{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T23:11:53Z","timestamp":1777590713398,"version":"3.51.4"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T00:00:00Z","timestamp":1765324800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T00:00:00Z","timestamp":1765756800000},"content-version":"vor","delay-in-days":5,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"iaxing Provinces and Cities Jointly Cultivate Discipline - General Surgery (Minimally Invasive) National Oncology Clinical Key Specialty Construction Project","award":["2023-PYXK-001"],"award-info":[{"award-number":["2023-PYXK-001"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur J Med Res"],"DOI":"10.1186\/s40001-025-03592-2","type":"journal-article","created":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T11:55:54Z","timestamp":1765367754000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Radiomics-based diagnosis of carotid artery stenosis using non-contrast CT: model development and validation"],"prefix":"10.1186","volume":"30","author":[{"given":"Guoliang","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuhang","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liu","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianqi","family":"Ni","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yifeng","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qin","family":"Jin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,12,10]]},"reference":[{"issue":"3","key":"3592_CR1","doi-asserted-by":"publisher","first-page":"695","DOI":"10.1016\/j.jvs.2023.11.004","volume":"79","author":"KI Paraskevas","year":"2024","unstructured":"Paraskevas KI, Brown MM, Lal BK, et al. Recent advances and controversial issues in the optimal management of asymptomatic carotid stenosis. J Vasc Surg. 2024;79(3):695\u2013703.","journal-title":"J Vasc Surg"},{"key":"3592_CR2","doi-asserted-by":"publisher","first-page":"39","DOI":"10.3174\/ajnr.A5918","volume":"40","author":"W Qiu","year":"2019","unstructured":"Qiu W, Kuang H, Nair J, Assis Z, Najm M, McDougall C, et al. Radiomics-based intracranial thrombus features on CT and CTA predict recanalization with intravenous alteplase in patients with acute ischemic stroke. AJNR Am J Neuroradiol. 2019;40:39\u201344.","journal-title":"AJNR Am J Neuroradiol"},{"key":"3592_CR3","doi-asserted-by":"publisher","first-page":"795","DOI":"10.1016\/S1474-4422(21)00252-0","volume":"20","author":"Collaborators G2S","year":"2021","unstructured":"Collaborators G2S. Global, regional, and national burden of stroke and its risk factors, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Neurol. 2021;20:795\u2013820.","journal-title":"Lancet Neurol"},{"key":"3592_CR4","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1016\/j.atherosclerosis.2018.07.018","volume":"276","author":"A Palanca","year":"2018","unstructured":"Palanca A, Castelblanco E, Perpi\u00f1\u00e1n H, et al. Prevalence and progression of subclinical atherosclerosis in patients with chronic kidney disease and diabetes. Atherosclerosis. 2018;276:50\u20137.","journal-title":"Atherosclerosis"},{"issue":"1","key":"3592_CR5","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1186\/s12933-022-01638-x","volume":"21","author":"M Wang","year":"2022","unstructured":"Wang M, Mei L, Jin A, et al. Association between triglyceride glucose index and atherosclerotic plaques and burden: findings from a community-based study. Cardiovasc Diabetol. 2022;21(1):204.","journal-title":"Cardiovasc Diabetol"},{"issue":"4","key":"3592_CR6","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1038\/nrcardio.2013.8","volume":"10","author":"A Csordas","year":"2013","unstructured":"Csordas A, Bernhard D. The biology behind the atherothrombotic effects of cigarette smoke. Nat Rev Cardiol. 2013;10(4):219\u201330.","journal-title":"Nat Rev Cardiol"},{"issue":"14","key":"3592_CR7","doi-asserted-by":"publisher","first-page":"1617","DOI":"10.1016\/j.jacc.2020.02.026","volume":"75","author":"B L\u00f3pez-Melgar","year":"2020","unstructured":"L\u00f3pez-Melgar B, Fern\u00e1ndez-Friera L, Oliva B, et al. Short-term progression of multiterritorial subclinical atherosclerosis. J Am Coll Cardiol. 2020;75(14):1617\u201327.","journal-title":"J Am Coll Cardiol"},{"issue":"3","key":"3592_CR8","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1517\/14728222.2013.745512","volume":"17","author":"D Santovito","year":"2013","unstructured":"Santovito D, Mandolini C, Marcantonio P, et al. Overexpression of microRNA-145 in atherosclerotic plaques from hypertensive patients. Expert Opin Ther Targets. 2013;17(3):217\u201323.","journal-title":"Expert Opin Ther Targets"},{"issue":"12","key":"3592_CR9","doi-asserted-by":"publisher","first-page":"1294","DOI":"10.1136\/jnis-2023-021243","volume":"16","author":"H Chen","year":"2024","unstructured":"Chen H, Colasurdo M, Costa M, Nossek E, Kan P. Carotid webs: a review of pathophysiology, diagnostic findings, and treatment options. J Neurointerv Surg. 2024;16(12):1294\u20138.","journal-title":"J Neurointerv Surg"},{"issue":"11","key":"3592_CR10","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics14111065","volume":"14","author":"R Cau","year":"2024","unstructured":"Cau R, Saba L, Balestrieri A, et al. Photon-counting computed tomography in atherosclerotic plaque characterization. Diagnostics. 2024;14(11):1065.","journal-title":"Diagnostics"},{"issue":"1","key":"3592_CR11","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1186\/s12880-024-01390-6","volume":"24","author":"HL Zeng","year":"2024","unstructured":"Zeng HL, Shao FQ, Peng XF, Lei CY. Systematic review and meta-analysis of the diagnostic value of computed tomography angiography for severe internal carotid artery stenosis. BMC Med Imaging. 2024;24(1):215.","journal-title":"BMC Med Imaging"},{"issue":"3","key":"3592_CR12","doi-asserted-by":"publisher","DOI":"10.3390\/biology12030337","volume":"12","author":"Z Ma","year":"2023","unstructured":"Ma Z, Jin L, Zhang L, et al. Diagnosis of acute aortic syndromes on non-contrast CT images with radiomics-based machine learning. Biology. 2023;12(3):337.","journal-title":"Biology"},{"issue":"3","key":"3592_CR13","doi-asserted-by":"publisher","first-page":"627","DOI":"10.1007\/s12072-022-10326-7","volume":"16","author":"J Wang","year":"2022","unstructured":"Wang J, Tang S, Mao Y, et al. Radiomics analysis of contrast-enhanced CT for staging liver fibrosis: an update for image biomarker. Hepatol Int. 2022;16(3):627\u201339.","journal-title":"Hepatol Int"},{"key":"3592_CR14","doi-asserted-by":"publisher","first-page":"1116","DOI":"10.1016\/j.jcmg.2016.09.030","volume":"10","author":"A Varga-Szemes","year":"2017","unstructured":"Varga-Szemes A, Wichmann JL, Schoepf UJ, Suranyi P, De Cecco CN, Muscogiuri G, et al. Accuracy of noncontrast quiescent-interval single-shot lower extremity MR angiography versus CT angiography for diagnosis of peripheral artery disease: comparison with digital subtraction angiography. JACC Cardiovasc Imaging. 2017;10:1116\u201324.","journal-title":"JACC Cardiovasc Imaging"},{"key":"3592_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2020.108850","volume":"125","author":"L Dercle","year":"2020","unstructured":"Dercle L, Ma J, Xie C, Chen AP, Wang D, Luk L, et al. Using a single abdominal computed tomography image to differentiate five contrast-enhancement phases: a machine-learning algorithm for radiomics-based precision medicine. Eur J Radiol. 2020;125:108850.","journal-title":"Eur J Radiol"},{"key":"3592_CR16","doi-asserted-by":"publisher","first-page":"1043","DOI":"10.1007\/s00234-020-02628-0","volume":"63","author":"F Zaccagna","year":"2021","unstructured":"Zaccagna F, Ganeshan B, Arca M, Rengo M, Napoli A, Rundo L, et al. CT texture-based radiomics analysis of carotid arteries identifies vulnerable patients: a preliminary outcome study. Neuroradiology. 2021;63:1043\u201352.","journal-title":"Neuroradiology"},{"key":"3592_CR17","doi-asserted-by":"publisher","first-page":"3033","DOI":"10.1038\/s41591-023-02640-w","volume":"29","author":"K Cao","year":"2023","unstructured":"Cao K, Xia Y, Yao J, Han X, Lambert L, Zhang T, et al. Large-scale pancreatic cancer detection via non-contrast CT and deep learning. Nat Med. 2023;29:3033\u201343.","journal-title":"Nat Med"},{"key":"3592_CR18","doi-asserted-by":"publisher","first-page":"3499","DOI":"10.1038\/s41598-021-82760-w","volume":"11","author":"E Le","year":"2021","unstructured":"Le E, Rundo L, Tarkin JM, Evans NR, Chowdhury MM, Coughlin PA, et al. Assessing robustness of carotid artery CT angiography radiomics in the identification of culprit lesions in cerebrovascular events. Sci Rep. 2021;11:3499.","journal-title":"Sci Rep"},{"issue":"2","key":"3592_CR19","doi-asserted-by":"publisher","first-page":"1582","DOI":"10.21037\/qims-24-1512","volume":"15","author":"W Fu","year":"2025","unstructured":"Fu W, Ma Z, Mei B, et al. Predicting progression of cerebral small vessel disease: relevance of carotid perivascular fat density based on computed tomography angiography. Quant Imaging Med Surg. 2025;15(2):1582\u201398.","journal-title":"Quant Imaging Med Surg"},{"key":"3592_CR20","doi-asserted-by":"publisher","first-page":"1153784","DOI":"10.3389\/fradi.2023.1153784","volume":"3","author":"J Wu","year":"2023","unstructured":"Wu J, Xia Y, Wang X, Wei Y, Liu A, Innanje A, et al. uRP: an integrated research platform for one-stop analysis of medical images. Front Radiol. 2023;3:1153784.","journal-title":"Front Radiol"},{"key":"3592_CR21","first-page":"7067","volume":"31","author":"Y Guo","year":"2021","unstructured":"Guo Y, Chen X, Lin X, Chen L, Shu J, Pang P, et al. Non-contrast CT-based radiomic signature for screening thoracic aortic dissections: a multicenter study. European. 2021;31:7067\u201376.","journal-title":"European"},{"key":"3592_CR22","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1016\/j.jcmg.2024.07.004","volume":"18","author":"Z Huang","year":"2025","unstructured":"Huang Z, Cheng XQ, Lu RR, Bi XJ, Liu YN, Deng YB. Incremental prognostic value of carotid plaque-RADS over stenosis degree in relation to stroke risk. JACC Cardiovasc Imaging. 2025;18:77\u201389.","journal-title":"JACC Cardiovasc Imaging"},{"issue":"4","key":"3592_CR23","first-page":"462","volume":"139","author":"M Mahdian","year":"2025","unstructured":"Mahdian M, Ahmed AA, Bhattacharya M, Prasanna P. Deep learning and radiomics-based vascular calcification characterization in dental cone beam computed tomography as a predictive tool for cardiovascular disease. Oral Surgery Oral. 2025;139(4):462\u20139.","journal-title":"Oral Surgery Oral"},{"key":"3592_CR24","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1186\/s12880-023-01051-0","volume":"23","author":"C Chen","year":"2023","unstructured":"Chen C, Chen M, Tao Q, Hu S, Hu C. Non-contrast CT-based radiomics nomogram of pericoronary adipose tissue for predicting haemodynamically significant coronary stenosis in patients with type 2. BMC Med Imaging. 2023;23:99.","journal-title":"BMC Med Imaging"},{"key":"3592_CR25","doi-asserted-by":"publisher","first-page":"4498","DOI":"10.1007\/s00330-017-4859-z","volume":"27","author":"I Shiri","year":"2017","unstructured":"Shiri I, Rahmim A, Ghaffarian P, Geramifar P, Abdollahi H, Bitarafan-Rajabi A. The impact of image reconstruction settings on 18F-FDG PET radiomic features: multi-scanner phantom and patient studies. Eur Radiol. 2017;27:4498\u2013509.","journal-title":"Eur Radiol"},{"key":"3592_CR26","doi-asserted-by":"publisher","first-page":"1715","DOI":"10.1016\/j.jcmg.2022.04.003","volume":"15","author":"D van Dam-Nolen","year":"2022","unstructured":"van Dam-Nolen D, Truijman M, van der Kolk AG, Liem MI, Schreuder F, Boersma E, et al. Carotid plaque characteristics predict recurrent ischemic stroke and TIA: The PARISK (Plaque At RISK) study. JACC Cardiovasc Imag. 2022;15:1715\u201326.","journal-title":"JACC Cardiovasc Imag"},{"key":"3592_CR27","first-page":"II17","volume":"87","author":"JR Crouse 3rd","year":"1993","unstructured":"Crouse JR 3rd, Thompson CJ. An evaluation of methods for imaging and quantifying coronary and carotid lumen stenosis and atherosclerosis. Circulation. 1993;87:II17-33.","journal-title":"Circulation"},{"key":"3592_CR28","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3310\/hta10300","volume":"10","author":"JM Wardlaw","year":"2006","unstructured":"Wardlaw JM, Chappell FM, Stevenson M, De Nigris E, Thomas S, Gillard J, et al. Accurate, practical and cost-effective assessment of carotid stenosis in the UK. Health Technol Assess. 2006;10:1\u2013182.","journal-title":"Health Technol Assess"},{"key":"3592_CR29","doi-asserted-by":"publisher","first-page":"10415","DOI":"10.1038\/s41598-025-92855-3","volume":"15","author":"W Hu","year":"2025","unstructured":"Hu W, Lin G, Chen W, Wu J, Zhao T, Xu L, et al. Radiomics based on dual-energy CT virtual monoenergetic images to identify symptomatic carotid plaques: a multicenter study. Sci Rep. 2025;15:10415.","journal-title":"Sci Rep"},{"key":"3592_CR30","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1097\/FJC.0000000000001664","volume":"85","author":"Q Lao","year":"2025","unstructured":"Lao Q, Zhou R, Wu Y, Feng C, Pang J, Ma L, et al. Predicting vulnerability status of carotid plaques using CTA-based quantitative analysis. J Cardiovasc Pharmacol. 2025;85:217\u201324.","journal-title":"J Cardiovasc Pharmacol"},{"key":"3592_CR31","doi-asserted-by":"publisher","first-page":"972","DOI":"10.1016\/j.acra.2020.09.021","volume":"28","author":"F Homayounieh","year":"2021","unstructured":"Homayounieh F, Yan P, Digumarthy SR, Kruger U, Wang G, Kalra MK. Prediction of coronary calcification and stenosis: role of radiomics from low-dose CT. Acad Radiol. 2021;28:972\u20139.","journal-title":"Acad Radiol"},{"key":"3592_CR32","doi-asserted-by":"publisher","first-page":"1742","DOI":"10.3390\/tomography8040147","volume":"8","author":"P Theofilis","year":"2022","unstructured":"Theofilis P, Sagris M, Antonopoulos AS, Oikonomou E, Tsioufis K, Tousoulis D. Non-invasive modalities in the assessment of vulnerable coronary atherosclerotic plaques. Tomography. 2022;8:1742\u201358.","journal-title":"Tomography"},{"key":"3592_CR33","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1007\/s00234-022-03080-y","volume":"65","author":"A Camargo","year":"2023","unstructured":"Camargo A, Zacharia T, Kanekar S, Bruno M, Tian Z, Zhou S, et al. Value of CTA\/MRA in the setting of intraparenchymal hemorrhage in the emergency department. Neuroradiology. 2023;65:97\u2013103.","journal-title":"Neuroradiology"},{"key":"3592_CR34","doi-asserted-by":"publisher","first-page":"274","DOI":"10.1016\/j.jcct.2019.04.007","volume":"13","author":"M Kolossv\u00e1ry","year":"2019","unstructured":"Kolossv\u00e1ry M, De Cecco CN, Feuchtner G, Maurovich-Horvat P. Advanced atherosclerosis imaging by CT: radiomics, machine learning and deep learning. J Cardiovasc Comput Tomogr. 2019;13:274\u201380.","journal-title":"J Cardiovasc Comput Tomogr"},{"key":"3592_CR35","doi-asserted-by":"publisher","first-page":"R150","DOI":"10.1088\/0031-9155\/61\/13\/R150","volume":"61","author":"SS Yip","year":"2016","unstructured":"Yip SS, Aerts HJ. Applications and limitations of radiomics. Phys Med Biol. 2016;61:R150\u201366.","journal-title":"Phys Med Biol"},{"key":"3592_CR36","doi-asserted-by":"publisher","first-page":"300060524123814","DOI":"10.1177\/03000605241238141","volume":"52","author":"J Yang","year":"2024","unstructured":"Yang J, Cai H, Liu N, Huang J, Pan Y, Zhang B, et al. Application of radiomics in ischemic stroke. J Int Med Res. 2024;52:3000605241238141.","journal-title":"J Int Med Res"},{"key":"3592_CR37","doi-asserted-by":"publisher","first-page":"4616","DOI":"10.21037\/qims-24-1974","volume":"15","author":"H Wang","year":"2025","unstructured":"Wang H, Liang Y, Song M, Zhang Z, Gu M, Mao Q, et al. Classification of carotid artery plaques: promising alternative methods to computed tomography angiography through radiomics approach using neck non-contrast computed tomography. Quant Imaging Med Surg. 2025;15:4616\u201328.","journal-title":"Quant Imaging Med Surg"},{"key":"3592_CR38","doi-asserted-by":"publisher","first-page":"035016","DOI":"10.1088\/2057-1976\/ad34db","volume":"10","author":"S Raptis","year":"2024","unstructured":"Raptis S, Ilioudis C, Theodorou K. From pixels to prognosis: unveiling radiomics models with SHAP and LIME for enhanced interpretability. Biomed Phys Eng Express. 2024;10:035016.","journal-title":"Biomed Phys Eng Express"},{"key":"3592_CR39","doi-asserted-by":"publisher","first-page":"401","DOI":"10.1053\/j.semvascsurg.2023.07.002","volume":"36","author":"SS Dossabhoy","year":"2023","unstructured":"Dossabhoy SS, Ho VT, Ross EG, Rodriguez F, Arya S. Artificial intelligence in clinical workflow processes in vascular surgery and beyond. Semin Vasc Surg. 2023;36:401\u201312.","journal-title":"Semin Vasc Surg"},{"key":"3592_CR40","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2024.108289","volume":"254","author":"M Ferdowsi","year":"2024","unstructured":"Ferdowsi M, Hasan MM, Habib W. Responsible AI for cardiovascular disease detection: towards a privacy-preserving and interpretable model. Comput Methods Programs Biomed. 2024;254:108289.","journal-title":"Comput Methods Programs Biomed"},{"key":"3592_CR41","volume":"16","author":"AL Boudi","year":"2024","unstructured":"Boudi AL, Boudi M, Chan C, Boudi FB. Ethical challenges of artificial intelligence in medicine. Cureus. 2024;16:e74495.","journal-title":"Cureus"},{"key":"3592_CR42","doi-asserted-by":"publisher","first-page":"18994","DOI":"10.1038\/s41598-024-70073-7","volume":"14","author":"YH Li","year":"2024","unstructured":"Li YH, Li YL, Wei MY, Li GY. Innovation and challenges of artificial intelligence technology in personalized healthcare. Sci Rep. 2024;14:18994.","journal-title":"Sci Rep"}],"container-title":["European Journal of Medical Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40001-025-03592-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s40001-025-03592-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40001-025-03592-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T17:02:41Z","timestamp":1765818161000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s40001-025-03592-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,10]]},"references-count":42,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["3592"],"URL":"https:\/\/doi.org\/10.1186\/s40001-025-03592-2","relation":{},"ISSN":["2047-783X"],"issn-type":[{"value":"2047-783X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,10]]},"assertion":[{"value":"18 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 November 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 December 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 approved by the Ethics Committee of the First Hospital of Jiaxing (approval number: 2024-LY-089, 2025-LY-032).","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing of interests"}}],"article-number":"1237"}}