{"title":"神经血管内手术中的人工智能。","authors":"Kenichi Kono","doi":"10.5797/jnet.ra.2024-0107","DOIUrl":null,"url":null,"abstract":"<p><p>Recent advances in artificial intelligence (AI) have significantly transformed neuroendovascular procedures, offering innovative solutions for image analysis, procedural assistance, and clinical decision-making. This review examines the current state and future potential of AI applications in neuroendovascular interventions, focusing on 3 topics: AI-based image recognition, real-time procedural assistance, and future developments. From a research perspective, deep learning algorithms have demonstrated reasonable accuracy in vascular structure analysis and device detection, successfully identifying critical conditions such as vascular perforation, aneurysm location, and vessel occlusions. Real-time AI assistance systems may have potential clinical utility in various procedures, including carotid artery stenting, aneurysm coiling, and liquid embolization, potentially enhancing procedural safety and operator awareness. The future of AI in neuroendovascular procedures shows promise in integration with robotic systems and applications in medical education. While current systems have some limitations, ongoing technological advances suggest an expanding role of AI in enhancing procedural safety, standardization, and patient outcomes.</p>","PeriodicalId":73856,"journal":{"name":"Journal of neuroendovascular therapy","volume":"19 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11873741/pdf/","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence in Neuroendovascular Procedures.\",\"authors\":\"Kenichi Kono\",\"doi\":\"10.5797/jnet.ra.2024-0107\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Recent advances in artificial intelligence (AI) have significantly transformed neuroendovascular procedures, offering innovative solutions for image analysis, procedural assistance, and clinical decision-making. This review examines the current state and future potential of AI applications in neuroendovascular interventions, focusing on 3 topics: AI-based image recognition, real-time procedural assistance, and future developments. From a research perspective, deep learning algorithms have demonstrated reasonable accuracy in vascular structure analysis and device detection, successfully identifying critical conditions such as vascular perforation, aneurysm location, and vessel occlusions. Real-time AI assistance systems may have potential clinical utility in various procedures, including carotid artery stenting, aneurysm coiling, and liquid embolization, potentially enhancing procedural safety and operator awareness. The future of AI in neuroendovascular procedures shows promise in integration with robotic systems and applications in medical education. While current systems have some limitations, ongoing technological advances suggest an expanding role of AI in enhancing procedural safety, standardization, and patient outcomes.</p>\",\"PeriodicalId\":73856,\"journal\":{\"name\":\"Journal of neuroendovascular therapy\",\"volume\":\"19 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11873741/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of neuroendovascular therapy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5797/jnet.ra.2024-0107\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/2/27 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of neuroendovascular therapy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5797/jnet.ra.2024-0107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/27 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Artificial Intelligence in Neuroendovascular Procedures.
Recent advances in artificial intelligence (AI) have significantly transformed neuroendovascular procedures, offering innovative solutions for image analysis, procedural assistance, and clinical decision-making. This review examines the current state and future potential of AI applications in neuroendovascular interventions, focusing on 3 topics: AI-based image recognition, real-time procedural assistance, and future developments. From a research perspective, deep learning algorithms have demonstrated reasonable accuracy in vascular structure analysis and device detection, successfully identifying critical conditions such as vascular perforation, aneurysm location, and vessel occlusions. Real-time AI assistance systems may have potential clinical utility in various procedures, including carotid artery stenting, aneurysm coiling, and liquid embolization, potentially enhancing procedural safety and operator awareness. The future of AI in neuroendovascular procedures shows promise in integration with robotic systems and applications in medical education. While current systems have some limitations, ongoing technological advances suggest an expanding role of AI in enhancing procedural safety, standardization, and patient outcomes.