Augmented reality navigation in external ventricular drain insertion—a systematic review and meta-analysis

Author:

Buwaider AliORCID,El-Hajj Victor GabrielORCID,Iop AlessandroORCID,Romero MarioORCID,C Jean WalterORCID,Edström ErikORCID,Elmi-Terander AdrianORCID

Abstract

AbstractExternal ventricular drain (EVD) insertion using the freehand technique is often associated with misplacements resulting in unfavorable outcomes. Augmented Reality (AR) has been increasingly used to complement conventional neuronavigation. The accuracy of AR guided EVD insertion has been investigated in several studies, on anthropomorphic phantoms, cadavers, and patients. This review aimed to assess the current knowledge and discuss potential benefits and challenges associated with AR guidance in EVD insertion. MEDLINE, EMBASE, and Web of Science were searched from inception to August 2023 for studies evaluating the accuracy of AR guidance for EVD insertion. Studies were screened for eligibility and accuracy data was extracted. The risk of bias was assessed using the Cochrane Risk of Bias Tool and the quality of evidence was assessed using the Newcastle-Ottawa-Scale. Accuracy was reported either as the average deviation from target or according to the Kakarla grading system. Of the 497 studies retrieved, 14 were included for analysis. All included studies were prospectively designed. Insertions were performed on anthropomorphic phantoms, cadavers, or patients, using several different AR devices and interfaces. Deviation from target ranged between 0.7 and 11.9 mm. Accuracy according to the Kakarla grading scale ranged between 82 and 96%. Accuracy was higher for AR compared to the freehand technique in all studies that had control groups. Current evidence demonstrates that AR is more accurate than free-hand technique for EVD insertion. However, studies are few, the technology developing, and there is a need for further studies on patients in relevant clinical settings.

Funder

Karolinska Institute

Publisher

Springer Science and Business Media LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3