Evaluation of 3D Robotic-Guided Exoscopic Visualization in Microneurosurgery.

Objective: The three-dimensional (3D) exoscope is a novel apparatus introduced in recent years. Although an operating microscope (OM) is customarily used, this novel application offers several advantages. Therefore, this study aimed to determine the feasibility of deploying a robotic-guided 3D-exoscope for microneurosurgery and gauge its subsequent performance.
Methods: The use of a 3D exoscope was compared with that of OM during 16 surgical procedures. Postoperatively, surgeons completed an eight-item Likert-scale satisfaction survey. As a second step, a predefined surgical task was then undertaken by surgeons with varying levels of experience, assessing the time entailed. Two questionnaires, the satisfaction survey and NASA task load index (NASA-TLX), were administered.
Results: During routine procedures, the exoscope proved superior in magnification and ergonomic maintenance, showing inferior image contrast, quality, and illumination. It again ranked higher in magnification and ergonomic maintenance during the suturing task, and the OM excelled in treatment satisfaction and stereoscopic orientation. Workload assessment using the NASA-TLX revealed no difference by modality in the pairwise analysis of all components. At varying levels of experience, beginners bear a significantly higher burden in all principle components than mid-level and expert participants ( p = 0.0018). Completion times for the suturing task did not differ ( p = 0.22).
Conclusion: The quality of visualization by 3D exoscope seems adequate for treatment and its ergonomic benefit is superior to that of OM. Although experienced surgeons performed a surgical simulation faster under the OM, no difference was evident in NASA-TLX surveys. The 3D exoscope is an excellent alternative to the OM.
Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
(Copyright © 2022 Keric, Krenzlin, Kurz, Wesp, Kalasauskas and Ringel.)