Confusion and speech problems are frequent signs of seizures, but babies offer few such clues as to what ails them.
Now scientists at the Evelyn F. and William L. McKnight Brain Institute of the University of Florida report they have found a mathematical way to translate complicated brain wave readings into simple terms to help doctors and nurses more easily identify babies at risk for epilepsy.
Epilepsy describes a group of disorders that occur when bursts of electrical activity in the brain cause seizures. It strikes more than 2 million people in the United States, according to the National Institute of Neurological Diseases and Stroke. Newborn children have the highest risk of seizures, according to the National Society for Epilepsy, because of immature brain development.
But it is difficult to tell whether babies are epileptic because they are often asleep. Even when awake, they cannot provide clues through their speech, nor do abnormal movements necessarily indicate a seizure.
One way for doctors to be certain whether a newborn is having a seizure is through a diagnostic test called an electroencephalogram, or EEG, which monitors electrical activity through electrodes placed on a patient’s scalp. But the test is expensive, requires a high level of training to interpret and often isn’t readily available in hospitals.
“An EEG provides a squiggly line readout of brain activity,” said Dr. Paul Carney, chief of pediatric neurology at UF’s College of Medicine and a professor at the B.J. and Eve Wilder Center for Excellence in Epilepsy Research at the McKnight Brain Institute. “Our goal is to take our findings and develop a tool that can run in real time right next to the blood pressure and other monitoring devices in a hospital. If successful it would be one of the first brain function monitors for clinical use in the neonatal intensive care unit.”
UF researchers presenting today (5-17) at the annual meeting of the Pediatric Academic Societies in Washington, D.C., say they can convert an EEG readout into a quantitative value. For example, a reading of “20” would indicate normal brain activity and a reading of “10” would indicate a seizure.
They tested their idea by reviewing the EEGs of 35 babies up to a month old, 23 of whom had normal brain function. They were able to pinpoint the newborns at risk for seizures through differences in key statistical values of brain activity.
“An experienced pediatric neurologist and electroencephalographer could certainly distinguish abnormal from normal newborns by reviewing their EEGs,” said Deng-Shan Shiau, an assistant research neuroscientist at UF’s Brain Dynamics Laboratory. “However, from my understanding, for abnormal neonates with lower degrees of severity, abnormal EEG patterns may only be obvious in a few segments in the entire recording. Quantitative EEG analysis may help doctors quickly identify these segments and determine if a neonate is normal.”
The researchers and UF have applied for a patent for the technology. Work thus far has been funded through the American Epilepsy Society and the Epilepsy Foundation.
“Looking at electrical signaling in the newborn brain is very important,” said Dr. Gregory Holmes, chief of neurology at Dartmouth Medical School and president-elect of the American Epilepsy Society. “If there are abnormal patterns of brain activity early in life, the brain is not going to wire correctly, and that’s going to stay with these children for the rest of their lives. Detecting these patterns and intervening will be very powerful.”
