Dec. 18 (UPI) — An implanted brain stimulation device may be able to predict and help prevent seizures in epileptics, according to a study published Thursday by The Lancet Neurology.
The device, called the NeuroPace RNS System, is intended to halt seizures by stimulating specific regions of the brain at the first signs of one, the researchers said.
It also can monitor and record seizure-related brain activity over many months or even years in epileptics as they go about their normal lives — data that may be able to help “forecast” seizures.
“People with epilepsy live with constant uncertainty about when the next seizure might occur, which is stressful and can limit the types of activities that are possible,” study co-author Dr. Vikram Rao told UPI Friday.
This technology “might help reduce the uncertainty associated with epilepsy by forecasting periods of times when seizures are more or less likely over horizons that allow behaviors to be modified accordingly,” said Rao, a neurologist at the University of California-San Francisco Epilepsy Center.
It also could potentially allow for tailor medications and other treatments based on seizure risk, he said.
Epilepsy is a chronic disease characterized by recurrent seizures, which are brief surges of electrical activity in the brain that can cause convulsions, hallucinations and unconsciousness.
The NeurpPace RNS is an implantable device that monitors brain activity using continuous electroencephalogram technology. Electroencephalograms, or EEGs, can measure the electrical activity in the brain to detect and avert imminent seizure, Rao said.
The U.S. Food and Drug Administration approved the device for use in epileptics in the early 2000s, and it has been implanted in about 3,000 patients nationally since then, he said.
For this study, Rao and his colleagues analyzed data collected by the device in 175 adults with drug-resistant focal epilepsy. The analysis revealed that seizures are “less random” than previously thought, according to researchers.
The technology identified weekly-to-monthly cycles of “brain irritability” that effectively predicted when study patients were nearly 10 times more likely to have a seizure with up to 80% accuracy, the researchers said.
In some patients, signs of these periods of heightened risk could be detected several days in advance. However, this elevated risk does not necessarily mean a seizure will occur.
While risk could be predicted several days in advance in 40% of study participants, others’ brain data only predicted the following day’s risk and still others didn’t exhibit the activity cycles needed for reliable predictions at all, the researchers said.
What causes a seizure to happen at a particular moment in time remains unknown, although they have been linked with certain triggers such as stress, alcohol, missed medication doses or lack of sleep.
“The fact that an existing device can provide data that is useful for seizure forecasting suggests that we may not need to wait for years of device development before bringing this technology to patients,” Rao told UPI.
“That said, seizure forecasting is not yet ready for real-world clinical applications, and much more testing in prospective trials will be required before it is widely available,” he said.