{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T21:54:36Z","timestamp":1757627676644,"version":"3.44.0"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T00:00:00Z","timestamp":1755734400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T00:00:00Z","timestamp":1755734400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Imaging"],"DOI":"10.1186\/s12880-025-01890-z","type":"journal-article","created":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T09:32:38Z","timestamp":1755768758000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A non-invasive preoperative model for predicting sentinel lymph node metastasis in breast cancer using clinical data and MRI"],"prefix":"10.1186","volume":"25","author":[{"given":"Yunqing","family":"Yang","sequence":"first","affiliation":[]},{"given":"Zhulin","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Haidong","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Yun","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Yang","family":"Fu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,8,21]]},"reference":[{"issue":"6","key":"1890_CR1","first-page":"524","volume":"72","author":"AN Giaquinto","year":"2022","unstructured":"Giaquinto AN, Sung H, Miller KD, Kramer JL, Newman LA, Minihan A, Jemal A, Siegel RL. Breast cancer statistics, 2022. CA Cancer J Clin. 2022;72(6):524\u201341.","journal-title":"CA Cancer J Clin"},{"issue":"1","key":"1890_CR2","first-page":"17","volume":"73","author":"RL Siegel","year":"2023","unstructured":"Siegel RL, Miller KD, Wagle NS, Jemal A. Cancer statistics, 2023. CA Cancer J Clin. 2023;73(1):17\u201348.","journal-title":"CA Cancer J Clin"},{"issue":"4","key":"1890_CR3","doi-asserted-by":"publisher","first-page":"1020","DOI":"10.1016\/j.ijrobp.2007.07.2376","volume":"70","author":"M Deutsch","year":"2008","unstructured":"Deutsch M, Land S, Begovic M, Sharif S. The incidence of arm edema in women with breast cancer randomized on the national surgical adjuvant breast and bowel project study B-04 to radical mastectomy versus total mastectomy and radiotherapy versus total mastectomy alone. Int J Radiat Oncol Biol Phys. 2008;70(4):1020\u20134.","journal-title":"Int J Radiat Oncol Biol Phys"},{"issue":"5","key":"1890_CR4","doi-asserted-by":"publisher","first-page":"e96748","DOI":"10.1371\/journal.pone.0096748","volume":"9","author":"JT Hidding","year":"2014","unstructured":"Hidding JT, Beurskens CH, van der Wees PJ, van Laarhoven HW, Nijhuis-van DSM. Treatment related impairments in arm and shoulder in patients with breast cancer: a systematic review. PLoS One. 2014;9(5):e96748.","journal-title":"PLoS ONE"},{"issue":"2","key":"1890_CR5","doi-asserted-by":"publisher","first-page":"312","DOI":"10.1007\/s13193-021-01458-7","volume":"13","author":"S Gupta","year":"2022","unstructured":"Gupta S, Kadayaprath G, Ambastha R, Shrivastava SS. False negative rate of sentinel lymph node biopsy on intraoperative frozen section in early breast cancer patients: an institutional experience. Indian J Surg Oncol. 2022;13(2):312\u20135.","journal-title":"Indian J Surg Oncol"},{"issue":"1","key":"1890_CR6","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1102\/1470-7330.2005.0020","volume":"5","author":"RM Gore","year":"2005","unstructured":"Gore RM. Upper gastrointestinal tract tumours: diagnosis and staging strategies. Cancer Imaging. 2005;5(1):95\u20138.","journal-title":"Cancer Imaging"},{"issue":"1","key":"1890_CR7","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1007\/s00330-017-4935-4","volume":"28","author":"J Liu","year":"2018","unstructured":"Liu J, Wang Z, Shao H, Qu D, Liu J, Yao L. Improving CT detection sensitivity for nodal metastases in oesophageal cancer with combination of smaller size and lymph node axial ratio. Eur Radiol. 2018;28(1):188\u201395.","journal-title":"EUR RADIOL"},{"issue":"10","key":"1890_CR8","doi-asserted-by":"publisher","first-page":"1230","DOI":"10.1016\/j.mri.2014.07.001","volume":"32","author":"EJ Kim","year":"2014","unstructured":"Kim EJ, Kim SH, Kang BJ, Choi BG, Song BJ, Choi JJ. Diagnostic value of breast MRI for predicting metastatic axillary lymph nodes in breast cancer patients: diffusion-weighted MRI and conventional MRI. Magn Reson Imaging. 2014;32(10):1230\u20136.","journal-title":"MAGN RESON IMAGING"},{"issue":"2","key":"1890_CR9","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11547-024-01768-0","volume":"129","author":"W Zhang","year":"2024","unstructured":"Zhang W, Wang S, Wang Y, Sun J, Wei H, Xue W, Dong X, Wang X. Ultrasound-based radiomics nomogram for predicting axillary lymph node metastasis in early-stage breast cancer. Radiol Med. 2024;129(2):211\u201321.","journal-title":"RADIOL MED"},{"key":"1890_CR10","doi-asserted-by":"publisher","first-page":"21196","DOI":"10.1038\/srep21196","volume":"6","author":"SQ Qiu","year":"2016","unstructured":"Qiu SQ, Zeng HC, Zhang F, Chen C, Huang WH, Pleijhuis RG, Wu JD, van Dam GM, Zhang GJ. A nomogram to predict the probability of axillary lymph node metastasis in early breast cancer patients with positive axillary ultrasound. Sci Rep. 2016;6:21196.","journal-title":"Sci Rep"},{"issue":"42","key":"1890_CR11","doi-asserted-by":"publisher","first-page":"e35672","DOI":"10.1097\/MD.0000000000035672","volume":"102","author":"C Yuan","year":"2023","unstructured":"Yuan C, Xu G, Zhan X, Xie M, Luo M, She L, Xue Y. Molybdenum target mammography-based prediction model for metastasis of axillary sentinel lymph node in early-stage breast cancer. Med (Baltim). 2023;102(42):e35672.","journal-title":"Med (Baltim)"},{"key":"1890_CR12","doi-asserted-by":"publisher","first-page":"2071059190","DOI":"10.1177\/15330338231166218","volume":"22","author":"H Zhang","year":"2023","unstructured":"Zhang H, Zhao T, Zhang S, Sun J, Zhang F, Li X, Ni X. Prediction of axillary lymph node metastatic load of breast cancer based on ultrasound deep learning radiomics nomogram. Technol Cancer Res Treat. 2023;22:2071059190.","journal-title":"Technol Cancer Res Treat"},{"issue":"1","key":"1890_CR13","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1186\/s12967-023-04201-8","volume":"21","author":"H Zhang","year":"2023","unstructured":"Zhang H, Cao W, Liu L, Meng Z, Sun N, Meng Y, Fei J. Noninvasive prediction of node-positive breast cancer response to presurgical neoadjuvant chemotherapy therapy based on machine learning of axillary lymph node ultrasound. J Transl Med. 2023;21(1):337.","journal-title":"J TRANSL MED"},{"issue":"6","key":"1890_CR14","doi-asserted-by":"publisher","first-page":"1395","DOI":"10.1016\/j.ultrasmedbio.2020.01.030","volume":"46","author":"P Han","year":"2020","unstructured":"Han P, Yang H, Liu M, Cheng L, Wang S, Tong F, Liu P, Zhou B, Cao Y, Liu H, et al. Lymph node predictive model with in vitro ultrasound features for breast cancer lymph node metastasis. Ultrasound Med Biol. 2020;46(6):1395\u2013402.","journal-title":"ULTRASOUND MED BIOL"},{"key":"1890_CR15","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1186\/1472-6947-12-54","volume":"12","author":"M Takada","year":"2012","unstructured":"Takada M, Sugimoto M, Naito Y, Moon HG, Han W, Noh DY, Kondo M, Kuroi K, Sasano H, Inamoto T, et al. Prediction of axillary lymph node metastasis in primary breast cancer patients using a decision tree-based model. BMC Med Inf Decis Mak. 2012;12:54.","journal-title":"BMC Med Inf Decis Mak"},{"key":"1890_CR16","doi-asserted-by":"publisher","first-page":"104715","DOI":"10.1016\/j.compbiomed.2021.104715","volume":"136","author":"Z Liu","year":"2021","unstructured":"Liu Z, Ni S, Yang C, Sun W, Huang D, Su H, Shu J, Qin N. Axillary lymph node metastasis prediction by contrast-enhanced computed tomography images for breast cancer patients based on deep learning. Comput Biol Med. 2021;136:104715.","journal-title":"COMPUT BIOL MED"},{"issue":"1","key":"1890_CR17","doi-asserted-by":"publisher","first-page":"1264","DOI":"10.1186\/s12885-023-11751-z","volume":"23","author":"L Yang","year":"2023","unstructured":"Yang L, Gu Y, Wang B, Sun M, Zhang L, Shi L, Wang Y, Zhang Z, Yin Y. A multivariable model of ultrasound and clinicopathological features for predicting axillary nodal burden of breast cancer: potential to prevent unnecessary axillary lymph node dissection. BMC Cancer. 2023;23(1):1264.","journal-title":"BMC Cancer"},{"issue":"20","key":"1890_CR18","doi-asserted-by":"publisher","first-page":"1429","DOI":"10.2217\/fon-2023-0070","volume":"19","author":"X Li","year":"2023","unstructured":"Li X, Yang L, Jiao X. Deep learning-based multiomics integration model for predicting axillary lymph node metastasis in breast cancer. Future Oncol. 2023;19(20):1429\u201338.","journal-title":"FUTURE ONCOL"},{"issue":"4","key":"1890_CR19","doi-asserted-by":"publisher","first-page":"e428","DOI":"10.1016\/j.clbc.2021.10.014","volume":"22","author":"M Xue","year":"2022","unstructured":"Xue M, Che S, Tian Y, Xie L, Huang L, Zhao L, Guo N, Li J. Nomogram based on breast MRI and clinicopathologic features for predicting axillary lymph node metastasis in patients with Early-Stage invasive breast cancer: a retrospective study. Clin Breast Cancer. 2022;22(4):e428\u201337.","journal-title":"CLIN BREAST CANCER"},{"issue":"1","key":"1890_CR20","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1186\/s12957-022-02531-3","volume":"20","author":"A Yiming","year":"2022","unstructured":"Yiming A, Wubulikasimu M, Yusuying N. Analysis on factors behind sentinel lymph node metastasis in breast cancer by color ultrasonography, molybdenum target, and pathological detection. World J Surg Oncol. 2022;20(1):72.","journal-title":"WORLD J SURG ONCOL"},{"issue":"2","key":"1890_CR21","doi-asserted-by":"publisher","first-page":"1336","DOI":"10.21037\/qims-21-580","volume":"12","author":"B Li","year":"2022","unstructured":"Li B, Zhao X, Wang Q, Jing H, Shao H, Zhang L, Cheng W. Prediction of high nodal burden in invasive breast cancer by quantitative shear wave elastography. Quant Imaging Med Surg. 2022;12(2):1336\u201347.","journal-title":"Quant Imaging Med Surg"},{"issue":"1","key":"1890_CR22","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1186\/s40644-022-00450-w","volume":"22","author":"D Song","year":"2022","unstructured":"Song D, Yang F, Zhang Y, Guo Y, Qu Y, Zhang X, Zhu Y, Cui S. Dynamic contrast-enhanced MRI radiomics nomogram for predicting axillary lymph node metastasis in breast cancer. Cancer Imaging. 2022;22(1):17.","journal-title":"Cancer Imaging"},{"key":"1890_CR23","doi-asserted-by":"publisher","first-page":"830910","DOI":"10.3389\/fonc.2022.830910","volume":"12","author":"H Zhang","year":"2022","unstructured":"Zhang H, Dong Y, Jia X, Zhang J, Li Z, Chuan Z, Xu Y, Hu B, Huang Y, Chang C, et al. Comprehensive risk system based on shear wave elastography and BI-RADS categories in assessing axillary lymph node metastasis of invasive breast cancer-a multicenter study. Front Oncol. 2022;12:830910.","journal-title":"FRONT ONCOL"},{"issue":"1060","key":"1890_CR24","doi-asserted-by":"publisher","first-page":"20150614","DOI":"10.1259\/bjr.20150614","volume":"89","author":"I Guvenc","year":"2016","unstructured":"Guvenc I, Akay S, Ince S, Yildiz R, Kilbas Z, Oysul FG, Tasar M. Apparent diffusion coefficient value in invasive ductal carcinoma at 3.0 tesla: is it correlated with prognostic factors? Br J Radiol. 2016;89(1060):20150614.","journal-title":"Br J Radiol"},{"issue":"11","key":"1890_CR25","doi-asserted-by":"publisher","first-page":"2137","DOI":"10.1016\/j.ejrad.2015.08.009","volume":"84","author":"JY Kim","year":"2015","unstructured":"Kim JY, Seo HB, Park S, Moon JI, Lee JW, Lee NK, Lee SW, Bae YT. Early-stage invasive ductal carcinoma: association of tumor apparent diffusion coefficient values with axillary lymph node metastasis. Eur J Radiol. 2015;84(11):2137\u201343.","journal-title":"EUR J RADIOL"},{"issue":"1","key":"1890_CR26","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1186\/s12880-021-00722-0","volume":"21","author":"X Ou","year":"2021","unstructured":"Ou X, Zhu J, Qu Y, Wang C, Wang B, Xu X, Wang Y, Wen H, Ma A, Liu X, et al. Imaging features of Sentinel lymph node mapped by multidetector-row computed tomography lymphography in predicting axillary lymph node metastasis. BMC Med Imaging. 2021;21(1):193.","journal-title":"BMC MED IMAGING"},{"issue":"12","key":"1890_CR27","doi-asserted-by":"publisher","first-page":"990","DOI":"10.21037\/atm-21-2374","volume":"9","author":"G Zhang","year":"2021","unstructured":"Zhang G, Li Y, Wang Q, Zheng H, Yuan L, Gao Z, Li J, Li X, Zhao S. Development of a prediction model for the risk of recurrent laryngeal nerve lymph node metastasis in thoracolaparoscopic esophagectomy with cervical anastomosis. Ann Transl Med. 2021;9(12):990.","journal-title":"Ann Transl Med"},{"issue":"6","key":"1890_CR28","doi-asserted-by":"publisher","first-page":"676","DOI":"10.1016\/j.asjsur.2019.09.001","volume":"43","author":"N Nakai","year":"2020","unstructured":"Nakai N, Yamaguchi T, Kinugasa Y, Shiomi A, Kagawa H, Yamakawa Y, Numata M, Furutani A, Yamaoka Y, Manabe S, et al. Diagnostic value of computed tomography (CT) and positron emission tomography (PET) for paraaortic lymph node metastasis from left-sided colon and rectal cancer. Asian J Surg. 2020;43(6):676\u201382.","journal-title":"ASIAN J SURG"}],"container-title":["BMC Medical Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12880-025-01890-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12880-025-01890-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12880-025-01890-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T04:29:51Z","timestamp":1757478591000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcmedimaging.biomedcentral.com\/articles\/10.1186\/s12880-025-01890-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,21]]},"references-count":28,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["1890"],"URL":"https:\/\/doi.org\/10.1186\/s12880-025-01890-z","relation":{},"ISSN":["1471-2342"],"issn-type":[{"type":"electronic","value":"1471-2342"}],"subject":[],"published":{"date-parts":[[2025,8,21]]},"assertion":[{"value":"24 November 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 August 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 August 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This study was performed in accordance with the Declaration of Helsinki, and approved by the Zhengzhou University Institutional Review Board (No. 2023-KY-0586). Given its retrospective design and the use of anonymized data, the requirement for informed consent was waived.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Given its retrospective design and the use of anonymized data, the requirement for informed consent was waived.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"343"}}