Standard work tools for dynamic stereoelectroencephalography using ROSA: naming convention and perioperative planning

Accuracy of Depth Electrodes is Not Time-Dependent in Robot-Assisted Stereoelectroencephalography in a Pediatric Population

BACKGROUND AND OBJECTIVES

Robot-assisted stereoelectroencephalography (sEEG) is steadily supplanting traditional frameless and frame-based modalities for minimally invasive depth electrode placement in epilepsy workup. Accuracy rates similar to gold-standard frame-based techniques have been achieved, with improved operative efficiency. Limitations in cranial fixation and placement of trajectories in pediatric patients are believed to contribute to a time-dependent accumulation of stereotactic error. Thus, we aim to study the impact of time as a marker of cumulative stereotactic error during robotic sEEG.

METHODS

All patients between October 2018 and June 2022 who underwent robotic sEEG were included. Radial errors at entry and target points as well as depth and Euclidean distance errors were collected for each electrode, excluding those with errors over 10 mm. Target point errors were standardized by planned trajectory length. ANOVA and error rates over time were analyzed using GraphPad Prism 9.

RESULTS

Forty-four patients met inclusion criteria for a total of 539 trajectories. Number of electrodes placed ranged from 6 to 22. Average root mean squared error was 0.45 ± 0.12 mm. Average entry, target, depth, and Euclidean distance errors were 1.12 ± 0.41 mm, 1.46 ± 0.44 mm, -1.06 ± 1.43 mm, and 3.01 ± 0.71 mm, respectively. There was no significant increased error with each sequential electrode placed (entry error P -value = .54, target error P -value = .13, depth error P -value = .22, Euclidean distance P -value = .27).

CONCLUSION

No decremental accuracy over time was observed. This may be secondary to our workflow which prioritizes oblique and longer trajectories first and then into less error-prone trajectories. Further study on the effect of level of training may reveal a novel difference in error rates.

A Method of Intraoperative Registration Verification to Prevent Accuracy Errors in Robot-Assisted Stereotactic Electroencephalography Electrode Placement

BACKGROUND

Robotic-assisted stereotactic electroencephalography (sEEG) electrode placement is increasingly common at specialized epilepsy centers. High accuracy and low complication rates are essential to realizing the benefits of sEEG surgery. The aim of this study was to describe for the first time in the literature a method for a stereotactic registration checkpoint to verify intraoperative accuracy during robotic-assisted sEEG and to report our institutional experience with this technique.

METHODS

All cases performed with this technique since the adoption of robotic-assisted sEEG at our institution were retrospectively reviewed.

RESULTS

In 4 of 111 consecutive sEEG operations, use of the checkpoint detected an intraoperative registration error, which was addressed before completion of sEEG electrode placement.

CONCLUSIONS

The use of a registration checkpoint in robotic-assisted sEEG surgery is a simple technique that can prevent electrode misplacement and improve the safety profile of this procedure.

Advances in human intracranial electroencephalography research, guidelines and good practices

Since the second-half of the twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into the human brain. At the interface between fundamental research and the clinic, iEEG provides both high temporal resolution and high spatial specificity but comes with constraints, such as the individual's tailored sparsity of electrode sampling. Over the years, researchers in neuroscience developed their practices to make the most of the iEEG approach. Here we offer a critical review of iEEG research practices in a didactic framework for newcomers, as well addressing issues encountered by proficient researchers. The scope is threefold: (i) review common practices in iEEG research, (ii) suggest potential guidelines for working with iEEG data and answer frequently asked questions based on the most widespread practices, and (iii) based on current neurophysiological knowledge and methodologies, pave the way to good practice standards in iEEG research. The organization of this paper follows the steps of iEEG data processing. The first section contextualizes iEEG data collection. The second section focuses on localization of intracranial electrodes. The third section highlights the main pre-processing steps. The fourth section presents iEEG signal analysis methods. The fifth section discusses statistical approaches. The sixth section draws some unique perspectives on iEEG research. Finally, to ensure a consistent nomenclature throughout the manuscript and to align with other guidelines, e.g., Brain Imaging Data Structure (BIDS) and the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), we provide a glossary to disambiguate terms related to iEEG research.