The MR radiomic signature can predict preoperative lymph node metastasis in patients with esophageal cancer
The MR radiomic signature can predict preoperative lymph node metastasis in patients with esophageal cancer
复制标题
MR放射组学特征可以预测食管癌患者的术前淋巴结转移。
DOI：
10.1007/s00330-018-5583-z
复制
发表时间：
2019-02-01
影响因子：
5.9
通讯作者：
Li, Hailiang
中科院分区：
文献类型：
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作者：
Qu, Jinrong;Shen, Chen;Li, Hailiang
PurposeTo评估MR放射组学标记在术前预测食管癌（EC）患者淋巴结（LN）转移中的作用。患者和方法2015年4月至2017年9月期间，共有181例EC患者入选本研究。病理证实有淋巴结转移。将该队列的前半部分（90例患者）设置为训练队列，将后半部分（91例患者）设置为验证队列。从MR图像（T2-TSE-BLADE和对比度增强StarVIBE）中提取了总共1578个放射组学特征。利用套索和弹性网络回归模型进行特征空间的降维和选择。采用多因素Logistic回归分析确定病理受累淋巴结的放射学特征。以受试者工作特征曲线下面积（AUC）评价鉴别性能。采用Mann-Whitney U检验来测试在训练和验证cohols.ResultsNine放射组学特征中放射组学特征和LN状态的潜在相关性，以创建与LN转移显著相关的放射组学特征（p < 0.001）。训练队列中放射组学特征性能的AUC为0.821（95% CI：0.7042-0.9376），验证队列中为0.762（95% CI：0.7127-0.812）。该模型表现出良好的区分转移性和非转移性lymph nodes.ConclusionThe目前的研究表明，MRI放射组学特征，可以潜在地预测转移性LN参与EC patients.Key Points中心点的术前评估MRI在食管癌患者的术前分期中的作用是increasing.center点MRI放射组学特征显示的能力，预测LN转移EC patients.center点ICC显示出色的interreader协议提取的MR功能。
PurposeTo assess the role of the MR radiomic signature in preoperative prediction of lymph node (LN) metastasis in patients with esophageal cancer (EC).Patients and methodsA total of 181 EC patients were enrolled in this study between April 2015 and September 2017. Their LN metastases were pathologically confirmed. The first half of this cohort (90 patients) was set as the training cohort, and the second half (91 patients) was set as the validation cohort. A total of 1578 radiomic features were extracted from MR images (T2-TSE-BLADE and contrast-enhanced StarVIBE). The lasso and elastic net regression model was exploited for dimension reduction and selection of the feature space. The multivariable logistic regression analysis was adopted to identify the radiomic signature of pathologically involved LNs. The discriminating performance was assessed with the area under receiver-operating characteristic curve (AUC). The Mann-Whitney U test was adopted for testing the potential correlation of the radiomic signature and the LN status in both training and validation cohorts.ResultsNine radiomic features were selected to create the radiomic signature significantly associated with LN metastasis (p < 0.001). AUC of radiomic signature performance in the training cohort was 0.821 (95% CI: 0.7042-0.9376) and in the validation cohort was 0.762 (95% CI: 0.7127-0.812). This model showed good discrimination between metastatic and non-metastatic lymph nodes.ConclusionThe present study showed MRI radiomic features that could potentially predict metastatic LN involvement in the preoperative evaluation of EC patients.Key Points center dot The role of MRI in preoperative staging of esophageal cancer patients is increasing.center dot MRI radiomic features showed the ability to predict LN metastasis in EC patients.center dot ICCs showed excellent interreader agreement of the extracted MR features.