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Differentiate Thyroid Follicular Adenoma from Carcinoma with Combined Ultrasound Radiomics Features and Clinical Ultrasound Features

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Abstract

Noninvasive differentiating thyroid follicular adenoma from carcinoma preoperatively is of great clinical value to decrease the risks resulted from excessive surgery for patients with follicular neoplasm. The purpose of this study is to investigate the accuracy of ultrasound radiomics features integrating with ultrasound features in the differentiation between thyroid follicular carcinoma and adenoma. A total of 129 patients diagnosed as thyroid follicular neoplasm with pathologically confirmed follicular adenoma and carcinoma were enrolled and analyzed retrospectively. Radiomics features were extracted from preoperative ultrasound images with manually contoured targets. Ultrasound features and clinical parameters were also obtained from electronic medical records. Radiomics signature, combined model integrating radiomics features, ultrasound features, and clinical parameters were constructed and validated to differentiate the follicular carcinoma from adenoma. A total of 23 optimal features were selected from 449 extracted radiomics features. Clinical and ultrasound parameters of sex (p = 0.003), interior structure (p = 0.035), edge (p = 0.02), platelets (p = 0.007), and creatinine (p = 0.001) were associated with the differentiation between benign and malignant follicular neoplasm. The values of area under curves (AUCs) of the radiomics signature, clinical model, and combined model were 0.772 (95% CI: 0.707–0.838), 0.792 (95% CI: 0.715–0.869), and 0.861 (95% CI: 0.775–0.909), respectively. A final corrected AUC of 0.844 was achieved for the combined model after internal validation. Radiomics features from ultrasound images combined with ultrasound features and clinical factors are feasible to differentiate thyroid follicular carcinoma from adenoma noninvasive before operation to decrease the unnecessary of diagnostic thyroidectomy for patients with benign follicular adenoma.

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Acknowledgements

This work was partially funded by Radiation Oncology Basic and Translational Research Key Lab of Wenzhou (2021100848)

Funding

This work was partially funded by Wenzhou Municipal Science and Technology Bureau (2018ZY016, 2019) and National Natural Science Foundation of China (No.11675122, 2016).

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Author notes

  1. Bing Yu and Yanyan Li are contributed equally to this work.

Authors and Affiliations

  1. Radiotherapy Center, Wenzhou Medical University First Affiliated Hospital, Wenzhou, 32500, China

    Bing Yu, Yao Ai, Juebin Jin, Ji Zhang, Congying Xie & Xiance Jin

  2. Department of Ultrasound Imaging, Wenzhou Medical University Second Affiliated Hospital, Wenzhou, 32500, China

    Yanyan Li, YuHua Zhang, Hui Zhu & Yan Yang

  3. Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China

    Xiangle Yu & Meixiao Shen

  4. Radiation and Medical Oncology, Wenzhou Medical University Second Affiliated Hospital, Wenzhou, 32500, China

    Congying Xie

  5. School of Basic Medical Science, Wenzhou Medical University, Wenzhou, 325000, China

    Xiance Jin

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  1. Bing Yu
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  3. Xiangle Yu
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Corresponding authors

Correspondence to Meixiao Shen, Yan Yang or Xiance Jin.

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This study was approved by the institutional review board and conducted in accordance with the Declaration of Helsinki (ECCR no. 2019059). Informed consent was waived by ECCR for the retrospective nature of this study.

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Yu, B., Li, Y., Yu, X. et al. Differentiate Thyroid Follicular Adenoma from Carcinoma with Combined Ultrasound Radiomics Features and Clinical Ultrasound Features. J Digit Imaging 35, 1362–1372 (2022). https://doi.org/10.1007/s10278-022-00639-2

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  • DOI: https://doi.org/10.1007/s10278-022-00639-2

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