Liu Yu, Jiang Ning, Zou Zhiqiang, Liu Hongxiu, Zang Chuanhang, Gu Jia, Xin Ning
Department of Thoracic Surgery, PLA 960th Hospital, Jinan, China.
Department of Thoracic Surgery, The Second Hospital of Shandong University, Jinan, China.
Thorac Cardiovasc Surg. 2025 Jun;73(4):308-316. doi: 10.1055/a-2380-6799. Epub 2024 Aug 6.
More effective methods are urgently needed for predicting the pathological grade and lymph node metastasis of cT1-stage lung adenocarcinoma.
We analyzed the relationships between CT quantitative parameters (including three-dimensional parameters) and pathological grade and lymph node metastasis in cT1-stage lung adenocarcinoma patients of our center between January 2015 and December 2023.
A total of 343 patients were included, of which there were 233 males and 110 females, aged 61.8 ± 9.4 (30-82) years. The area under the receiver operating characteristic (ROC) curve for predicting the pathological grade of lung adenocarcinoma using the consolidation-tumor ratio (CTR) and the solid volume ratio (SVR) were 0.761 and 0.777, respectively. The areas under the ROC curves (AUCs) for predicting lymph node metastasis were 0.804 and 0.873, respectively. Multivariate logistic regression analysis suggested that the SVR was an independent predictor of highly malignant lung adenocarcinoma pathology, while the SVR and pathological grade were independent predictors of lymph node metastasis. The sensitivity of predicting the pathological grading of lung adenocarcinoma based on SVR >5% was 97.2%, with a negative predictive value of 96%. The sensitivity of predicting lymph node metastasis based on SVR >47.1% was 97.3%, and the negative predictive value was 99.5%.
The SVR has greater diagnostic value than the CTR in the preoperative prediction of pathologic grade and lymph node metastasis in stage cT1-stage lung adenocarcinoma patients, and the SVR may replace the diameter and CTR as better criteria for guiding surgical implementation.
迫切需要更有效的方法来预测cT1期肺腺癌的病理分级和淋巴结转移情况。
我们分析了2015年1月至2023年12月本中心cT1期肺腺癌患者的CT定量参数(包括三维参数)与病理分级和淋巴结转移之间的关系。
共纳入343例患者,其中男性233例,女性110例,年龄61.8±9.4(30 - 82)岁。使用实变-肿瘤比(CTR)和实性体积比(SVR)预测肺腺癌病理分级的受试者操作特征(ROC)曲线下面积分别为0.761和0.777。预测淋巴结转移的ROC曲线下面积(AUC)分别为0.804和0.873。多因素logistic回归分析表明,SVR是高恶性肺腺癌病理的独立预测因子,而SVR和病理分级是淋巴结转移的独立预测因子。基于SVR>5%预测肺腺癌病理分级的敏感性为97.2%,阴性预测值为96%。基于SVR>47.1%预测淋巴结转移的敏感性为97.3%,阴性预测值为99.5%。
在术前预测cT1期肺腺癌患者的病理分级和淋巴结转移方面,SVR比CTR具有更大的诊断价值,SVR可能取代直径和CTR,成为指导手术实施的更好标准。