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Change in multimodal MRI markers predicts dementia risk in cerebral small vessel disease

OBJECTIVE: To determine whether MRI markers, including diffusion tensor imaging (DTI), can predict cognitive decline and dementia in patients with cerebral small vessel disease (SVD). METHODS: In the prospective St George's Cognition and Neuroimaging in Stroke study, multimodal MRI was performe...

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Detalles Bibliográficos
Autores principales: Zeestraten, Eva A., Lawrence, Andrew J., Lambert, Christian, Benjamin, Philip, Brookes, Rebecca L., Mackinnon, Andrew D., Morris, Robin G., Barrick, Thomas R., Markus, Hugh S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5664300/
https://www.ncbi.nlm.nih.gov/pubmed/28978655
http://dx.doi.org/10.1212/WNL.0000000000004594
Descripción
Sumario:OBJECTIVE: To determine whether MRI markers, including diffusion tensor imaging (DTI), can predict cognitive decline and dementia in patients with cerebral small vessel disease (SVD). METHODS: In the prospective St George's Cognition and Neuroimaging in Stroke study, multimodal MRI was performed annually for 3 years and cognitive assessments annually for 5 years in a cohort of 99 patients with SVD, defined as symptomatic lacunar stroke and confluent white matter hyperintensities (WMH). Progression to dementia was determined in all patients. Progression of WMH, brain volume, lacunes, cerebral microbleeds, and a DTI measure (the normalized peak height of the mean diffusivity histogram distribution) as a marker of white matter microstructural damage were determined. RESULTS: Over 5 years of follow-up, 18 patients (18.2%) progressed to dementia. A significant change in all MRI markers, representing deterioration, was observed. The presence of new lacunes, and rate of increase in white matter microstructural damage on DTI, correlated with both decline in executive function and global functioning. Growth of WMH and deterioration of white matter microstructure on DTI predicted progression to dementia. A model including change in MRI variables together with their baseline values correctly classified progression to dementia with a C statistic of 0.85. CONCLUSIONS: This longitudinal prospective study provides evidence that change in MRI measures including DTI, over time durations during which cognitive change is not detectable, predicts cognitive decline and progression to dementia. It supports the use of MRI measures, including DTI, as useful surrogate biomarkers to monitor disease and assess therapeutic interventions.