Artificial Intelligence-assisted Contrast-enhanced Ultrasound Diagnosis of Thyroid Nodules

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University1,955 enrolled

Overview

The goal of this intervention study is to learn about the diagnostic performance of artificial intelligence to assist the contrast-enhanced ultrasound diagnosis of thyroid nodules. The main questions it aims to answer are: 1. Can we develop an artificial intelligence model to assist the contrast-enhanced ultrasound diagnosis of thyroid nodules? 2. Can artificial intelligent reduce the unnecessary biopsy of thyroid nodules? Participants will be asked to undergo contrast-enhanced ultrasound examination and ultrasound-guided fine-needle aspiration of thyroid nodules. Researchers will calculate the diagnostic performance of the contrast-enhanced ultrasound diagnosis of thyroid nodules with and without artificial intelligent assistance.

Study Type

INTERVENTIONAL

Allocation

Purpose

DIAGNOSTIC

Masking

NONE

Enrollment

1,955

Conditions

Thyroid Nodule

Interventions

Eligibility

Sex: ALLMin age: 18 Years

Medical Language ↔ Plain English

Inclusion Criteria: * 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. Exclusion Criteria: * Patients with cytopathology of Bethesda I, III, or IV and without final benign or malignant pathology； * Patients with a history of thyroid ablation or surgery; * Patients with low-quality ultrasound images.

Outcomes

Primary Outcomes

Diagnostic performance

Sensitivity, specificity, positive predictive value, negative predictive value, accuracy, area under the curve

Time frame: First week after primary completion date.

The necessity of biopsy

Unnecessary biopsy rate