Prevalence of photoparoxysmal response in patients with epilepsy: Effect of the underlying syndrome and treatment status

Electroclinical Features and Long-Term Photosensitivity Outcome in Patients With Photoparoxysmal Response With Epilepsy

BACKGROUND

To investigate electroclinical phenotypes and long-term photosensitivity outcome in a large pediatric cohort of patients with epilepsy with photosensitivity.

METHODS

Patients with epilepsy with photosensitivity with four or more years of follow-up were included. Sustained terminal remission (STR) of photosensitivity (≥3.5 years) and seizure control were investigated, as well as the prognostic factors of photosensitivity. Furthermore, a cluster analysis was used to study the different subgroups of photoparoxysmal responses (PPR).

RESULTS

We included 190 individuals with a median age at diagnosis of photosensitivity of 93.1 months (interquartile range [IQR] 62.8 to 120 months) and a median follow-up duration of 68.5 months (IQR 51.8 to 84 months). STR of photosensitivity was achieved in 97 (51.1%) patients, and the mean time from age at diagnosis of photosensitivity onset to STR was 16.5 months. Age at the last follow-up (9 to 18 years [P = 0.001]), a history of photoconvulsive response (PCR) (P = 0.009), and posterior epileptiform discharges (EDs) of PPRs (P = 0.05) were significantly associated with a lower chance of entering STR according to a Cox proportional hazards model. The subgroup of generalized epilepsy syndrome exhibited 46.2% of eye closure sensitivity and 47.7% of PCR. The rates of focal epilepsy syndrome (cluster 1), generalized epilepsy syndrome (cluster 2), and unclassified epilepsy (cluster 3) were similar and not statistically different in photosensitive outcome (P = 0.527).

CONCLUSIONS

Age nine to 18 years, a history of PCR, and posterior EDs of PPRs were the adverse factors affecting photosensitivity, suggesting the effect of age-related brain changes in STR. There was no difference in the prognosis of photosensitivity in different epileptic syndromes.

Data Augmentation Effects on Highly Imbalanced EEG Datasets for Automatic Detection of Photoparoxysmal Responses

Photosensitivity is a neurological disorder in which a person's brain produces epileptic discharges, known as Photoparoxysmal Responses (PPRs), when it receives certain visual stimuli. The current standardized diagnosis process used in hospitals consists of submitting the subject to the Intermittent Photic Stimulation process and attempting to trigger these phenomena. The brain activity is measured by an Electroencephalogram (EEG), and the clinical specialists manually look for the PPRs that were provoked during the session. Due to the nature of this disorder, long EEG recordings may contain very few PPR segments, meaning that a highly imbalanced dataset is available. To tackle this problem, this research focused on applying Data Augmentation (DA) to create synthetic PPR segments from the real ones, improving the balance of the dataset and, thus, the global performance of the Machine Learning techniques applied for automatic PPR detection. K-Nearest Neighbors and a One-Hidden-Dense-Layer Neural Network were employed to evaluate the performance of this DA stage. The results showed that DA is able to improve the models, making them more robust and more able to generalize. A comparison with the results obtained from a previous experiment also showed a performance improvement of around 20% for the Accuracy and Specificity measurements without Sensitivity suffering any losses. This project is currently being carried out with subjects at Burgos University Hospital, Spain.

Virtual Reality Therapy for People With Epilepsy and Related Anxiety: Protocol for a 3-Phase Pilot Clinical Trial

BACKGROUND

Anxiety is one of the most common psychiatric comorbidities in people with epilepsy and often involves fears specifically related to the condition, such as anxiety related to the fear of having another seizure. These epilepsy- or seizure-related fears have been reported as being more disabling than the seizures themselves and significantly impact quality of life. Although research has suggested that exposure therapy (ET) is helpful in decreasing anxiety in people with epilepsy, no research to our knowledge has been conducted on ET in people with epilepsy using virtual reality (VR). The use of novel technologies such as an immersive VR head-mounted display for ET in this population offers several benefits. Indeed, using VR can increase accessibility for people with epilepsy with transportation barriers (eg, those who live outside urban centers or who have a suspended driver's license owing to their condition), among other advantages. In the present research protocol, we describe the design of an innovative VR-ET program administered in the home that focuses on decreasing anxiety in people with epilepsy, specifically anxiety related to their epilepsy or seizures.

OBJECTIVE

Our primary objective is to examine the feasibility of the study protocol and proposed treatment as well as identify suggestions for improvement when designing subsequent larger clinical trials. Our secondary objective is to evaluate whether VR-ET is effective in decreasing anxiety in a pilot study. We hypothesize that levels of anxiety in people with epilepsy will decrease from using VR-ET.

METHODS

This mixed methods study comprises 3 phases. Phase 1 involves engaging with those with lived experience through a web-based questionnaire to validate assumptions about anxiety in people with epilepsy. Phase 2 involves filming videos using a 360° camera for the VR-ET intervention (likely consisting of 3 sets of scenes, each with 3 intensity levels) based on the epilepsy- and seizure-related fears most commonly reported in the phase 1 questionnaire. Finally, phase 3 involves evaluating the at-home VR-ET intervention and study methods using a series of validated scales, as well as semistructured interviews.

RESULTS

This pilot study was funded in November 2021. Data collection for phase 1 was completed as of August 7, 2022, and had a final sample of 18 participants.

CONCLUSIONS

Our findings will add to the limited body of knowledge on anxiety in people with epilepsy and the use of VR in this population. We anticipate that the insights gained from this study will lay the foundation for a novel and accessible VR intervention for this underrecognized and undertreated comorbidity in people with epilepsy.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05296057; https://clinicaltrials.gov/ct2/show/NCT05296057.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/41523.

Visually sensitive seizures: An updated review by the Epilepsy Foundation

Light flashes, patterns, or color changes can provoke seizures in up to 1 in 4000 persons. Prevalence may be higher because of selection bias. The Epilepsy Foundation reviewed light-induced seizures in 2005. Since then, images on social media, virtual reality, three-dimensional (3D) movies, and the Internet have proliferated. Hundreds of studies have explored the mechanisms and presentations of photosensitive seizures, justifying an updated review. This literature summary derives from a nonsystematic literature review via PubMed using the terms "photosensitive" and "epilepsy." The photoparoxysmal response (PPR) is an electroencephalography (EEG) phenomenon, and photosensitive seizures (PS) are seizures provoked by visual stimulation. Photosensitivity is more common in the young and in specific forms of generalized epilepsy. PS can coexist with spontaneous seizures. PS are hereditable and linked to recently identified genes. Brain imaging usually is normal, but special studies imaging white matter tracts demonstrate abnormal connectivity. Occipital cortex and connected regions are hyperexcitable in subjects with light-provoked seizures. Mechanisms remain unclear. Video games, social media clips, occasional movies, and natural stimuli can provoke PS. Virtual reality and 3D images so far appear benign unless they contain specific provocative content, for example, flashes. Images with flashes brighter than 20 candelas/m² at 3-60 (particularly 15-20) Hz occupying at least 10 to 25% of the visual field are a risk, as are red color flashes or oscillating stripes. Equipment to assay for these characteristics is probably underutilized. Prevention of seizures includes avoiding provocative stimuli, covering one eye, wearing dark glasses, sitting at least two meters from screens, reducing contrast, and taking certain antiseizure drugs. Measurement of PPR suppression in a photosensitivity model can screen putative antiseizure drugs. Some countries regulate media to reduce risk. Visually-induced seizures remain significant public health hazards so they warrant ongoing scientific and regulatory efforts and public education.

Genetic generalized epilepsies in adults - challenging assumptions and dogmas

Genetic generalized epilepsy (GGE) syndromes start during childhood or adolescence, and four commonly persist into adulthood, making up 15-20% of all cases of epilepsy in adults. These four GGE syndromes are childhood absence epilepsy, juvenile absence epilepsy, juvenile myoclonic epilepsy and epilepsy with generalized tonic-clonic seizures alone. However, in ~20% of patients with GGE, characteristics of more than one syndrome are present. Novel insights into the genetic aetiology, comorbidities and prognosis of the GGE syndromes have emerged and challenge traditional concepts about these conditions. Evidence has shown that the mode of inheritance in GGE is mostly polygenic. Neuropsychological and imaging studies indicate similar abnormalities in unaffected relatives of patients with GGE, supporting the concept that underlying alterations in bilateral frontothalamocortical networks are genetically determined. Contrary to popular belief, first-line anti-seizure medication often fails to provide seizure freedom in combination with good tolerability. Nevertheless, long-term follow-up studies have shown that with advancing age, many patients can discontinue their anti-seizure medication without seizure relapses. Several outcome predictors have been identified, but prognosis across the syndromes is more homogeneous than previously assumed. Overall, overlap in pathophysiology, seizure types, treatment responses and outcomes support the idea that GGEs are not separate nosological entities but represent a neurobiological continuum.

Virtual reality and machine learning in the automatic photoparoxysmal response detection

Photosensitivity, in relation to epilepsy, is a genetically determined condition in which patients have epileptic seizures of different severity provoked by visual stimuli. It can be diagnosed by detecting epileptiform discharges in their electroencephalogram (EEG), known as photoparoxysmal responses (PPR). The most accepted PPR detection method—a manual method—considered as the standard one, consists in submitting the subject to intermittent photic stimulation (IPS), i.e. a flashing light stimulation at increasing and decreasing flickering frequencies in a hospital room under controlled ambient conditions, while at the same time recording her/his brain response by means of EEG signals. This research focuses on introducing virtual reality (VR) in this context, adding, to the conventional infrastructure a more flexible one that can be programmed and that will allow developing a much wider and richer set of experiments in order to detect neurological illnesses, and to study subjects’ behaviours automatically. The loop includes the subject, the VR device, the EEG infrastructure and a computer to analyse and monitor the EEG signal and, in some cases, provide feedback to the VR. As will be shown, AI modelling will be needed in the automatic detection of PPR, but it would also be used in extending the functionality of this system with more advanced features. This system is currently in study with subjects at Burgos University Hospital, Spain.