ORIGINAL RESEARCH article
Front. Endocrinol.
Sec. Thyroid Endocrinology
Volume 16 - 2025 | doi: 10.3389/fendo.2025.1634875
This article is part of the Research TopicRadiomics and Artificial Intelligence in Oncology ImagingView all 8 articles
A Novel Deep Learning Model Based on Multimodal Contrast-Enhanced Ultrasound Dynamic Video for Predicting Occult Lymph Node Metastasis in Papillary Thyroid Carcinoma
Provisionally accepted
- 1Department of Medical Ultrasound, The First Affiliated Hospital of Gannan Medical University, Ganzhou, China
- 2Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
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Objective: This study aimed to evaluate the value of constructing a multimodal deep-learning video model based on 2D ultrasound and contrastenhanced ultrasound (CEUS) dynamic video for the preoperative prediction of OLNM in papillary thyroid carcinoma (PTC) patients.A retrospective analysis was conducted on 396 cases of clinically lymph node-negative PTC cases with ultrasound images collected between January and September 2023. Five representative deep learning architectures were pre-trained to construct deep learning static image models (DL_image), CEUS dynamic video models (DL_CEUSvideo), and combined models (DL_combined). The area under the receiver operating characteristic curve (AUC) was used to evaluate model performance, with comparisons made using the Delong test. A P-value of less than 0.05 was considered statistically significant.The DL_CEUSvideo, DL_image, and DL_combined models were successfully developed and demonstrated. The AUC values were 0.826 (95% CI: 0.771-0.881), 0.759 (95% CI: 0.690-0.828), and 0.926 (95% CI: 0.891-0.962) in the training set, and 0.701 (95% CI: 0.589-0.813), 0.624 (95% CI: 0.502-0.745), and 0.734 (95% CI: 0.627-0.842) in the test set. Finally, sensitivity, specificity, and accuracy for the DL_CEUSvideo, DL_image, and DL_combined models were 0.836, 0.671, 0.704; 0.673, 0.716, 0.707; and 0.818, 0.902, 0.886 in the training set, and 0.556, 0.775, 0.724; 0.556, 0.674, 0.647; and 0.704, 0.663, 0.672 in the test set, respectively.These results demonstrated that the multimodal deep learning dynamic video model could preoperatively predict OLNM in PTC patients.The DL_CEUSvideo model outperformed the DL_image model, while the DL_combined model significantly enhanced sensitivity without compromising specificity.
Keywords: Papillary thyroid carcinoma, Occult lymph node metastasis, Dynamic video, deep learning, contrast-enhanced ultrasound
Received: 25 May 2025; Accepted: 08 Jul 2025.
Copyright: © 2025 Liu, Yuan, Wang, Chen, Ye and He. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Jun Ye, Department of Medical Ultrasound, The First Affiliated Hospital of Gannan Medical University, Ganzhou, China
Yun He, Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
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