Clinical trainee performance on task-based AR/VR-guided surgical simulation is correlated with their 3D image spatial reasoning scores

IF 2.8 Q3 ENGINEERING, BIOMEDICAL
Roy Eagleson, Denis Kikinov, Liam Bilbie, Sandrine de Ribaupierre
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Abstract

This paper describes a methodology for the assessment of training simulator-based computer-assisted intervention skills on an AR/VR-guided procedure making use of CT axial slice views for a neurosurgical procedure: external ventricular drain (EVD) placement. The task requires that trainees scroll through a stack of axial slices and form a mental representation of the anatomical structures in order to subsequently target the ventricles to insert an EVD. The process of observing the 2D CT image slices in order to build a mental representation of the 3D anatomical structures is the skill being taught, along with the cognitive control of the subsequent targeting, by planned motor actions, of the EVD tip to the ventricular system to drain cerebrospinal fluid (CSF). Convergence is established towards the validity of this assessment methodology by examining two objective measures of spatial reasoning, along with one subjective expert ranking methodology, and comparing these to AR/VR guidance. These measures have two components: the speed and accuracy of the targeting, which are used to derive the performance metric. Results of these correlations are presented for a population of PGY1 residents attending the Canadian Neurosurgical “Rookie Bootcamp” in 2019.

Abstract Image

临床受训人员在基于任务的 AR/VR 导向手术模拟中的表现与其三维图像空间推理得分有关
本文介绍了一种方法,用于评估基于模拟器的计算机辅助干预技能培训,该技能是在 AR/VR 引导下,利用 CT 轴切片视图进行神经外科手术:心室外引流管(EVD)置入。这项任务要求受训者滚动浏览一叠轴向切片,形成解剖结构的心理表征,以便随后瞄准脑室插入 EVD。通过观察二维 CT 图像切片来建立三维解剖结构的心理表征是所要教授的技能,同时还要通过计划的运动动作来认知控制随后将 EVD 尖端瞄准脑室系统以引流脑脊液 (CSF)。通过研究空间推理的两种客观测量方法和一种主观专家排名方法,并将其与 AR/VR 引导进行比较,可以确定这种评估方法的有效性。这些测量方法有两个组成部分:目标定位的速度和准确性,用于得出性能指标。这些相关性的结果是针对参加 2019 年加拿大神经外科 "新手训练营 "的 PGY1 住院医师群体提出的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Healthcare Technology Letters
Healthcare Technology Letters Health Professions-Health Information Management
CiteScore
6.10
自引率
4.80%
发文量
12
审稿时长
22 weeks
期刊介绍: Healthcare Technology Letters aims to bring together an audience of biomedical and electrical engineers, physical and computer scientists, and mathematicians to enable the exchange of the latest ideas and advances through rapid online publication of original healthcare technology research. Major themes of the journal include (but are not limited to): Major technological/methodological areas: Biomedical signal processing Biomedical imaging and image processing Bioinstrumentation (sensors, wearable technologies, etc) Biomedical informatics Major application areas: Cardiovascular and respiratory systems engineering Neural engineering, neuromuscular systems Rehabilitation engineering Bio-robotics, surgical planning and biomechanics Therapeutic and diagnostic systems, devices and technologies Clinical engineering Healthcare information systems, telemedicine, mHealth.
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