A model based on Chinese thyroid imaging reporting and data systems for predicting Bethesda III/IV thyroid nodules

Area of Science:

• Radiology
• Endocrinology
• Oncology

Background:

• Accurate prediction of Bethesda III/IV thyroid nodules before fine needle aspiration (FNA) is crucial for diagnosis and treatment planning.
• Existing methods like the Chinese Thyroid Imaging Reporting and Data Systems (C-TIRADS) have limitations in predicting malignancy risk.

Purpose of the Study:

• To develop and evaluate a predictive model for Bethesda III/IV thyroid nodules using C-TIRADS, clinical, and ultrasound characteristics.
• To compare the performance of the developed model against C-TIRADS alone in predicting Bethesda III/IV thyroid nodules.

Main Methods:

• A retrospective study included 855 thyroid nodules from 810 patients.
• Nodules were categorized using C-TIRADS and classified into Bethesda III/IV and non-III/IV groups based on cytologic diagnosis.
• Logistic regression analysis identified independent predictors, and a predictive model was constructed and validated using Area Under the Curve (AUC).

Main Results:

• Independent predictors for Bethesda III/IV nodules included C-TIRADS category, homogeneous echotexture, presence of blood flow signal, and unchanged posterior echo.
• The developed predictive model demonstrated a significantly higher AUC (0.746 overall) compared to C-TIRADS alone.
• The model's predictive efficacy was particularly notable for nodules with a diameter greater than 10mm (AUC 0.779).

Conclusions:

• A novel predictive model integrating C-TIRADS and ultrasound features effectively predicts Bethesda III/IV thyroid nodules.
• This model offers improved diagnostic performance, especially for larger nodules, aiding in optimal FNA strategy selection.
• The model has the potential to enhance the definitive diagnosis rate of the first FNA and reduce the need for repeat procedures.