AI Tool MELD Graph Revolutionizes Epilepsy Diagnosis by Detecting Hidden Brain Lesions

AI Can Guide Surgery For Childhood Epilepsy

THURSDAY, Feb. 27, 2024 (HealthDay News) -- Artificial intelligence (AI) might help treat childhood epilepsy by detecting brain abnormalities that are causing kids' seizures, a new study suggests. The AI tool, called MELD Graph, found 64% of brain lesions linked to epilepsy that human radiologists had previously missed, researchers report in JAMA Neurology. Surgery to remove these lesions can be an effective way to stop epileptic seizures, but they are difficult to see with the human eye, researchers said. "Many of the children I see have experienced years of seizures and investigations before we find a lesion," researcher Helen Cross, director of the University College London Great Ormand Street Institute of Child Health in the U.K., said in a news release. About 1 in 5 people with epilepsy have seizures caused by lesions in the brain, which are called focal cortical dysplasias (FCDs), researchers said in background notes. To develop the new AI, researchers pooled MRI data from nearly 1,200 people treated at 23 epilepsy centers around the world. The initiative was called the Multicenter Epilepsy Lesion Detection Project, or MELD. "The epilepsy community is searching for ways to speed up diagnosis and treatment," Cross said. "Initiatives such as MELD have the potential to rapidly identify abnormalities that can be removed and potentially cure the epilepsy." Researchers trained the AI using the half of the MRI scans, teaching it to detect subtle lesions that might otherwise be overlooked. The team then tested the AI's effectiveness on the other half of the scans. In the independent testing, the AI accurately detected 82% of known lesions that had already been successfully removed in surgeries that rendered patients seizure-free, results show. The AI also revealed another 64% of lesions that radiologists previously missed when reviewing MRI scans, researchers 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," researcher Dr. Luca de Palma, a neurologist with Bambino Gesu Children's Hospital in Rome, said in a news release. Overall, the AI accurately identified about 70% of the brain lesions in the MRIs, researchers said. There also was a fourfold reduction in false positives -- brain areas erroneously identified as seizure-causing lesions. "This tool could identify patients with surgically operable epilepsy and help with surgical planning -- reducing risks, saving money, improving outcomes," de Palma added. The tool is not yet available to doctors, but the research team has released it as open-source software. They currently are running workshops to train doctors and researchers in how to use it. More information The Epilepsy Foundation has more on epilepsy caused by abnormal brain structures.

AI to diagnose 'invisible' brain abnormalities in children with epilepsy

Scientists have developed an AI-powered tool that detects 64% of brain abnormalities linked to epilepsy that human radiologists miss. MELD Graph is an AI tool that could drastically change the care for 30,000 patients in the UK and 4 million worldwide with one cause of epilepsy, researchers say. The study, published today 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. Researchers say the tool will speed up 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 ("lesion") in the brain. FCDs are a common structural cause of epilepsy and in people with this type of epilepsy, seizures are usually not able to be controlled with medications. Surgery to remove the lesion can be an effective and safe way to stop the seizures. However, the challenge is that FCDs can be subtle and difficult to see with the human eye and up to half of these lesions are missed by radiologists. Delays to diagnosis and surgery mean more seizures, more visits to A&E, and more disruption to school, work and home life. In the study, the researchers pooled MRI data from 1185 participants -- including 703 people with FCD and 482 controls -- from 23 epilepsy centres around the world in the Multicentre Epilepsy Lesion Detection project (MELD). Half of the dataset is from children. They then trained the artificial intelligence tool, MELD Graph, on the scans to detect these subtle brain abnormalities that might otherwise go undetected. 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 around the world, including Great Ormond Street Hospital and the Cleveland Clinic, in how to use it. First author, Dr Mathilde Ripart from UCL, said "One of the highlights for me is hearing from doctors around the world, including the UK, Chile, India and France have been able to use our tools to help their own patients." Co-author Professor Helen Cross, Prince of Wales's Chair of Childhood Epilepsy, President of the International League Against Epilepsy, Consultant Epileptologist at Great Ormond Street Hospital, and Director of the UCL Great Ormond Street Institute of Child Health, OBE said: "Many of the children I see have experienced years of seizures and investigations before we find a lesion. The epilepsy community is searching for ways to speed up diagnosis and treatment. Initiatives such as MELD have the potential to rapidly identify abnormalities that can be removed and potentially cure the epilepsy." Co-lead Dr Sophie Adler from UCL said: "This type of research is only possible with international collaboration. We were privileged to work with 75 researchers and clinicians towards this common goal of "no missed epilepsy lesions worldwide." "

AI-powered tool detects invisible brain abnormalities in children with epilepsy

Scientists have developed an AI-powered tool that detects 64% of brain abnormalities linked to epilepsy that human radiologists miss. MELD Graph is an AI tool that could drastically change the care for 30,000 patients in the UK and 4 million worldwide with one cause of epilepsy, researchers say. 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 dysplasias (FCDs), which is a leading cause of epilepsy. Researchers say the tool will speed up 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, one in 100 people are affected by epilepsy. One in five people with epilepsy have seizures caused by a structural abnormality ("lesion") in the brain. FCDs are a common structural cause of epilepsy and in people with this type of epilepsy, seizures are usually not able to be controlled with medications. Surgery to remove the lesion can be an effective and safe way to stop the seizures. However, the challenge is that FCDs can be subtle and difficult to see with the human eye and up to half of these lesions are missed by radiologists. Delays to diagnosis and surgery mean more seizures, more visits to A&E, and more disruption to school, work and home life. In the study, the researchers pooled MRI data from 1,185 participants -- including 703 people with FCD and 482 controls -- from 23 epilepsy centers around the world in the Multicenter Epilepsy Lesion Detection project (MELD). Half of the dataset is from children. They then trained the artificial intelligence tool, MELD Graph, to detect these subtle brain abnormalities that might otherwise go undetected. 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, and 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 around the world, including Great Ormond Street Hospital and the Cleveland Clinic, in how to use it. First author, Dr. Mathilde Ripart from UCL, said "One of the highlights for me is hearing from doctors around the world, including the UK, Chile, India and France have been able to use our tools to help their own patients." Co-author Professor Helen Cross, Prince of Wales's Chair of Childhood Epilepsy, President of the International League Against Epilepsy, Consultant Epileptologist at Great Ormond Street Hospital, and Director of the UCL Great Ormond Street Institute of Child Health, OBE said, "Many of the children I see have experienced years of seizures and investigations before we find a lesion. "The epilepsy community is searching for ways to speed up diagnosis and treatment. Initiatives such as MELD have the potential to rapidly identify abnormalities that can be removed and potentially cure the epilepsy." Co-lead Dr. Sophie Adler from UCL said, "This type of research is only possible with international collaboration. We were privileged to work with 75 researchers and clinicians towards this common goal of 'no missed epilepsy lesions worldwide'".

AI-powered tool improves the detection of focal cortical dysplasia

King's College LondonFeb 24 2025 Scientists have developed an AI-powered tool that detects 64% of brain abnormalities linked to epilepsy that human radiologists miss. MELD Graph is an AI tool that could drastically change the care for 30,000 patients in the UK and 4 million worldwide with one cause of epilepsy, researchers say. The study, published today 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. Researchers say the tool will speed up 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 ("lesion") in the brain. FCDs are a common structural cause of epilepsy and in people with this type of epilepsy, seizures are usually not able to be controlled with medications. Surgery to remove the lesion can be an effective and safe way to stop the seizures. However, the challenge is that FCDs can be subtle and difficult to see with the human eye and up to half of these lesions are missed by radiologists. Delays to diagnosis and surgery mean more seizures, more visits to A&E, and more disruption to school, work and home life. In the study, the researchers pooled MRI data from 1185 participants - including 703 people with FCD and 482 controls - from 23 epilepsy centres around the world in the Multicentre Epilepsy Lesion Detection project (MELD). Half of the dataset is from children. They then trained the artificial intelligence tool, MELD Graph, on the scans to detect these subtle brain abnormalities that might otherwise go undetected. 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." Dr. Konrad Wagstyl, project lead-author, from King's College London 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 around the world, including Great Ormond Street Hospital and the Cleveland Clinic, in how to use it. First author, Dr. Mathilde Ripart from UCL, said "One of the highlights for me is hearing from doctors around the world, including the UK, Chile, India and France have been able to use our tools to help their own patients." Co-author Professor Helen Cross, Prince of Wales's Chair of Childhood Epilepsy, President of the International League Against Epilepsy, Consultant Epileptologist at Great Ormond Street Hospital, and Director of the UCL Great Ormond Street Institute of Child Health, OBE said: "Many of the children I see have experienced years of seizures and investigations before we find a lesion. The epilepsy community is searching for ways to speed up diagnosis and treatment. Initiatives such as MELD have the potential to rapidly identify abnormalities that can be removed and potentially cure the epilepsy." Co-lead Dr. Sophie Adler from UCL said: "This type of research is only possible with international collaboration. We were privileged to work with 75 researchers and clinicians towards this common goal of "no missed epilepsy lesions worldwide"". King's College London Journal reference: Ripart, M., et al. (2025). Detection of Epileptogenic Focal Cortical Dysplasia Using Graph Neural Networks: A MELD Study. JAMA Neurology. doi.org/10.1001/jamaneurol.2024.5406.

Epilepsy AI tool detects brain lesions doctors miss

Study co-author and childhood epilepsy consultant Prof Helen Cross said it had the potential "to rapidly identify abnormalities that can be removed and potentially cure the epilepsy". Uncontrolled epilepsy was "incapacitating", she said. Many of the children she sees as a consultant at Great Ormond Street Hospital have had years of seizures and investigations before a lesion is found. Charity Epilepsy Action said the new AI tool's potential was "really exciting" and could give people faster diagnosis, but did not solve the issue of lack of specialist epilepsy nurses in England. "It remains early days and, as always, we must proceed with caution," said Ley Sander from the Epilepsy Society, adding that if the tool could identify more people as candidates for brain surgery, that could be "life-changing for many more people with epilepsy". The researchers are hoping for official approval to use MELD Graph as a diagnostic tool - but other trials are needed first to investigate the long-term benefits for patients whose brain lesions are detected. In the meantime, the research team has made the tool available on open-source software, so it can be used for clinical research by hospitals worldwide.