MELD Graph, a context-aware graph neural network, could drastically change the care for 30,000 patients in the UK and four million worldwide with one cause of epilepsy, the researchers said.
The study, published in JAMA Neurology by a team at King’s College London and University College London (UCL), shows how the tool significantly improves the detection of focal cortical dysplasia’s (FCDs), which is a leading cause of epilepsy.
The researchers said the tool will accelerate diagnosis times, get patients the surgical treatment they need quicker, and reduce costs to the NHS by up to £55,000 per patient.
In the UK, 1 in 100 people are affected by epilepsy. 1 in 5 people with epilepsy have seizures caused by a structural abnormality, or lesion, in the brain.
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FCDs are a common structural cause of epilepsy and difficult to control with medications, but surgery to remove the lesion can be effective. However, FCDs can be subtle and difficult to see with the human eye and up to half of these lesions are missed by radiologists.
In the study, the researchers pooled MRI data from 1185 participants – including 703 people with FCD and 482 controls - from 23 global epilepsy centres in the Multicentre Epilepsy Lesion Detection project (MELD). Half of the dataset is from children. They then trained MELD Graph on the scans to detect these subtle brain abnormalities that might otherwise go undetected.
In a statement, project lead-author, Dr Konrad Wagstyl, from King’s College London, said: “Radiologists are currently inundated with images they have to review. Using an AI-powered tool like MELD Graph can support them with their decisions, making the NHS more efficient, speeding time to treatment for patients and relieving them of unnecessary and costly tests and procedures.”
Co-author Dr Luca Palma, from Bambino Gesù Children's Hospital, Italy, said: “MELD Graph identified a subtle lesion missed by many radiologists in a 12-year-old boy who had daily seizures and had tried nine anti-seizure medications with no improvement to his condition. This tool could identify patients with surgically operable epilepsy and help with surgical planning – reducing risks, saving money, improving outcomes.”
While the tool is not yet clinically available, the research team have released the AI-tool as an open-source software. They are running workshops to train clinicians and researchers globally, including London’s Great Ormond Street Hospital and the Cleveland Clinic, in how to use it.
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