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This study investigates the potential of dual-layer spectral detector computed tomography (SDCT) quantitative parameters in predicting LNM in ESCC.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method<\/jats:title>\n                    <jats:p>The study included 158 patients with pathologically confirmed ESCC, comprising 92 patients without LNM and 66 patients with LNM. The chi-square test or Fisher\u2019s exact test was utilized to analyze the basic clinical data and lymph node morphological features of the patients. To evaluate the differences in various SDCT quantitative parameters between the LNM and non-LNM groups, the Mann-Whitney U-test and independent sample t-test were applied. Patients were randomly assigned to training and test groups in a 7:3 ratio. The area under the receiver operating characteristic (ROC) curve (AUC) was used to assess the machine learning model. Furthermore, decision curve analysis (DCA) was performed to evaluate the model\u2019s diagnostic efficacy, leading to the development of a nomogram.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Both univariate and LASSO analyses identified LAD, SAD, CT\n                      <jats:sub>V\u221240keV<\/jats:sub>\n                      , NIC\n                      <jats:sub>V<\/jats:sub>\n                      , ED, ECV\n                      <jats:sub>V<\/jats:sub>\n                      , and Nct as significant predictors of LNM in EC. The logistic regression model demonstrated superior performance, achieving ROC-AUC values of 0.885 and 0.827 in the training and test cohorts, respectively. The Brier scores for the combined model were 0.135 and 0.172 in the training and test cohorts, respectively.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The logistic regression model, which integrates SDCT quantitative parameters and lymph node morphological features, exhibited substantial diagnostic value for assessing LNM in EC. It demonstrated excellent diagnostic efficacy and provides a non-invasive evaluation method for clinical practice.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s40644-026-00993-2","type":"journal-article","created":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T11:35:45Z","timestamp":1769686545000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Dual-layer spectral detector computed tomography multiparameter machine learning model for prediction of lymph node metastases in esophageal squamous cell carcinoma"],"prefix":"10.1186","volume":"26","author":[{"given":"Junjie","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ligang","family":"Hao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peiyi","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiuxu","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linyi","family":"Jia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fengxiao","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,1,29]]},"reference":[{"issue":"3","key":"993_CR1","doi-asserted-by":"publisher","first-page":"229","DOI":"10.3322\/caac.21834","volume":"74","author":"F Bray","year":"2024","unstructured":"Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, Jemal A. 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Ethics Committee of Hebei Medical University Fourth Affiliated Hospital, reference number: 2022KS017, data 20222.6.27. Ethics approval was obtained from the Ethics Committee of Hebei Medical University Fourth Affiliated Hospital, and waivers of consent were given to the study subjects.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"We confirm that the manuscript has been submitted solely to this journal and is not published, in press, or submitted elsewhere. Written informed consent was obtained from the individuals for the publication of any potentially identifiable images or data included in this article.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"31"}}