Newly Designed Simulator Paves Way for Patient-Specific Epilepsy Treatment

The computer model can virtually predict the recurrence of seizures and the nodes in the brain responsible for the development of seizures.

Epilepsy is a common neurological disorder affecting many people around the world. Epileptic seizures are the prominent symptom and lack of effective personalized treatment has led to its recurrence in many treated individuals.

The treatments for epilepsy include medications and to remove the nodes responsible for seizures through surgery. Even then, the chances of recurrence of seizures is very high.

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‘A computer model developed to identify the parts of a person’s brain responsible for epileptic seizures may help in designing personalized surgical procedures.’

Researchers from the Newcastle University in England have developed a simulator that can analyze the nodes in brain of epileptic patients. The computer model can virtually predict the recurrence of seizures and the nodes in the brain responsible for the development of seizures.

The software uses patients MRI scans to create a model that it can manipulate. The simulator mimics the removal of different nodes to see how they affect the activity in the rest of the network.

The researchers compared the response of targeting of commonly removed areas to those selected uniquely for each patient, showing a marked improvement in ability to fight seizures. But since this is still entirely a computer-based simulation, the researchers will have to compare the software against real patient cases to see whether it actually works.

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By simulating brain activity within each patient-specific network, they successfully identified regions that were more prone to seizures. The study is published in the Journal PLOS Computational Biology.

Researchers explained that patients tend to transit from non-epileptic to epileptic states more often than controls in the model. Regions in the left hemisphere (particularly within temporal and subcortical regions) that are known to be involved in TLE are the most frequent starting points for seizures in patients in the model. The model predicts that patient-specific surgery may lead to better outcomes than the currently used routine clinical procedure.

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Dr Peter Taylor, who co-led the study, explained: "This research may help to explain why surgery is so often unsuccessful, as this work predicts that the areas most commonly removed in surgery are not always involved in starting and spreading seizures.”

Research lead, Frances Hutchings added: “Removal of brain tissue is often the final option for treatment of temporal lobe epilepsy but we know that it is not always effective. It’s early days and there is more work to be done, but this model could assist surgeons in targeting surgical procedures more effectively and help people with epilepsy lead a more normal life.”

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Professor Marcus Kaiser, Professor of Neuroinformatics at Newcastle University, said: “The next steps are to compare the computationally predicted outcomes with the actual surgery outcomes in individual patients and to investigate how alternative surgery targets can be included in the future treatment.”

Source-Medindia