Augmented reality technology shortens aneurysm surgery learning curve for residents.

IF 1.5 4区 医学 Q3 SURGERY Computer Assisted Surgery Pub Date : 2024-12-01 Epub Date: 2024-02-05 DOI:10.1080/24699322.2024.2311940
Xinman Liu, Weiping Xiao, Yibing Yang, Yan Yan, Feng Liang
{"title":"Augmented reality technology shortens aneurysm surgery learning curve for residents.","authors":"Xinman Liu, Weiping Xiao, Yibing Yang, Yan Yan, Feng Liang","doi":"10.1080/24699322.2024.2311940","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>We aimed to prospectively investigate the benefit of using augmented reality (AR) for surgery residents learning aneurysm surgery.</p><p><strong>Materials and methods: </strong>Eight residents were included, and divided into an AR group and a control group (4 in each group). Both groups were asked to locate an aneurysm with a blue circle on the same screenshot after their viewing of surgery videos from both AR and non-AR tests. Only the AR group was allowed to inspect and manipulate an AR holographic representation of the aneurysm in AR tests. The actual location of the aneurysm was defined by a yellow circle by an attending physician after each test. Localization deviation was determined by the distance between the blue and yellow circle.</p><p><strong>Results: </strong>Localization deviation was lower in the AR group than in the control group in the last 2 tests (AR Test 2: 2.7 ± 1.0 mm vs. 5.8 ± 4.1 mm, <i>p</i> = 0.01, non-AR Test 2: 2.1 ± 0.8 mm vs. 5.9 ± 5.8 mm, <i>p</i> < 0.001). The mean deviation was lower in non-AR Test 2 as compared to non-AR Test 1 in both groups (AR: <i>p</i> < 0.001, control: <i>p</i> = 0.391). The localization deviation of the AR group decreased from 8.1 ± 3.8 mm in Test 2 to 2.7 ± 1.0 mm in AR Test 2 (<i>p</i> < 0.001).</p><p><strong>Conclusion: </strong>AR technology provides an effective and interactive way for neurosurgery training, and shortens the learning curve for residents in aneurysm surgery.</p>","PeriodicalId":56051,"journal":{"name":"Computer Assisted Surgery","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Assisted Surgery","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/24699322.2024.2311940","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/2/5 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"SURGERY","Score":null,"Total":0}
引用次数: 0

Abstract

Objectives: We aimed to prospectively investigate the benefit of using augmented reality (AR) for surgery residents learning aneurysm surgery.

Materials and methods: Eight residents were included, and divided into an AR group and a control group (4 in each group). Both groups were asked to locate an aneurysm with a blue circle on the same screenshot after their viewing of surgery videos from both AR and non-AR tests. Only the AR group was allowed to inspect and manipulate an AR holographic representation of the aneurysm in AR tests. The actual location of the aneurysm was defined by a yellow circle by an attending physician after each test. Localization deviation was determined by the distance between the blue and yellow circle.

Results: Localization deviation was lower in the AR group than in the control group in the last 2 tests (AR Test 2: 2.7 ± 1.0 mm vs. 5.8 ± 4.1 mm, p = 0.01, non-AR Test 2: 2.1 ± 0.8 mm vs. 5.9 ± 5.8 mm, p < 0.001). The mean deviation was lower in non-AR Test 2 as compared to non-AR Test 1 in both groups (AR: p < 0.001, control: p = 0.391). The localization deviation of the AR group decreased from 8.1 ± 3.8 mm in Test 2 to 2.7 ± 1.0 mm in AR Test 2 (p < 0.001).

Conclusion: AR technology provides an effective and interactive way for neurosurgery training, and shortens the learning curve for residents in aneurysm surgery.

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
增强现实技术缩短了住院医师的动脉瘤手术学习曲线。
目的我们旨在对外科住院医师学习动脉瘤手术时使用增强现实技术(AR)的益处进行前瞻性研究:8 名住院医师被分为增强现实组和对照组(每组 4 人)。两组均被要求在观看完 AR 和非 AR 测试的手术视频后,在同一截图上用蓝色圆圈定位动脉瘤。在 AR 测试中,只有 AR 组被允许检查和操作动脉瘤的 AR 全息图像。每次测试后,主治医生都会用黄圈标出动脉瘤的实际位置。定位偏差由蓝色圆圈和黄色圆圈之间的距离决定:在最后 2 次测试中,AR 组的定位偏差低于对照组(AR 测试 2:2.7 ± 1.0 mm vs. 5.8 ± 4.1 mm,p = 0.01;非 AR 测试 2:2.1 ± 0.8 mm vs. 5.9 ± 5.8 mm,p = 0.391)。AR 组的定位偏差从测试 2 中的 8.1 ± 3.8 mm 下降到 AR 测试 2 中的 2.7 ± 1.0 mm(p 结论:AR 技术提供了一种有效的互动方式:AR 技术为神经外科培训提供了一种有效的互动方式,缩短了住院医师在动脉瘤手术方面的学习曲线。
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
Computer Assisted Surgery
Computer Assisted Surgery Medicine-Surgery
CiteScore
2.30
自引率
0.00%
发文量
13
审稿时长
10 weeks
期刊介绍: omputer Assisted Surgery aims to improve patient care by advancing the utilization of computers during treatment; to evaluate the benefits and risks associated with the integration of advanced digital technologies into surgical practice; to disseminate clinical and basic research relevant to stereotactic surgery, minimal access surgery, endoscopy, and surgical robotics; to encourage interdisciplinary collaboration between engineers and physicians in developing new concepts and applications; to educate clinicians about the principles and techniques of computer assisted surgery and therapeutics; and to serve the international scientific community as a medium for the transfer of new information relating to theory, research, and practice in biomedical imaging and the surgical specialties. The scope of Computer Assisted Surgery encompasses all fields within surgery, as well as biomedical imaging and instrumentation, and digital technology employed as an adjunct to imaging in diagnosis, therapeutics, and surgery. Topics featured include frameless as well as conventional stereotactic procedures, surgery guided by intraoperative ultrasound or magnetic resonance imaging, image guided focused irradiation, robotic surgery, and any therapeutic interventions performed with the use of digital imaging technology.
期刊最新文献
Ultrasound-based 3D bone modelling in computer assisted orthopedic surgery - a review and future challenges. Augmented reality technology shortens aneurysm surgery learning curve for residents. Feasibility of proton dosimetry overriding planning CT with daily CBCT elaborated through generative artificial intelligence tools. SwinD-Net: a lightweight segmentation network for laparoscopic liver segmentation. Risk prediction and analysis of gallbladder polyps with deep neural network.
×
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