Brain’s seizure onset zone (SOZ) in record time located by University of Houston biomedical engineer Nuri Ince. SOZ is the actual part of the brain that causes seizures, in patients with epilepsy. Nearly 30 percent of epilepsy patients are resistant to drug therapy, so they have the option of surgery to remove their seizure onset zones. Most of them opt in, according to assistant professor Nuri Ince, noting the improved quality of life for sufferers.
‘New method to locate seizure onset zone could save patients weeks of hospitalization and reduce complications.’Using oscillating brain waves, rather than observing seizures as they happen, Ince locates the seizure onset zone in one hour. Current treatment protocols for detecting the zone require prolonged monitoring in the hospital for up to 10 days. Ince's new method to locate the seizure onset zone, reported in Brain, A Journal of Neurology, could save patients weeks of hospitalization, reduce complications and costs associated with what has traditionally been an arduous, and often painful, procedure.
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"We observed that the high frequency oscillations in the SOZ form random, repetitive waveform patterns that identify their location," said Ince, who compares the process to a broken bike or car which makes the same sound randomly, yet repetitively. "In a car it's a sound, in a brain it's the oscillatory patterns that are almost screaming 'I am here!'"
Exploring the brain
Ince and his former graduate student, Su Liu, studied pediatric and adult brain patterns provided by collaborators at Texas Children's Hospital, Baylor College of Medicine, University of Texas MD Anderson Cancer Center, Istanbul University and University of Minnesota.
Ince developed a pipeline of machine learning algorithms to interpret the brain waves, and after two years his algorithm identified the pattern.
Critical to Ince's discovery is delineating between the high-frequency oscillations that signify the SOZ from the ones ignited by normal functioning, like movements or talking. The regions can be located very close together, and the overlap between physiological and pathological oscillations are seemingly indistinguishable. That, along with difficulties associated with visual inspection of prolonged invasive recordings, is why current detection protocol ignores the oscillations, tracking only the seizures themselves. The current method, requiring prolonged patient hospitalization, requires a patient and medical team to wait for seizures to occur to identify their onset location.