It is a major challenge in clinical epilepsy to diagnose and treat a disease characterized by infrequent seizures based on patient or caregiver reports and limited duration clinical testing. The poor ...reliability of self-reported seizure diaries for many people with epilepsy is well-established, but these records remain necessary in clinical care and therapeutic studies. A number of wearable devices have emerged, which may be capable of detecting seizures, recording seizure data, and alerting caregivers. Developments in non-invasive wearable sensors to measure accelerometry, photoplethysmography (PPG), electrodermal activity (EDA), electromyography (EMG), and other signals outside of the traditional clinical environment may be able to identify seizure-related changes. Non-invasive scalp electroencephalography (EEG) and minimally invasive subscalp EEG may allow direct measurement of seizure activity. However, significant network and computational infrastructure is needed for continuous, secure transmission of data. The large volume of data acquired by these devices necessitates computer-assisted review and detection to reduce the burden on human reviewers. Furthermore, user acceptability of such devices must be a paramount consideration to ensure adherence with long-term device use. Such devices can identify tonic–clonic seizures, but identification of other seizure semiologies with non-EEG wearables is an ongoing challenge. Identification of electrographic seizures with subscalp EEG systems has recently been demonstrated over long (>6 month) durations, and this shows promise for accurate, objective seizure records. While the ability to detect and forecast seizures from ambulatory intracranial EEG is established, invasive devices may not be acceptable for many individuals with epilepsy. Recent studies show promising results for probabilistic forecasts of seizure risk from long-term wearable devices and electronic diaries of self-reported seizures. There may also be predictive value in individuals' symptoms, mood, and cognitive performance. However, seizure forecasting requires perpetual use of a device for monitoring, increasing the importance of the system's acceptability to users. Furthermore, long-term studies with concurrent EEG confirmation are lacking currently. This review describes the current evidence and challenges in the use of minimally and non-invasive devices for long-term epilepsy monitoring, the essential components in remote monitoring systems, and explores the feasibility to detect and forecast impending seizures
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long-term use of these systems.
•Statistically significant differences were found between patients with intellectual disability and normal cognition.•No statistically significant differences were found between typing statistics at ...baseline and within 15 min following a confirmed seizure.•Good adherence to the keyboard technology with 3000 sessions acrosss 6 patients.•This technology seems feasible for cognitive impairment with least patient burden.•Further research is needed to assess this technology in other epilepsy aspects.
Efficient, non-invasive monitoring may provide a more accurate and comprehensive understanding of seizure frequency and the development of some comorbidities in people with epilepsy. Novel keyboard technology measuring digital keypress statistics has demonstrated its practical value for neurodegenerative diseases including Parkinson’s Disease and Dementia. Smartphones integrated into daily life may serve as a low-burden longitudinal monitoring system for patients with epilepsy.
This study aimed to assess the feasibility of keyboard statistics as an objective measure of seizure frequency for patients with epilepsy, in addition to tracking differences between cognitively normal and cognitively impaired patients.
Six adult patients admitted to the Epilepsy Monitoring Unit (EMU) at Mayo Clinic in Rochester, Minnesota were studied. The keyboard was installed on the patient’s smartphone. In the EMU, typing statistics were correlated to electroencephalogram (EEG) confirmed seizures. After discharge, participants continued using their keyboards and kept a seizure log. We also analyzed the key press/release times and usage of participants’ keyboards for adherence.
Keyboard sessions during and after seizures assessed for key press/release differences versus baseline showed no statistically significant difference (p = 0.44). Using one-way ANOVA, cognitive impairment’s potential impact on keyboard statistics was explored in patients who had neuropsychological testing (N = 3). Significant differences were found between patients with and without cognitive impairment (p < 0.001). No significant difference was noted between patients with mild intellectual disability and normal cognitive function (p = 0.55).
Developing new tools to better understand disorders of the nervous system, with a goal to more effectively treat them, is an active area of bioelectronic medicine research. Future tools must be ...flexible and configurable, given the evolving understanding of both neuromodulation mechanisms and how to configure a system for optimal clinical outcomes. We describe a system, the Summit RC+S "neural coprocessor," that attempts to bring the capability and flexibility of a microprocessor to a prosthesis embedded within the nervous system. This paper describes the updated system architecture for the Summit RC+S system, the five custom integrated circuits required for bi-directional neural interfacing, the supporting firmware/software ecosystem, and the verification and validation activities to prepare for human implantation. Emphasis is placed on design changes motivated by experience with the CE-marked Activa PC+S research tool; specifically, enhancement of sense-stim performance for improved bi-directional communication to the nervous system, implementation of rechargeable technology to extend device longevity, and application of MICS-band telemetry for algorithm development and data management. The technology was validated in a chronic treatment paradigm for canines with naturally occurring epilepsy, including free ambulation in the home environment, which represents a typical use case for future human protocols.
Objective: This paper describes a data-analytic modeling approach for the prediction of epileptic seizures from intracranial electroencephalogram (iEEG) recording of brain activity. Even though it is ...widely accepted that statistical characteristics of iEEG signal change prior to seizures, robust seizure prediction remains a challenging problem due to subject-specific nature of data-analytic modeling. Methods: Our work emphasizes the understanding of clinical considerations important for iEEG-based seizure prediction, and proper translation of these clinical considerations into data-analytic modeling assumptions. Several design choices during preprocessing and postprocessing are considered and investigated for their effect on seizure prediction accuracy. Results: Our empirical results show that the proposed support vector machine-based seizure prediction system can achieve robust prediction of preictal and interictal iEEG segments from dogs with epilepsy. The sensitivity is about 90-100%, and the false-positive rate is about 0-0.3 times per day. The results also suggest that good prediction is subject specific (dog or human), in agreement with earlier studies. Conclusion : Good prediction performance is possible only if the training data contain sufficiently many seizure episodes, i.e., at least 5-7 seizures. Significance: The proposed system uses subject-specific modeling and unbalanced training data. This system also utilizes three different time scales during training and testing stages.
Chronic brain recordings suggest that seizure risk is not uniform, but rather varies systematically relative to daily (circadian) and multiday (multidien) cycles. Here, one human and seven dogs with ...naturally occurring epilepsy had continuous intracranial EEG (median 298 days) using novel implantable sensing and stimulation devices. Two pet dogs and the human subject received concurrent thalamic deep brain stimulation (DBS) over multiple months. All subjects had circadian and multiday cycles in the rate of interictal epileptiform spikes (IES). There was seizure phase locking to circadian and multiday IES cycles in five and seven out of eight subjects, respectively. Thalamic DBS modified circadian (all 3 subjects) and multiday (analysis limited to the human participant) IES cycles. DBS modified seizure clustering and circadian phase locking in the human subject. Multiscale cycles in brain excitability and seizure risk are features of human and canine epilepsy and are modifiable by thalamic DBS.
By crowdsourcing, via an international competition, algorithms for seizure prediction based on long-term human brain activity recordings, Kuhlmann et al. show that clinically relevant seizure ...prediction is possible in a wider range of patients than previously thought. The data and algorithms are available on epilepsyecosystem.org to support further development.
Abstract
Accurate seizure prediction will transform epilepsy management by offering warnings to patients or triggering interventions. However, state-of-the-art algorithm design relies on accessing adequate long-term data. Crowd-sourcing ecosystems leverage quality data to enable cost-effective, rapid development of predictive algorithms. A crowd-sourcing ecosystem for seizure prediction is presented involving an international competition, a follow-up held-out data evaluation, and an online platform, Epilepsyecosystem.org, for yielding further improvements in prediction performance. Crowd-sourced algorithms were obtained via the 'Melbourne-University AES-MathWorks-NIH Seizure Prediction Challenge' conducted at kaggle.com. Long-term continuous intracranial electroencephalography (iEEG) data (442 days of recordings and 211 lead seizures per patient) from prediction-resistant patients who had the lowest seizure prediction performances from the NeuroVista Seizure Advisory System clinical trial were analysed. Contestants (646 individuals in 478 teams) from around the world developed algorithms to distinguish between 10-min inter-seizure versus pre-seizure data clips. Over 10 000 algorithms were submitted. The top algorithms as determined by using the contest data were evaluated on a much larger held-out dataset. The data and top algorithms are available online for further investigation and development. The top performing contest entry scored 0.81 area under the classification curve. The performance reduced by only 6.7% on held-out data. Many other teams also showed high prediction reproducibility. Pseudo-prospective evaluation demonstrated that many algorithms, when used alone or weighted by circadian information, performed better than the benchmarks, including an average increase in sensitivity of 1.9 times the original clinical trial sensitivity for matched time in warning. These results indicate that clinically-relevant seizure prediction is possible in a wider range of patients than previously thought possible. Moreover, different algorithms performed best for different patients, supporting the use of patient-specific algorithms and long-term monitoring. The crowd-sourcing ecosystem for seizure prediction will enable further worldwide community study of the data to yield greater improvements in prediction performance by way of competition, collaboration and synergism.
10.1093/brain/awy210_video1
awy210media1
5817489051001
Synchronization of local and distributed neuronal assemblies is thought to underlie fundamental brain processes such as perception, learning, and cognition. In neurological disease, neuronal ...synchrony can be altered and in epilepsy may play an important role in the generation of seizures. Linear cross-correlation and mean phase coherence of local field potentials (LFPs) are commonly used measures of neuronal synchrony and have been studied extensively in epileptic brain. Multiple studies have reported that epileptic brain is characterized by increased neuronal synchrony except possibly prior to seizure onset when synchrony may decrease. Previous studies using intracranial electroencephalography (EEG), however, have been limited to patients with epilepsy. Here we investigate neuronal synchrony in epileptic and control brain using intracranial EEG recordings from patients with medically resistant partial epilepsy and control subjects with intractable facial pain. For both epilepsy and control patients, average LFP synchrony decreases with increasing interelectrode distance. Results in epilepsy patients show lower LFP synchrony between seizure-generating brain and other brain regions. This relative isolation of seizure-generating brain underlies the paradoxical finding that control patients without epilepsy have greater average LFP synchrony than patients with epilepsy. In conclusion, we show that in patients with focal epilepsy, the region of epileptic brain generating seizures is functionally isolated from surrounding brain regions. We further speculate that this functional isolation may contribute to spontaneous seizure generation and may represent a clinically useful electrophysiological signature for mapping epileptic brain.
IMPORTANCE A focal lesion detected by use of magnetic resonance imaging (MRI) is a favorable prognostic finding for epilepsy surgery. Patients with normal MRI findings and extratemporal lobe epilepsy ...have less favorable outcomes. Most studies investigating the outcomes of patients with normal MRI findings who underwent (nonlesional) extratemporal epilepsy surgery are confined to a highly select group of patients with limited follow-up. OBJECTIVE To evaluate noninvasive diagnostic test results and their association with excellent surgical outcomes (defined using Engel classes I-IIA of surgical outcomes) in a group of patients with medically resistant nonlesional extratemporal epilepsy. DESIGN A retrospective study. SETTING Mayo Clinic, Rochester, Minnesota. PARTICIPANTS From 1997 through 2002, we identified 85 patients with medically resistant extratemporal lobe epilepsy who had normal MRI findings. Based on a standardized presurgical evaluation and review at a multidisciplinary epilepsy surgery conference, some of these patients were selected for intracranial electroencephalographic (EEG) monitoring and epilepsy surgery. EXPOSURE Nonlesional extratemporal lobe epilepsy surgery. MAIN OUTCOMES AND MEASURES The results of noninvasive diagnostic tests and the clinical variables potentially associated with excellent surgical outcome were examined in patients with a minimum follow-up of 1 year (mean follow-up, 9 years). RESULTS Based on the noninvasive diagnostic test results, a clear hypothesis for seizure origin was possible for 47 of the 85 patients (55%), and 31 of these 47 patients (66%) proceeded to intracranial EEG monitoring. For 24 of these 31 patients undergoing long-term intracranial EEG (77%), a seizure focus was identified and surgically resected. Of these 24 patients, 9 (38%) had an excellent outcome after resective epilepsy surgery. All patients with an excellent surgical outcome had at least 10 years of follow-up. Univariate analysis showed that localized interictal epileptiform discharges on scalp EEGs were associated with an excellent surgical outcome. CONCLUSIONS AND RELEVANCE Scalp EEG was the most useful test for identifying patients with normal MRI findings and extratemporal lobe epilepsy who were likely to have excellent outcomes after epilepsy surgery. Extending outcome analysis beyond the resective surgery group to the entire group of patients who were evaluated further highlights the challenge that these patients pose. Although 9 of 24 patients undergoing resective surgery (38%) had excellent outcomes, only 9 of 31 patients undergoing intracranial EEG (29%) and only 9 of 85 patient with nonlesional extratemporal lobe epilepsy (11%) had long-term excellent outcomes.
Although it is still early in its application, laser interstitial thermal therapy (LiTT) has increasingly been employed as a surgical option for patients with mesial temporal lobe epilepsy. This ...study aimed to describe mesial temporal lobe ablation volumes and seizure outcomes following LiTT across the Mayo Clinic's 3 epilepsy surgery centers.
This was a multi-site, single-institution, retrospective review of seizure outcomes and ablation volumes following LiTT for medically intractable mesial temporal lobe epilepsy between October 2011 and October 2015. Pre-ablation and post-ablation follow-up volumes of the hippocampus were measured using FreeSurfer, and the volume of ablated tissue was also measured on intraoperative MRI using a supervised spline-based edge detection algorithm. To determine seizure outcomes, results were compared between those patients who were seizure free and those who continued to experience seizures.
There were 23 patients who underwent mesial temporal LiTT within the study period. Fifteen patients (65%) had left-sided procedures. The median follow-up was 34 months (range 12-70 months). The mean ablation volume was 6888 mm3. Median hippocampal ablation was 65%, with a median amygdala ablation of 43%. At last follow-up, 11 (48%) of these patients were seizure free. There was no correlation between ablation volume and seizure freedom (p = 0.69). There was also no correlation between percent ablation of the amygdala (p = 0.28) or hippocampus (p = 0.82) and seizure outcomes. Twelve patients underwent formal testing with computational visual fields. Visual field changes were seen in 67% of patients who underwent testing. Comparing the 5 patients with clinically noticeable visual field deficits to the rest of the cohort showed no significant difference in ablation volume between those patients with visual field deficits and those without (p = 0.94). There were 11 patients with follow-up neuropsychological testing. Within this group, verbal learning retention was 76% in the patients with left-sided procedures and 89% in those with right-sided procedures.
In this study, there was no significant correlation between the ablation volume after LiTT and seizure outcomes. Visual field deficits were common in formally tested patients, much as in patients treated with open temporal lobectomy. Further studies are required to determine the role of amygdalohippocampal ablation.
To date, the unpredictability of seizures remains a source of suffering for people with epilepsy, motivating decades of research into methods to forecast seizures. Originally, only few scientists and ...neurologists ventured into this niche endeavor, which, given the difficulty of the task, soon turned into a long and winding road. Over the past decade, however, our narrow field has seen a major acceleration, with trials of chronic electroencephalographic devices and the subsequent discovery of cyclical patterns in the occurrence of seizures. Now, a burgeoning science of seizure timing is emerging, which in turn informs best forecasting strategies for upcoming clinical trials. Although the finish line might be in view, many challenges remain to make seizure forecasting a reality. This review covers the most recent scientific, technical, and medical developments, discusses methodology in detail, and sets a number of goals for future studies.
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