{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T10:32:08Z","timestamp":1788517928535,"version":"build-2803163510"},"reference-count":23,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,4,30]],"date-time":"2024-04-30T00:00:00Z","timestamp":1714435200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,4,30]],"date-time":"2024-04-30T00:00:00Z","timestamp":1714435200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"The youth project start-up fund","award":["2022QN091"],"award-info":[{"award-number":["2022QN091"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Transl Med"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Purpose<\/jats:title>\n                <jats:p>The aim of this study is to construct a combined model that integrates radiomics, clinical risk factors and machine learning algorithms to predict para-laryngeal lymph node metastasis in esophageal squamous cell carcinoma.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>A retrospective study included 361 patients with esophageal squamous cell carcinoma from 2 centers. Radiomics features were extracted from the computed tomography scans. Logistic regression, k nearest neighbor, multilayer perceptron, light Gradient Boosting Machine, support vector machine, random forest algorithms were used to construct radiomics models. The receiver operating characteristic curve and The Hosmer\u2013Lemeshow test were employed to select the better-performing model. Clinical risk factors were identified through univariate logistic regression analysis and multivariate logistic regression analysis and utilized to develop a clinical model. A combined model was then created by merging radiomics and clinical risk factors. The performance of the models was evaluated using ROC curve analysis, and the clinical value of the models was assessed using decision curve analysis.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>A total of 1024 radiomics features were extracted. Among the radiomics models, the KNN model demonstrated the optimal diagnostic capabilities and accuracy, with an area under the curve (AUC) of 0.84 in the training cohort and 0.62 in the internal test cohort. Furthermore, the combined model exhibited an AUC of 0.97 in the training cohort and 0.86 in the internal test cohort.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>A clinical-radiomics integrated nomogram can predict occult para-laryngeal lymph node metastasis in esophageal squamous cell carcinoma and provide guidance for personalized treatment.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12967-024-05217-4","type":"journal-article","created":{"date-parts":[[2024,4,30]],"date-time":"2024-04-30T05:01:39Z","timestamp":1714453299000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Potential value of CT-based comprehensive nomogram in predicting occult lymph node metastasis of esophageal squamous cell paralaryngeal nerves: a two-center study"],"prefix":"10.1186","volume":"22","author":[{"given":"Ting","family":"Xue","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyi","family":"Wan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Taohu","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qin","family":"Zou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chao","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jieqiong","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,4,30]]},"reference":[{"key":"5217_CR1","doi-asserted-by":"publisher","first-page":"394","DOI":"10.3322\/caac.21492","volume":"68","author":"F Bray","year":"2018","unstructured":"Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68:394\u2013424.","journal-title":"CA Cancer J Clin"},{"key":"5217_CR2","doi-asserted-by":"publisher","first-page":"1951","DOI":"10.1200\/JCO.2014.58.0423","volume":"33","author":"W Wei","year":"2015","unstructured":"Wei W, Chen Z, He Y, et al. Long-term follow-up of a community assignment, one-time endoscopic screening study of esophageal cancer in China. J Clin Oncol. 2015;33:1951\u20137.","journal-title":"J Clin Oncol"},{"issue":"1","key":"5217_CR3","first-page":"1","volume":"30","author":"T Kanemura","year":"2017","unstructured":"Kanemura T, Makino T, Miyazaki Y, et al. Distribution patterns of metastases in recurrent laryngeal nerve lymph nodes in patients with squamous cell esophageal cancer. Dis Esophagus. 2017;30(1):1\u20137.","journal-title":"Dis Esophagus"},{"issue":"1","key":"5217_CR4","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1046\/j.1442-2050.2003.00286.x","volume":"16","author":"S Nakagawa","year":"2003","unstructured":"Nakagawa S, Nishimaki T, Kosugi S, et al. Cervical lymphadenectomyis beneficial for patients with carcinoma of the upper and mid-thoracic esophagus. Dis Esophagus. 2003;16(1):4\u20138.","journal-title":"Dis Esophagus"},{"issue":"4","key":"5217_CR5","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1097\/01.sla.0000118562.97742.29","volume":"239","author":"H Igaki","year":"2004","unstructured":"Igaki H, Tachimori Y, Kato H. Improved survival for patients with upper and\/or middle mediastinal lymph node metastasis of squamous cell carcinoma of the lower thoracic esophagus treated with 3-field dissection. Ann Surg. 2004;239(4):483\u201390.","journal-title":"Ann Surg"},{"issue":"47","key":"5217_CR6","doi-asserted-by":"publisher","first-page":"18022","DOI":"10.3748\/wjg.v20.i47.18022","volume":"20","author":"GW Ma","year":"2014","unstructured":"Ma GW, Situ DR, Ma QL, et al. Three-field vs two-field lymphnode dissection for esophageal cancer: a meta-analysis. World J Gastroenterol. 2014;20(47):18022\u201330.","journal-title":"World J Gastroenterol"},{"issue":"8","key":"5217_CR7","doi-asserted-by":"publisher","first-page":"737","DOI":"10.3748\/wjg.v27.i8.737","volume":"27","author":"K Jiang","year":"2021","unstructured":"Jiang K, Huang H, Chen W, et al. Risk factors for lymph node metastasis in T1 esophageal squamous cell carcinoma: a systematic review and meta-analysis. World J Gastroenterol. 2021;27(8):737\u201350.","journal-title":"World J Gastroenterol"},{"issue":"5","key":"5217_CR8","doi-asserted-by":"publisher","first-page":"1221","DOI":"10.1245\/s10434-018-6390-0","volume":"25","author":"Y Kumakura","year":"2018","unstructured":"Kumakura Y, Yokobori T, Yoshida T, et al. Elucidation of the anatomical mechanism of nodal skip metastasis in superficial thoracic esophageal squamous cell carcinoma. Ann Surg Oncol. 2018;25(5):1221\u20138.","journal-title":"Ann Surg Oncol"},{"issue":"8","key":"5217_CR9","doi-asserted-by":"publisher","first-page":"862","DOI":"10.1016\/j.jacr.2015.04.019","volume":"12","author":"A Mazurowski","year":"2015","unstructured":"Mazurowski A. Radiogenomics: what it is and why it is important. J Am Coll Radiol. 2015;12(8):862\u20136.","journal-title":"J Am Coll Radiol"},{"issue":"5","key":"5217_CR10","doi-asserted-by":"publisher","first-page":"2058","DOI":"10.1007\/s00330-017-5146-8","volume":"28","author":"L Yang","year":"2018","unstructured":"Yang L, Dong D, Fang M, et al. Can CT-based radiomics signature predict KRAS\/NRAS\/BRAF mutations in colorectal cancer. Eur Radiol. 2018;28(5):2058\u201367.","journal-title":"Eur Radiol"},{"issue":"4","key":"5217_CR11","doi-asserted-by":"publisher","first-page":"350","DOI":"10.1080\/00207454.2018.1536052","volume":"129","author":"B Dhruv","year":"2019","unstructured":"Dhruv B, Mittal N, Modi M. Study of Haralick\u2019s and GLCM texture analysis on 3D medical images. Int J Neurosci. 2019;129(4):350\u201362.","journal-title":"Int J Neurosci"},{"key":"5217_CR12","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2021.644165","volume":"11","author":"Y Li","year":"2021","unstructured":"Li Y, Yu M, Wang G, et al. Contrast-enhanced CT-based radiomics analysis in predicting lymphovascular invasion in esophageal squamous cell carcinoma. Front Oncol. 2021;11: 644165.","journal-title":"Front Oncol"},{"issue":"1","key":"5217_CR13","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1186\/s40644-021-00407-5","volume":"21","author":"S Tang","year":"2021","unstructured":"Tang S, Ou J, Liu J, et al. Application of contrast-enhanced CT radiomics in prediction of early recurrence of locally advanced oesophageal squamous cell carcinoma after trimodal therapy. Cancer Imaging. 2021;21(1):38.","journal-title":"Cancer Imaging"},{"issue":"1","key":"5217_CR14","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1186\/s13014-021-01925-z","volume":"16","author":"H Luo","year":"2021","unstructured":"Luo H, Chen Y, Huang W, et al. Development and validation of a radiomics-based model to predict local progression-free survival after chemo-radiotherapy in patients with esophageal squamous cell cancer. Radiat Oncol. 2021;16(1):201.","journal-title":"Radiat Oncol"},{"key":"5217_CR15","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/j.bpg.2018.11.009","volume":"36\u201337","author":"K Foley","year":"2018","unstructured":"Foley K, Findlay J, Goh V. Novel imaging techniques in staging oesophageal cancer. Best Pract Res Clin Gastroenterol. 2018;36\u201337:17\u201325.","journal-title":"Best Pract Res Clin Gastroenterol"},{"key":"5217_CR16","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1016\/j.crad.2014.07.017","volume":"70","author":"R Van","year":"2015","unstructured":"Van R, Van L, Lips I, Meijer G, et al. Imaging of oesophageal cancer with FDG-PET\/CT and MRI. Clin Radiol. 2015;70:81\u201395.","journal-title":"Clin Radiol"},{"key":"5217_CR17","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2021.663802","volume":"11","author":"R Ruan","year":"2021","unstructured":"Ruan R, Chen S, Tao Y, et al. A Nomogram for predicting lymphovascular invasion in superficial esophageal squamous cell carcinoma. Front Oncol. 2021;11: 663802.","journal-title":"Front Oncol"},{"issue":"5","key":"5217_CR18","doi-asserted-by":"publisher","first-page":"2196","DOI":"10.1007\/s00330-018-5770-y","volume":"29","author":"L Yang","year":"2019","unstructured":"Yang L, Yang J, Zhou X, et al. Development of a radiomics nomogram based on the 2D and 3D CT features to predict the survival of non-small cell lung cancer patients. Eur Radiol. 2019;29(5):2196\u2013206.","journal-title":"Eur Radiol"},{"issue":"1","key":"5217_CR19","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1186\/s41747-018-0068-z","volume":"2","author":"S Rizzo","year":"2018","unstructured":"Rizzo S, Botta F, Raimondi S, et al. Radiomics: the facts and the challenges of image analysis. Eur Radiol Exp. 2018;2(1):36.","journal-title":"Eur Radiol Exp"},{"issue":"4","key":"5217_CR20","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1016\/j.ejca.2011.11.036","volume":"48","author":"P Lambin","year":"2012","unstructured":"Lambin P, Rios-Velazquez E, Leijenaar R, et al. Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer. 2012;48(4):441\u20136.","journal-title":"Eur J Cancer"},{"issue":"12","key":"5217_CR21","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2020.28086","volume":"3","author":"YF Yu","year":"2020","unstructured":"Yu YF, Tan YJ, Xie CM, et al. Development and validation of a preoperative magnetic resonance imaging radiomics-based signature to predict axillary lymph node metastasis and disease-free survival in patients with early-stage breast cancer. JAMA Netw Open. 2020;3(12): e2028086.","journal-title":"JAMA Netw Open"},{"issue":"9","key":"5217_CR22","doi-asserted-by":"publisher","first-page":"1217","DOI":"10.1016\/j.acra.2019.11.004","volume":"27","author":"HN Tan","year":"2020","unstructured":"Tan HN, Gan FW, Wu YP, et al. Preoperative prediction of axillary lymph node metastasis in breast carcinoma using radiomics features based on the fat-suppressed T2 sequence. Acad Radiol. 2020;27(9):1217\u201325.","journal-title":"Acad Radiol"},{"key":"5217_CR23","doi-asserted-by":"publisher","first-page":"1463","DOI":"10.3389\/fonc.2020.01463","volume":"10","author":"YN Shan","year":"2020","unstructured":"Shan YN, Xu W, Wang R, et al. A nomogram combined radiomics and kinetic curve pattern as imaging biomarker for detecting metastatic axillary lymph node in invasive breast cancer. Front Oncol. 2020;10:1463.","journal-title":"Front Oncol"}],"container-title":["Journal of Translational Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12967-024-05217-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12967-024-05217-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12967-024-05217-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,30]],"date-time":"2024-04-30T05:02:27Z","timestamp":1714453347000},"score":1,"resource":{"primary":{"URL":"https:\/\/translational-medicine.biomedcentral.com\/articles\/10.1186\/s12967-024-05217-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,30]]},"references-count":23,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["5217"],"URL":"https:\/\/doi.org\/10.1186\/s12967-024-05217-4","relation":{},"ISSN":["1479-5876"],"issn-type":[{"value":"1479-5876","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4,30]]},"assertion":[{"value":"26 January 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 April 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 April 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The study was approved by the ethics committee of the Second Affiliated Hospital of Naval Medical University, and the requirement of informed consent was exempted.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Written informed consent was waived by the Institutional Review Board.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}],"article-number":"399"}}