• Eur J Radiol · Sep 2019

    Radiomic analysis for preoperative prediction of cervical lymph node metastasis in patients with papillary thyroid carcinoma.

    • Wei Lu, Lianzhen Zhong, Di Dong, Mengjie Fang, Qi Dai, Shaoyi Leng, Liwen Zhang, Wei Sun, Jie Tian, Jianjun Zheng, and Yinhua Jin.
    • Department of Medical Imaging, Hwa Mei Hospital, University of Chinese Academy of Sciences, Ningbo, Zhejiang, China; CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China. Electronic address: luwei19@ucas.ac.cn.
    • Eur J Radiol. 2019 Sep 1; 118: 231-238.

    PurposeCervical lymph node (LN) metastasis of papillary thyroid carcinoma (PTC) is critical for treatment and prognosis. We explored the feasibility of using radiomics to preoperatively predict cervical LN metastasis in PTC patients.MethodTotal 221 PTC patients (training cohort: n = 154; validation cohort: n = 67; divided randomly at the ratio of 7:3) were enrolled and divided into 2 groups based on LN pathologic diagnosis (N0: n = 118; N1a and N1b: n = 88 and 15, respectively). We extracted 546 radiomic features from non-contrast and venous contrast-enhanced computed tomography (CT) images. We selected 8 groups of candidate feature sets by minimum redundancy maximum relevance (mRMR), and obtained 8 radiomic sub-signatures by support vector machine (SVM) to construct the radiomic signature. Incorporating the radiomic signature, CT-reported cervical LN status and clinical risk factors, a nomogram was constructed using multivariable logistic regression. The nomogram's calibration, discrimination, and clinical utility were assessed.ResultsThe radiomic signature was associated significantly with cervical LN status (p < 0.01 for both training and validation cohorts). The radiomic signature showed better predictive performance than any radiomic sub-signatures devised by SVM. Addition of radiomic signature to the nomogram improved the predictive value (area under the curve (AUC), 0.807 to 0.867) in the training cohort; this was confirmed in an independent validation cohort (AUC, 0.795 to 0.822). Good agreement was observed using calibration curves in both cohorts. Decision curve analysis demonstrated the radiomic nomogram was worthy of clinical application.ConclusionsOur radiomic nomogram improved the preoperative prediction of cervical LN metastasis in PTC patients.Copyright © 2019 Elsevier B.V. All rights reserved.

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