Virtual stimulation of the interictal EEG network localizes the EZ as a measure of cortical excitability.

Introduction: For patients with drug-resistant epilepsy, successful localization and surgical treatment of the epileptogenic zone (EZ) can bring seizure freedom. However, surgical success rates vary widely because there are currently no clinically validated biomarkers of the EZ. Highly epileptogenic regions often display increased levels of cortical excitability, which can be probed using single-pulse electrical stimulation (SPES), where brief pulses of electrical current are delivered to brain tissue. It has been shown that high-amplitude responses to SPES can localize EZ regions, indicating a decreased threshold of excitability. However, performing extensive SPES in the epilepsy monitoring unit (EMU) is time-consuming. Thus, we built patient-specific in silico dynamical network models from interictal intracranial EEG (iEEG) to test whether virtual stimulation could reveal information about the underlying network to identify highly excitable brain regions similar to physical stimulation of the brain. Methods: We performed virtual stimulation in 69 patients that were evaluated at five centers and assessed for clinical outcome 1 year post surgery. We further investigated differences in observed SPES iEEG responses of 14 patients stratified by surgical outcome. Results: Clinically-labeled EZ cortical regions exhibited higher excitability from virtual stimulation than non-EZ regions with most significant differences in successful patients and little difference in failure patients. These trends were also observed in responses to extensive SPES performed in the EMU. Finally, when excitability was used to predict whether a channel is in the EZ or not, the classifier achieved an accuracy of 91%. Discussion: This study demonstrates how excitability determined via virtual stimulation can capture valuable information about the EZ from interictal intracranial EEG.

Robotic-Assisted Navigation for Stereotactic Neurosurgery: A Cadaveric Investigation of Accuracy, Time, and Radiation.

BACKGROUND AND OBJECTIVES: Despite frequent use, stereotactic head frames require manual coordinate calculations and manual frame settings that are associated with human error. This study examines freestanding robot-assisted navigation (RAN) as a means to reduce the drawbacks of traditional cranial stereotaxy and improve targeting accuracy. METHODS: Seven cadaveric human torsos with heads were tested with 8 anatomic coordinates selected for lead placement mirrored in each hemisphere. Right and left hemispheres of the brain were randomly assigned to either the traditional stereotactic arc-based (ARC) group or the RAN group. Both target accuracy and trajectory accuracy were measured. Procedural time and the radiation required for registration were also measured. RESULTS: The accuracy of the RAN group was significantly greater than that of the ARC group in both target (1.2 ± 0.5 mm vs 1.7 ± 1.2 mm, P = .005) and trajectory (0.9 ± 0.6 mm vs 1.3 ± 0.9 mm, P = .004) measurements. Total procedural time was also significantly faster for the RAN group than for the ARC group (44.6 ± 7.7 minutes vs 86.0 ± 12.5 minutes, P < .001). The RAN group had significantly reduced time per electrode placement (2.9 ± 0.9 minutes vs 5.8 ± 2.0 minutes, P < .001) and significantly reduced radiation during registration (1.9 ± 1.1 mGy vs 76.2 ± 5.0 mGy, P < .001) compared with the ARC group. CONCLUSION: In this cadaveric study, cranial leads were placed faster and with greater accuracy using RAN than those placed with conventional stereotactic arc-based technique. RAN also required significantly less radiation to register the specimen's coordinate system to the planned trajectories. Clinical testing should be performed to further investigate RAN for stereotactic cranial surgery.

Using pre-surgical suspicion to guide insula implantation strategy.

Rationale: Insular epilepsy can be a challenging diagnosis due to overlapping semiology and scalp EEG findings with frontal, temporal, and parietal lobe epilepsies. Stereotactic electroencephalography (sEEG) provides an opportunity to better localize seizure onset. The possibility of improved localization is balanced by implantation risk in this vascularly rich anatomic region. We review both safety and pre-implantation factors involved in insular electrode placement across four years at an academic medical center. Methods: Presurgical data, operative reports, and invasive EEG summaries were retrospectively reviewed for patients undergoing invasive epilepsy monitoring on the insula from 2016 through 2019. EEG reports were reviewed to record the presence of insula ictal and interictal involvement. We recorded which presurgical findings suggested insular involvement (insula lesion on MRI, insula changes on PET/SPECT/scalp EEG, characteristic semiology, or history of failed anterior temporal lobectomy). The likelihood of pre-sEEG insular onset was categorized as low suspicion if no presurgical findings were present ("rule out"), moderate suspicion if one finding was present, and high suspicion if two or more findings were present. Results: 76 patients received 189 insular electrodes as part of their implantation strategy for 79 surgical cases. Seven patients (8.9%) had insular ictal onset. One clinically significant complication (left hemiparesis) occurred in a patient with moderate suspicion for insular onset. There were 38 low suspicion cases, 36 moderate suspicion cases, and 5 high suspicion cases for pre-sEEG insula ictal onset. Two low suspicion (5.3%), three moderate suspicion (8.6%), and two high suspicion (40%) cases had insular ictal onset. Conclusions: The insula can safely receive sEEG. Having two or more presurgical factors indicating insular onset is a strong, albeit incomplete, predictor of insular seizure onset. Using pre-implantation clinical findings can offer clinicians predictive value for targeting the insula during invasive EEG monitoring.

Source-sink connectivity: a novel interictal EEG marker for seizure localization.

Over 15 million epilepsy patients worldwide have drug-resistant epilepsy. Successful surgery is a standard of care treatment but can only be achieved through complete resection or disconnection of the epileptogenic zone, the brain region(s) where seizures originate. Surgical success rates vary between 20% and 80%, because no clinically validated biological markers of the epileptogenic zone exist. Localizing the epileptogenic zone is a costly and time-consuming process, which often requires days to weeks of intracranial EEG (iEEG) monitoring. Clinicians visually inspect iEEG data to identify abnormal activity on individual channels occurring immediately before seizures or spikes that occur interictally (i.e. between seizures). In the end, the clinical standard mainly relies on a small proportion of the iEEG data captured to assist in epileptogenic zone localization (minutes of seizure data versus days of recordings), missing opportunities to leverage these largely ignored interictal data to better diagnose and treat patients. IEEG offers a unique opportunity to observe epileptic cortical network dynamics but waiting for seizures increases patient risks associated with invasive monitoring. In this study, we aimed to leverage interictal iEEG data by developing a new network-based interictal iEEG marker of the epileptogenic zone. We hypothesized that when a patient is not clinically seizing, it is because the epileptogenic zone is inhibited by other regions. We developed an algorithm that identifies two groups of nodes from the interictal iEEG network: those that are continuously inhibiting a set of neighbouring nodes ('sources') and the inhibited nodes themselves ('sinks'). Specifically, patient-specific dynamical network models were estimated from minutes of iEEG and their connectivity properties revealed top sources and sinks in the network, with each node being quantified by source-sink metrics. We validated the algorithm in a retrospective analysis of 65 patients. The source-sink metrics identified epileptogenic regions with 73% accuracy and clinicians agreed with the algorithm in 93% of seizure-free patients. The algorithm was further validated by using the metrics of the annotated epileptogenic zone to predict surgical outcomes. The source-sink metrics predicted outcomes with an accuracy of 79% compared to an accuracy of 43% for clinicians' predictions (surgical success rate of this dataset). In failed outcomes, we identified brain regions with high metrics that were untreated. When compared with high frequency oscillations, the most commonly proposed interictal iEEG feature for epileptogenic zone localization, source-sink metrics outperformed in predictive power (by a factor of 1.2), suggesting they may be an interictal iEEG fingerprint of the epileptogenic zone.

sEEG for expansion of a surgical epilepsy program: Safety and efficacy in 152 consecutive cases.

OBJECTIVE: Stereoelectroencephalography (sEEG) is an intracranial encephalography method of expanding use. The need for increased epilepsy surgery access has led to the consideration of sEEG adoption by new or expanding surgical epilepsy programs. Data regarding safety and efficacy are uncommon outside of high-volume, well-established centers, which may be less applicable to newer or low-volume centers. The objective of this study was to add to the sEEG outcomes in the literature from the perspective of a rapidly expanding center. METHODS: A retrospective chart review of consecutive sEEG cases from January 2016 to December 2019 was performed. Data extraction included demographic data, surgical data, and outcome data, which pertinently examined surgical method, progression to therapeutic procedure, clinically significant adverse events, and Engel outcomes. RESULTS: One hundred and fifty-two sEEG procedures were performed on 131 patients. Procedures averaged 10.5 electrodes for a total of 1603 electrodes. The majority (84%) of patients progressed to a therapeutic procedure. Six clinically significant complications occurred: three retained electrodes, two hemorrhages, and one failure to complete investigation. Only one complication resulted in a permanent deficit. Engel 1 outcome was achieved in 63.3% of patients reaching one-year follow-up after a curative procedure. SIGNIFICANCE: New or expanding epilepsy surgery centers can appropriately consider the use of sEEG. The complication rate is low and the majority of patients progress to therapeutic surgery. Procedural safety, progression to therapeutic intervention, and Engel outcomes are comparable to cohorts from long-established epilepsy surgery programs.

Atlanto-occipital dislocation.

Atlanto-occipital dislocation (AOD) is being increasingly recognized as a potentially survivable injury as a result of improved prehospital management of polytrauma patients and increased awareness of this entity, leading to earlier diagnosis and more aggressive treatment. However, despite overall improved outcomes, AOD is still associated with significant morbidity and mortality. The purpose of this paper is to review the biomechanical aspects, clinical features, radiologic criteria, and treatment strategies of AOD. Given that the diagnosis of AOD can be very challenging, a high degree of clinical suspicion is essential to ensure timely recognition and treatment, thus preventing neurological decline or death.

Extramedullary spinal ependymoma: a diagnostic challenge and review of the literature.

Of the 15 cases of intradural extramedullary ependymomas in the literature, only 3 patients were male. The authors report the fourth case to be diagnosed in a male patient and discuss the pathogenesis, presentation, and treatment of this rare form of ependymoma. These cases most commonly show a similar clinical preoperative course to that of a benign meningioma. Although most instances have been reported in females, hormonal influence may not completely explain this neoplasm's pathogenesis. Close follow-up is warranted because of potential recurrence, metastasis, and anaplastic transformation. An ependymoma should be included in the differential diagnosis of intradural extramedullary tumors.