Nakada Takeo, Yabe Mitsuo, Ohtsuka Takashi
Department of Surgery, Division of Thoracic Surgery, The Jikei University School of Medicine, Tokyo 105-8471, Japan.
Oncol Lett. 2022 Aug 9;24(4):332. doi: 10.3892/ol.2022.13452. eCollection 2022 Oct.
In patients with clinical stage I non-small cell lung cancer (NSCLC), the prediction of occult lymph node metastasis (LNM) based on a combination of morphology using high-resolution computed tomography (HRCT) and metabolism using positron emission tomography (PET)-CT is unknown. The present study evaluated the use of predictive radiological tools, chest CT and PET-CT, for occult LNM in patients with clinical stage I NSCLC. The records of patients who underwent lobectomy between July 2014 and November 2021 were retrospectively reviewed. The differences in clinicopathological parameters, including CT and PET, between the LNM and non-LNM groups were assessed. Pure solid tumor was defined as a consolidation-to-tumor ratio of 1. The optimal cut-off value for predictive radiological tools for LNM was assessed according to the area under the receiver operating characteristic (ROC) curve. The present study included 288 patients, of whom 39 (13.5%) had LNM; of these 38 (97.4%) were pure solid type. Larger consolidation size (CS), higher maximal standardized uptake (SUVmax) value and histological type were statistically associated with LNM (all P<0.05). The optimal cutoff values of CS and SUVmax for predicting LNM were 19 mm and 5.5 respectively, as assessed using the area under the ROC curve. The combination of CS ≥19 mm and SUVmax ≥5.5 demonstrated a markedly higher odds ratio (9.184; 95% CI, 4.345-19.407) than each parameter individually. The minimum values of CS and SUVmax associated with LNM were 10 mm and 0.8 respectively. Pure solid formation and CS as morphology and SUVmax as metabolism were useful tools that complemented each other in predicting LNM. The combined method of evaluating SUVmax and CS may identify eligibility for LN dissection. However, considering the minimum values of CS and SUVmax in LNM, it cannot affirm the omission of LN dissection for cases that do not meet the combined criteria using HRCT and PET-CT.
在临床I期非小细胞肺癌（NSCLC）患者中，基于高分辨率计算机断层扫描（HRCT）的形态学与正电子发射断层扫描（PET）-CT的代谢相结合来预测隐匿性淋巴结转移（LNM）尚不清楚。本研究评估了预测性放射学工具胸部CT和PET-CT在临床I期NSCLC患者隐匿性LNM中的应用。回顾性分析了2014年7月至2021年11月期间接受肺叶切除术患者的记录。评估了LNM组和非LNM组之间临床病理参数（包括CT和PET）的差异。纯实性肿瘤定义为实变与肿瘤比值为1。根据受试者操作特征（ROC）曲线下面积评估LNM预测性放射学工具的最佳截断值。本研究纳入了288例患者，其中39例（13.5%）发生LNM；其中38例（97.4%）为纯实性类型。更大的实变大小（CS）、更高的最大标准化摄取值（SUVmax）和组织学类型与LNM有统计学关联（均P<0.05）。使用ROC曲线下面积评估，预测LNM的CS和SUVmax的最佳截断值分别为19 mm和5.5。CS≥19 mm和SUVmax≥5.5的组合显示出比每个参数单独使用时明显更高的优势比（9.184；95%CI，4.345-19.407）。与LNM相关的CS和SUVmax的最小值分别为10 mm和0.8。纯实性形成以及作为形态学的CS和作为代谢的SUVmax是在预测LNM中相互补充的有用工具。评估SUVmax和CS的联合方法可能有助于确定是否适合进行淋巴结清扫。然而，考虑到LNM中CS和SUVmax的最小值，对于不符合HRCT和PET-CT联合标准的病例，不能肯定可以省略淋巴结清扫。
