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Abstract #0440

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

Elena Cantoni1, Giovanni Sighinolfi1, Ilaria Cani1,2, Fiorina Bartiromo1, Gianfranco Vornetti1,2, Tommaso Kaswalder3, Giovanna Calandra-Buonaura1,2, Luca Baldelli1,2, Paolo Mantovani1, Paola Berardi3, Giulia Giannini1,2, Alfredo Conti1,2, Caterina Tonon1,2, and Raffaele Lodi1,2
1IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy, 2Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy, 3AUSL di Bologna, Bologna, Italy

Synopsis

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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Keywords