Azarnoush Hamed, Alzhrani Gmaan, Winkler-Schwartz Alexander, Alotaibi Fahad, Gelinas-Phaneuf Nicholas, Pazos Valérie, Choudhury Nusrat, Fares Jawad, DiRaddo Robert, Del Maestro Rolando F
Neurosurgical Simulation Research Center, Department of Neurosurgery and Neurology, 2nd Floor, Montreal Neurological Institute and Hospital, McGill University, 3801 University, Suite W201, Montreal, QC, H3A 2B4, Canada,
Int J Comput Assist Radiol Surg. 2015 May;10(5):603-18. doi: 10.1007/s11548-014-1091-z. Epub 2014 Jun 27.
Virtual reality simulator technology together with novel metrics could advance our understanding of expert neurosurgical performance and modify and improve resident training and assessment. This pilot study introduces innovative metrics that can be measured by the state-of-the-art simulator to assess performance. Such metrics cannot be measured in an operating room and have not been used previously to assess performance.
Three sets of performance metrics were assessed utilizing the NeuroTouch platform in six scenarios with simulated brain tumors having different visual and tactile characteristics. Tier 1 metrics included percentage of brain tumor resected and volume of simulated "normal" brain tissue removed. Tier 2 metrics included instrument tip path length, time taken to resect the brain tumor, pedal activation frequency, and sum of applied forces. Tier 3 metrics included sum of forces applied to different tumor regions and the force bandwidth derived from the force histogram.
The results outlined are from a novice resident in the second year of training and an expert neurosurgeon. The three tiers of metrics obtained from the NeuroTouch simulator do encompass the wide variability of technical performance observed during novice/expert resections of simulated brain tumors and can be employed to quantify the safety, quality, and efficiency of technical performance during simulated brain tumor resection. Tier 3 metrics derived from force pyramids and force histograms may be particularly useful in assessing simulated brain tumor resections.
Our pilot study demonstrates that the safety, quality, and efficiency of novice and expert operators can be measured using metrics derived from the NeuroTouch platform, helping to understand how specific operator performance is dependent on both psychomotor ability and cognitive input during multiple virtual reality brain tumor resections.
虚拟现实模拟器技术与新颖的指标相结合，能够增进我们对神经外科专家手术表现的理解，并改进住院医师培训与评估。这项初步研究引入了可通过先进模拟器测量的创新指标来评估手术表现。此类指标无法在手术室中测量，且此前未用于评估手术表现。
利用NeuroTouch平台，在六个模拟具有不同视觉和触觉特征的脑肿瘤场景中评估三组手术表现指标。一级指标包括切除的脑肿瘤百分比以及切除的模拟“正常”脑组织体积。二级指标包括器械尖端路径长度、切除脑肿瘤所需时间、踏板激活频率以及施加力的总和。三级指标包括施加于不同肿瘤区域的力的总和以及从力直方图得出的力带宽。
所概述的结果来自一名处于培训第二年的新手住院医师和一名神经外科专家。从NeuroTouch模拟器获得的这三级指标确实涵盖了在模拟脑肿瘤的新手/专家切除过程中观察到的技术表现的广泛变异性，并且可用于量化模拟脑肿瘤切除过程中技术表现 的安全性、质量和效率。从力金字塔和力直方图得出的三级指标在评估模拟脑肿瘤切除时可能特别有用。
我们的初步研究表明，新手和专家操作者的安全性、质量和效率可以使用从NeuroTouch平台得出的指标来衡量，这有助于理解在多次虚拟现实脑肿瘤切除过程中，特定操作者的表现如何既依赖于心理运动能力又依赖于认知输入。
