Time Efficiency in Stereotactic Robot-Assisted Surgery: An Appraisal of the Surgical Procedure and Surgeon's Learning Curve.
Adult
Aged
Electroencephalography
/ methods
Female
Humans
Imaging, Three-Dimensional
/ methods
Learning Curve
Male
Middle Aged
Neurosurgical Procedures
/ methods
Operative Time
Retrospective Studies
Robotic Surgical Procedures
/ methods
Stereotaxic Techniques
/ standards
Surgeons
/ education
Time Factors
Brain biopsy
Frameless stereotactic surgery
Learning curve
Registration modality
Robot-assisted surgery
Stereoelectroencephalography
Journal
Stereotactic and functional neurosurgery
ISSN: 1423-0372
Titre abrégé: Stereotact Funct Neurosurg
Pays: Switzerland
ID NLM: 8902881
Informations de publication
Date de publication:
2021
2021
Historique:
received:
24
01
2020
accepted:
11
07
2020
pubmed:
6
10
2020
medline:
14
7
2021
entrez:
5
10
2020
Statut:
ppublish
Résumé
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.
Sections du résumé
BACKGROUND
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.
METHODS
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.
RESULTS
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).
CONCLUSION
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.
Identifiants
pubmed: 33017833
pii: 000510107
doi: 10.1159/000510107
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
25-33Informations de copyright
© 2020 S. Karger AG, Basel.