In children who have had surgery to control their epilepsy, FCD is the most common cause, and in adults it is the third most common cause.
Additionally, of patients who have epilepsy that have an abnormality in the brain that cannot be found on MRI scans, FCD is the most common cause.
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Co-first author, Dr. Hannah Spitzer (Helmholtz Munich) said: “Our algorithm automatically learns to detect lesions from thousands of MRI scans of patients. It can reliably detect lesions of different types, shapes and sizes, and even many of those lesions that were previously missed by radiologists.”
Co-senior author, Dr Sophie Adler (UCL Great Ormond Street Institute of Child Health) added: “We hope that this technology will help to identify epilepsy-causing abnormalities that are currently being missed. Ultimately it could enable more people with epilepsy to have potentially curative brain surgery.”
This study on FCD detection uses the largest MRI cohort of FCDs to date, meaning it is able to detect all types of FCD.
The MELD FCD classifier tool can be run on any patient with a suspicion of having an FCD who is over the age of 3 years and has an MRI scan.
The MELD project is supported by the Rosetrees Trust.
Study limitations
Different MRI scanners were used at the 22 hospitals involved in the study around the globe, which enables the algorithm to be more robust but might also affect algorithm sensitivity and specificity.
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