An Ultrasound Radiomics Nomogram for Preoperative Prediction of Central Neck Lymph Node Metastasis in Papillary Thyroid Carcinoma

Shi-Chong Zhou; Tong-Tong Liu; Jin Zhou; Yun-Xia Huang; Yi Guo; Jin-Hua Yu; Yuan-Yuan Wang; Cai Chang

doi:10.3389/fonc.2020.01591

An Ultrasound Radiomics Nomogram for Preoperative Prediction of Central Neck Lymph Node Metastasis in Papillary Thyroid Carcinoma

Front Oncol. 2020 Sep 4:10:1591. doi: 10.3389/fonc.2020.01591. eCollection 2020.

Authors

Shi-Chong Zhou^{1

2}, Tong-Tong Liu^{3

4}, Jin Zhou^{1

2}, Yun-Xia Huang^{1

2}, Yi Guo^{3

4}, Jin-Hua Yu^{3

4}, Yuan-Yuan Wang^{3

4}, Cai Chang^{1

2}

Affiliations

¹ Department of Ultrasonography, Fudan University Shanghai Cancer Center, Shanghai, China.
² Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
³ Department of Electronic Engineering, Fudan University, Shanghai, China.
⁴ Key Laboratory of Medical Imaging, Computing and Computer-Assisted Intervention, Shanghai, China.

Abstract

Purpose: This study aimed to establish and validate an ultrasound radiomics nomogram for the preoperative prediction of central lymph node (LN) metastasis in patients with papillary thyroid carcinoma (PTC). Patients and Methods: The prediction model was developed in 609 patients with clinicopathologically confirmed unifocal PTC who received ultrasonography between Jan 2018 and June 2018. Radiomic features were extracted after the ultrasonography of PTC. Lasso regression model was used for data dimensionality reduction, feature selection, and radiomics signature building. The predicting model was established based on the multivariable logistic regression analysis in which the radiomics signature, ultrasonography-reported LN status, and independent clinicopathologic risk factors were incorporated, and finally a radiomics nomogram was established. The performance of the nomogram was assessed with respect to the discrimination and consistence. An independent validation was performed in 326 consecutive patients from July 2018 to Sep 2018. Results: The radiomics signature consisted of 23 selected features and was significantly associated with LN status in both primary and validation cohorts. The independent predictors in the radiomics nomogram included the radiomics signature, age, TG level, TPOAB level, and ultrasonography-reported LN status. The model showed good discrimination and consistence in both cohorts: C-index of 0.816 (95% CI, 0.808-0.824) in the primary cohort and 0.858 (95% CI, 0.849-0.867) in the validation cohort. The area under receiver operating curve was 0.858. In the validation cohort, the accuracy, sensitivity, specificity and AUC of this model were 0.812, 0.816, 0.810, and 0.858 (95% CI, 0.785-0.930), respectively. Decision curve analysis indicated the radiomics nomogram was clinically useful. Conclusion: This study presents a convenient, clinically useful ultrasound radiomics nomogram that can be used for the pre-operative individualized prediction of central LN metastasis in patients with PTC.

Keywords: lymph node; metastasis; papillary thyroid carcinoma; radiomics; ultrasound.