{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T03:39:36Z","timestamp":1788493176330,"version":"build-2803163510"},"reference-count":63,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T00:00:00Z","timestamp":1763596800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Cardiovasc. Med."],"abstract":"<jats:p>Abdominal and thoracic aortic repairs increasingly rely on endovascular solutions, but device selection in anatomically complex cases remains prone to error due to measurement variability, tortuosity, short\/angulated necks, and heterogeneous post-EVAR evolution. This article focuses on artificial intelligence (AI) tools that support intravascular device selection and planning, particularly in abdominal and thoracic aortic aneurysms, and type B dissection scenarios where endovascular repair (EVAR\/TEVAR) is applicable. We synthesize evidence on (i) automated centerline extraction and 3D measurements that standardize sizing; (ii) risk models that predict inadequate sealing or endoleakage to guide oversizing and landing zone strategy; and (iii) procedural environment \u201caugmented intelligence\u201d maps and extended reality modules that operationalize device selections in the laboratory. We summarize commercial and research-level systems, clinical readiness, and regulatory status, and outline validation, explainability, and bias considerations. While current evidence-based workflows achieve excellent results, targeted AI components reduce variability and can support consistent device decisions across complex anatomies. Prospective, multicenter validation is needed before routine implementation; for now, AI should be viewed as a complement, rather than a replacement, to established EVAR\/TEVAR planning and oversight.<\/jats:p>","DOI":"10.3389\/fcvm.2025.1585299","type":"journal-article","created":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T13:02:52Z","timestamp":1763643772000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["AI-driven decision making for intravascular device selection in aortic disease. Current insights and prospects"],"prefix":"10.3389","volume":"12","author":[{"given":"Rasit","family":"Dinc","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nurittin","family":"Ardic","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,11,20]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"e334","DOI":"10.1161\/CIR.0000000000001106","article-title":"2022 ACC\/AHA guideline for the diagnosis and management of aortic disease: a report of the American heart association\/American college of cardiology joint committee on clinical practice guidelines","volume":"146","author":"Isselbacher","year":"2022","journal-title":"Circulation"},{"key":"B2","doi-asserted-by":"publisher","first-page":"e266","DOI":"10.1161\/CIR.0b013e3181d4739e","article-title":"2010 ACCF\/AHA\/AATS\/ACR\/ASA\/SCA\/SCAI\/SIR\/STS\/SVM guidelines for the diagnosis and management of patients with thoracic aortic disease: a report of the American college of cardiology foundation\/American heart association task force on practice guidelines, American association for thoracic surgery, American college of radiology, American stroke association, society of cardiovascular anesthesiologists, society for cardiovascular angiography and interventions, society of interventional radiology, society of thoracic surgeons, and society for vascular medicine","volume":"121","author":"Hiratzka","year":"2010","journal-title":"Circulation"},{"key":"B3","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1111\/joim.12958","article-title":"Lack of an effective drug therapy for abdominal aortic aneurysm","volume":"288","author":"Golledge","year":"2020","journal-title":"J Intern Med"},{"key":"B4","doi-asserted-by":"publisher","first-page":"539","DOI":"10.24875\/CIRU.24000348","article-title":"Multilayer flow modulator stents in aortic aneurysms: an overview based on preliminary experience","volume":"93","author":"Tanyeli","year":"2025","journal-title":"Cir Cir"},{"key":"B5","doi-asserted-by":"publisher","first-page":"535","DOI":"10.21470\/1678-9741-2020-0089","article-title":"The aortic pathologies: how far we understand it and its implications on thoracic aortic surgery","volume":"36","author":"Harky","year":"2021","journal-title":"Braz J Cardiovasc Surg"},{"key":"B6","doi-asserted-by":"publisher","first-page":"523","DOI":"10.1002\/bjs.11123","article-title":"Meta-analysis of long-term survival after elective endovascular or open repair of abdominal aortic aneurysm","volume":"106","author":"Bulder","year":"2019","journal-title":"Br J Surg"},{"key":"B7","first-page":"3","article-title":"Endovascular aortic aneurysm repair (EVAR)","volume":"82","author":"England","year":"2013","journal-title":"Ulster Med J"},{"key":"B8","doi-asserted-by":"publisher","first-page":"620","DOI":"10.1016\/j.jvs.2022.03.891","article-title":"Fully automatic volume segmentation using deep learning approaches to assess aneurysmal sac evolution after infrarenal endovascular aortic repair","volume":"76","author":"Caradu","year":"2022","journal-title":"J Vasc Surg"},{"key":"B9","doi-asserted-by":"publisher","first-page":"496","DOI":"10.1186\/s13019-024-02996-1","article-title":"Study on the clinical value of computed tomography angiography in the diagnosis of aortic aneurysm","volume":"19","author":"Yan","year":"2024","journal-title":"J. Cardiothorac Surg"},{"key":"B10","doi-asserted-by":"publisher","first-page":"1040053","DOI":"10.3389\/fcvm.2022.1040053","article-title":"Deep-learning method for fully automatic segmentation of the abdominal aortic aneurysm from computed tomography imaging","volume":"9","author":"Abdolmanafi","year":"2023","journal-title":"FrontCardiovasc Med"},{"key":"B11","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1055\/s-0035-1556878","article-title":"Surveillance imaging following endovascular aneurysm repair","volume":"32","author":"Pandey","year":"2015","journal-title":"Semin Intervent Radiol"},{"key":"B12","doi-asserted-by":"publisher","first-page":"S157","DOI":"10.21037\/cdt.2018.01.01","article-title":"Repair of abdominal aortic aneurysms: preoperative imaging and evaluation","volume":"8","author":"Hu","year":"2018","journal-title":"Cardiovasc Diagn Ther"},{"key":"B13","doi-asserted-by":"publisher","first-page":"2479","DOI":"10.1016\/j.jcin.2023.07.022","article-title":"Artificial intelligence, computational simulations, and extended reality in cardiovascular interventions","volume":"16","author":"Samant","year":"2023","journal-title":"JACC Cardiovasc Interv"},{"key":"B14","doi-asserted-by":"publisher","first-page":"100179","DOI":"10.1016\/j.jvsvi.2024.100179","article-title":"The role of artificial intelligence in vascular care","volume":"3","author":"Nimmagadda","year":"2025","journal-title":"JVS Vascular Insights"},{"key":"B15","doi-asserted-by":"publisher","first-page":"14604582251366141","DOI":"10.1177\/14604582251366141","article-title":"Emerging trends in multi-modal artificial intelligence for clinical decision support: a narrative review","volume":"31","author":"Ardic","year":"2025","journal-title":"Health Inform J"},{"key":"B16","doi-asserted-by":"publisher","first-page":"465","DOI":"10.3390\/biomimetics9080465","article-title":"Current applications and future perspectives of artificial and biomimetic intelligence in vascular surgery and peripheral artery disease","volume":"9","author":"Martelli","year":"2024","journal-title":"Biomimetics"},{"key":"B17","doi-asserted-by":"publisher","first-page":"204","DOI":"10.34172\/jcvtr.2023.33031","article-title":"Artificial intelligence in cardiovascular medicine: an updated review of the literature","volume":"15","author":"Zargarzadeh","year":"2023","journal-title":"J Cardiovasc Thorac Res"},{"key":"B18","doi-asserted-by":"publisher","first-page":"1166","DOI":"10.5551\/jat.62941","article-title":"Height and mortality from aortic aneurysm and dissection","volume":"29","author":"Takada","year":"2022","journal-title":"J Atheroscler Thromb"},{"key":"B19","doi-asserted-by":"publisher","first-page":"1846","DOI":"10.1161\/CIRCULATIONAHA.117.031264","article-title":"Insights from the international registry of acute aortic dissection: a 20-year experience of collaborative clinical research","volume":"137","author":"Evangelista","year":"2018","journal-title":"Circulation"},{"key":"B20","article-title":"Anatomy, Abdomen and Pelvis: Abdominal Aorta","volume-title":"StatPearls","author":"Tran","year":"2023"},{"key":"B21","doi-asserted-by":"publisher","first-page":"675","DOI":"10.6515\/ACS.202309_39(5).20230531A","article-title":"The role of immune mechanisms in abdominal aortic aneurysm: could it be a promising therapeutic strategy?","volume":"39","author":"Dinc","year":"2023","journal-title":"Acta Cardiol. Sin"},{"key":"B22","first-page":"215","article-title":"Pre- and post-aortic endovascular interventions: what a radiologist needs to know","volume-title":"Diseases of the Chest, Breast, Heart and Vessels 2019\u20132022: Diagnostic and Interventional Imaging","author":"Bley","year":"2019"},{"key":"B23","doi-asserted-by":"publisher","first-page":"W347","DOI":"10.2214\/AJR.13.11735","article-title":"Essentials of endovascular abdominal aortic aneurysm repair imaging: preprocedural assessment","volume":"203","author":"Picel","year":"2014","journal-title":"AJR Am J Roentgenol"},{"key":"B24","first-page":"206","article-title":"Imaging of acute aortic syndromes","volume-title":"Diseases of the Chest, Breast, Heart and Vessels 2019\u20132022: Diagnostic and Interventional Imaging","author":"Grist","year":"2019"},{"key":"B25","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1016\/j.jvs.2017.10.044","article-title":"The society for vascular surgery practice guidelines on the care of patients with an abdominal aortic aneurysm","volume":"67","author":"Chaikof","year":"2018","journal-title":"J Vasc Surg"},{"key":"B26","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1016\/j.jvs.2010.07.052","article-title":"Treatment options for delayed AAA rupture following endovascular repair","volume":"53","author":"Mehta","year":"2011","journal-title":"J Vasc Surg"},{"key":"B27","doi-asserted-by":"publisher","first-page":"869","DOI":"10.1016\/j.ejvs.2021.07.013","article-title":"Pre-surgical and post-surgical aortic aneurysm Maximum diameter measurement: full automation by artificial intelligence","volume":"62","author":"Adam","year":"2021","journal-title":"Eur J Vasc Endovasc Surg"},{"key":"B28","first-page":"75","article-title":"AI, automation, and aortic aneurysm care","volume":"22","author":"Fabre","year":"2023","journal-title":"Endovasc Today"},{"key":"B29","doi-asserted-by":"publisher","first-page":"500","DOI":"10.51594\/imsrj.v4i4.1052","article-title":"The role of artificial intelligence in healthcare: a systematic review of applications and challenges","volume":"4","author":"Udegbe","year":"2024","journal-title":"Int Med Sci Res J"},{"key":"B30","doi-asserted-by":"publisher","first-page":"4910","DOI":"10.35940\/ijitee.L3550.1081219","article-title":"Machine learning and deep learning","volume":"8","author":"Chahal","year":"2019","journal-title":"Int J Innov Technol Explor Eng"},{"key":"B31","doi-asserted-by":"publisher","first-page":"507","DOI":"10.3390\/life13020507","article-title":"Artificial intelligence in cardiovascular CT and MR imaging","volume":"13","author":"Lanzafame","year":"2023","journal-title":"Life"},{"key":"B32","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1186\/s12909-023-04698-z","article-title":"Revolutionizing healthcare: the role of artificial intelligence in clinical practice","volume":"23","author":"Alowais","year":"2023","journal-title":"BMC Med Educ"},{"key":"B33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.12968\/hmed.2024.0972","article-title":"Artificial intelligence in healthcare: current regulatory landscape and future directions","volume":"86","author":"Ardic","year":"2025","journal-title":"Br J Hosp Med"},{"key":"B34","doi-asserted-by":"publisher","first-page":"e0129024","DOI":"10.1371\/journal.pone.0129024","article-title":"An artificial neural network stratifies the risks of reintervention and mortality after endovascular aneurysm repair; a retrospective observational study","volume":"10","author":"Karthikesalingam","year":"2015","journal-title":"PLoS One"},{"key":"B35","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1177\/15385744231189024","article-title":"Applying artificial intelligence to predict complications after endovascular aneurysm repair","volume":"58","author":"Long","year":"2024","journal-title":"Vasc Endovascular Surg"},{"key":"B36","doi-asserted-by":"publisher","first-page":"e195","DOI":"10.1016\/S2589-7500(20)30292-2","article-title":"Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015\u201320): a comparative analysis","volume":"3","author":"Muehlematter","year":"2021","journal-title":"Lancet Digit Health"},{"key":"B37","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1162\/99608f92.5a8a3a3d","article-title":"Why are we using black box models in AI when we don\u2019t need to? A lesson from an explainable AI competition","volume":"1","author":"Rudin","year":"2019","journal-title":"Harvard Data Sci Rev"},{"key":"B38","doi-asserted-by":"publisher","first-page":"e745","DOI":"10.1016\/S2589-7500(21)00208-9","article-title":"The false hope of current approaches to explainable artificial intelligence in health care","volume":"3","author":"Ghassemi","year":"2021","journal-title":"Lancet Digit Health"},{"key":"B39","doi-asserted-by":"publisher","first-page":"100702","DOI":"10.1016\/j.hlpt.2022.100702","article-title":"Addressing algorithmic bias and the perpetuation of health inequities: an AI bias aware framework","volume":"12","author":"Agarwal","year":"2023","journal-title":"Health Policy Technol"},{"key":"B40","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1126\/science.aax2342","article-title":"Dissecting racial bias in an algorithm used to manage the health of populations","volume":"366","author":"Obermeyer","year":"2019","journal-title":"Science"},{"key":"B41","doi-asserted-by":"publisher","first-page":"982","DOI":"10.1016\/j.jvs.2022.12.033","article-title":"Use of surgical augmented intelligence maps can reduce radiation and improve safety in the endovascular treatment of complex aortic aneurysms","volume":"77","author":"Patel","year":"2023","journal-title":"J Vasc Surg"},{"key":"B42","doi-asserted-by":"publisher","first-page":"418","DOI":"10.1016\/j.ejvs.2013.07.018","article-title":"The benefits of EVAR planning using a 3D workstation","volume":"46","author":"Sobocinski","year":"2013","journal-title":"Eur J Vasc Endovasc Surg"},{"key":"B43","doi-asserted-by":"publisher","first-page":"100016","DOI":"10.1016\/j.jvsvi.2023.100016","article-title":"A review of mature machine learning-and artificial intelligence-enabled applications in aortic surgery","volume":"1","author":"Stonko","year":"2023","journal-title":"JVS Vascular Insights"},{"key":"B44","year":"2021"},{"key":"B45","doi-asserted-by":"publisher","first-page":"101177","DOI":"10.1016\/j.adro.2023.101177","article-title":"Clinical validation of Siemens\u2019 Syngo.via automatic contouring system","volume":"8","author":"Pera","year":"2023","journal-title":"Adv Radiat Oncol"},{"key":"B46","article-title":"Evaluation and volumetric analysis of aorto-iliac calcification on CT-angiography: proof of concept of the Siemens syngo.via software","author":"Srinivas","year":"2022"},{"key":"B47","year":""},{"key":"B48","author":"Park","year":"2022"},{"key":"B49","author":"Salehi","year":"2022"},{"key":"B50","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1097\/RCT.0000000000000958","article-title":"Machine learning to predict the rapid growth of small abdominal aortic aneurysm","volume":"44","author":"Hirata","year":"2020","journal-title":"J Comput Assist Tomogr"},{"key":"B51","doi-asserted-by":"publisher","first-page":"e79662","DOI":"10.7759\/cureus.79662","article-title":"Artificial intelligence-based predictive modeling for aortic aneurysms","volume":"17","author":"Abbas","year":"2025","journal-title":"Cureus"},{"key":"B52","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1016\/j.jacc.2020.11.030","article-title":"Machine learning and the future of cardiovascular care: JACC state-of-the-art review","volume":"77","author":"Quer","year":"2021","journal-title":"J Am Coll Cardiol"},{"key":"B53","doi-asserted-by":"publisher","first-page":"489","DOI":"10.1007\/s40846-024-00881-9","article-title":"Deep learning models for aorta segmentation in computed tomography images. A systematic review and meta-analysis","volume":"44","author":"Wang","year":"2024","journal-title":"J Med Biol Eng"},{"key":"B54","doi-asserted-by":"publisher","first-page":"373","DOI":"10.3174\/ajnr.A6468","article-title":"Artificial intelligence in the management of intracranial aneurysms: current status and future perspectives","volume":"41","author":"Shi","year":"2020","journal-title":"AJNR Am J Neuroradiol"},{"key":"B55","doi-asserted-by":"publisher","first-page":"654","DOI":"10.1038\/s41467-024-44824-z","article-title":"Segment anything in medical images","volume":"15","author":"Ma","year":"2024","journal-title":"Nat Commun"},{"key":"B56","doi-asserted-by":"publisher","first-page":"101504","DOI":"10.1016\/j.imu.2024.101504","article-title":"Deep learning for medical image segmentation. State-of-the-art advancements and challenges","volume":"47","author":"Rayed","year":"2024","journal-title":"Inform Med Unlocked"},{"key":"B57","year":"2025"},{"key":"B58","year":"2024"},{"key":"B59","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1038\/s41746-020-00323-1","article-title":"The future of digital health with federated learning","volume":"3","author":"Rieke","year":"2020","journal-title":"NPJ Digit Med"},{"key":"B60","year":"2024"},{"key":"B61","year":"2025"},{"key":"B62","doi-asserted-by":"publisher","first-page":"4793","DOI":"10.1109\/TNNLS.2020.3027314","article-title":"A survey on explainable artificial intelligence (XAI): toward medical XAI","volume":"32","author":"Tjoa","year":"2021","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"B63","doi-asserted-by":"publisher","first-page":"2693","DOI":"10.1007\/s00146-022-01602-z","article-title":"AI Ethics: from principles to practice","volume":"38","author":"Zhou","year":"2023","journal-title":"AI Soc"}],"container-title":["Frontiers in Cardiovascular Medicine"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fcvm.2025.1585299\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T13:02:53Z","timestamp":1763643773000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fcvm.2025.1585299\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,20]]},"references-count":63,"alternative-id":["10.3389\/fcvm.2025.1585299"],"URL":"https:\/\/doi.org\/10.3389\/fcvm.2025.1585299","relation":{},"ISSN":["2297-055X"],"issn-type":[{"value":"2297-055X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,20]]},"article-number":"1585299"}}