A preprocessed multimodal neuroimaging dataset from Quebec Parkinson Network for biomarker discovery

Abstract

Open, multimodal, neuroimaging datasets are a key resource for the development of biomarkers and statistical models that can support disease monitoring and treatment planning in Parkinson’s disease (PD). Here we present the first release of Quebec Parkinson Network Neuroimaging Cohort (QPN-NC), a cross-sectional cohort of 202 individuals with PD and 69 older adults with multimodal MRI and extensive clinical and neuropsychological evaluations. The main objective of this data collection is to investigate neural correlates of motor and non-motor symptoms and facilitate comparisons with other PD studies. This QPN-NC release comprises well-characterized clinical assessments and curated imaging data processed through five neuroimaging pipelines. Additionally, we provide harmonized data annotations to facilitate search and cohort matching across other PD datasets. We share the tools and software used in this data release to enable data discovery, reproduce image processing, and help other studies to adopt best practices and community standards. Together with other datasets, QPN-NC will improve our understanding of PD and aid the translation of neuroimaging biomarkers into the clinic.