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Updated: Sep 13, 2025
A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
Published on: April 21, 2023
Diagnostic Performance of Imaging-Based Artificial Intelligence Models for Preoperative Detection of Cervical Lymph
Bosheng Li1, Gang Cheng2, Yeping Mo1
1Department of Ultrasound, Changde Hospital, Xiangya School of Medicine, Central South University, Changde, Hunan, China.
Purpose:
This systematic review and meta-analysis evaluated the performance of imaging-based artificial intelligence (AI) models in diagnosing preoperative cervical lymph node metastasis (LNM) in clinically node-negative (cN0) papillary thyroid carcinoma (PTC).
Methods:
We conducted a literature search in PubMed, Embase, and Web of Science until February 25, 2025. Studies were selected that focused on imaging-based AI models for predicting cervical LNM in cN0 PTC. The diagnostic performance metrics were analyzed using a bivariate random-effects model, and study quality was assessed with the QUADAS-2 tool.
Results:
From 671 articles, 11 studies involving 3366 patients were included. Ultrasound (US)-based AI models showed pooled sensitivity of 0.79 and specificity of 0.82, significantly higher than radiologists (p < 0.001). CT-based AI models demonstrated sensitivity of 0.78 and specificity of 0.89.
Conclusions:
Imaging-based AI models, particularly US-based AI, show promising diagnostic performance. There is a need for further multicenter prospective studies for validation.
Trial Registration:
PROSPERO: (CRD420251063416).
