Mark A Kramer Lauren M Ostrowski Daniel Y Song Emily L Thorn Sally M Stoyell McKenna Parnes Dhinakaran Chinappen Grace Xiao Uri T Eden Kevin J Staley Steven M Stufflebeam Catherine J Chu. Scalp recorded spike ripples predict seizure risk in childhood epilepsy better than spikes. Brain, awz059, https://doi.org/10.1093/brain/awz059. Published: 25 March 2019
In the past decade, brief bursts of fast oscillations in the ripple range have been identified in the scalp EEG as a promising non-invasive biomarker for epilepsy. However, investigation and clinical application of this biomarker have been limited because standard approaches to identify these brief, low amplitude events are difficult, time consuming, and subjective. Recent studies have demonstrated that ripples co-occurring with epileptiform discharges (‘spike ripple events’) are easier to detect than ripples alone and have greater pathological significance. Here, we used objective techniques to quantify spike ripples and test whether this biomarker predicts seizure risk in childhood epilepsy. We evaluated spike ripples in scalp EEG recordings from a prospective cohort of children with a self-limited epilepsy syndrome, benign epilepsy with centrotemporal spikes, and healthy control children. We compared the rate of spike ripples between children with epilepsy and healthy controls, and between children with epilepsy during periods of active disease (active, within 1 year of seizure) and after a period of sustained seizure-freedom (seizure-free, >1 year without seizure), using semi-automated and automated detection techniques. Spike ripple rate was higher in subjects with active epilepsy compared to healthy controls (P = 0.0018) or subjects with epilepsy who were seizure-free ON or OFF medication (P = 0.0018). Among epilepsy subjects with spike ripples, each month seizure-free decreased the odds of a spike ripple by a factor of 0.66 [95% confidence interval (0.47, 0.91), P = 0.021]. Comparing the diagnostic accuracy of the presence of at least one spike ripple versus a classic spike event to identify group, we found comparable sensitivity and negative predictive value, but greater specificity and positive predictive value of spike ripples compared to spikes (P = 0.016 and P = 0.006, respectively). We found qualitatively consistent results using a fully automated spike ripple detector, including comparison with an automated spike detector. We conclude that scalp spike ripple events identify disease and track with seizure risk in this epilepsy population, using both semi-automated and fully automated detection methods, and that this biomarker outperforms analysis of spikes alone in categorizing seizure risk. These data provide evidence that spike ripples are a specific non-invasive biomarker for seizure risk in benign epilepsy with centrotemporal spikes and support future work to evaluate the utility of this biomarker to guide medication trials and tapers in these children and predict seizure risk in other at-risk populations.
"This biomarker outperforms analysis of spikes alone in categorizing seizure risk," Dr. Catherine J. Chu of Massachusetts General Hospital and Harvard University in Boston and colleagues conclude. "These data provide evidence that spike ripples are a specific non-invasive biomarker for seizure risk in benign epilepsy with centrotemporal spikes (BECTS)."
The team prospectively evaluated spike ripples in scalp electroencephalography (EEG) recordings from 21 children between 5 and 17 years of age with BECTS and 13 healthy controls between 9 and 14 years of age, at one medical center. Children without both a history of focal motor or generalized seizures and an EEG showing sleep-activated centrotemporal spikes were excluded from the study…
Dr. Ahmed T. Abdelmoity, director of the division of child neurology at Children's Mercy Kansas City in Missouri, told Reuters Health by email, "BECTS sometimes poses a challenge in the neurology clinic as most patients have a benign course and will not require treatment; however about 10% to 15% will require treatment and sometimes might develop a drug-resistant form of epilepsy."
Dr. Abdelmoity, who was not involved in the study, noted that "accuracy in predicting patients who might require treatment through EEG and initiating treatment earlier are important, to help prevent seizures and reduce family anxiety."
"These findings bring clarity, with the knowledge that patients with BECTS can have different outcomes," he added. "They also explain some of the neurophysiology of those outcomes."
The researchers recommend further related studies to investigate using this biomarker to guide medication and predict seizure risk.