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Can neuroimaging predict dementia in Parkinson’s disease?
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 poten...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6113860/ https://www.ncbi.nlm.nih.gov/pubmed/30137209 http://dx.doi.org/10.1093/brain/awy211 |
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author | Lanskey, Juliette H McColgan, Peter Schrag, Anette E Acosta-Cabronero, Julio Rees, Geraint Morris, Huw R Weil, Rimona S |
author_facet | Lanskey, Juliette H McColgan, Peter Schrag, Anette E Acosta-Cabronero, Julio Rees, Geraint Morris, Huw R Weil, Rimona S |
author_sort | Lanskey, Juliette H |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6113860 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-61138602018-09-04 Can neuroimaging predict dementia in Parkinson’s disease? Lanskey, Juliette H McColgan, Peter Schrag, Anette E Acosta-Cabronero, Julio Rees, Geraint Morris, Huw R Weil, Rimona S Brain Review Article 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. Oxford University Press 2018-09 2018-08-29 /pmc/articles/PMC6113860/ /pubmed/30137209 http://dx.doi.org/10.1093/brain/awy211 Text en © The Author(s) (2018). Published by Oxford University Press on behalf of the Guarantors of Brain. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Lanskey, Juliette H McColgan, Peter Schrag, Anette E Acosta-Cabronero, Julio Rees, Geraint Morris, Huw R Weil, Rimona S Can neuroimaging predict dementia in Parkinson’s disease? |
title | Can neuroimaging predict dementia in Parkinson’s disease? |
title_full | Can neuroimaging predict dementia in Parkinson’s disease? |
title_fullStr | Can neuroimaging predict dementia in Parkinson’s disease? |
title_full_unstemmed | Can neuroimaging predict dementia in Parkinson’s disease? |
title_short | Can neuroimaging predict dementia in Parkinson’s disease? |
title_sort | can neuroimaging predict dementia in parkinson’s disease? |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6113860/ https://www.ncbi.nlm.nih.gov/pubmed/30137209 http://dx.doi.org/10.1093/brain/awy211 |
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