Spatial distribution of cerebral white matter lesions predicts progression to mild cognitive impairment and dementia

Marion Mortamais; Christelle Reynes; Adam Brickman; Frank Provenzano; Jordan Muraskin; Florence Portet; Claudine Berr; Jacques Touchon; Alain Bonafé; Emmanuelle Le Bars; Jerome Maller; Chantal Meslin; Robert Sabatier; Karen Ritchie; Sylvaine Artero

doi:10.1371/journal.pone.0056972

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Spatial distribution of cerebral white matter lesions predicts progression to mild cognitive impairment and dementia

Journal article

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Spatial distribution of cerebral white matter lesions predicts progression to mild cognitive impairment and dementia

Marion Mortamais, Christelle Reynes, Adam Brickman, Frank Provenzano, Jordan Muraskin, Florence Portet, Claudine Berr, Jacques Touchon, Alain Bonafé, Emmanuelle Le Bars, …

PloS one, Vol.8(2), p.e56972

02/14/2013

DOI: 10.1371/journal.pone.0056972

PMCID: PMC3572965

PMID: 23457645

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Abstract

CONTEXT: White matter lesions (WML) increase the risk of dementia. The relevance of WML location is less clear. We sought to determine whether a particular WML profile, based on the density and location of lesions, could be associated with an increased risk of mild cognitive impairment (MCI) or dementia over the following 7 years. METHODS: In 426 healthy subjects from a cohort of community-dwelling people aged 65 years and over (ESPRIT Project), standardized cognitive and neurological evaluations were repeated after 2, 4 and 7 years. Patterns of WML were computed with a supervised data mining approach (decision trees) using the regional WML volumes (frontal, parietal, temporal, and occipital regions) and the total WML volume estimated at baseline. Cox proportional hazard models were then constructed to study the association between WML patterns and risk of MCI/dementia. RESULTS: Total WML volume and percentage of WML in the temporal region proved to be the best predictors of progression to MCI and dementia. Specifically, severe total WML load with a high proportion of lesions in the temporal region was significantly associated with the risk of developing MCI or dementia. CONCLUSIONS: Above a certain threshold of damage, a pattern of WML clustering in the temporal region identifies individuals at increased risk of MCI or dementia. As this WML pattern is observed before the onset of clinical symptoms, it may facilitate the detection of patients at risk of MCI/dementia.

Aged

Brain

Data Mining

Decision Trees

Dementia

Discriminant Analysis

Disease Progression

Female

Follow-Up Studies

Humans

Life Sciences

Male

Mild Cognitive Impairment

Neurons and Cognition

Risk

Santé publique et épidémiologie

Spatial Analysis

Statistics as Topic

Details

Title: Subtitle: Spatial distribution of cerebral white matter lesions predicts progression to mild cognitive impairment and dementia
Creators: Marion Mortamais - Université de Montpellier
Christelle Reynes - Université de Montpellier
Adam Brickman - Columbia University
Frank Provenzano - Columbia University
Jordan Muraskin - Columbia University
Florence Portet - Centre Hospitalier Universitaire de Montpellier
Claudine Berr - Université de Montpellier
Jacques Touchon - Université de Montpellier
Alain Bonafé - Université de Montpellier
Emmanuelle Le Bars - Université de Montpellier
Jerome Maller - The Alfred Hospital
Chantal Meslin - Australian National University
Robert Sabatier - Université de Montpellier
Karen Ritchie - Imperial College London
Sylvaine Artero - Inserm
Resource Type: Journal article
Publication Details: PloS one, Vol.8(2), p.e56972
DOI: 10.1371/journal.pone.0056972
PMID: 23457645
PMCID: PMC3572965
NLM abbreviation: PLoS One
ISSN: 1932-6203
eISSN: 1932-6203
Publisher: Public Library of Science
Language: English
Date published: 02/14/2013
Academic Unit: Radiology
Record Identifier: 9984848419502771

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