Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, No.1 Youyi Road, Yuzhong District, Chongqing 400016, China.
Department of Pathology, Chongqing Medical University, No.1 Youyi Road, Yuzhong District, Chongqing 400016, China.
Eur J Radiol. 2021 Nov;144:109981. doi: 10.1016/j.ejrad.2021.109981. Epub 2021 Sep 27.
To investigate the value of combining clinicopathological characteristics with computed tomographic (CT) features of tumours for predicting occult lymph node metastasis (OLNM) in peripheral solid non-small cell lung cancer (PS-NSCLC).
The study included 478 NSCLC clinically N0 (cN0) patients who underwent lobectomy and systemic lymph node dissection from January 2014 to August 2019. Patients were classified into OLNM and negative lymph node metastasis (NLNM) groups. The CT features of non-metastatic and metastatic lymph nodes with a largest short-diameter > 5 mm were compared in the OLNM group. Thereafter, the clinicopathological characteristics and CT morphological features of tumours were compared between both groups. Multivariable logistic regression analysis and receiver-operating characteristic curve were developed.
CT images detected 103 metastatic and 705 non-metastatic lymph nodes, and no significant differences in CT features of lymph nodes were found in all 161 OLNM patients (P > 0.05). For both groups, sex, carcinoembryonic antigen and pathological type differed significantly (all P < 0.05), while tumour size, necrosis, calcification, vascular convergence, pleural involvement, and the shortest interval of tumour-pleura differed significantly on CT images (all P < 0.05). Multivariable logistic regression analysis showed that carcinoembryonic antigen > 5.00 ng/ml, adenocarcinoma, absence of vascular convergence, and pleural involvement of Type II (one linear or cord-like pleural tag or tumour abut to the pleura with a broad base observed on both lung and mediastinal window images) were independent predicting factors of OLNM.
CT findings of lymph nodes can provide limited value and integrating clinicopathological characteristics with the CT morphological features of tumours is helpful in predicting OLNM in patients with PS-NSCLC.
探讨将肿瘤临床病理特征与 CT 特征相结合，预测外周型非小细胞肺癌（PS-NSCLC）隐匿性淋巴结转移（OLNM）的价值。
纳入 2014 年 1 月至 2019 年 8 月期间行肺叶切除术和系统性淋巴结清扫术的 478 例临床 N0（cN0）PS-NSCLC 患者。将患者分为 OLNM 组和阴性淋巴结转移（NLNM）组。比较 OLNM 组中最大短径>5mm 的非转移性和转移性淋巴结的 CT 特征。然后，比较两组的肿瘤临床病理特征和 CT 形态特征。采用多变量逻辑回归分析和受试者工作特征曲线。
CT 图像共检测到 103 个转移性和 705 个非转移性淋巴结，在所有 161 例 OLNM 患者中，两组淋巴结的 CT 特征无显著差异（均 P>0.05）。两组间性别、癌胚抗原和病理类型差异均有统计学意义（均 P<0.05），肿瘤大小、坏死、钙化、血管汇聚、胸膜累及和肿瘤-胸膜最短距离在 CT 图像上差异均有统计学意义（均 P<0.05）。多变量逻辑回归分析显示，癌胚抗原>5.00ng/ml、腺癌、无血管汇聚、Ⅱ型胸膜累及（在肺窗和纵隔窗图像上均可见线性或索状胸膜标记或肿瘤与胸膜宽基底相贴）是 OLNM 的独立预测因素。
淋巴结的 CT 表现提供的价值有限，将临床病理特征与肿瘤 CT 形态特征相结合有助于预测 PS-NSCLC 患者的 OLNM。
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