Keywords: Parkinson's Disease, fMRI (resting state), Parkinson's disease, Deep Brain Stimulation, graph analysis, susceptibility artifacts, segmentation
Motivation: Deep brain stimulation (DBS) is widely used for treating of motor symptoms in Parkinson's disease. Functional connectivity modifications are of great interest, but DBS-induced artifacts, interfering with fMRI analysis, must be considered.
Goal(s): This study aims to improve artifact detection and analyse DBS-related network alterations in the brain using resting-state fMRI.
Approach: An automated tool, artDBS, was developed to isolate MRI artifacts. Resting-state fMRI data were analysed with graph analysis, comparing patients' connectivity metrics pre- and post-DBS and against healthy controls.
Results: artDBS effectively identified DBS artifacts. Significant alterations in network connectivity, particularly within motor and attentional networks with cerebellar involvement were observed.
Impact: This MRI study introduces a novel method for precise DBS artifact recognition, and advances our understanding of Parkinson’s disease by revealing new insights into the role of resting-state brain and cerebellar functional networks in DBS-treated patients.
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