Non-Invasive, Automated MRI for Parkinson’s Diagnosis

In an international study at 17 MRI centers in the U.S., Austria, and Germany, a research team led by UF’s David Vaillancourt, Ph.D., used a non-invasive MRI method with 1,002 patients to develop an automated system to accurately diagnose Parkinson’s disease and related but different neurodegenerative disorders.

In the study published Aug. 27 in The Lancet Digital Health, researchers used diffusion-weighted MRI, an imaging method that measures how water molecules diffuse in the brain and are particularly helpful in identifying where neurodegeneration is occurring.

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