Artificial Intelligent Accelerates the Learning Curve for Mastering Thyroid Imaging Reporting and Data System of Contrast-enhanced Ultrasound
The goal of this observational study is to learn about the learning curve for mastering the thyroid imaging reporting and data system of contrast-enhanced ultrasound with the assistance of artificial intelligence in patients with thyroid nodules. The main questions it aims to answer are: 1. Can we develop a artificial intelligent software to assist doctors in the diagnosis of thyroid nodules using contrast-enhanced ultrasound? 2. Can artificial intelligent reduce the number of cases and time for doctors to master the contrast-enhanced ultrasound diagnosis of thyroid nodules? Participants will be asked to undergo contrast-enhanced ultrasound examination and ultrasound-guided fine-needle aspiration of thyroid nodules. Researchers will compare the number of cases and time for doctors with and without artificial intelligent assistance to master the contrast-enhanced ultrasound diagnosis of thyroid nodules to see if artificial intelligent reduce the number of cases and time.
• Patients with thyroid nodules with a solid component ≥5 mm confirmed by conventional ultrasound;
• Patients who underwent conventional ultrasound, contrast-enhanced ultrasound, and fine-needle aspiration biopsy;
• Patients with a final benign or malignant pathological results.