GAINESVILLE, Fla. — A new software developed by researchers at the University of Florida and the UF Health Norman Fixel Institute for Neurological Diseases promises to greatly enhance the accuracy of Parkinson’s disease diagnoses, potentially exceeding 96% accuracy. This advance addresses a long-standing diagnostic challenge, given that existing methods have accuracy rates between 55% and 78% during the first five years of assessment.
Parkinson’s disease, while recognized, encompasses a range of conditions, including idiopathic Parkinson’s (the most common type) and other movement disorders like multiple system atrophy (Parkinsonian variant) and progressive supranuclear palsy. These disorders share motor and nonmotor features, such as changes in gait, yet possess distinct pathologies and prognoses. This overlap often leads to misdiagnoses; roughly one in four, or even one in two, patients are initially misdiagnosed.
The new software, called Automated Imaging Differentiation for Parkinsonism (AIDP), is an automated MRI processing and machine learning tool featuring a noninvasive biomarker technique. Using diffusion-weighted MRI, which measures how water molecules move in the brain, the software identifies areas of neurodegeneration. A machine learning algorithm, tested against in-person clinic diagnoses, analyzes the brain scan and provides clinicians with results indicating the specific type of Parkinson’s.
“In many cases, MRI manufacturers don’t communicate with each other due to marketplace competition,” said David Vaillancourt, Ph.D., chair and professor in the UF Department of Applied Physiology and Kinesiology. “They all have their own software and their own sequences. Here, we’ve developed novel software that works across all of them.”
The study, published in JAMA Neurology and funded by the National Institutes of Health, was conducted across 21 sites, 19 in the United States and two in Canada. Even the most experienced movement disorder specialists can benefit from such a tool, Vaillancourt noted.
“This is an instance where the innovation between technology and artificial intelligence has been proven to enhance diagnostic precision, allowing us the opportunity to further improve treatment for patients with Parkinson’s disease,” said Michael Okun, M.D., medical advisor to the Parkinson’s Foundation and director of the Norman Fixel Institute for Neurological Diseases at UF Health. “We look forward to seeing how this innovation can further impact the Parkinson’s community and advance our shared goal of better outcomes for all.”
The team is now seeking approval from the U.S. Food and Drug Administration.
“This effort truly highlights the importance of interdisciplinary collaboration,” said Angelos Barmpoutis, Ph.D., a professor at the Digital Worlds Institute at UF. “Thanks to the combined medical expertise, scientific expertise and technological expertise, we were able to accomplish a goal that will change the lives of countless individuals.”
Vaillancourt and Barmpoutis are partial owners of a company called Neuropacs, which aims to commercialize the software to improve patient care and clinical trials.
