Deep Brain Stimulation in Parkinson’s disease: from the MRI artifacts recognition tool artDBS to resting-state fMRI graph analysis

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.