FCDs are areas of the brain that have evolved abnormally and therefore cause drug-resistant epilepsy. Generally, its treatment requires surgery. But it’s challenging to spot these lesions via MRI since FCDs appear normal in MRI scans.
The team of researchers quantified cortical features from the MRI scans and employed about 300,000 locations across the brain to develop the algorithm. The next step was to train the algorithm on cases categorized by expert radiologists as having a healthy brain or having FCD. The results demonstrated that, on average, the algorithm was successful in identifying the FCD in 67 percent of cases in the cohort (538 participants).
Previous research couldn’t uncover the abnormalities in 178 of the participants, which means that radiologists had been unable to find the abnormality. The MELD algorithm, on the other hand, managed to spot the FCD in 63% of these cases.
Paving the way for the cure
This development is important, especially for detecting abnormality.
“We put an emphasis on creating an AI algorithm that was interpretable and could help doctors make decisions. Showing doctors how the MELD algorithm made its predictions was an essential part of that process,” said Mathilde Ripart, the co-first author of the study. “
“This algorithm could help to find more of these hidden lesions in children and adults with epilepsy, and enable more patients with epilepsy to be considered for brain surgery that could cure the epilepsy and improve their cognitive development,” added a co-senior author of the study, Dr. Konrad Wagstyl. “Roughly 440 children per year could benefit from epilepsy surgery in England,” he added.