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

ABSTRACT: To determine whether MRI markers, including diffusion tensor imaging (DTI), can predict cognitive decline and dementia in patients with cerebral small vessel disease (SVD).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.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.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.

SUBMITTER: Zeestraten EA

PROVIDER: S-EPMC5664300 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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

Zeestraten Eva A EA Lawrence Andrew J AJ Lambert Christian C Benjamin Philip P Brookes Rebecca L RL Mackinnon Andrew D AD Morris Robin G RG Barrick Thomas R TR Markus Hugh S HS

Neurology 20171004 18

<h4>Objective</h4>To determine whether MRI markers, including diffusion tensor imaging (DTI), can predict cognitive decline and dementia in patients with cerebral small vessel disease (SVD).<h4>Methods</h4>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 (WM ...[more]

PMID: 28978655

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Project description:Sporadic cerebral small vessel disease is an important cause of vascular dementia, a syndrome of cognitive impairment together with vascular brain damage. At post-mortem pure vascular dementia is rare, with evidence of co-existing Alzheimer's disease pathology in 95% of cases. This work used MRI to characterize structural abnormalities during the preclinical phase of vascular dementia in symptomatic small vessel disease. 121 subjects were recruited into the St George's Cognition and Neuroimaging in Stroke study and followed up longitudinally for five years. Over this period 22 individuals converted to dementia. Using voxel-based morphometry, we found structural abnormalities present at baseline in those with preclinical dementia, with reduced grey matter density in the left striatum and hippocampus, and more white matter hyperintensities in the frontal white-matter. The lacunar data revealed that some of these abnormalities may be due to lesions within the striatum and centrum semiovale. Using support vector machines, future dementia could be best predicted using hippocampal and striatal Jacobian determinant data, achieving a balanced classification accuracy of 73%. Using cluster ward linkage we identified four anatomical subtypes. Successful predictions were restricted to groups with lower levels of vascular damage. The subgroup that could not be predicted were younger, further from conversion, had the highest levels of vascular damage, with milder cognitive impairment at baseline but more rapid deterioration in processing speed and executive function, consistent with a primary vascular dementia. In contrast, the remaining groups had decreasing levels of vascular damage and increasing memory impairment consistent with progressively more Alzheimer's-like pathology. Voxel-wise rates of hippocampal atrophy supported these distinctions, with the vascular group closely resembling the non-dementing cohort, whereas the Alzheimer's like group demonstrated global hippocampal atrophy. This work reveals distinct anatomical endophenotypes in preclinical vascular dementia, forming a spectrum between vascular and Alzheimer's like pathology. The latter group can be identified using baseline MRI, with 73% converting within 5 years. It was not possible to predict the vascular dominant dementia subgroup, however 19% of negative predictions with high levels of vascular disease would ultimately develop dementia. It may be that techniques more sensitive to white matter damage, such as diffusion weighted imaging, may prove more useful for this vascular dominant subgroup in the future. This work provides a way to accurately stratify patients using a baseline MRI scan, and has utility in future clinical trials designed to slow or prevent the onset of dementia in these high-risk cohorts.

Project description:Background and objectivesCerebral small vessel disease is a major cause of stroke and dementia. Metabolomics can help identify novel risk factors to better understand pathogenesis and predict disease progression and severity.MethodsWe analyzed baseline metabolomic profiles from 118,021 UK Biobank participants. We examined cross-sectional associations of 325 metabolites with MRI markers of small vessel disease, evaluated longitudinal associations with incident stroke and dementia, and ascertained causal relationships using Mendelian randomization.ResultsIn cross-sectional analyses, lower levels of apolipoproteins, free cholesterol, cholesteryl esters, fatty acids, lipoprotein particle concentrations, phospholipids, and triglycerides were associated with increased white matter microstructural damage on diffusion tensor MRI. In longitudinal analyses, lipoprotein subclasses of very large high-density lipoprotein cholesterol (HDL) were associated with an increased risk of stroke, and acetate and 3-hydroxybutyrate were associated with an increased risk of dementia. Mendelian randomization analyses identified strong evidence supporting causal relationships for many findings. A few metabolites had consistent associations across multiple analysis types. Increased total lipids in very large HDL and increased HDL particle size were associated with increased white matter damage (lower fractional anisotropy: OR: 1.44, 95% CI 1.07-1.95, and OR: 1.19, 95% CI 1.06-1.34, respectively; mean diffusivity: OR: 1.49, 95% CI 1.11-2.01, and OR: 1.24, 95% CI 1.11-1.40, respectively) and an increased risk of incident all stroke (HR: 4.04, 95% CI 2.13-7.64, and HR: 1.54, 95% CI 1.20-1.98, respectively) and ischemic stroke (HR: 3.12, 95% CI 1.53-6.38; HR: 1.37, 95% CI 1.04-1.81). Valine was associated with decreased mean diffusivity (OR: 0.51, 95% CI 0.30-0.88) and had a protective association with all-cause dementia (HR: 0.008, 95% CI 0.002-0.035). Increased levels of cholesterol in small HDL were associated with a decreased risk of incident all stroke (HR: 0.17, 95% CI 0.08-0.39) and ischemic stroke (HR: 0.19, 95% CI 0.08-0.46) and were supported by evidence of a causal association with MRI-confirmed lacunar stroke (OR: 0.96, 95% CI 0.93-0.99).DiscussionIn this large-scale metabolomics study, we found multiple metabolites associated with stroke, dementia, and MRI markers of small vessel disease. Further studies may help inform the development of personalized prediction models and provide insights into mechanistic pathways and future treatment approaches.

Project description:Even with postmortem pathological examination, only limited information is provided of the foci of in vivo clinical information. Cerebral small vessel disease, which is associated with ageing, dementia and stroke, highlights the difficulty in arriving at a definitive diagnosis of the lesions detected on in vivo radiological examination. We performed a radiological-pathological comparative study using ex vivo MRI to examine small cerebral lesions. Four patients with small vessel disease lesions detected on in vivo MRI were studied. Exact pathological findings of in vivo MRI-detected lesions were revealed. The ischaemic lesion after 17 days from onset showed positivity for peroxiredoxin, cluster of differentiation 204 and glial fibrillary acidic protein, indicating sterile inflammation and neuroprotective reaction. Cortical microinfarcts beneath the cortical superficial siderosis were associated with inflammation from the superficial layer in a patient with cerebral amyloid angiopathy; in this patient, a bilinear track-like appearance of the cortical superficial siderosis on the ex vivo MRI was compatible with iron deposition on the pia matter and within cortical layers II-III. An in vivo MRI-detected cerebral microbleed was revealed to be heterogeneous. An in vivo MRI-detected cerebral microbleed was revealed to be a venous angioma. Furthermore, a neuropathologically confirmed embolic cerebral microbleed was firstly detected using this method. Our results suggest that in vivo MRI-detected lobar cerebral microbleeds can be caused by non-cerebral amyloid angiopathy aetiologies, such as microembolism and venous angioma. Venous angioma and embolic microbleeds may mimic cerebral amyloid angiopathy markers on in vivo MRI. To clarify the clinical importance of these lesions, we should investigate their rate and frequency in a large cohort of healthy individuals and patients with cardiac risk factors. Thus, we provide evidence that ex vivo micro-MRI improves the clinical diagnosis of small vessel diseases.

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

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

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