Photoparoxysmal response and its characteristics in a large EEG database using the SCORE system

Photosensitivity and self-induction in patients aged 50 and older

OBJECTIVE

Photosensitivity is known to occur predominantly in children and adolescents and with a clear female predominance. Little is known on the prevalence of photosensitivity in older patients (50+) and its phenotypical appearance.

METHODS

A retrospective observational study was performed investigating the prevalence of a photoparoxysmal EEG response (PPR) on at least one EEG during the period 2015-2021. Data were gathered from patients aged 50 years and older by retrieving clinical and EEG characteristics from existing medical records. Data on photosensitivity-related symptoms in daily life were gathered with telephone interviewing.

RESULTS

In 248 patients a PPR had been elicited, of whom 16 patients (6.5%) were 50 years or older. In older patients, photosensitivity was a persistent feature of childhood-onset epilepsy (n = 8), of adult-onset epilepsy (n = 7), or an incidental finding (n = 1). In the 50+ group, 56% of photosensitive patients was female, whereas 72% in the total PPR-group. In six of 16 older patients, eye closure sensitivity was observed; two of these patients reported self-induction. Symptoms of photosensitivity in daily life were present in eight out of nine patients who consented in a telephone interview. For seven of these patients, wearing sunglasses was helpful.

SIGNIFICANCE

Female preponderance for photosensitivity was not found in epilepsy patients of 50 years and older. In 44% of the older photosensitive patients in this series, the PPR was a feature of adult-onset epilepsy. Symptoms of photosensitivity in daily life in older patients with epilepsy seem comparable to those in younger patients, and thus worthwhile to diagnose and treat them equally.

Seizure provocation in EEG recordings: A data-driven approach

OBJECTIVE

Recording seizures on video-EEG has a high diagnostic value. However, bilateral convulsive seizures constitute a risk for the patients. Our aim was to investigate the diagnostic yield and associated risks of provocation methods in short-term video-EEGs.

METHODS

We extracted data on seizures and provocation methods from a large database of short-term video-EEGs with standardized annotations using SCORE (Standardized Computer-based Organized reporting of EEG).

RESULTS

2742 paroxysmal clinical episodes were recorded in 11 919 consecutive EEGs. Most epileptic seizures (54%) were provoked. Hyperventilation provoked most of typical absence seizures (55%), intermittent photic stimulation (IPS) provoked myoclonic seizures (25%) and most of bilateral convulsive seizures (55%), while 43% of focal seizures were precipitated by sleep. All but one of the 16 bilateral convulsive seizures were provoked by IPS or sleep. Latency between start of generalized photoparoxysmal EEG response and bilateral convulsive seizures were ≤3 s in all but one patient.

SIGNIFICANCE

The large, structured database provides evidence for the diagnostic utility of various provocation methods in short-term video-EEGs. The risk of bilateral convulsive seizures is relatively small, but it cannot be prevented by stopping IPS after 3 s. A priori knowledge about seizure semiology helps planning patient-tailored provocation strategy in short-term video-EEGs.

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.

Reproductive Performance of Zi-Goose Promoted by Red Color Illumination

The color of light affects the reproductive performance of poultry, but it is not clear what efficient illumination strategy could be adopted to improve the reproductive performance of Zi-goose. Red light can increase the average weekly egg production rate, egg production, and qualified production. It can increase the serum GnRH level and decrease the serum PRL, MT, and T4 levels. In our study, red light for 12 h increased the average weekly laying rate, average qualified egg production, and hatching rate of Zi-goose eggs, and increased the serum levels of FSH, LH, P4, E2, MT, T3, and T4. Blue light at 14 h improved the average weekly egg production rate, average egg production, and average qualified egg production, and reduce serum PRL and MT levels to ensure the improvement of reproductive performance of goose. A total of 705,714 overlapping group sequences, 471,145 transcript sequences, and 268,609 single gene sequences were obtained from 18 sequencing samples, with a total length of 323.04, 668.53, and 247.88 M, respectively. About 176,416 unigenes were annotated successfully in six databases, accounting for 65.68% of the total unigenes obtained. 2,106, 2,142, and 8,892 unigenes were identified in the hypothalamus, pituitary gland, and ovary of the birds respectively, with different expressions of light regulation. The hypothalamus, ovary, and pituitary were involved in 279, 327, and 275 KEGG (Kyoto Encyclopedia of Genes and Genomes) metabolic pathways in response to light, respectively. Through further significance analysis and differential discovery rate control, a total of five metabolic pathways were obtained which were closely related to the reproductive hormones of goose. Ten candidate genes related to the reproductive performance of goslings were selected according to the identification results of differentially expressed genes of goslings under red light and white light conditions and the genes involved in metabolic pathways significantly related to the reproductive hormones of goslings. The expression levels of GnRh-1 in the hypothalamus, GnRH-R, FSH β and LH β in the pituitary gland, and FSH-R and LH-R candidate genes in the ovary were higher under the 12 h red light treatment than white light. However, the expression levels of VIP, PRL, and PRL-R candidate genes in the hypothalamus, pituitary and ovary were lower under 12 h red light than under 12 h white light.

Implementing the SCORE system improves the quality of clinical EEG reading

Objective

To assess whether implementing the freeware version of the SCORE EEG system (Standardized Computer-based Organized Reporting of EEG) leads to improvement in the quality of clinical EEG reading, and whether EEG reports in SCORE EEG are understood and accepted by the referring physicians.

Methods

We generated EEG reports in the conventional, free-text style and then using SCORE EEG, in consecutive patients referred to routine EEG. We used the Georgian translation in the SCORE EEG Free Edition. We pre-defined quality indicators consisting of a list of 24 key features that need to be addressed in EEG reports. We compared these quality indicators in free-text reports with SCORE EEG. In addition, EEG reports in SCORE EEG format were assessed by ten referring physicians, who evaluated their usability on a 7-point Likert scale.

Results

We included and evaluated EEG reports from 157 patients (80 female; age: 1-75 years; median: 28 years). Fourteen features were reported exclusively in SCORE EEG, four were reported significantly more often in SCORE EEG than in free-text format, and six features were reported equally often in SCORE EEG and in free-text format. Usability aspects of SCORE EEG were highly rated by the referring physicians (median 6-7 on the 7-point Likert scale).

Conclusions

The structured system of EEG reporting in SCORE EEG helped the experts reading clinical EEG to cover the important aspects and increase the quality of clinical EEG reports.

Significance

Implementing the freeware version of SCORE EEG in underprivileged areas will help improving management of patients with epilepsy.

Moving the field forward: detection of epileptiform abnormalities on scalp electroencephalography using deep learning—clinical application perspectives

The application of deep learning approaches for the detection of interictal epileptiform discharges is a nascent field, with most studies published in the past 5 years. Although many recent models have been published demonstrating promising results, deficiencies in descriptions of data sets, unstandardized methods, variation in performance evaluation and lack of demonstrable generalizability have made it difficult for these algorithms to be compared and progress to clinical validity. A few recent publications have provided a detailed breakdown of data sets and relevant performance metrics to exemplify the potential of deep learning in epileptiform discharge detection. This review provides an overview of the field and equips computer and data scientists with a synopsis of EEG data sets, background and epileptiform variation, model evaluation parameters and an awareness of the performance metrics of high impact and interest to the trained clinical and neuroscientist EEG end user. The gold standard and inter-rater disagreements in defining epileptiform abnormalities remain a challenge in the field, and a hierarchical proposal for epileptiform discharge labelling options is recommended. Standardized descriptions of data sets and reporting metrics are a priority. Source code-sharing and accessibility to public EEG data sets will increase the rigour, quality and progress in the field and allow validation and real-world clinical translation.

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.

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.