4.7 Review

Can neuroimaging predict dementia in Parkinson's disease?

Journal

BRAIN
Volume 141, Issue -, Pages 2545-2560

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/brain/awy211

Keywords

Parkinson's disease; dementia; imaging; MRI

Funding

  1. Clinical Research Career Development Fellowship from the Wellcome Trust [201567/Z/16/Z]
  2. UCL
  3. Academy of Medical Sciences
  4. National Institute for Health Research University College London Hospitals Biomedical Research Centre [BRC302/NS/RW/101410]
  5. Wellcome Trust
  6. Wellcome [203147/Z/16/Z]
  7. Parkinson's UK
  8. NIHR UCLH BRC
  9. Guarantors of Brain
  10. Drake Foundation
  11. Cure Parkinson's Trust
  12. S Koe Research Fellowship
  13. CBD Solutions
  14. PSP Association
  15. MRC
  16. ESRC
  17. NIHR
  18. GE Healthcare [23/5/13 PO2580367614]
  19. EU Commission
  20. National Institute for Health Research University College London Hospitals Biomedical Research Centre
  21. MRC [G0700943] Funding Source: UKRI

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Dementia in Parkinson's disease affects 50% of patients within 10 years of diagnosis but there is wide variation in severity and timing. Thus, robust neuroimaging prediction of cognitive involvement in Parkinson's disease is important: (i) to identify at-risk individuals for clinical trials of potential new treatments; (ii) to provide reliable prognostic information for individuals and populations; and (iii) to shed light on the pathophysiological processes underpinning Parkinson's disease dementia. To date, neuroimaging has not made major contributions to predicting cognitive involvement in Parkinson's disease. This is perhaps unsurprising considering conventional methods rely on macroscopic measures of topographically distributed neurodegeneration, a relatively late event in Parkinson's dementia. However, new technologies are now emerging that could provide important insights through detection of other potentially relevant processes. For example, novel MRI approaches can quantify magnetic susceptibility as a surrogate for tissue iron content, and increasingly powerful mathematical approaches can characterize the topology of brain networks at the systems level. Here, we present an up-to-date overview of the growing role of neuroimaging in predicting dementia in Parkinson's disease. We discuss the most relevant findings to date, and consider the potential of emerging technologies to detect the earliest signs of cognitive involvement in Parkinson's disease.

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