The MR radiomic signature can predict preoperative lymph node metastasis in patients with esophageal cancer

被引:75
作者
Qu, Jinrong [1 ,2 ]
Shen, Chen [2 ,3 ]
Qin, Jianjun [4 ]
Wang, Zhaoqi [1 ]
Liu, Zhenyu [3 ]
Guo, Jia [1 ]
Zhang, Hongkai [1 ]
Gao, Pengrui [1 ]
Bei, Tianxia [1 ]
Wang, Yingshu [1 ]
Liu, Hui [1 ]
Kamel, Ihab R. [5 ]
Tian, Jie [2 ,3 ]
Li, Hailiang [1 ]
机构
[1] Zhengzhou Univ, Henan Canc Hosp, Dept Radiol, Affiliated Canc Hosp, Zhengzhou 450003, Henan, Peoples R China
[2] Xidian Univ, Sch Life Sci & Technol, Xian 710126, Shaanxi, Peoples R China
[3] Chinese Acad Sci, Inst Automat, Key Lab Mol Imaging, Beijing 100190, Peoples R China
[4] Zhengzhou Univ, Henan Canc Hosp, Dept Thorac Surg, Affiliated Canc Hosp, Zhengzhou 450003, Henan, Peoples R China
[5] Johns Hopkins Univ, Sch Med, Dept Radiol, Baltimore, MD 21205 USA
基金
中国国家自然科学基金;
关键词
Magnetic resonance imaging; Esophageal cancer; Lymph nodes; Metastasis; CT TEXTURE; HETEROGENEITY; SEQUENCE; NUMBER;
D O I
10.1007/s00330-018-5583-z
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
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.
引用
收藏
页码:906 / 914
页数:9
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