{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T02:07:54Z","timestamp":1792030074526,"version":"4.4.0"},"reference-count":38,"publisher":"Elsevier BV","issue":"10","license":[{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"content-domain":{"domain":["clinicalkey.fr","clinicalkey.jp","clinicalkey.es","clinicalkey.com.au","academicradiology.org","clinicalkey.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Academic Radiology"],"published-print":{"date-parts":[[2024,10]]},"DOI":"10.1016\/j.acra.2024.04.010","type":"journal-article","created":{"date-parts":[[2024,4,23]],"date-time":"2024-04-23T08:52:49Z","timestamp":1713862369000},"page":"3917-3928","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":14,"title":["Ultrasound-Based Deep Learning Radiomics Nomogram for the Assessment of Lymphovascular Invasion in Invasive Breast Cancer: A Multicenter Study"],"prefix":"10.1016","volume":"31","author":[{"given":"Di","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wang","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wen-Wu","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xia-Chuan","family":"Qin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xian-Ya","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun-Li","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan-Hong","family":"Luo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ya-Yang","family":"Duan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chao-Xue","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.acra.2024.04.010_bib1","doi-asserted-by":"crossref","first-page":"209","DOI":"10.3322\/caac.21660","article-title":"Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"71","author":"Sung","year":"2021","journal-title":"CA Cancer J Clin"},{"issue":"6","key":"10.1016\/j.acra.2024.04.010_bib2","doi-asserted-by":"crossref","first-page":"842","DOI":"10.1016\/j.cmet.2017.09.018","article-title":"Acetyl-CoA carboxylase 1-dependent protein acetylation controls breast cancer metastasis and recurrence","volume":"26","author":"Rios Garcia","year":"2017","journal-title":"Cell Metab"},{"issue":"12","key":"10.1016\/j.acra.2024.04.010_bib3","doi-asserted-by":"crossref","first-page":"1129","DOI":"10.1038\/s41416-019-0486-6","article-title":"A key genomic subtype associated with lymphovascular invasion in invasive breast cancer","volume":"120","author":"Kurozumi","year":"2019","journal-title":"Br J Cancer"},{"issue":"3\u20134","key":"10.1016\/j.acra.2024.04.010_bib4","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1159\/000433583","article-title":"Molecular mechanisms underlying lymphovascular invasion in invasive breast cancer","volume":"82","author":"Aleskandarany","year":"2015","journal-title":"Pathobiology"},{"issue":"3","key":"10.1016\/j.acra.2024.04.010_bib5","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1007\/s10549-016-3837-5","article-title":"Lymphovascular invasion is an independent predictor of survival in breast cancer after neoadjuvant chemotherapy","volume":"157","author":"Liu","year":"2016","journal-title":"Breast Cancer Res Treat"},{"issue":"1","key":"10.1016\/j.acra.2024.04.010_bib6","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1186\/s12885-022-09193-0","article-title":"Lympho-vascular invasion impacts the prognosis in breast-conserving surgery: a systematic review and meta-analysis","volume":"22","author":"Zhong","year":"2022","journal-title":"BMC Cancer"},{"issue":"12","key":"10.1016\/j.acra.2024.04.010_bib7","doi-asserted-by":"crossref","first-page":"2275","DOI":"10.1007\/s12094-020-02369-9","article-title":"Potential roles of lymphovascular space invasion based on tumor characteristics provide important prognostic information in T1 tumors with ER and HER2 positive breast cancer","volume":"22","author":"Zhao","year":"2020","journal-title":"Clin Transl Oncol"},{"issue":"7","key":"10.1016\/j.acra.2024.04.010_bib8","doi-asserted-by":"crossref","first-page":"626","DOI":"10.3348\/kjr.2022.0974","article-title":"Prediction of tumor progression during neoadjuvant chemotherapy and survival outcome in patients with triple-negative breast cancer","volume":"24","author":"Yoen","year":"2023","journal-title":"Korean J Radiol"},{"key":"10.1016\/j.acra.2024.04.010_bib9","doi-asserted-by":"crossref","DOI":"10.3389\/fonc.2022.890659","article-title":"Predicting lymphovascular invasion in clinically node-negative breast cancer detected by abbreviated magnetic resonance imaging: Transfer learning vs. radiomics","volume":"12","author":"Feng","year":"2022","journal-title":"Front Oncol"},{"issue":"2","key":"10.1016\/j.acra.2024.04.010_bib10","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1007\/s10549-017-4610-0","article-title":"Lymphovascular invasion after neoadjuvant chemotherapy is strongly associated with poor prognosis in breast carcinoma","volume":"169","author":"Hamy","year":"2018","journal-title":"Breast Cancer Res Treat"},{"issue":"10","key":"10.1016\/j.acra.2024.04.010_bib11","doi-asserted-by":"crossref","first-page":"2867","DOI":"10.1245\/s10434-018-6578-3","article-title":"Predicting non-sentinel lymph node metastases in patients with a positive sentinel lymph node after neoadjuvant chemotherapy","volume":"25","author":"Barron","year":"2018","journal-title":"Ann Surg Oncol"},{"key":"10.1016\/j.acra.2024.04.010_bib12","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.breast.2020.02.013","article-title":"Evaluation of 2014 margin guidelines on re-excision and recurrence rates after breast conserving surgery: A multi-institution retrospective study","volume":"51","author":"Kuritzky","year":"2020","journal-title":"Breast (Edinburgh, Scotland)"},{"issue":"2","key":"10.1016\/j.acra.2024.04.010_bib13","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1093\/annonc\/mdp317","article-title":"Adverse prognostic value of peritumoral vascular invasion: is it abrogated by adequate endocrine adjuvant therapy? Results from two International Breast Cancer Study Group randomized trials of chemoendocrine adjuvant therapy for early breast cancer","volume":"21","author":"Viale","year":"2010","journal-title":"Ann Oncol"},{"key":"10.1016\/j.acra.2024.04.010_bib14","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.ejrad.2018.08.024","article-title":"Breast MRI for prediction of lymphovascular invasion in breast cancer patients with clinically negative axillary lymph nodes","volume":"107","author":"Igarashi","year":"2018","journal-title":"Eur J Radiol"},{"issue":"1","key":"10.1016\/j.acra.2024.04.010_bib15","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1097\/00000478-200301000-00002","article-title":"Correlation of histologic prognostic factors in core biopsies and therapeutic excisions of invasive breast carcinoma","volume":"27","author":"Harris","year":"2003","journal-title":"Am J Surg Pathol"},{"issue":"6","key":"10.1016\/j.acra.2024.04.010_bib16","doi-asserted-by":"crossref","first-page":"3703","DOI":"10.1007\/s00330-020-07502-4","article-title":"Intra-tumoural lipid composition and lymphovascular invasion in breast cancer via non-invasive magnetic resonance spectroscopy","volume":"31","author":"Cheung","year":"2021","journal-title":"Eur Radiol"},{"issue":"3","key":"10.1016\/j.acra.2024.04.010_bib17","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1002\/jmri.26688","article-title":"Preoperative prediction of lymphovascular invasion in invasive breast cancer with dynamic contrast-enhanced-MRI-based radiomics","volume":"50","author":"Liu","year":"2019","journal-title":"J Magn Reson Imaging"},{"issue":"4","key":"10.1016\/j.acra.2024.04.010_bib18","doi-asserted-by":"crossref","first-page":"1037","DOI":"10.1002\/jmri.25710","article-title":"Preoperative MRI features associated with lymphovascular invasion in node-negative invasive breast cancer: a\u00a0propensity-matched analysis","volume":"46","author":"Cheon","year":"2017","journal-title":"J Magn Reson Imaging"},{"issue":"1","key":"10.1016\/j.acra.2024.04.010_bib19","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1186\/s12885-020-6712-z","article-title":"Value of digital mammography in predicting lymphovascular invasion of breast cancer","volume":"20","author":"Liu","year":"2020","journal-title":"BMC Cancer"},{"issue":"5","key":"10.1016\/j.acra.2024.04.010_bib20","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1097\/PAS.0000000000001451","article-title":"Integrin \u03b24 is an effective and efficient marker in synchronously highlighting lymphatic and blood vascular invasion, and perineural aggression in malignancy","volume":"44","author":"Li","year":"2020","journal-title":"Am J Surg Pathol"},{"key":"10.1016\/j.acra.2024.04.010_bib21","doi-asserted-by":"crossref","first-page":"1515","DOI":"10.2147\/CMAR.S359986","article-title":"Value of histogram of gray-scale ultrasound image in differential diagnosis of small triple negative breast invasive ductal carcinoma and fibroadenoma","volume":"14","author":"Xu","year":"2022","journal-title":"Cancer Manag Res"},{"issue":"6","key":"10.1016\/j.acra.2024.04.010_bib22","first-page":"1125","article-title":"The association between ultrasound features and biological properties of invasive breast carcinoma is modified by age, tumor size, and the preoperative axilla status","volume":"39","author":"Tong","year":"2020","journal-title":"J\u00a0Ultrasound Med\u00a0Offl\u00a0J\u00a0Am\u00a0Inst\u00a0Ultrasound Med"},{"issue":"3","key":"10.1016\/j.acra.2024.04.010_bib23","first-page":"517","article-title":"The value of nomograms in pre-operative prediction of lymphovascular invasion in primary breast cancer undergoing modified radical surgery: based on multiparametric ultrasound and clinicopathologic indicators","volume":"47","author":"Zhou","year":"2021","journal-title":"Ultrasound\u00a0Med\u00a0Biol"},{"issue":"4","key":"10.1016\/j.acra.2024.04.010_bib24","doi-asserted-by":"crossref","first-page":"445","DOI":"10.11152\/mu-4080","article-title":"An overview of ultrasound-derived radiomics and deep learning in liver","volume":"25","author":"Zhang","year":"2023","journal-title":"Med Ultrason"},{"issue":"10","key":"10.1016\/j.acra.2024.04.010_bib25","first-page":"1206","article-title":"A sonogram radiomics model for differentiating granulomatous lobular mastitis from invasive breast cancer: a multicenter study","volume":"128","author":"Ma","year":"2023","journal-title":"La Radiol\u00a0Med"},{"key":"10.1016\/j.acra.2024.04.010_bib26","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.ejca.2021.01.028","article-title":"Ultrasound-based deep learning radiomics in the assessment of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer","volume":"147","author":"Jiang","year":"2021","journal-title":"Eur J Cancer (Oxf, Engl: 1990)"},{"issue":"3","key":"10.1016\/j.acra.2024.04.010_bib27","doi-asserted-by":"crossref","first-page":"356","DOI":"10.1002\/cncr.34540","article-title":"Deep learning radiomics of ultrasonography for comprehensively predicting tumor and axillary lymph node status after neoadjuvant chemotherapy in breast cancer patients: a\u00a0multicenter study","volume":"129","author":"Gu","year":"2023","journal-title":"Cancer"},{"issue":"5","key":"10.1016\/j.acra.2024.04.010_bib28","doi-asserted-by":"crossref","DOI":"10.1148\/radiol.221843","article-title":"Combining deep learning and handcrafted radiomics for classification of suspicious lesions on contrast-enhanced mammograms","volume":"307","author":"Beuque","year":"2023","journal-title":"Radiology"},{"issue":"21","key":"10.1016\/j.acra.2024.04.010_bib29","doi-asserted-by":"crossref","first-page":"e104","DOI":"10.1158\/0008-5472.CAN-17-0339","article-title":"Computational radiomics system to decode the radiographic phenotype","volume":"77","author":"van Griethuysen","year":"2017","journal-title":"Cancer Res"},{"key":"10.1016\/j.acra.2024.04.010_bib30","article-title":"Preoperative prediction of lymphovascular invasion in patients with T1 breast invasive ductal carcinoma based on radiomics nomogram using grayscale ultrasound","volume":"12","author":"Xu","year":"2022","journal-title":"Front\u00a0Oncol"},{"issue":"12","key":"10.1016\/j.acra.2024.04.010_bib31","doi-asserted-by":"crossref","first-page":"1773","DOI":"10.1016\/j.acra.2022.03.011","article-title":"Radiomics analysis on digital breast tomosynthesis: preoperative evaluation of lymphovascular invasion status in invasive breast cancer","volume":"29","author":"Wang","year":"2022","journal-title":"Acad Radiol"},{"key":"10.1016\/j.acra.2024.04.010_bib32","article-title":"Assessment of lymphovascular invasion in breast cancer using a combined MRI morphological features, radiomics, and deep learning approach based on dynamic contrast-enhanced MRI","author":"Yang","year":"2023","journal-title":"J Magn Reson Imaging"},{"issue":"2","key":"10.1016\/j.acra.2024.04.010_bib33","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1002\/jmri.28776","article-title":"Intra- and peritumoral based radiomics for assessment of lymphovascular invasion in invasive breast cancer","volume":"59","author":"Jiang","year":"2024","journal-title":"J Magn Reson Imaging"},{"key":"10.1016\/j.acra.2024.04.010_bib34","article-title":"MRI-based radiomics for preoperative prediction of lymphovascular invasion in patients with invasive breast cancer","volume":"12","author":"Nijiati","year":"2022","journal-title":"Front\u00a0Oncol"},{"issue":"6","key":"10.1016\/j.acra.2024.04.010_bib35","first-page":"4079","article-title":"Multiparametric MRI-based radiomics nomogram for preoperative prediction of lymphovascular invasion and clinical outcomes in patients with breast invasive ductal carcinoma","volume":"32","author":"Zhang","year":"2022","journal-title":"Eur\u00a0Radiol"},{"issue":"4","key":"10.1016\/j.acra.2024.04.010_bib36","doi-asserted-by":"crossref","first-page":"488","DOI":"10.2967\/jnumed.118.222893","article-title":"Introduction to radiomics","volume":"61","author":"Mayerhoefer","year":"2020","journal-title":"J Nucl Med\u00a0Offl\u00a0Publ\u00a0Soc\u00a0Nucl\u00a0Med"},{"issue":"1","key":"10.1016\/j.acra.2024.04.010_bib37","first-page":"165","article-title":"Differentiation of acute and chronic vertebral compression fractures using conventional CT based on deep transfer learning features and hand-crafted radiomics features","volume":"24","author":"Zhang","year":"2023","journal-title":"BMC\u00a0Musculoskelet\u00a0Disord"},{"issue":"1","key":"10.1016\/j.acra.2024.04.010_bib38","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1007\/s00330-023-09995-1","article-title":"Ultrasound radiomics-based nomogram to predict lymphovascular invasion in invasive breast cancer: a multicenter, retrospective study","volume":"34","author":"Du","year":"2024","journal-title":"Eur Radiol"}],"container-title":["Academic Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1076633224002174?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1076633224002174?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,10,17]],"date-time":"2024-10-17T16:00:27Z","timestamp":1729180827000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1076633224002174"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10]]},"references-count":38,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2024,10]]}},"alternative-id":["S1076633224002174"],"URL":"https:\/\/doi.org\/10.1016\/j.acra.2024.04.010","relation":{},"ISSN":["1076-6332"],"issn-type":[{"value":"1076-6332","type":"print"}],"subject":[],"published":{"date-parts":[[2024,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Ultrasound-Based Deep Learning Radiomics Nomogram for the Assessment of Lymphovascular Invasion in Invasive Breast Cancer: A Multicenter Study","name":"articletitle","label":"Article Title"},{"value":"Academic Radiology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.acra.2024.04.010","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}]}}