No change in network connectivity measurements between separate rsfMRI acquisition times.

The role of resting state functional MRI (rsfMRI) is increasing in the field of epilepsy surgery because it is possible to interpolate network connectivity patterns across the brain with a high degree of spatial resolution. Prior studies have shown that by rsfMRI with scalp electroencephalography (EEG), an epileptogenic network can be modeled and visualized with characteristic patterns of connectivity that are relevant to both seizure-related and neuropsychological outcomes after surgery. The aim of this study is to show that a 5-min acquisition time provides reproducible results related to the relevant connectivity metrics when compared to a separately acquired 5-min scan. Fourteen separate rsfMRI sessions from ten different patients were used for comparison, comprised of patients with temporal lobe epilepsy both pre- and post-operation. Results showed that there was no significant difference in any of the connectivity metrics when comparing both 5-min scans to each other. These data support the continued use of a 5-min scan for epileptogenic network modeling in future studies because the inter-scan variability is sufficiently low as not to alter the output metrics characterizing the network connectivity.

Value of smartphone videos for diagnosis of seizures: Everyone owns half an epilepsy monitoring unit.

The diagnosis of epilepsy is primarily based on the history and the verbal description of the events in question. Smartphone videos are increasingly used to assist in the diagnosis. The purpose of this study is to evaluate their value for the diagnosis of seizures. We prospectively collected smartphone videos from patients who presented to our epilepsy center over two years. The video-based diagnosis was then compared to the eventual diagnosis based on video-electroencephalographic (EEG) monitoring with recorded episodes. Video-EEG studies and smartphone videos were reviewed by two separate physicians, each blinded to the other's interpretation. Fifty-four patients were included in the final analysis (mean age = 34.7 years, SD = 17 years). Data (either smartphone video or video-EEG monitoring) were inconclusive in 18 patients. Of the 36 patients with conclusive data, 34 (94%) were in agreement. Smartphone video interpretation can be a useful adjunctive tool in the diagnosis of seizure-like events.

The Yield of Ambulatory EEG-Video Monitoring.

INTRODUCTION: The availability of ambulatory EEG-video monitoring gives an alternative to traditional inpatient EEG-video, but its yield and diagnostic value are not well known. This study evaluates the yield of ambulatory EEG-video for the diagnosis of epilepsy. METHODS: We retrospectively reviewed the ambulatory EEG-video monitoring data from 200 consecutive and unselected patients aged 12 years and older performed by a single company (RSC Diagnostic Services) between January 2018 and May 2018. Studies were processed by two senior certified long-term monitoring EEG technologists and interpreted by neurologists. RESULTS: Of the 200 patients, 130 (65%) were women, mean age was 45 years. Mean duration of studies were 76.6 hours (range 23-175 hours). There were 110 studies (55%) with events recorded and 101 (92%) were captured on video. Epileptic events accounted for 17.8% (18/101) of the events captured and 9% (18/200) of our total cohort. Nonepileptic diagnosis accounted for 38% of the total number of patients in study (76/200). CONCLUSION: Ambulatory EEG-video monitoring may be a useful alternative to inpatient epilepsy monitoring unit, particularly with high clinical suspicion for nonepileptic events.

The role of EEG in patients with suspected epilepsy.

Despite the advances in imaging, EEG remains a critical test for the diagnosis of epilepsy. Not only can it confirm the diagnosis, but it can also clarify the type of epilepsy. There are many different types of EEG recordings depending on duration, the presence of video, and inpatient or outpatient setting, each with its pros and cons. Interictal epileptiform abnormalities are very specific to epilepsy, but they can be over-interpreted by inexperienced readers. In addition to diagnosis of epilepsy, EEG also has a role in the decision to discontinue treatment in seizure-free patients, and in assessing critically ill patients for possible status epilepticus and encephalopathies. EEG reports should be relatively standardized and clear to the clinician who requested the EEG.

Surgical disconnection of epilepsy network correlates with improved outcomes.

PURPOSE: A novel software algorithm combining non-invasive EEG and resting state functional MRI data to map networks of cortex correlated to epileptogenic tissue was used to map an epilepsy network non-invasively. The relationship between epilepsy network connectivity and outcomes after surgery was investigated using this non-invasive and non-concurrent modeling algorithm. METHOD: Scalp EEG and resting state functional MRI were acquired for nineteen patients with temporal lobe epilepsy. The hypothetical irritative zone was mapped, and resting state functional MRI data was used to model regions functionally correlated with the irritative zone. Epilepsy network connectivity was measured in patient with temporal lobe epilepsy (n = 19) both pre- and post-operatively. Temporal networks were also mapped in healthy control participants (n = 6). RESULTS: Thirteen of nineteen patients (68 %) were seizure free after 20.3 ± 4.8 months. Epilepsy network connectivity within the temporal lobe was significantly higher among patients with temporal lobe epilepsy compared to the healthy control patients (p < 0.05). Disconnection of the epilepsy network was significantly higher in patients who were seizure free. Using spearman rho analyses, neuropsychological function after surgery was found to be relatively better in patients with higher degree of epilepsy network disconnection. CONCLUSIONS: The magnitude of network disconnection after surgery was strongly associated with increased rates of seizure freedom and relatively better neuropsychological measures of memory and naming function. It was shown that seizure-free outcomes and relatively improved neuropsychological function correlated with surgical disconnection of a highly synchronous epilepsy network.

Seizure Freedom After Epilepsy Surgery and Higher Baseline Cognition May Be Associated With a Negatively Correlated Epilepsy Network in Temporal Lobe Epilepsy.

Background: Brain regions positively correlated with the epileptogenic zone in patients with temporal lobe epilepsy vary in spread across the brain and in the degree of correlation to the temporal lobes, thalamus, and limbic structures, and these parameters have been associated with pre-operative cognitive impairment and seizure freedom after epilepsy surgery, but negatively correlated regions have not been as well studied. We hypothesize that connectivity within a negatively correlated epilepsy network may predict which patients with temporal lobe epilepsy will respond best to surgery. Methods: Scalp EEG and resting state functional MRI (rsfMRI) were collected from 19 patients with temporal lobe epilepsy and used to estimate the irritative zone. Using patients' rsfMRI, the negatively correlated epilepsy network was mapped by determining all the brain voxels that were negatively correlated with the voxels in the epileptogenic zone and the spread and average connectivity within the network was determined. Results: Pre-operatively, connectivity within the negatively correlated network was inversely related to the spread (diffuseness) of that network and positively associated with higher baseline verbal and logical memory. Pre-operative connectivity within the negatively correlated network was also significantly higher in patients who would go on to be seizure free. Conclusion: Patients with higher connectivity within brain regions negatively correlated with the epilepsy network had higher baseline memory function, narrower network spread, and were more likely to be seizure free after surgery.

Network connectivity separate from the hypothesized irritative zone correlates with impaired cognition and higher rates of seizure recurrence.

INTRODUCTION: Surgery remains an essential option for the treatment of medically intractable temporal lobe epilepsy (TLE). However, only 66% of patients achieve postoperative seizure freedom, perhaps attributable to an incomplete understanding of brain network alterations in surgical candidates. Here, we applied a novel network modeling algorithm and measured key characteristics of epileptic networks correlated with surgical outcomes and objective measures of cognition. METHODS: Twenty-two patients were prospectively included, and relevant demographic information was attained. Resting state functional magnetic resonance imaging (rsfMRI) and electroencephalography (EEG) data were recorded and preprocessed. Using our novel algorithm, patient-specific epileptic networks were mapped preoperatively, and geographic spread was quantified. Global functional connectivity was also determined using a volumetric functional atlas. Neuropsychological pre- and postsurgical raw and standardized scores obtained blinded to epileptic network status. Key demographic data and features of epileptic networks were then correlated with surgical outcome using Pearson's product-moment correlation. RESULTS: At an average follow-up of 18.4 months, 15/22 (68%) patients were seizure-free. Connectivity was measured globally using a functional 3D atlas. Higher mean global connectivity correlated with worse scores in preoperative neuropsychological testing of executive functioning (Ruff Figural Fluency Test [RFFT]-ER; R = 0.943, p = 0.005). A higher ratio of highly correlated connections between regions of interest (ROIs) in the hemisphere contralateral to the seizure onset correlated with impairment in executive functioning (RFFT-ER; R = 0.943, p = 0.005). Higher numbers of highly correlated connections between ROIs in the contralateral hemisphere correlated with impairment in both short- and long-term measures of verbal memory (Rey Auditory Verbal Learning Test Trials 6, 7 [RAVLT6, RAVLT7]; R = -0.650, p = 0.020, R = -0.676, p = 0.030). Epilepsy networks were modeled in each patient, and localization of the epilepsy network in the bitemporal lobes correlated with lower scores in neuropsychological tests measuring verbal learning and short-term memory (RAVLT6; R = -0.671, p = 0.024). Higher rates of seizure recurrence correlated with localization of the epilepsy network bitemporally (R = -0.542, p = 0.014), with the stronger correlation found with localization to the contralateral temporal lobe from side of surgery (R = - 0.530, p = 0.016). CONCLUSION: Increased connectivity contralateral to seizure onset and epilepsy network spread in the bitemporal lobes correlated with lower measures of executive functioning and verbal memory. Epilepsy network localization to the bitemporal lobes, in particular, the contralateral temporal lobe, is associated with higher rates of seizure recurrence. These findings may reflect network-level disruption that has infiltrated the contralateral hemisphere and the bitemporal lobes contributing to impaired cognition and relatively worse surgical outcomes. Further identification of network parameters that predict patient outcomes may aid in patient selection, resection planning, and ultimately the efficacy of epilepsy surgery.

EEG Findings in Posterior Reversible Encephalopathy Syndrome.

Introduction. Posterior reversible encephalopathy syndrome (PRES) is a relatively common cause of encephalopathy in the hospital setting, and the EEG findings have not been well described. The purpose of this study was to review the EEG findings in a series of patients with PRES. Methods. We retrospectively reviewed our electronic medical record database to identify patients who received a diagnosis of PRES at Tampa General Hospital from January 2016 to October 2017. The diagnosis of PRES was suspected on clinical presentation and confirmed by magnetic resonance imaging. We selected patients with PRES who had received at least 1 EEG. EEGs were interpreted by 2 board-certified electroencephalographers. Results. From January 2016 to October 2017, 19 patients were diagnosed with PRES at Tampa General Hospital. Of those, 10 received at least 1 EEG. Four patients were male, 6 were female. The ages ranged from 21 to 87 (mean was 47). The patients had the following clinical presentations: 5 with encephalopathy, 8 with seizures, 2 with vision changes, and 3 with headache (some patients had more than 1 symptom). EEGs findings were as follows: 3 were normal; 3 showed intermittent generalized slowing; 2 showed continuous generalized slowing; 3 showed background slowing; 1 showed background suppression; 1 showed generalized rhythmic delta activity (GRDA); 1 showed GRDA, plus spike/sharp-wave discharges; 1 showed generalized periodic discharges. The etiologies were as follows: 9 from hypertension, 1 secondary to eclampsia, 3 due to posttransplant immunosuppression, and 1 patient was undergoing chemotherapy (some were multifactorial). Conclusion. EEG findings in PRES are diverse, with no specific or even predominant pattern, based on this small sample size.

Multimodal, noninvasive seizure network mapping software: A novel tool for preoperative epilepsy evaluation.

BACKGROUND: Despite rigorous preoperative evaluation, epilepsy surgery achieves seizure freedom in only two-thirds of cases. Current preoperative evaluation does not include a detailed network analysis despite the association of network-level changes with epilepsy. OBJECTIVE: We sought to create a software algorithm to map individualized epilepsy networks by combining noninvasive electroencephalography (EEG) source localization and nonconcurrent resting state functional magnetic resonance imaging (rsfMRI). METHODS: Scalp EEG and rsfMRI data were acquired for three sample cases: one healthy control case, one case of right temporal lobe epilepsy, and one case of bitemporal seizure onset. Data from rsfMRI were preprocessed, and a time-series function was extracted. Connection coefficients were used to threshold out spurious connections and model global functional networks in a 3D map. Epileptic discharges were localized using a forward model of cortical mesh dipoles followed by an empirical Bayesian approach of inverse source reconstruction and co-registered with rsfMRI. Co-activating brain regions were mapped. RESULTS: Three illustrative sample cases are presented. In the healthy control case, the software showed symmetrical global connectivity. In the right temporal lobe epilepsy case, asymmetry was found in the global connectivity metrics with a paucity of connectivity ipsilateral to the epileptogenic cortex. The superior longitudinal fasciculus, uncinate fasciculus, and commissural fibers connecting disparate and discontinuous cortical regions involved in the epilepsy network were visualized. In the case with bitemporal lobe epilepsy, global connectivity was symmetric. It showed a network of correlating cortical activity local to epileptogenic tissue in both temporal lobes. The network involved white matter tracks in a similar pattern to those seen in the right temporal case. CONCLUSIONS: This modeling algorithm allows better definition of the global brain network and potentially demonstrates differences in connectivity between an epileptic and a non-epileptic brain. This finding may be useful for mapping cortico-cortical connections representing the putative epilepsy networks. With this methodology, we localized the epileptogenic brain and showed network asymmetry and long-distance cortical co-activation. This software tool is the first to use a multimodal, nonconcurrent, and noninvasive approach to model and visualize the epilepsy network.