Wang Hongya, Yang He, Liu Zicheng, Chen Liang, Xu Xinfeng, Zhu Quan
Department of Thoracic Surgery, Jiangsu Province Hospital, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
Zhongguo Fei Ai Za Zhi. 2022 Oct 20;25(10):723-729. doi: 10.3779/j.issn.1009-3419.2022.102.39. Epub 2022 Sep 28.
At present, more and more studies predict invasive adenocarcinoma (IAC) through three-dimensional features of pulmonary nodules, but few studies have confirmed that three-dimensional features have more advantages in diagnosing IAC than traditional two-dimensional features of pulmonary nodules. This study analyzed the differences of chest computed tomography (CT) features between IAC and minimally invasive adenocarcinoma (MIA) from three-dimensional and two-dimensional levels, and compared the ability of diagnosing IAC. The non-invasive adenocarcinoma group includes precursor glandular lesions (PGL) and minimally invasive adenocarcinoma (MIA).
The clinical data of 1,045 patients with ground glass opacity (GGO) from January to December 2019 were collected. Then the correlation between preoperative CT image characteristics and pathological results were analyzed retrospectively. The independent influencing factors for the identification of IAC were screened out according to two-dimensional and three-dimensional classification by multivariate Logistic regression and the cut-off point for the identification of IAC was found out through the receiver operating characteristic (ROC) curve. At last, the ability of diagnosing IAC was evaluated by Yoden index.
The diameter of nodule, the diameter of solid component, the diameter of mediastinal window nodule in two-dimensional factors, and the volume of nodule, the volume of solid part and the average CT value in three-dimensional factors were independent risk factors for the diagnosis of IAC. These factors were arranged by Yoden index: solid partial volume (0.601)>nodule volume (0.536)>solid component diameter (0.525)>nodule diameter (0.518)>mediastinal window nodule diameter (0.488)>proportion of solid component volume (0.471)>1-tumor disappearance ratio (TDR) (0.468)>consolidation tumor ratio (CTR) (0.394)>average CT value (0.380).
The CT features of three-dimensional are better than two-dimensional in the diagnosis of IAC, and the size of solid components is better than the overall size of nodules.
目前,越来越多的研究通过肺结节的三维特征预测浸润性腺癌(IAC),但很少有研究证实三维特征在诊断IAC方面比传统的肺结节二维特征更具优势。本研究从三维和二维层面分析IAC与微浸润性腺癌(MIA)胸部计算机断层扫描(CT)特征的差异,并比较诊断IAC的能力。非浸润性腺癌组包括前驱腺性病变(PGL)和微浸润性腺癌(MIA)。
收集2019年1月至12月1045例磨玻璃影(GGO)患者的临床资料。然后回顾性分析术前CT图像特征与病理结果之间的相关性。根据二维和三维分类,通过多因素Logistic回归筛选出IAC识别的独立影响因素,并通过受试者操作特征(ROC)曲线找出IAC识别的截断点。最后,通过约登指数评估诊断IAC的能力。
二维因素中的结节直径、实性成分直径、纵隔窗结节直径,以及三维因素中的结节体积、实性部分体积和平均CT值是诊断IAC的独立危险因素。这些因素按约登指数排列为:实性部分体积(0.601)>结节体积(0.536)>实性成分直径(0.525)>结节直径(0.518)>纵隔窗结节直径(0.488)>实性成分体积比例(0.471)>1-肿瘤消失率(TDR)(0.468)>实变肿瘤比例(CTR)(0.394)>平均CT值(0.380)。
三维CT特征在诊断IAC方面优于二维,实性成分大小优于结节整体大小。