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Artificial intelligence algorithm finds “needle in a haystack” brain abnormalities on MRI

Some patients with epilepsy that is not controlled with medications have brain abnormalities that are missed on MRI scans. These patients can have probes inserted into their brain to find the abnormality. A recent study co-authored by Konrad Wagstyl (Computational Anatomy Team) and Sophie Adler finds that their artificial intelligence (AI) algorithm can find some of these hidden MRI abnormalities without the need for invasive procedures. They are now running a clinical trial testing the use of this algorithm to plan epilepsy surgeries.

Epilepsy is not just one condition, but a group of many different ‘epilepsies’ with one thing in common: a tendency to have seizures that start in the brain. Anyone can develop epilepsy, at any time of life. It happens in people of all ages, races, and social classes. Epilepsy is most commonly diagnosed in children and in people over 65. Around 1 in 100 people are diagnosed with epilepsy in the UK. The patients in this study had a type of epilepsy caused by a brain abnormality present from birth.

Epilepsy surgery is a procedure that removes or alters an area of the brain where seizures originate. Epilepsy surgery is most effective when seizures always originate in a single location in the brain. In children with a single seizure location, like in this study, surgery can offer seizure freedom in approximately 70%. However, in some patients the brain abnormality is not found on MRI scans and the patients require probes to be inserted to help find it.

In this study researchers used deep learning to train an algorithm to detect these brain abnormalities. The algorithm was then tested on patients with severe epilepsy who despite extensive investigations, the location of the abnormality was not clear. The algorithm successfully detected 86% of the focal cortical dysplasias, a type of isolated brain abnormality known to cause epilepsy.

The researchers are now running a clinical trial where they aim to help neurosurgeons plan brain implantations with the algorithm. They are also running an international collaborative study, the Multi-centre Epilepsy Lesion Detection project (MELD) with epilepsy centres from around the world, training and testing the algorithm on patients from the collaborating hospitals.


The full paper titled “Planning stereoelectroencephalography using automated lesion detection: Retrospective feasibility study” can be read in Epilepsia here.