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A Model Based on C-TIRADS Combined with SWE for Predicting Bethesda I Thyroid Nodules

Overview
Journal Front Oncol
Specialty Oncology
Date 2024 Sep 16
PMID 39281385
Authors
An Wei
Yu-Long Tang
Shi-Chu Tang
Xian-Ya Zhang
Jia-Yu Ren
Long Shi
Xin-Wu Cui
Chao-Xue Zhang
Affiliations
Soon will be listed here.
Abstract

Objectives: This study aimed to explore the performance of a model based on Chinese Thyroid Imaging Reporting and Data Systems (C-TIRADS), clinical characteristics, and shear wave elastography (SWE) for the prediction of Bethesda I thyroid nodules before fine needle aspiration (FNA).

Materials And Methods: A total of 267 thyroid nodules from 267 patients were enrolled. Ultrasound and SWE were performed for all nodules before FNA. The nodules were scored according to the 2020 C-TIRADS, and the ultrasound and SWE characteristics of Bethesda I and non-I thyroid nodules were compared. The independent predictors were determined by univariate analysis and multivariate logistic regression analysis. A predictive model was established based on independent predictors, and the sensitivity, specificity, and area under the curve (AUC) of the independent predictors were compared with that of the model.

Results: Our study found that the maximum diameter of nodules that ranged from 15 to 20 mm, the C-TIRADS category <4C, and <52.5 kPa were independent predictors for Bethesda I thyroid nodules. Based on multiple logistic regression, a predictive model was established: Logit (p) = -3.491 + 1.630 × maximum diameter + 1.719 × C-TIRADS category + 1.046 × (kPa). The AUC of the model was 0.769 (95% CI: 0.700-0.838), which was significantly higher than that of the independent predictors alone.

Conclusion: We developed a predictive model for predicting Bethesda I thyroid nodules. It might be beneficial to the clinical optimization of FNA strategy in advance and to improve the accurate diagnostic rate of the first FNA, reducing repeated FNA.

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