Experience in the diagnosis and treatment of non-invasive bilateral carotid cavernous sinus fistula based on CT image examination

IF 2.5 4区医学 Q3 BIOCHEMICAL RESEARCH METHODS SLAS Technology Pub Date : 2024-09-16 DOI:10.1016/j.slast.2024.100191

{"title":"Experience in the diagnosis and treatment of non-invasive bilateral carotid cavernous sinus fistula based on CT image examination","authors":"","doi":"10.1016/j.slast.2024.100191","DOIUrl":null,"url":null,"abstract":"<div><p>Carotid cavernous fistula is a rare but clinically important vascular abnormality that is challenging to diagnose and treat. The clinical data of a patient with bilateral carotid cavernous fistula diagnosed by CT images were retrospectively analyzed. Through the analysis of CT images, the patient was accurately located and the diagnosis was confirmed. CT images can provide detailed anatomical information and accurately show the location, morphology and hemodynamic characteristics of carotid cavernous fistula. Through CT image examination, we successfully diagnosed bilateral carotid cavernous fistula patients, and can provide an important reference for surgical treatment. Therefore, CT image examination can provide accurate diagnosis and surgical planning information, and provide support for the formulation of individual treatment plans for patients. The application of this method is helpful to improve the early diagnosis rate and treatment effect of carotid cavernous fistula.</p></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2472630324000736/pdfft?md5=1928739854258fac5740430b1b53f767&pid=1-s2.0-S2472630324000736-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SLAS Technology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2472630324000736","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}

引用次数: 0

Abstract

Carotid cavernous fistula is a rare but clinically important vascular abnormality that is challenging to diagnose and treat. The clinical data of a patient with bilateral carotid cavernous fistula diagnosed by CT images were retrospectively analyzed. Through the analysis of CT images, the patient was accurately located and the diagnosis was confirmed. CT images can provide detailed anatomical information and accurately show the location, morphology and hemodynamic characteristics of carotid cavernous fistula. Through CT image examination, we successfully diagnosed bilateral carotid cavernous fistula patients, and can provide an important reference for surgical treatment. Therefore, CT image examination can provide accurate diagnosis and surgical planning information, and provide support for the formulation of individual treatment plans for patients. The application of this method is helpful to improve the early diagnosis rate and treatment effect of carotid cavernous fistula.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

根据 CT 图像检查诊断和治疗无创双侧颈动脉海绵窦瘘的经验。

颈动脉海绵瘘是一种罕见但在临床上非常重要的血管异常，诊断和治疗都很困难。本文回顾性分析了一名通过 CT 图像诊断为双侧颈动脉海绵瘘患者的临床资料。通过对 CT 图像的分析，对患者进行了准确定位并确诊。CT 图像能提供详细的解剖信息，准确显示颈动脉海绵瘘的位置、形态和血流动力学特征。通过CT图像检查，我们成功确诊了双侧颈动脉海绵瘘患者，为手术治疗提供了重要参考。因此，CT 图像检查可以为患者提供准确的诊断和手术方案信息，为患者制定个性化治疗方案提供支持。该方法的应用有助于提高颈动脉海绵瘘的早期诊断率和治疗效果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

SLAS Technology Computer Science-Computer Science Applications

CiteScore

6.30

自引率

7.40%

发文量

审稿时长

106 days

期刊介绍： SLAS Technology emphasizes scientific and technical advances that enable and improve life sciences research and development; drug-delivery; diagnostics; biomedical and molecular imaging; and personalized and precision medicine. This includes high-throughput and other laboratory automation technologies; micro/nanotechnologies; analytical, separation and quantitative techniques; synthetic chemistry and biology; informatics (data analysis, statistics, bio, genomic and chemoinformatics); and more.