4.7 Article

Arterial spin labelling reveals an abnormal cerebral perfusion pattern in Parkinson's disease

Journal

BRAIN
Volume 134, Issue -, Pages 845-855

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/brain/awq377

Keywords

Parkinson's disease; arterial spin labelling; magnetic resonance imaging; perfusion; network analysis; cognition

Funding

  1. GE Healthcare
  2. Merck Co.
  3. NIH [1 R01 CA115745-01A1, 1 R01 AG027435-01, R01-EB004582, R01 MH80729-01A2, R01 MH077073-01A2, R01DC008796-01A1, R01 NS047029-04A2, 1P50 CA101942-01]
  4. Siemens Medical
  5. Neurological Foundation of New Zealand
  6. Canterbury Medical Research Foundation

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There is a need for objective imaging markers of Parkinson's disease status and progression. Positron emission tomography and single photon emission computed tomography studies have suggested patterns of abnormal cerebral perfusion in Parkinson's disease as potential functional biomarkers. This study aimed to identify an arterial spin labelling magnetic resonance-derived perfusion network as an accessible, non-invasive alternative. We used pseudo-continuous arterial spin labelling to measure cerebral grey matter perfusion in 61 subjects with Parkinson's disease with a range of motor and cognitive impairment, including patients with dementia and 29 age- and sex-matched controls. Principal component analysis was used to derive a Parkinson's disease-related perfusion network via logistic regression. Region of interest analysis of absolute perfusion values revealed that the Parkinson's disease pattern was characterized by decreased perfusion in posterior parieto-occipital cortex, precuneus and cuneus, and middle frontal gyri compared with healthy controls. Perfusion was preserved in globus pallidus, putamen, anterior cingulate and post- and pre-central gyri. Both motor and cognitive statuses were significant factors related to network score. A network approach, supported by arterial spin labelling-derived absolute perfusion values may provide a readily accessible neuroimaging method to characterize and track progression of both motor and cognitive status in Parkinson's disease.

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