30~3.80，P<0.05]和原发肿瘤CV（OR=1.5，95%CI:1.20~1.80，P<0.01）是影响淋巴结转移状态的独立危险因素。ROC曲线分析结果显示，原发肿瘤CV的曲线下面积（AUC）=0.97（SD=0.02，95%CI:0.94~0.99，P<0.01），当CV>30.5时，其诊断淋巴结转移的灵敏度为97.5%、特异度为41.7%；淋巴结SUV_max的AUC=0.91（SD=0.30，95%CI:0.85~0.97，P<0.01），当淋巴结SUV_max>3.1时，其诊断淋巴结转移的灵敏度和特异度分别为95.2%和23.3%。将2种危险因素进行联合诊断，得出的AUC=0.98（SD=0.01，95%CI:0.96~1.00，P<0.01）。 结论 18F-FDG PET/CT代谢参数中原发肿瘤CV和淋巴结SUV_max是预测NSCLC患者纵隔淋巴结转移状态的独立危险因素，可为患者诊疗方案的制定提供重要参考依据。

Clinical value of 18F-FDG PET/CT metabolic parameters in the prediction of mediastinal lymph node metastasis in patients with non-small cell lung cancer

Objective To explore the clinical value of 18F-fluorodeoxyglucose (FDG) PET/CT metabolic parameters in the prediction of mediastinal lymph node metastasis in patients with non-small cell lung cancer (NSCLC). Methods A total of 102 patients with NSCLC histopathologically confirmed from January 2018 to March 2021 in Fuyang People's Hospital were restrospectively analyzed in this study. The patients consisted of 59 males and 43 females aged 33–90 (66.0±11.2) years. All patients underwent 18F-FDG PET/CT imaging before operation to analyze and calculate the metabolic parameters. The coefficient of variation (CV) is the ratio of the standard deviation (SD) of the maximum standardized uptake value (SUV_max) to SUV_max of the lesion; LMV is the ratio of the SUV_max of the lymph node to the mean standardized uptake value (SUV_mean) of the mediastinal blood pool; the total lesion glycolysis (TLG) is the product of metabolic tumor volume (MTV) and SUV_mean. The receiver operator characteristic (ROC) curve was drawn to determine the optimal cut-off value for predicting lymph node metastasis and calculate the sensitivity and specificity. Enumeration data were evaluated using χ2 test or Fisher's exact probability method, and continuous measurement data were compared using independent-sample t test. Univariate and multivariate Logistic regression analysis were used in screening the predictors of lymph node metastasis. Results The univariate Logistic regression analysis results showed that when the long diameter of the lung primary tumor was over 30.0 mm or the short diameter of the lymph nodes was over 10.0 mm, lymph node metastasis was likely to occur (61.9% vs. 38.1%, 59.5% vs. 40.5%; χ2=9.16, 5.20; both P<0.05); the CV of the primary tumor and the SUV_max and LMV of lymph nodes of patients with lymph node metastasis were higher than those of patients without lymph node metastasis (46.7±6.1 vs. 29.4±6.0, 5.9±1.9 vs. 2.8±1.6, 2.2±0.6 vs. 1.4±0.3; t=13.81, 8.60, 3.97; all P<0.05). The multivariate Logistic regression analysis results suggested that the SUV_max of lymph nodes (OR=2.2, 95% confidence interval (CI): 1.30–3.80, P<0.05) and the CV of the primary tumor (OR=1.5, 95%CI: 1.20–1.80, P<0.01) were independent risk factors affecting the status of lymph node metastasis. The ROC curve analysis results showed that the area under the CV curve of the primary tumor was 0.97 (SD=0.02, 95%CI: 0.94–0.99, P<0.01). When CV>30.5, the sensitivity of diagnosis of lymph node metastasis was 97.5%, and the specificity was 41.7%. The area under the curve of lymph node SUV_max was 0.91 (SD=0.30, 95%CI: 0.85–0.97, P<0.01). When the lymph node SUV_max>3.1, the sensitivity and specificity of the diagnosis of lymph node metastasis were 95.2% and 23.3%, respectively. The combined diagnosis of the two risk factors resulted in an area under the curve of 0.98 (SD=0.01, 95%CI: 0.96–1.00, P<0.01). Conclusion Among the metabolic parameters of 18F-FDG PET/CT, the CV of the primary tumor and the SUV_max of lymph nodes are independent risk factors for predicting mediastinal lymph node metastasis in patients with NSCLC and can provide useful information for treatment.