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MR brain connectivity predicts Parkinson's disease progression, study finds

por Gus Iversen, Editor in Chief | June 25, 2024
MRI
The structural and functional organization of the brain, as revealed by MR, can predict the progression of brain atrophy in early-stage, mild Parkinson's disease, according to a study published in Radiology, a journal of the RSNA.

Parkinson's disease, which affects over 8.5 million people globally, is a progressive disorder characterized by tremors, slow movement, and rigidity. Symptoms can worsen over time to include cognitive impairments and sleep issues. The World Health Organization reports that the prevalence of Parkinson's has doubled in the past 25 years.

A hallmark of Parkinson's is the accumulation of misfolded alpha-synuclein proteins in the brain, forming Lewy bodies and Lewy neurites that spread and damage nerve cells. Researchers aimed to determine if brain connectivity mapping could predict atrophy patterns in patients with mild Parkinson's disease.
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The study utilized MR data from 86 patients with mild Parkinson's disease and 60 healthy controls to create a connectome — a map of the brain's neural connections. This connectome helped develop an index of disease exposure, which was then correlated with atrophy at two and three years, post-baseline. The models predicted gray matter atrophy in several brain regions over the three years.

"In the present study, brain connectome, both structural and functional, showed the potential to predict progression of gray matter alteration in patients with mild Parkinson’s disease," said study co-author Dr. Federica Agosta, associate professor of neurology at the Neuroimaging Research Unit of IRCCS San Raffaele Scientific Institute in Milan, Italy.

The findings suggest that MR could play a role in intervention trials aimed at preventing or delaying disease progression, particularly when individual patient data is considered. Dr. Agosta emphasized the importance of incorporating individual-specific information into future models to account for variability in disease progression.

"We believe that understanding the organization and dynamics of the human brain network is a pivotal goal in neuroscience, achievable through the study of the human connectome," Agosta added. "The idea that this approach could help identify different biomarkers capable of modulating Parkinson’s disease progression inspires our work."

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