{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T23:23:23Z","timestamp":1788996203135,"version":"build-2803163510"},"reference-count":29,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2024,11,18]],"date-time":"2024-11-18T00:00:00Z","timestamp":1731888000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,18]],"date-time":"2024-11-18T00:00:00Z","timestamp":1731888000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Endocrine"],"DOI":"10.1007\/s12020-024-04091-w","type":"journal-article","created":{"date-parts":[[2024,11,18]],"date-time":"2024-11-18T09:22:07Z","timestamp":1731921727000},"page":"1060-1069","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Deep learning based analysis of dynamic video ultrasonography for predicting cervical lymph node metastasis in papillary thyroid carcinoma"],"prefix":"10.1007","volume":"87","author":[{"given":"Tingting","family":"Qian","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yahan","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jincao","family":"Yao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Ni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sohaib","family":"Asif","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lujiao","family":"lv","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Di","family":"Ou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0583-240X","authenticated-orcid":false,"given":"Dong","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,11,18]]},"reference":[{"issue":"no. 1","key":"4091_CR1","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1038\/s41574-019-0263-x","volume":"16","author":"J Kim","year":"2020","unstructured":"J. Kim, J.E. Gosnell, S.A. Roman, Geographic influences in the global rise of thyroid cancer. Nat. Rev. Endocrinol. 16(no. 1), 17\u201329 (2020). https:\/\/doi.org\/10.1038\/s41574-019-0263-x.","journal-title":"Nat. Rev. Endocrinol."},{"issue":"no. 1","key":"4091_CR2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-18497-3","volume":"11","author":"J Yu","year":"2020","unstructured":"J. Yu et al. Lymph node metastasis prediction of papillary thyroid carcinoma based on transfer learning radiomics. Nat. Commun. 11(no. 1), 4807 (2020). https:\/\/doi.org\/10.1038\/s41467-020-18497-3.","journal-title":"Nat. Commun."},{"issue":"no. 6","key":"4091_CR3","doi-asserted-by":"publisher","first-page":"1277","DOI":"10.1002\/hed.27025","volume":"44","author":"DC Shonka Jr.","year":"2022","unstructured":"D.C. Shonka Jr. et al. American Head and Neck Society Endocrine Surgery Section and International Thyroid Oncology Group consensus statement on mutational testing in thyroid cancer: Defining advanced thyroid cancer and its targeted treatment. Head Neck 44(no. 6), 1277\u20131300 (2022). https:\/\/doi.org\/10.1002\/hed.27025.","journal-title":"Head Neck"},{"issue":"no. 1","key":"4091_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.ecl.2018.10.001","volume":"48","author":"SL Asa","year":"2019","unstructured":"S.L. Asa, The current histologic classification of thyroid cancer. Endocrinol. Metab. Clin. 48(no. 1), 1\u201322 (2019). https:\/\/doi.org\/10.1016\/j.ecl.2018.10.001.","journal-title":"Endocrinol. Metab. Clin."},{"issue":"no. 6","key":"4091_CR5","doi-asserted-by":"publisher","first-page":"601","DOI":"10.1530\/ERC-19-0074","volume":"26","author":"K Bergdorf","year":"2019","unstructured":"K. Bergdorf, D.C. Ferguson, M. Mehrad, K. Ely, T. Stricker, V.L. Weiss, Papillary thyroid carcinoma behavior: clues in the tumor microenvironment. Endocr. Relat. Cancer 26(no. 6), 601\u2013614 (2019). https:\/\/doi.org\/10.1530\/ERC-19-0074.","journal-title":"Endocr. Relat. Cancer"},{"issue":"no. 11","key":"4091_CR6","doi-asserted-by":"publisher","first-page":"4981","DOI":"10.1210\/jc.2019-00962","volume":"104","author":"G Grani","year":"2019","unstructured":"G. Grani et al. Thyroid cancer patients with no evidence of disease: the need for repeat neck ultrasound. J. Clin. Endocrinol. Metab. 104(no. 11), 4981\u20134989 (2019). https:\/\/doi.org\/10.1210\/jc.2019-00962.","journal-title":"J. Clin. Endocrinol. Metab."},{"issue":"no. 12","key":"4091_CR7","doi-asserted-by":"publisher","first-page":"1156","DOI":"10.1001\/jamaoto.2022.3360","volume":"148","author":"AJ Gordon","year":"2022","unstructured":"A.J. Gordon et al. American thyroid association guidelines and national trends in management of papillary thyroid carcinoma. JAMA Otolaryngol. Head Neck Surg. 148(no. 12), 1156\u20131163, (2022). https:\/\/doi.org\/10.1001\/jamaoto.2022.3360.","journal-title":"JAMA Otolaryngol. Head Neck Surg."},{"issue":"no. 6","key":"4091_CR8","doi-asserted-by":"publisher","first-page":"101318","DOI":"10.1016\/j.bjorl.2023.101318","volume":"89","author":"Y Li","year":"2023","unstructured":"Y. Li, L. Lao, Comparison of prophylactic ipsilateral and bilateral central lymph node dissection in papillary thyroid carcinoma: a meta-analysis. Braz. J. Otorhinolaryngol. 89(no. 6), 101318 (2023). https:\/\/doi.org\/10.1016\/j.bjorl.2023.101318.","journal-title":"Braz. J. Otorhinolaryngol."},{"key":"4091_CR9","doi-asserted-by":"publisher","first-page":"101666","DOI":"10.1016\/j.suronc.2021.101666","volume":"39","author":"Y Wang","year":"2021","unstructured":"Y. Wang et al. The diagnostic value of thyroglobulin in fine-needle aspiration of metastatic lymph nodes in patients with papillary thyroid cancer and its influential factors. Surg. Oncol. 39, 101666 (2021). https:\/\/doi.org\/10.1016\/j.suronc.2021.101666.","journal-title":"Surg. Oncol."},{"issue":"no. 9 Pt B","key":"4091_CR10","doi-asserted-by":"publisher","first-page":"1318","DOI":"10.1016\/j.jacr.2019.06.004","volume":"16","author":"Z Akkus","year":"2019","unstructured":"Z. Akkus et al. A Survey of deep-learning applications in ultrasound: artificial intelligence-powered ultrasound for improving clinical workflow. J. Am. Coll. Radiol. JACR 16(no. 9 Pt B), 1318\u20131328 (2019). https:\/\/doi.org\/10.1016\/j.jacr.2019.06.004.","journal-title":"J. Am. Coll. Radiol. JACR"},{"key":"4091_CR11","doi-asserted-by":"publisher","DOI":"10.1186\/s12880-022-00809-2","volume":"22","author":"Y Tong","year":"2022","unstructured":"Y. Tong et al. Ultrasound-based radiomics analysis for preoperative prediction of central and lateral cervical lymph node metastasis in papillary thyroid carcinoma: a multi-institutional study. BMC Med. Imaging 22, 82 (2022). https:\/\/doi.org\/10.1186\/s12880-022-00809-2.","journal-title":"BMC Med. Imaging"},{"issue":"no. 11","key":"4091_CR12","doi-asserted-by":"publisher","first-page":"5881","DOI":"10.1007\/s00330-020-06906-6","volume":"30","author":"X Tian","year":"2020","unstructured":"X. Tian et al. Papillary thyroid carcinoma: an ultrasound-based nomogram improves the prediction of lymph node metastases in the central compartment. Eur. Radiol. 30(no. 11), 5881\u20135893 (2020). https:\/\/doi.org\/10.1007\/s00330-020-06906-6.","journal-title":"Eur. Radiol."},{"issue":"no. 3","key":"4091_CR13","doi-asserted-by":"publisher","first-page":"487","DOI":"10.1002\/lary.21227","volume":"121","author":"HS Hwang","year":"2011","unstructured":"H.S. Hwang, L.A. Orloff, Efficacy of preoperative neck ultrasound in the detection of cervical lymph node metastasis from thyroid cancer. The Laryngoscope 121(no. 3), 487\u2013491 (2011). https:\/\/doi.org\/10.1002\/lary.21227.","journal-title":"The Laryngoscope"},{"key":"4091_CR14","doi-asserted-by":"publisher","first-page":"102007","DOI":"10.1016\/j.eclinm.2023.102007","volume":"60","author":"Y Liu","year":"2023","unstructured":"Y. Liu et al. Deep learning to predict cervical lymph node metastasis from intraoperative frozen section of tumour in papillary thyroid carcinoma: a multicentre diagnostic study. EClinicalMedicine 60, 102007 (2023). https:\/\/doi.org\/10.1016\/j.eclinm.2023.102007.","journal-title":"EClinicalMedicine"},{"key":"4091_CR15","doi-asserted-by":"publisher","first-page":"S36","DOI":"10.1016\/j.metabol.2017.01.011","volume":"69S","author":"P Hamet","year":"2017","unstructured":"P. Hamet, J. Tremblay, Artificial intelligence in medicine. Metabolism 69S, S36\u2013S40 (2017). https:\/\/doi.org\/10.1016\/j.metabol.2017.01.011.","journal-title":"Metabolism"},{"key":"4091_CR16","doi-asserted-by":"publisher","first-page":"8","DOI":"10.21037\/aot.2020.04.01","volume":"5","author":"YJ Chai","year":"2020","unstructured":"Y.J. Chai, J. Song, M. Shaear, K.H. Yi, Artificial intelligence for thyroid nodule ultrasound image analysis. Ann. Thyroid 5, 8\u20138 (2020). https:\/\/doi.org\/10.21037\/aot.2020.04.01.","journal-title":"Ann. Thyroid"},{"key":"4091_CR17","doi-asserted-by":"publisher","first-page":"109717","DOI":"10.1016\/j.ejrad.2021.109717","volume":"139","author":"YT Shen","year":"2021","unstructured":"Y.T. Shen, L. Chen, W.W. Yue, H.X. Xu, Artificial intelligence in ultrasound. Eur. J. Radiol. 139, 109717 (2021). https:\/\/doi.org\/10.1016\/j.ejrad.2021.109717.","journal-title":"Eur. J. Radiol."},{"key":"4091_CR18","doi-asserted-by":"publisher","first-page":"1066508","DOI":"10.3389\/fonc.2022.1066508","volume":"12","author":"C Ni","year":"2022","unstructured":"C. Ni et al. Value of deep learning models based on ultrasonic dynamic videos for distinguishing thyroid nodules. Front. Oncol. 12, 1066508 (2022). https:\/\/doi.org\/10.3389\/fonc.2022.1066508.","journal-title":"Front. Oncol."},{"key":"4091_CR19","doi-asserted-by":"publisher","unstructured":"M. Niethammer, R. Kwitt, F.X. Vialard, \u201cMetric Learning for Image Registration,\u201d in 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, USA: IEEE, Jun. 2019, pp. 8455\u20138464. https:\/\/doi.org\/10.1109\/CVPR.2019.00866.","DOI":"10.1109\/CVPR.2019.00866"},{"issue":"no. 1","key":"4091_CR20","doi-asserted-by":"publisher","first-page":"Art. no. 1","DOI":"10.1609\/aaai.v31i1.11231","volume":"31","author":"C Szegedy","year":"2017","unstructured":"C. Szegedy, S. Ioffe, V. Vanhoucke, A. Alemi, Inception-v4, Inception-ResNet and the impact of residual connections on learning. Proc. AAAI Conf. Artif. Intell. 31(no. 1), Art. no. 1 (2017). https:\/\/doi.org\/10.1609\/aaai.v31i1.11231.","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"4091_CR21","doi-asserted-by":"crossref","unstructured":"C. Szegedy et al., \u201cGoing Deeper With Convolutions,\u201d presented at the Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 1\u20139. Accessed: Aug. 07, 2023. [Online]. Available: https:\/\/www.cv-foundation.org\/openaccess\/content_cvpr_2015\/html\/Szegedy_Going_Deeper_With_2015_CVPR_paper.html.","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"4091_CR22","doi-asserted-by":"crossref","unstructured":"K. He, X. Zhang, S. Ren, J. Sun, \u201cDeep Residual Learning for Image Recognition,\u201d presented at the Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 770\u2013778. Accessed: Aug. 29, 2023. [Online]. Available: https:\/\/openaccess.thecvf.com\/content_cvpr_2016\/html\/He_Deep_Residual_Learning_CVPR_2016_paper.html.","DOI":"10.1109\/CVPR.2016.90"},{"key":"4091_CR23","doi-asserted-by":"publisher","first-page":"101905","DOI":"10.1016\/j.eclinm.2023.101905","volume":"58","author":"Q Qi","year":"2023","unstructured":"Q. Qi et al. Ultrasound image-based deep learning to assist in diagnosing gross extrathyroidal extension thyroid cancer: a retrospective multicenter study. EClinicalMedicine 58, 101905 (2023). https:\/\/doi.org\/10.1016\/j.eclinm.2023.101905.","journal-title":"EClinicalMedicine"},{"key":"4091_CR24","doi-asserted-by":"publisher","first-page":"713475","DOI":"10.3389\/fendo.2021.713475","volume":"12","author":"Y Min","year":"2021","unstructured":"Y. Min et al. Preoperatively predicting the central lymph node metastasis for papillary thyroid cancer patients with Hashimoto\u2019s thyroiditis. Front. Endocrinol. 12, 713475 (2021). https:\/\/doi.org\/10.3389\/fendo.2021.713475.","journal-title":"Front. Endocrinol."},{"key":"4091_CR25","doi-asserted-by":"publisher","first-page":"917794","DOI":"10.3389\/fendo.2022.917794","volume":"13","author":"W Wang","year":"2022","unstructured":"W. Wang, Y. Ding, W. Jiang, X. Li, Can cervical lymph node metastasis increase the risk of distant metastasis in papillary thyroid carcinoma? Front. Endocrinol. 13, 917794 (2022). https:\/\/doi.org\/10.3389\/fendo.2022.917794.","journal-title":"Front. Endocrinol."},{"key":"4091_CR26","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1016\/j.ijsu.2017.12.029","volume":"50","author":"YK So","year":"2018","unstructured":"Y.K. So, M.J. Kim, S. Kim, Y.I. Son, Lateral lymph node metastasis in papillary thyroid carcinoma: A systematic review and meta-analysis for prevalence, risk factors, and location. Int. J. Surg. Lond. Engl 50, 94\u2013103 (2018). https:\/\/doi.org\/10.1016\/j.ijsu.2017.12.029.","journal-title":"Int. J. Surg. Lond. Engl"},{"issue":"no. 3","key":"4091_CR27","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1097\/01.SLA.0000055273.58908.19","volume":"237","author":"N Wada","year":"2003","unstructured":"N. Wada et al. Lymph node metastasis from 259 papillary thyroid microcarcinomas: frequency, pattern of occurrence and recurrence, and optimal strategy for neck dissection. Ann. Surg. 237(no. 3), 399\u2013407 (2003). https:\/\/doi.org\/10.1097\/01.SLA.0000055273.58908.19.","journal-title":"Ann. Surg."},{"issue":"no. 12","key":"4091_CR28","doi-asserted-by":"publisher","first-page":"2993","DOI":"10.1002\/jum.16006","volume":"41","author":"C Zhang","year":"2022","unstructured":"C. Zhang, D. Liu, L. Huang, Y. Zhao, L. Chen, Y. Guo, Classification of thyroid nodules by using deep learning radiomics based on ultrasound dynamic video. J. Ultrasound Med. 41(no. 12), 2993\u20133002 (2022). https:\/\/doi.org\/10.1002\/jum.16006.","journal-title":"J. Ultrasound Med."},{"key":"4091_CR29","doi-asserted-by":"publisher","first-page":"110885","DOI":"10.1016\/j.ejrad.2023.110885","volume":"165","author":"G Zhao","year":"2023","unstructured":"G. Zhao, D. Kong, X. Xu, S. Hu, Z. Li, J. Tian, Deep learning-based classification of breast lesions using dynamic ultrasound video. Eur. J. Radiol. 165, 110885 (2023). https:\/\/doi.org\/10.1016\/j.ejrad.2023.110885.","journal-title":"Eur. J. Radiol."}],"container-title":["Endocrine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12020-024-04091-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12020-024-04091-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12020-024-04091-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:20:17Z","timestamp":1740147617000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12020-024-04091-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,18]]},"references-count":29,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025,3]]}},"alternative-id":["4091"],"URL":"https:\/\/doi.org\/10.1007\/s12020-024-04091-w","relation":{},"ISSN":["1559-0100"],"issn-type":[{"value":"1559-0100","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,18]]},"assertion":[{"value":"1 September 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 October 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 November 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This retrospective study\u2019s protocol was approved by the Independent Ethics Committee of Zhejiang Cancer Hospital (NO: IRB-2020-287), and written informed consent from the patient was waived by the ethics committee of the Independent Ethics Committee of Zhejiang Cancer Hospital. Patient records were anonymised and deidentified before analysis. We confirm that all methods were performed in accordance with the relevant guidelines and regulations.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}}]}}