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Title: [Analysis on CT in diagnosis of lymph node metastasis of thoracic esophageal cancer with minimum diameter greater than 1 cm].
Author: Wu HR, Liu CQ, Guo MF, Xu MQ, Mei XY.
Journal: Zhonghua Wai Ke Za Zhi; 2019 Aug 01; 57(8):601-606. PubMed ID: 31422630.
Abstract:
Objectives: To evaluate the diagnostic value of CT for lymph node metastasis of thoracic esophageal carcinoma with a diameter of more than 1 cm, and to find the optimal diagnostic index by comparing relevant CT indexes. Methods: Totally 80 patients with pathologically proved thoracic esophageal cancer with preoperative CT examination revealed lymph node diameter greater than 1 cm admitted at Department of Thoracic Surgery, the First Affiliated Hospital of University of Science and Technology of China from January 2016 to January 2018 were enrolled in this study. There were 70 males and 10 females, aging of (60±14) years (range: 40-85 years). According to the pathological result of lymph nodes, all the patients and lymph nodes were divided into two groups (N+group: 47 patients, 62 lymph nodes; N-group: 33 patients, 39 lymph nodes). The average number of dissected lymph nodes were 21±4 and 101 lymph nodes' diameter were greater than 1 cm. The clinicopathologic factors, postoperative complications, lymph node dissection and relevant CT indexes like the minimum diameter of lymph nodes (Min D), the maximum diameter of lymph node (Max D), lymph node axial ratio(LAR), the enhancement of lymph node (ELN) and the boundary of lymph node (BLN) were compared. The clinicopathological data, lymph node dessection and CT parameters of the two groups were compared by t test, χ(2) test or Wilcoxon rank sum test. Receiver operating characteristic (ROC) curve analysis was used to compare the ability to predict lymph node metastasis between Min D, Max D, LAR, ELN and BLN. Multiple Logistic regression analysis were performed to determine the independent variables for prediction of lymph node metastasis. Results: The difference of tumor segmentation, pN stage, pTNM stage, total number of metastatic lymph nodes, total number of abdominal lymph node metastases, Min D, Max D, ELN and BLN between the two groups were statistically significant. The results of univariate and multivariate analyses showed that gender (OR=0.128, 95%CI: 0.019 to 0.858, P=0.034), pTNM stage (OR=1.514, 95%CI: 1.020 to 2.247, P=0.039), Min D (OR=0.102, 95%CI: 0.010 to 0.995, P=0.050) and LAR (OR=0.195, 95%CI: 0.052 to 0.731, P=0.015) were the independent relative factors. The area under the curve of ROC curve analysis of Min D, Max D, LAR, ELN and BLN were 0.679, 0.666, 0.561, 0.650 and 0.820, respectively. BLN was the best CT index to diagnosis lymph node metastasis, while the accuracy of dignosis of lymph node metastasis of BLN was 97.0%. The Youden index of Min D, Max D and LAR were 1.25 cm, 1.64 cm and 0.77, respectively. Combining the BLN and ELN had a higher diagnostic rate (97.0%) of lymph node metastasis. Conclusions: CT has high diagnostic value for lymph node metastasis in thoracic esophagel cancer when the lymph node diameter is greater than 1 cm. BLN is the best diagnostic index for lymph node metastasis. 目的： 探讨CT对胸段食管癌最小径>1 cm淋巴结转移的诊断价值及最佳诊断指标。 方法： 回顾性收集中国科学技术大学附属第一医院胸外科2016年1月至2018年1月收治的术前CT检查提示纵隔或上腹部存在最小径>1 cm的淋巴结且有术后病理学诊断的80例（101枚淋巴结）食管癌患者的病例资料。男性70例，女性10例；年龄（60±14）岁（范围：40~85岁）。根据淋巴结病理学检查是否存在肿瘤转移分为阳性组（47例，62枚）和阴性组（33例，39枚）。采用t检验、χ(2)检验或Wilcoxon秩和检验比较两组患者的临床病理资料、淋巴结清扫情况和CT相关参数资料。应用单因素和多因素分析筛选淋巴结转移阳性的相关因素，并绘制受试者工作特征曲线。 结果： 两组患者的肿瘤分段、pN分期、pTNM分期、转移淋巴结总数、腹腔转移淋巴结总数，淋巴结最小径、最大径、边界是否清晰和增强后是否强化的差异有统计学意义（P值均<0.05）。多因素Logistic回归结果显示，性别（OR=0.128，95%CI：0.019~0.858，P=0.034）、pTNM分期（OR=1.514，95%CI：1.020~2.247，P=0.039）、最小径（OR=0.102，95%CI：0.010~0.995，P=0.050）和最小径/最大径（OR=0.195，95%CI：0.052~0.731，P=0.015）是淋巴结转移阳性的独立相关因素。边界是否清晰的受试者工作特征曲线的曲线下面积为0.820（P=0.000），增强后有无强化为0.650（P=0.004），最小径为0.679（P=0.001），最大径为0.666（P=0.001），最小径/最大径为0.561（P=0.241）。计算约登指数后取截断值，最小径、最大径和LAR的截断值分别为1.25 cm、1.64 cm和0.77。联合增强后是否强化与边界是否清晰诊断淋巴结转移的准确率为97.0%。 结论： CT对胸段食管癌最小径>1 cm的淋巴结转移具有重要诊断意义。CT参数中淋巴结边界是否清晰是淋巴结转移的最佳诊断指标，增强后是否强化与边界是否清晰联合诊断的准确率较高。.

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