<b><i>Background:</i></b> 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. <b><i>Methods:</i></b> 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. <b><i>Results:</i></b> 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; <i>p</i> = 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; <i>p</i> < 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; <i>p</i> < 0.001). In contrast to BFR and SFR, there was a significant reduction in LSR time during that period (<i>p</i> = 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; <i>p</i> < 0.001). There was a significant improvement in LSR quality during the evaluation period (<i>p</i> = 0.035). <b><i>Conclusion:</i></b> 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.
OBJECTIVE There is an increasing interest in stereo-electroencephalography (SEEG) for invasive evaluation of insular epilepsy. The implantation of insular SEEG electrodes, however, is still challenging due to the anatomical location and complex functional segmentation in both an anteroposterior and ventrodorsal (i.e., superoinferior) direction. While the orthogonal approach (OA) is the shortest trajectory to the insula, it might insufficiently cover these networks. In contrast, the anterior approach (AOA) or posterior oblique approach (POA) has the potential for full insular coverage, with fewer electrodes bearing a risk of being more inaccurate due to the longer trajectory. Here, the authors evaluated the implantation accuracy and the detection of epilepsy-related SEEG activity with AOA and POA insular trajectories. METHODS This retrospective study evaluated the accuracy of 220 SEEG electrodes in 27 patients. Twelve patients underwent a stereotactic frame-based procedure (frame group), and 15 patients underwent a frameless robot-assisted surgery (robot group). In total, 55 insular electrodes were implanted using the AOA or POA considering the insular anteroposterior and ventrodorsal functional organization. The entry point error (EPE) and target point error (TPE) were related to the implantation technique (frame vs robot), the length of the trajectory, and the location of the target (insular vs noninsular). Finally, the spatial distribution of epilepsy-related SEEG activity within the insula is described. RESULTS There were no significant differences in EPE (mean 0.9 ± 0.6 for the nonsinsular electrodes and 1.1 ± 0.7 mm for the insular electrodes) and TPE (1.5 ± 0.8 and 1.6 ± 0.9 mm, respectively), although the length of trajectories differed significantly (34.1 ± 10.9 and 70.1 ± 9.0 mm, repsectively). There was a significantly larger EPE in the frame group than in the robot group (1.5 ± 0.6 vs 0.7 ± 0.5 mm). However, there was no group difference in the TPE (1.5 ± 0.8 vs 1.6 ± 0.8 mm). Epilepsy-related SEEG activity was detected in 42% (23/55) of the insular electrodes. Spatial distribution of this activity showed a clustering in both anteroposterior and ventrodorsal directions. In purely insular onset cases, subsequent insular lesionectomy resulted in a good seizure outcome. CONCLUSIONS The implantation of insular electrodes via the AOA or POA is safe and efficient for SEEG implantation covering both anteroposterior and ventrodorsal functional organization with few electrodes. In this series, there was no decrease in accuracy due to the longer trajectory of insular SEEG electrodes in comparison with noninsular SEEG electrodes. The results of frame-based and robot-assisted implantations were comparable.
The detection of the infiltrative growth of meningiomas into CNS tissue has been integrated into the WHO classification as a stand-alone marker for atypical meningioma. However, its prognostic impact has been questioned. Infiltrative growth can also be detected intraoperatively. The prognostic impact of the intraoperative detection of the central nervous system tissue invasion of meningiomas was analyzed and compared to the histopathological assessment. The clinical data of 1517 cases with follow-up data regarding radiographic recurrence was collected. Histopathology and operative reports were reviewed and invasive growth was seen during resection in 23.7% (n = 345) while histopathology detected it in 4.8% (n = 73). The histopathological and intraoperative assessments were compatible in 63%. The prognostic impact of histopathological and intraoperative assessment was significant in the univariate but not in the multivariate analysis. Both methods of assessment combined reached statistical significance in the multivariate analysis (p = 0.0409). A score including all independent prognostic factors divided the cohort into three prognostic subgroups with a risk of recurrence of 33.8, 64.7 and 88.5%, respectively. The intraoperative detection of the infiltrative growth of primary meningiomas into the central nervous system tissue can complement the histopathological assessment of CNS invasion. The combined assessment is an independent prognostic factor regarding tumor recurrence and allows a risk-adapted tumor stratification.
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