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Clinical experiences and learning curves from robot-assisted neurosurgical biopsies with Stealth Autoguide™.
- Source :
-
Neuro-oncology advances [Neurooncol Adv] 2024 May 14; Vol. 6 (1), pp. vdae079. Date of Electronic Publication: 2024 May 14 (Print Publication: 2024). - Publication Year :
- 2024
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Abstract
- Background: Biopsies of intracranial lesions are a cornerstone in the diagnosis of unresectable tumors to guide neurooncological treatment; however, the procedure is also associated with risks. The results from the cranial robot guidance system Stealth Autoguide™ were studied after introduction at a neurosurgical department. Primary aims include the presentation of clinical and radiological data, accuracy of radiological diagnosis, learning curves of the new technology, diagnostic yield, and precision. The secondary aim was to study complications.<br />Methods: Retrospective data inclusion was performed on patients ≥ 18 years undergoing biopsy with Stealth Autoguide™ due to suspected brain tumors in the first 3 years after the introduction of the technique. Data regarding clinical characteristics, intraoperative variables, pathological diagnosis, and complications were recorded. Analyses of learning curves were performed.<br />Results: A total of 79 procedures were performed on 78 patients with a mean age of 62 years (SD 12.7, range 23-82), 30.8% were female. Tumors were often multifocal (63.3%) and supratentorial (89.9%). The diagnostic yield was 87.3%. The first-hand radiological diagnosis was correct in 62.0%. A slight decrease in operation time was observed, although not significant. The surgeon contributed to 12% of the variability.<br />Conclusions: Robot-assisted biopsies with Stealth Autoguide™ seem to be comparable, with regards to complications, to frame-based and other frameless neurosurgical biopsies. Learning curves demonstrated no statistical differences in time of surgery and only 12% surgeon-related variation (ie, variation caused by the change of performing surgeon), suggesting a successful implementation of this technical adjunct.<br />Competing Interests: Johan Ljungqvist: None. Hanna Barchéus: None. Fatima Abbas: None. Anneli Ozanne: None. Daniel Nilsson: None.<br /> (© The Author(s) 2024. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)
Details
- Language :
- English
- ISSN :
- 2632-2498
- Volume :
- 6
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Neuro-oncology advances
- Publication Type :
- Academic Journal
- Accession number :
- 38845693
- Full Text :
- https://doi.org/10.1093/noajnl/vdae079