Researchers in Germany have developed a technique, which allows them to predict the chances of success for a surgical procedure to treat epilepsy. It could prevent unnecessary surgery.
Epilepsy is a common neurological disorder. It occurs when many nerve cells fire simultaneously in the brain - leading to seizures. It affects around 50 million people in the world.
There are drugs that can help manage epilepsy, but some patients experience resistance to the treatment. For them, the only hope is surgery - the affected temporal lobe in the brain is often removed.
But the surgery doesn't always work - about a third of patients experience little or no improvement after the procedure. They face the threat of seizures for the rest of their lives.
"It affects their quality of life, it can affect their employment and their education opportunities and it can play a big part in their own life and that of their family," Louise Cousins from UK-based Epilepsy Action told DW.
Undergoing the surgical procedure presents a daunting decision for many patients. Apart from the risks associated with all surgery, epilepsy patients also have to deal with the fact that there's a 30 percent chance of the procedure failing.
Predicting surgery success
But this may soon change. Scientists from the Bonn University Hospital and the Max Planck Institute for neurological research in Cologne have come up with a technique which has enabled them to predict the success of the procedure for temporal lobe epilepsy in 9 out of 10 cases.
The system is based on machine learning algorithms, which allow computers to learn from data.
Using a computer program developed by Max Planck mathematician Delia-Lisa Feis, epilepsy specialists compared the MRI images of patients who improved following the surgical procedure and those of patients whose operations failed.
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Machine learning to help doctors predict the success of epilepsy brain surgery