Breakthrough Technology Pinpoints Seizures in Minutes

New techniques to aid in seizure diagnosis and surgical planning stand to benefit millions of epilepsy patients, but the road to progress has been slow and difficult. New research by Bin He of Carnegie Mellon University and his team, in partnership with UPMC and Harvard Medical School, presents a new network analysis technology that uses low-level resting-state electrophysiological recordings. invasive drugs to locate brain regions of seizure onset and predict seizure outcomes.

Epilepsy affects approximately 70 million people worldwide and more than 3.4 million Americans. Of those affected, about a third cannot be treated with medication alone. For these patients, surgical removal of seizure-causing tissue or neuromodulation procedures are potential treatment avenues to maintain quality of life.

In current practice, before any surgical removal of tissue, clinicians often drill holes in the skull to place recording electrodes at the top of the brain. The electrodes record electrical activity in the brain over the course of days or weeks, regardless of how long it takes for seizures to materialize, to inform where seizures are taking place. Although necessary, this practice can be time-consuming, expensive and uncomfortable for patients who must stay in hospital for days or weeks.

An alternative to the current clinical routine has been developed by He et al and recently published in Advanced sciences. Their new network analysis technique can identify seizure-initiating brain regions and predict the outcome of a patient’s seizures before surgery, using just 10 minutes of resting-state recordings without having to waiting for crises to occur.

“In a group of 27 patients, our accuracy in locating seizure-onset brain regions was 88%, which is a fascinating result,” said Bin He, professor of biomedical engineering at Carnegie Mellon University. “We use machine learning and network analysis to analyze a 10-minute resting state recording to predict where the seizure will occur. While this method is still invasive, it is to a considerably reduced, because we took the recording timeline from days or even weeks down to 10 minutes.”

He continued: “In the same group of patients, our accuracy in predicting the outcome of their seizures, or the possibility of having no more seizures after surgery, was 92%. Ultimately, this type of data could guide patients towards or away from surgery, and this is information that is not readily available today.”

The technique extracts the information flow on all the recording electrodes and makes a prediction based on the different levels of information flow. He and his colleagues found that the flow of information between non-seizure-producing tissue and seizure-initiating tissue is much greater than the reverse direction, and the noticeably greater difference in information flow leads often to a crisis-free outcome. Once implemented, this approach could have a major impact in informing clinicians and families whether a patient should pursue surgery and what the likelihood of surgical success would be.

Helping patients continues to be her motivation and primary goal. By focusing on non-invasive and minimally invasive approaches, he believes both the patient and the healthcare system can benefit.

“This research will not only provide insight into the likelihood of surgical success for people with epilepsy and their caregivers, but it will also help us understand the underlying mechanisms of seizures using a minimally invasive approach,” said Vicky. Whittemore, Ph.D., program director, National Institute of Neurological Disorders and Stroke, part of the National Institutes of Health.

Source of the story:

Material provided by College of Engineering, Carnegie Mellon University. Original written by Sara Vaccar. Note: Content may be edited for style and length.

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