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LymphUs: A multicenter open-access database of lymph node ultrasound images in patients with papillary thyroid carcinoma for clinical and artificial intelligence research.

March 17, 2026pubmed logopapers

Authors

Mohammadi A,Mohebbi A,Mirza-Aghazadeh-Attari M,Mohammadzadeh S,Acharya UR,Tan RS,Salvi M,Hatamikia S,Abbasian Ardakani A

Affiliations (12)

  • Department of Radiology, Faculty of Medicine, Urmia University of Medical Science, Urmia, Iran.
  • Clinical AI-Research in Omics and Medical Data Science (CAROM) group, Department of Medicine, Faculty of Medicine and Dentistry, Danube Private University, Krems an der Donau, Austria.
  • Division of Vascular and Interventional Radiology, Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA.
  • Universal Scientific Education and Research Network (USERN), Tehran, Iran.
  • School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
  • School of Mathematics, Physics and Computing, University of Southern Queensland, Springfield, Queensland, Australia.
  • Centre for Health Research, University of Southern Queensland, Springfield, Queensland, Australia.
  • National Heart Centre Singapore, Singapore.
  • Duke-NUS Medical School, Singapore.
  • Biolab, PolitoBIOMedLab, Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy.
  • Austrian Center for Medical Innovation and Technology (ACMIT), Wiener Neustadt, Austria.
  • Department of Radiology Technology, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Abstract

Approximately 30-50% of Papillary thyroid carcinoma (PTC) patients develop cervical lymph nodes (LNs) metastasis, significantly increasing the risk of disease recurrence and impacting long-term outcomes. We introduced an open-access multicenter lymph node ultrasound image database (LymphUs) specifically designed to advance research in LN assessment for PTC. Ultrasound imaging was performed on PTC patients at two independent clinical centers using standardized acquisition protocols. Experienced radiologists at each center documented sixteen semantic features for each LN. All LNs were annotated with segmentation masks serving as ground truth, and classification into benign or malignant categories was confirmed by fine needle aspiration biopsy results. The LymphUs comprises ultrasound images with segmentation masks from 338 PTC patients with suspected LN metastasis, divided into two center-specific cohorts: 180 patients (81 malignant, 99 benign) and 158 patients (82 malignant, 76 benign). The complete dataset, including semantic features and expert annotations, is freely accessible for research purposes. The LymphUs bridges a critical gap in medical imaging resources by providing a large-scale, multicenter ultrasound database for cervical LN assessment in PTC, supporting diagnostic algorithms, standardized reporting systems, and artificial intelligence applications to enhance preoperative LN staging and treatment planning.

Topics

Journal Article

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