1Department of Neurosurgery, University Hospital of Basel.
2Faculty of Medicine and.
Neurosurg Focus. 2021 Aug;51(2):E18. doi: 10.3171/2021.5.FOCUS21212.
Performing aneurysmal clipping requires years of training to successfully understand the 3D neurovascular anatomy. This training has traditionally been obtained by learning through observation. Currently, with fewer operative aneurysm clippings, stricter work-hour regulations, and increased patient safety concerns, novel teaching methods are required for young neurosurgeons. Virtual-reality (VR) models offer the opportunity to either train a specific surgical skill or prepare for an individual surgery. With this study, the authors aimed to compare the spatial orientation between traditional 2D images and 3D VR models in neurosurgical residents or medical students.
Residents and students were each randomly assigned to describe 4 aneurysm cases, which could be either 2D images or 3D VR models. The time to aneurysm detection as well as a spatial anatomical description was assessed via an online questionnaire and compared between the groups. The aneurysm cases were 10 selected patient cases treated at the authors' institution.
Overall, the time to aneurysm detection was shorter in the 3D VR model compared to 2D images, with a trend toward statistical significance (25.77 ± 37.26 vs 45.70 ± 51.94 seconds, p = 0.052). No significant difference was observed for residents (3D VR 24.47 ± 40.16 vs 2D 33.52 ± 56.06 seconds, p = 0.564), while in students a significantly shorter time to aneurysm detection was measured using 3D VR models (26.95 ± 35.39 vs 59.16 ± 44.60 seconds, p = 0.015). No significant differences between the modalities for anatomical and descriptive spatial mistakes were observed. Most participants (90%) preferred the 3D VR models for aneurysm detection and description, and only 1 participant (5%) described VR-related side effects such as dizziness or nausea.
VR platforms facilitate aneurysm recognition and understanding of its spatial anatomy, which could make them the preferred method compared to 2D images in the years to come.
成功理解 3D 神经血管解剖结构需要多年的培训才能进行动脉瘤夹闭手术。这种培训传统上是通过观察来获得的。目前,由于手术夹闭的动脉瘤数量减少、更严格的工作时间规定以及对患者安全的担忧增加,需要为年轻的神经外科医生寻找新的教学方法。虚拟现实 (VR) 模型提供了培训特定手术技能或为特定手术做准备的机会。通过这项研究,作者旨在比较神经外科住院医师或医学生在传统 2D 图像和 3D VR 模型之间的空间定位。
住院医师和学生均被随机分配描述 4 个动脉瘤病例,这些病例可以是 2D 图像或 3D VR 模型。通过在线问卷评估检测到动脉瘤的时间以及空间解剖描述,并比较两组之间的差异。这些动脉瘤病例是作者所在机构治疗的 10 个患者病例。
总体而言,与 2D 图像相比,3D VR 模型检测到动脉瘤的时间更短,尽管趋势具有统计学意义(25.77±37.26 与 45.70±51.94 秒,p=0.052)。住院医师之间未观察到显著差异(3D VR 为 24.47±40.16 秒,2D 为 33.52±56.06 秒,p=0.564),而在学生中,使用 3D VR 模型检测到动脉瘤的时间明显更短(26.95±35.39 与 59.16±44.60 秒,p=0.015)。在解剖和描述性空间错误方面,两种模式之间未观察到显著差异。大多数参与者(90%)更喜欢使用 3D VR 模型来检测和描述动脉瘤,只有 1 名参与者(5%)描述了与 VR 相关的副作用,如头晕或恶心。
VR 平台有助于识别动脉瘤并理解其空间解剖结构,与未来相比,这可能使其成为比 2D 图像更受欢迎的方法。