利用血管造影预测血流再定向腔内装置(FRED)部署的困难:一项技术说明

Hiroya Morita , Kiyoshi Kazekawa, Noriaki Tashiro, Hiroto Kawano, Hiroshi Aikawa
{"title":"利用血管造影预测血流再定向腔内装置(FRED)部署的困难:一项技术说明","authors":"Hiroya Morita ,&nbsp;Kiyoshi Kazekawa,&nbsp;Noriaki Tashiro,&nbsp;Hiroto Kawano,&nbsp;Hiroshi Aikawa","doi":"10.1016/j.neuri.2022.100073","DOIUrl":null,"url":null,"abstract":"<div><p>The Flow Re-direction Endoluminal Device (FRED) is widely used to treat large intracranial unruptured cerebral aneurysms; however, some cases of deployment failure have been observed. Most of these cases occur in internal carotid artery aneurysms around the siphon. We report a method that we developed to predict the success of FRED deployment by using a preoperative angiography in simple lateral view.</p></div>","PeriodicalId":74295,"journal":{"name":"Neuroscience informatics","volume":"2 2","pages":"Article 100073"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772528622000358/pdfft?md5=48b01581307ccabf877ca0e975eddaa3&pid=1-s2.0-S2772528622000358-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Predicting difficulty in Flow Re-direction Endoluminal Device (FRED) deployment using angiography: A technical note\",\"authors\":\"Hiroya Morita ,&nbsp;Kiyoshi Kazekawa,&nbsp;Noriaki Tashiro,&nbsp;Hiroto Kawano,&nbsp;Hiroshi Aikawa\",\"doi\":\"10.1016/j.neuri.2022.100073\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The Flow Re-direction Endoluminal Device (FRED) is widely used to treat large intracranial unruptured cerebral aneurysms; however, some cases of deployment failure have been observed. Most of these cases occur in internal carotid artery aneurysms around the siphon. We report a method that we developed to predict the success of FRED deployment by using a preoperative angiography in simple lateral view.</p></div>\",\"PeriodicalId\":74295,\"journal\":{\"name\":\"Neuroscience informatics\",\"volume\":\"2 2\",\"pages\":\"Article 100073\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2772528622000358/pdfft?md5=48b01581307ccabf877ca0e975eddaa3&pid=1-s2.0-S2772528622000358-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neuroscience informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772528622000358\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuroscience informatics","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772528622000358","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

血流重定向腔内装置(FRED)被广泛用于治疗颅内未破裂的大动脉瘤;但是,也观察到一些部署失败的情况。这些病例大多发生在虹吸管周围的颈内动脉动脉瘤。我们报告了一种方法,我们开发的预测FRED部署成功使用术前血管造影在简单的侧位视图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Predicting difficulty in Flow Re-direction Endoluminal Device (FRED) deployment using angiography: A technical note

The Flow Re-direction Endoluminal Device (FRED) is widely used to treat large intracranial unruptured cerebral aneurysms; however, some cases of deployment failure have been observed. Most of these cases occur in internal carotid artery aneurysms around the siphon. We report a method that we developed to predict the success of FRED deployment by using a preoperative angiography in simple lateral view.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Neuroscience informatics
Neuroscience informatics Surgery, Radiology and Imaging, Information Systems, Neurology, Artificial Intelligence, Computer Science Applications, Signal Processing, Critical Care and Intensive Care Medicine, Health Informatics, Clinical Neurology, Pathology and Medical Technology
自引率
0.00%
发文量
0
审稿时长
57 days
期刊最新文献
Editorial Board Contents Integrated analysis of lncRNA-miRNA-mRNA ceRNA network in neurodegenerative diseases Topic modeling of neuropsychiatric diseases related to gut microbiota and gut brain axis using artificial intelligence based BERTopic model on PubMed abstracts Brain network analysis in Parkinson's disease patients based on graph theory
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1