The diagnostic value of a nomogram based on multimodal ultrasonography for thyroid-nodule differentiation: A multicenter study

Dan Yi; Libin Fan; Jianbo Zhu; Jincao Yao; Chanjuan Peng; Dong Xu

doi:10.3389/fonc.2022.970758

The diagnostic value of a nomogram based on multimodal ultrasonography for thyroid-nodule differentiation: A multicenter study

Front Oncol. 2022 Aug 18:12:970758. doi: 10.3389/fonc.2022.970758. eCollection 2022.

Authors

Dan Yi^{1

2}, Libin Fan³, Jianbo Zhu¹, Jincao Yao⁴, Chanjuan Peng⁴, Dong Xu^{4

5

6}

Affiliations

¹ 1Department of Ultrasound, Shaoxing People's Hospital, Shaoxing, China.
² Zhejiang Chinese Medical University, Hangzhou, China.
³ Department of Surgery, Affiliated Hospital of Shaoxing University, Shaoxing, China.
⁴ Department of Ultrasound in Medicine, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China.
⁵ Key Laboratory of Head & Neck Cancer Translational Research of Zhejiang Province, Hangzhou, China.
⁶ Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology, Hangzhou, China.

Abstract

Objective: To establish and verify a nomogram based on multimodal ultrasonography (US) for the assessment of the malignancy risk of thyroid nodules and to explore its value in distinguishing benign from malignant thyroid nodules.

Methods: From September 2020 to December 2021, the data of 447 individuals with thyroid nodules were retrieved from the multicenter database of medical images of the National Health Commission's Capacity Building and Continuing Education Center, which includes data from more than 20 hospitals. All patients underwent contrast-enhanced US (CEUS) and elastography before surgery or fine needle aspiration. The training set consisted of three hundred datasets from the multicenter database (excluding Zhejiang Cancer Hospital), and the external validation set consisted of 147 datasets from Zhejiang Cancer Hospital. As per the pathological results, the training set was separated into benign and malignant groups. The characteristics of the lesions in the two groups were analyzed and compared using conventional US, CEUS, and elastography score. Using multivariate logistic regression to screen independent predictive risk indicators, then a nomogram for risk assessment of malignant thyroid nodules was created. The diagnostic performance of the nomogram was assessed utilizing calibration curves and receiver operating characteristic (ROC) from the training and validation cohorts. The nomogram and The American College of Radiology Thyroid Imaging, Reporting and Data System were assessed clinically using decision curve analysis (DCA).

Results: Multivariate regression showed that irregular shape, elastography score (≥ 3), lack of ring enhancement, and unclear margin after enhancement were independent predictors of malignancy. During the training (area under the ROC [AUC]: 0.936; 95% confidence interval [CI]: 0.902-0.961) and validation (AUC: 0.902; 95% CI: 0.842-0.945) sets, the multimodal US nomogram with these four variables demonstrated good calibration and discrimination. The DCA results confirmed the good clinical applicability of the multimodal US nomogram for predicting thyroid cancer.

Conclusions: As a preoperative prediction tool, our multimodal US-based nomogram showed good ability to distinguish benign from malignant thyroid nodules.

Keywords: contrast-enhanced ultrasonography; elastography; multimodality; nomogram; thyroid nodules.