Using Multimodal MRI Techniques to Derive a Biomarker for Tracking the Pathological Changes Occurring at Different Stages of Cognitive Decline in Parkinson's Disease in a Cross-Sectional Study Design

Abstract

Cognitive impairment is common in Parkinson's disease (PD) and can range from mild cognitive impairment (PD-MCI) to dementia (PDD). The aim of this study was to derive a multi-modal MRI-based biomarker for the reliable discrimination of PD patients at different stages of cognitive decline and to identify pathologic patterns related with dementia risk. The resting-state functional MRI (rs-fMRI), diffusion tensor imaging (DTI), Arterial Spin Labeling and MR spectroscopic imaging data of 60 PD patients (PD-N, PD-MCI, PDD) were collected. The rs-fMRI data revealed a combination of resting-state networks with significant discriminative power based on the expression scores of the resting-state networks. In combination with the DTI data we obtained a successful model for the discrimination of PDD patients and were able to identify progressive pathological changes that can be used as biomarker for PDD and could be established as clinical diagnostic tool for PD patients with high dementia risk.