BACKGROUND: The pursuit of improved accuracy for localization and electrode implantation in deep brain stimulation (DBS) and stereoelectroencephalography (sEEG) has fostered an abundance of disparate surgical/stereotactic practices. Specific practices/technologies directly modify implantation accuracy; however, no study has described their respective influence in multivariable context. OBJECTIVE: To synthesize the known literature to statistically quantify factors affecting implantation accuracy. METHODS: A systematic review and meta-analysis was conducted to determine the inverse-variance weighted pooled mean target error (MTE) of implanted electrodes among patients undergoing DBS or sEEG. MTE was defined as Euclidean distance between planned and final electrode tip. Meta-regression identified moderators of MTE in a multivariable-adjusted model. RESULTS: A total of 37 eligible studies were identified from a search return of 2,901 potential articles (2002-2018) - 27 DBS and 10 sEEG. Random-effects pooled MTE = 1.91 mm (95% CI: 1.7-2.1) for DBS and 2.34 mm (95% CI: 2.1-2.6) for sEEG. Meta-regression identified study year, robot use, frame/frameless technique, and intraoperative electrophysiologic testing (iEPT) as significant multivariable-adjusted moderators of MTE (P < .0001, R2 = 0.63). Study year was associated with a 0.92-mm MTE reduction over the 16-yr study period (P = .0035), and robot use with a 0.79-mm decrease (P = .0019). Frameless technique was associated with a mean 0.50-mm (95% CI: 0.17-0.84) increase, and iEPT use with a 0.45-mm (95% CI: 0.10-0.80) increase in MTE. Registration method, imaging type, intraoperative imaging, target, and demographics were not significantly associated with MTE on multivariable analysis. CONCLUSION: Robot assistance for stereotactic electrode implantation is independently associated with improved accuracy and reduced target error. This remains true regardless of other procedural factors, including frame-based vs frameless technique.
BACKGROUND: The pursuit of improved accuracy for localization and electrode implantation in deep brain stimulation (DBS) and stereoelectroencephalography (sEEG) has fostered an abundance of disparate surgical/stereotactic practices. Specific practices/technologies directly modify implantation accuracy; however, no study has described their respective influence in multivariable context. OBJECTIVE: To synthesize the known literature to statistically quantify factors affecting implantation accuracy. METHODS: A systematic review and meta-analysis was conducted to determine the inverse-variance weighted pooled mean target error (MTE) of implanted electrodes among patients undergoing DBS or sEEG. MTE was defined as Euclidean distance between planned and final electrode tip. Meta-regression identified moderators of MTE in a multivariable-adjusted model. RESULTS: A total of 37 eligible studies were identified from a search return of 2,901 potential articles (2002-2018) - 27 DBS and 10 sEEG. Random-effects pooled MTE = 1.91 mm (95% CI: 1.7-2.1) for DBS and 2.34 mm (95% CI: 2.1-2.6) for sEEG. Meta-regression identified study year, robot use, frame/frameless technique, and intraoperative electrophysiologic testing (iEPT) as significant multivariable-adjusted moderators of MTE (P < .0001, R2 = 0.63). Study year was associated with a 0.92-mm MTE reduction over the 16-yr study period (P = .0035), and robot use with a 0.79-mm decrease (P = .0019). Frameless technique was associated with a mean 0.50-mm (95% CI: 0.17-0.84) increase, and iEPT use with a 0.45-mm (95% CI: 0.10-0.80) increase in MTE. Registration method, imaging type, intraoperative imaging, target, and demographics were not significantly associated with MTE on multivariable analysis. CONCLUSION: Robot assistance for stereotactic electrode implantation is independently associated with improved accuracy and reduced target error. This remains true regardless of other procedural factors, including frame-based vs frameless technique.
Authors: Sina R Potel; Sara Marceglia; Sara Meoni; Suneil K Kalia; Rubens G Cury; Elena Moro Journal: Curr Neurol Neurosci Rep Date: 2022-07-15 Impact factor: 6.030
Authors: Andrea Spyrantis; Tirza Woebbecke; Daniel Rueß; Anne Constantinescu; Andreas Gierich; Klaus Luyken; Veerle Visser-Vandewalle; Eva Herrmann; Florian Gessler; Marcus Czabanka; Harald Treuer; Maximilian Ruge; Thomas M Freiman Journal: Front Neurorobot Date: 2022-03-25 Impact factor: 3.493