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Magnetic resonance imaging (MRI) radiomics of papillary thyroid cancer (PTC): a comparison of predictive performance of multiple classifiers modeling to identify cervical lymph node metastases before surgery

  • Diagnostic Imaging in Oncology
  • Published:
La radiologia medica Aims and scope Submit manuscript

Abstract

Purpose

To compare predictive efficiency of multiple classifiers modeling and establish a combined magnetic resonance imaging (MRI) radiomics model for identifying lymph node (LN) metastases of papillary thyroid cancer (PTC) preoperatively.

Materials and methods

A retrospective analysis based on the preoperative MRI scans of 109 PTC patients including 77 patients with LN metastases and 32 patients without metastases was conducted, and we divided enroll cases into trained group and validation group. Radiomics signatures were selected from fat-suppressed T2-weighted MRI images, and the optimal characteristics were confirmed by spearman correlation test, hypothesis testing and random forest methods, and then, eight predictive models were constructed by eight classifiers. The receiver operating characteristic (ROC) curves analysis were performed to demonstrate the effectiveness of the models.

Results

The area under the curve (AUC) of ROC based on MRI texture diagnosed LN status by naked eye was 0.739 (sensitivity = 0.571, specificity = 0.906). Based on the 5 optimal signatures, the best AUC of MRI radiomics model by logistics regression classifier had a considerable prediction performance with AUCs 0.805 in trained group and 0.760 in validation group, respectively, and a combination of best radiomics model with visual diagnosis of MRI texture had a high AUC as 0.969 (sensitivity = 0.938, specificity = 1.000), suggesting combined model had a preferable diagnostic efficiency in evaluating LN metastases of PTC.

Conclusion

Our combined radiomics model with visual diagnosis could be a potentially effective strategy to preoperatively predict LN metastases in PTC patients before clinical intervention.

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Funding

The study was supported by funds from the Guangxi Scientific Research and Technology Development Plan (1598011–4), the National Natural Science Foundation of China (grant no. NSFC81860319 and grant no. NSFC81960329) and Guangxi Science and Technology Program (grant no. GuiKeAB17195020) and Guangxi National Nature Science Foundation (2017GXNSFAA198253).

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Author notes

  1. Hui Qin and Qiao Que contributed equally to this work.

Authors and Affiliations

  1. Department of Medical Ultrasonics, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Guangxi Zhuang Autonomous Region, Nanning, People’s Republic of China

    Hui Qin, Qiao Que, Peng Lin, Yun He & Hong Yang

  2. Department of Gastrointestinal Surgery, The First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Guangxi Zhuang Autonomous Region, Nanning, People’s Republic of China

    Jun-qiang Chen

  3. Department of GE Healthcare Global Research, GE Healthcare, Shanghai, 201203, People’s Republic of China

    Xin Li & Xin-rong Wang

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  1. Hui Qin
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Hui Qin, Qiao Que, Peng Lin and Xin Li, Xin-rong Wang. The first draft of the manuscript was written by Hui Qin, Qiao Que, Hong Yang, Jun-qiang Chen and Yun He. Hong Yang, Jun-qiang Chen and Yun He corrected the manuscript. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. All listed authors qualify for authorship according to criteria. We has also certified that no part of the work described has been published before [except in the form of an abstract or as part of a published lecture, review, thesis, or dissertation (appropriately cited)]; that the work is not under consideration for publication elsewhere; and that the manuscript, or its parts, will not be published elsewhere subsequently in any language without the consent of the copyright holders.

Corresponding authors

Correspondence to Jun-qiang Chen or Hong Yang.

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All authors declare that they have no conflict of interest.

Ethical approval

The local ethics committee approved this retrospective study conducted between January 1, 2017, to January 1, 2021, and informed consent was waived by the institutional review board.

Human and animal participants

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration.

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The requirement for informed consent was waived by the institutional review board.

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Qin, H., Que, Q., Lin, P. et al. Magnetic resonance imaging (MRI) radiomics of papillary thyroid cancer (PTC): a comparison of predictive performance of multiple classifiers modeling to identify cervical lymph node metastases before surgery. Radiol med 126, 1312–1327 (2021). https://doi.org/10.1007/s11547-021-01393-1

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