在 CT 血管造影上识别 Sylvian 三角区:一种检测大脑中动脉远端闭塞的技术。

IF 1.5 4区 医学 Q4 CLINICAL NEUROLOGY
Stephen J Sozio, Alexandra Castro, Sri Hari Sundararajan, Steven Schonfeld, Gaurav Gupta, Nancy C Prendergast, Irwin A Keller, Sudipta Roychowdhury
{"title":"在 CT 血管造影上识别 Sylvian 三角区:一种检测大脑中动脉远端闭塞的技术。","authors":"Stephen J Sozio, Alexandra Castro, Sri Hari Sundararajan, Steven Schonfeld, Gaurav Gupta, Nancy C Prendergast, Irwin A Keller, Sudipta Roychowdhury","doi":"10.1177/15910199241258373","DOIUrl":null,"url":null,"abstract":"<p><p>Medium vessel occlusions (MeVOs), defined as occlusion of the M2/M3 and A2/A3 segments of the middle cerebral artery (MCA) and anterior cerebral artery, can be challenging to visualize on CT angiography (CTA) and MR angiography (MRA), given the anatomic complexity of the mid- and distal intracranial vasculature and smaller vessel caliber (Leary MC, Kidwell CS, Villablanca JP, et al. Validation of computed tomographic MCA \"dot\" sign: an angiographic correlation study. <i>Stroke</i> 2003; 34: 2636-2640; Luijten SPR, Wolff L, Duvekot MHC, et al. Diagnostic performance of an algorithm for automated large vessel occlusion (LVO) detection on CTA. <i>J Neurointerv Surg</i> 2022; 14: 794-798). In turn, the appearance of a sudden vessel cutoff in these vascular distributions on CTA or MRA is not always straightforward and may represent true occlusion, variant anatomy, and/or artifact (Leary MC, Kidwell CS, Villablanca JP, et al. Validation of computed tomographic MCA \"dot\" sign: an angiographic correlation study. <i>Stroke</i> 2003; 34: 2636-2640; Luijten SPR, Wolff L, Duvekot MHC, et al. Diagnostic performance of an algorithm for automated LVO detection on CTA. <i>J Neurointerv Surg</i> 2022; 14: 794-798). Given the importance of rapidly establishing an accurate diagnosis in the setting of stroke, combined with recent clinical trials and movements promoting the efficacy of endovascular therapeutic approaches to treat MeVOs, it remains imperative to detect such occlusions accurately and quickly on imaging. In turn, we present five imaging patterns of the Sylvian Triangle on sagittal reformatted images from CTA Head examinations, which our practice has utilized to assess patency of the M2 and M3 divisions. This approach is rapidly deployable and can be utilized by radiology and non-radiology healthcare providers alike, thus facilitating rapid and accurate diagnosis of MeVO, timely evaluation of candidacy for endovascular therapy, and ultimately supporting favorable door-to-intervention time and successful patient outcomes.</p>","PeriodicalId":49174,"journal":{"name":"Interventional Neuroradiology","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identifying the Sylvian Triangle on CT angiography: A technique for detecting distal middle cerebral artery occlusions.\",\"authors\":\"Stephen J Sozio, Alexandra Castro, Sri Hari Sundararajan, Steven Schonfeld, Gaurav Gupta, Nancy C Prendergast, Irwin A Keller, Sudipta Roychowdhury\",\"doi\":\"10.1177/15910199241258373\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Medium vessel occlusions (MeVOs), defined as occlusion of the M2/M3 and A2/A3 segments of the middle cerebral artery (MCA) and anterior cerebral artery, can be challenging to visualize on CT angiography (CTA) and MR angiography (MRA), given the anatomic complexity of the mid- and distal intracranial vasculature and smaller vessel caliber (Leary MC, Kidwell CS, Villablanca JP, et al. Validation of computed tomographic MCA \\\"dot\\\" sign: an angiographic correlation study. <i>Stroke</i> 2003; 34: 2636-2640; Luijten SPR, Wolff L, Duvekot MHC, et al. Diagnostic performance of an algorithm for automated large vessel occlusion (LVO) detection on CTA. <i>J Neurointerv Surg</i> 2022; 14: 794-798). In turn, the appearance of a sudden vessel cutoff in these vascular distributions on CTA or MRA is not always straightforward and may represent true occlusion, variant anatomy, and/or artifact (Leary MC, Kidwell CS, Villablanca JP, et al. Validation of computed tomographic MCA \\\"dot\\\" sign: an angiographic correlation study. <i>Stroke</i> 2003; 34: 2636-2640; Luijten SPR, Wolff L, Duvekot MHC, et al. Diagnostic performance of an algorithm for automated LVO detection on CTA. <i>J Neurointerv Surg</i> 2022; 14: 794-798). Given the importance of rapidly establishing an accurate diagnosis in the setting of stroke, combined with recent clinical trials and movements promoting the efficacy of endovascular therapeutic approaches to treat MeVOs, it remains imperative to detect such occlusions accurately and quickly on imaging. In turn, we present five imaging patterns of the Sylvian Triangle on sagittal reformatted images from CTA Head examinations, which our practice has utilized to assess patency of the M2 and M3 divisions. This approach is rapidly deployable and can be utilized by radiology and non-radiology healthcare providers alike, thus facilitating rapid and accurate diagnosis of MeVO, timely evaluation of candidacy for endovascular therapy, and ultimately supporting favorable door-to-intervention time and successful patient outcomes.</p>\",\"PeriodicalId\":49174,\"journal\":{\"name\":\"Interventional Neuroradiology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Interventional Neuroradiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/15910199241258373\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Interventional Neuroradiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/15910199241258373","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0

摘要

中型血管闭塞症(MeVOs)是指大脑中动脉(MCA)和大脑前动脉的 M2/M3 段和 A2/A3 段闭塞,由于颅内中远端血管解剖结构复杂且血管口径较小(Leary MC, Kidwell CS, Villablanca JP, et al.计算机断层扫描 MCA "点 "征的验证:血管造影相关性研究。Stroke 2003; 34: 2636-2640;Luijten SPR、Wolff L、Duvekot MHC 等:CTA 自动检测大血管闭塞(LVO)算法的诊断性能。J Neurointerv Surg 2022; 14: 794-798)。反过来,CTA 或 MRA 上这些血管分布中突然出现的血管断裂并不总是很直接,可能代表真正的闭塞、变异的解剖结构和/或伪影(Leary MC、Kidwell CS、Villablanca JP 等:《计算机断层扫描 MCA "点 "标志的验证:血管造影相关性研究》。Stroke 2003; 34: 2636-2640;Luijten SPR、Wolff L、Duvekot MHC 等:CTA 上自动 LVO 检测算法的诊断性能。J Neurointerv Surg 2022; 14: 794-798)。鉴于在脑卒中情况下迅速做出准确诊断的重要性,加上最近的临床试验和动向促进了血管内治疗方法治疗MeVOs的疗效,因此在成像上准确、快速地检测此类闭塞仍是当务之急。为此,我们介绍了 CTA 头部检查矢状位重新格式化图像上 Sylvian 三角区的五种成像模式,我们利用这些模式来评估 M2 和 M3 分部的通畅性。这种方法可快速部署,放射科和非放射科医疗服务提供者均可使用,从而有助于快速准确地诊断 MeVO,及时评估血管内治疗的候选资格,并最终支持缩短介入时间和成功的患者预后。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying the Sylvian Triangle on CT angiography: A technique for detecting distal middle cerebral artery occlusions.

Medium vessel occlusions (MeVOs), defined as occlusion of the M2/M3 and A2/A3 segments of the middle cerebral artery (MCA) and anterior cerebral artery, can be challenging to visualize on CT angiography (CTA) and MR angiography (MRA), given the anatomic complexity of the mid- and distal intracranial vasculature and smaller vessel caliber (Leary MC, Kidwell CS, Villablanca JP, et al. Validation of computed tomographic MCA "dot" sign: an angiographic correlation study. Stroke 2003; 34: 2636-2640; Luijten SPR, Wolff L, Duvekot MHC, et al. Diagnostic performance of an algorithm for automated large vessel occlusion (LVO) detection on CTA. J Neurointerv Surg 2022; 14: 794-798). In turn, the appearance of a sudden vessel cutoff in these vascular distributions on CTA or MRA is not always straightforward and may represent true occlusion, variant anatomy, and/or artifact (Leary MC, Kidwell CS, Villablanca JP, et al. Validation of computed tomographic MCA "dot" sign: an angiographic correlation study. Stroke 2003; 34: 2636-2640; Luijten SPR, Wolff L, Duvekot MHC, et al. Diagnostic performance of an algorithm for automated LVO detection on CTA. J Neurointerv Surg 2022; 14: 794-798). Given the importance of rapidly establishing an accurate diagnosis in the setting of stroke, combined with recent clinical trials and movements promoting the efficacy of endovascular therapeutic approaches to treat MeVOs, it remains imperative to detect such occlusions accurately and quickly on imaging. In turn, we present five imaging patterns of the Sylvian Triangle on sagittal reformatted images from CTA Head examinations, which our practice has utilized to assess patency of the M2 and M3 divisions. This approach is rapidly deployable and can be utilized by radiology and non-radiology healthcare providers alike, thus facilitating rapid and accurate diagnosis of MeVO, timely evaluation of candidacy for endovascular therapy, and ultimately supporting favorable door-to-intervention time and successful patient outcomes.

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
Interventional Neuroradiology
Interventional Neuroradiology CLINICAL NEUROLOGY-RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
CiteScore
3.60
自引率
11.80%
发文量
192
审稿时长
6-12 weeks
期刊介绍: Interventional Neuroradiology (INR) is a peer-reviewed clinical practice journal documenting the current state of interventional neuroradiology worldwide. INR publishes original clinical observations, descriptions of new techniques or procedures, case reports, and articles on the ethical and social aspects of related health care. Original research published in INR is related to the practice of interventional neuroradiology...
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信