Zhang Ran, Zhang Ranran, Luan Ting, Liu Biwei, Zhang Yimei, Xu Yaping, Sun Xiaorong, Xing Ligang
Department of Radiation Oncology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, People's Republic of China.
Tongji University, Shanghai, People's Republic of China.
Cancer Manag Res. 2021 Oct 28;13:8157-8167. doi: 10.2147/CMAR.S330824. eCollection 2021.
Clinical occult lymph node metastasis (cOLNM) means that the lymph node is negatively diagnosed by preoperative computed tomography (CT), but has been proven to be positive by postoperative pathology. The aim of this study was to establish and validate a nomogram based on radiomics features for the preoperative prediction of cOLNM in early-stage solid lung adenocarcinoma patients.
A total of 244 patients with clinical T1-2N0M0 solid lung adenocarcinoma who underwent preoperative contrast-enhanced chest CT were divided into a primary group (n = 160) and an independent validation group from another hospital (n = 84). The records of 851 radiomics features of each primary tumor were extracted. LASSO analysis was used to reduce the data dimensionality and select features. Multivariable logistic regression was utilized to identify independent predictors of cOLNM and develop a predictive nomogram. The performance of the predictive model was assessed by its calibration and discrimination. Decision curve analysis (DCA) was performed to estimate the clinical usefulness of the nomogram.
The predictive model consisted of a clinical factor (CT-reported tumor size) and a radiomics feature (Rad-score). The nomogram presented good discrimination, with a C-index of 0.782 (95% CI, 0.768-0.796) in the primary cohort and 0.813 (95% CI, 0.787-0.839) in the validation cohort, and good calibration. DCA showed that the radiomics nomogram was clinically useful.
This study develops and validates a nomogram that incorporates clinical and radiomics factors. It can be tailored for the individualized preoperative prediction of cOLNM in early-stage solid lung adenocarcinoma patients.
临床隐匿性淋巴结转移（cOLNM）是指淋巴结在术前计算机断层扫描（CT）检查中诊断为阴性，但术后病理证实为阳性。本研究的目的是建立并验证一种基于影像组学特征的列线图，用于术前预测早期实性肺腺癌患者的cOLNM。
共有244例临床T1-2N0M0实性肺腺癌患者接受了术前胸部增强CT检查，分为原发组（n = 160）和来自另一家医院的独立验证组（n = 84）。提取每个原发肿瘤的851个影像组学特征记录。采用LASSO分析进行数据降维和特征选择。利用多变量逻辑回归确定cOLNM的独立预测因素并建立预测列线图。通过校准和鉴别评估预测模型的性能。进行决策曲线分析（DCA）以评估列线图的临床实用性。
预测模型由一个临床因素（CT报告的肿瘤大小）和一个影像组学特征（Rad评分）组成。列线图具有良好的鉴别能力，在原发队列中的C指数为0.782（95%CI，0.768-0.796），在验证队列中的C指数为0.813（95%CI，0.787-0.839），并且校准良好。DCA显示影像组学列线图具有临床实用性。
本研究建立并验证了一个整合临床和影像组学因素的列线图。它可用于早期实性肺腺癌患者cOLNM的个体化术前预测。
