NIH-funded project aims to develop a virtual surgery tool to help clinicians better predict and protect language function after epilepsy surgery.
By: Grace Huff
For people with drug-resistant epilepsy, surgery can offer a life-changing opportunity to control seizures. But it can also come with questions about how a procedure could affect language, memory and communication.
A new $2.32 million NIH-funded project led by the University of Florida aims to give patients, families and clinicians more personalized information to help answer those questions before surgery takes place.
Led by Abbas Babajani-Feremi, Ph.D., associate professor in the UF Department of Neurology and director of the Magnetoencephalography or MEG, Laboratory at the Norman Fixel Institute for Neurological Diseases at UF Health, the project will combine advanced brain mapping, intracranial recordings and artificial intelligence to predict how different surgical approaches could affect a patient’s language function. UF is collaborating with Cincinnati Children’s Hospital Medical Center on this project.
“For a patient and family, one of the most difficult questions is not only, ‘Will surgery control the seizures?’ but also, ‘What might I lose because of the surgery?’” Babajani-Feremi said.
A single location in the brain does not control language; it relies on a network of regions and connections that can vary between people, particularly those who have lived with epilepsy for many years.
To create a more individualized picture of those networks, researchers will combine MEG, functional MRI, diffusion MRI and intracranial recordings. Each technology provides complementary information about where language processing occurs and how those regions are connected.
Machine-learning models will then integrate the brain-mapping data with patient-specific clinical information and characteristics of a proposed surgical resection. The goal is to estimate an individual patient’s risk of language changes rather than relying on population averages or a single brain-mapping technique.
A major goal of the project is to develop a virtual resection tool that could allow clinicians to compare potential surgical approaches on a patient’s own brain before an operation.
Clinicians could identify an area of brain tissue that might be removed or treated and overlay it onto the patient’s individualized language maps. An AI model would then estimate how the proposed approach could affect different aspects of language. Clinicians could adjust the proposed surgical area and compare different scenarios.
“In simple terms, it is similar to being able to test several possible surgeries virtually before choosing an actual surgical strategy,” Babajani-Feremi said.
The researchers hope the approach could ultimately help clinical teams balance seizure control with preservation of language and quality of life while giving patients and families more individualized information when making treatment decisions.
The project brings together expertise in epilepsy, neurosurgery, neuroimaging, neuropsychology and artificial intelligence. At the Fixel Institute, researchers have access to a 306-channel whole-head MEG system and an advanced 3T MRI, allowing the team to integrate multiple forms of brain imaging and intracranial recordings. UF’s AI and high-performance computing infrastructure will support the development of the machine-learning models and virtual resection platform.
“What excites me most is the possibility of changing the question we ask before epilepsy surgery,” Babajani-Feremi said. “Today, much of presurgical mapping asks, ‘Where is language located?’ I hope we can move toward the much more clinically meaningful question, ‘For this individual patient, what is likely to happen to language if we perform this particular surgery?’”