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Updated: Jul 16, 2026
Electromagnetic Navigation Transthoracic Nodule Localization for Minimally Invasive Thoracic Surgery
Published on: May 4, 2022
Using dynamic nomogram to modify TI-RADS and reduce the unnecessary FNA of thyroid nodules
Jiahui Ni1,2,3, Yunyun Liu1,2,3, Xiaolong Li4
1Center of Minimally Invasive Treatment for Tumor, Department of Medical Ultrasound, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Background:
Current guidelines recommend Fine Needle Aspiration (FNA) based on nodule size and ultrasound characteristics; however, these guidelines still lead to a certain amount of unnecessary FNAs.
Objective:
To develop a dynamic nomogram prediction model based on the ACR Thyroid Imaging, Reporting, and Data System (TI-RADS) to reduce unnecessary FNAs.
Methods:
This multicenter study analyzed 3313 thyroid nodules undergoing FNA. Univariate and multivariate logistic regression models were constructed. Patients were divided into a training cohort and two validation cohorts to compare diagnostic performance and unnecessary FNAs.
Results:
This nomogram achieved performance of Area Under the Curve (AUC) 0.914 (95%CI: 0.894-0.934), 0.923 (95%CI: 0.900-0.946), 0.948 (95%CI: 0.918-0.978) in the training, internal and external validation cohort. Using this model, the unnecessary FNA rates for nodules in ACR TI-RADS category 3 (TR3) have decreased from 99.4% to 0%, in TR4 from 77.6% to 47.1%, and in TR5 from 25.4% to 18.9% in Center1, in TR3 have decreased from 91.9% to 0%, in TR4 from 60.0% to 21.1%, and in TR5 from 11.5% to 4.5% in Center 2 (p < 0.01).
Conclusions:
This dynamic nomogram achieved better prediction of malignant thyroid nodules compared with the mentioned risk stratification system, leading to a more rational FNA strategy.
