Department of Neurosurgery, Eberhardt Karls University of Tübingen, Tübingen, Germany.
Division of Functional and Restorative Neurosurgery, Department of Neurosurgery, Eberhard Karls University of Tübingen, Tübingen, Germany.
Stereotact Funct Neurosurg. 2021;99(1):25-33. doi: 10.1159/000510107. Epub 2020 Oct 5.
Frame-based stereotactic procedures are still the gold standard in neurosurgery. However, there is an increasing interest in robot-assisted technologies. Introducing these increasingly complex tools in the clinical setting raises the question about the time efficiency of the system and the essential learning curve of the surgeon.
This retrospective study enrolled a consecutive series of patients undergoing a robot-assisted procedure after first system installation at one institution. All procedures were performed by the same neurosurgeon to capture the learning curve. The objective read-out were the surgical procedure time (SPT), the skin-to-skin time, and the intraoperative registration time (IRT) after laser surface registration (LSR), bone fiducial registration (BFR), and skin fiducial registration (SFR), as well as the quality of the registration (as measured by the fiducial registration error [FRE]). The time measures were compared to those for a patient group undergoing classic frame-based stereotaxy.
In the first 7 months, we performed 31 robot-assisted surgeries (26 biopsies, 3 stereotactic electroencephalography [SEEG] implantations, and 2 endoscopic procedures). The SPT was depending on the actual type of surgery (biopsies: 85.0 ± 36.1 min; SEEG: 154.9 ± 75.9 min; endoscopy: 105.5 ± 1.1 min; p = 0.036). For the robot-assisted biopsies, there was a significant reduction in SPT within the evaluation period, reaching the level of frame-based surgeries (58.1 ± 17.9 min; p < 0.001). The IRT was depending on the applied registration method (LSR: 16.7 ± 2.3 min; BFR: 3.5 ± 1.1 min; SFR: 3.5 ± 1.6 min; p < 0.001). In contrast to BFR and SFR, there was a significant reduction in LSR time during that period (p = 0.038). The FRE differed between the applied registration methods (LSR: 0.60 ± 0.17 mm; BFR: 0.42 ± 0.15 mm; SFR: 2.17 ± 0.78 mm; p < 0.001). There was a significant improvement in LSR quality during the evaluation period (p = 0.035).
Introducing stereotactic, robot-assisted surgery in an established clinical setting initially necessitates a prolonged intraoperative preparation time. However, there is a steep learning curve during the first cases, reaching the time level of classic frame-based stereotaxy. Thus, a stereotactic robot can be integrated into daily routine within a decent period of time, thereby expanding the neurosurgeons' armamentarium, especially for procedures with multiple trajectories.
基于框架的立体定向手术仍然是神经外科的金标准。然而，人们对机器人辅助技术越来越感兴趣。在临床环境中引入这些日益复杂的工具，引发了对系统时间效率和外科医生基本学习曲线的质疑。
本回顾性研究纳入了一家机构首次安装系统后，连续接受机器人辅助手术的患者系列。所有手术均由同一位神经外科医生完成，以捕获学习曲线。客观指标为手术时间（SPT）、皮肤到皮肤时间和激光表面配准（LSR）、骨基准标记配准（BFR）和皮肤基准标记配准（SFR）后的术中配准时间（IRT），以及配准质量（以基准标记配准误差[FRE]测量）。时间测量与接受经典框架立体定向的患者组进行比较。
在前 7 个月，我们完成了 31 例机器人辅助手术（26 例活检、3 例立体定向脑电图[SEEG]植入和 2 例内镜手术）。SPT 取决于实际手术类型（活检：85.0±36.1min；SEEG：154.9±75.9min；内镜：105.5±1.1min；p=0.036）。对于机器人辅助活检，在评估期间 SPT 显著减少，达到框架手术水平（58.1±17.9min；p<0.001）。IRT 取决于应用的配准方法（LSR：16.7±2.3min；BFR：3.5±1.1min；SFR：3.5±1.6min；p<0.001）。与 BFR 和 SFR 相比，在此期间 LSR 时间显著减少（p=0.038）。应用的配准方法之间的 FRE 不同（LSR：0.60±0.17mm；BFR：0.42±0.15mm；SFR：2.17±0.78mm；p<0.001）。在评估期间，LSR 质量得到显著改善（p=0.035）。
在既定的临床环境中引入立体定向、机器人辅助手术最初需要延长术中准备时间。然而，在前几个病例中存在陡峭的学习曲线，达到经典框架立体定向的时间水平。因此，立体定向机器人可以在合理的时间内整合到日常工作中，从而扩展神经外科医生的武器库，特别是对于具有多个轨迹的手术。
