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 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

Pattern and Rate of Cognitive Decline in Cerebral Small Vessel Disease: A Prospective Study.

OBJECTIVES: Cognitive impairment, predominantly affecting processing speed and executive function, is an important consequence of cerebral small vessel disease (SVD). To date, few longitudinal studies of cognition in SVD have been conducted. We determined the pattern and rate of cognitive decline in SVD and used the results to determine sample size calculations for clinical trials of interventions reducing cognitive decline. METHODS: 121 patients with MRI confirmed lacunar stroke and leukoaraiosis were enrolled into the prospective St George's Cognition And Neuroimaging in Stroke (SCANS) study. Patients attended one baseline and three annual cognitive assessments providing 36 month follow-up data. Neuropsychological assessment comprised a battery of tests assessing working memory, long-term (episodic) memory, processing speed and executive function. We calculated annualized change in cognition for the 98 patients who completed at least two time-points. RESULTS: Task performance was heterogeneous, but significant cognitive decline was found for the executive function index (p<0.007). Working memory and processing speed decreased numerically, but not significantly. The executive function composite score would require the smallest samples sizes for a treatment trial with an aim of halting decline, but this would still require over 2,000 patients per arm to detect a 30% difference with power of 0.8 over a three year follow-up. CONCLUSIONS: The pattern of cognitive decline seen in SVD over three years is consistent with the pattern of impairments at baseline. Rates of decline were slow and sample sizes would need to be large for clinical trials aimed at halting decline beyond initial diagnosis using cognitive scores as an outcome measure. This emphasizes the importance of more sensitive surrogate markers in this disease.This work was supported by the Wellcome Trust [grant number 081589] and Alzheimer's Research UK [grant number ARUK-PG2013-2].This is the final version of the article. It first appeared from PLOS via http://dx.doi.org/10.1371/journal.pone.013552

Longitudinal patterns of leukoaraiosis and brain atrophy in symptomatic small vessel disease.

Cerebral small vessel disease is a common condition associated with lacunar stroke, cognitive impairment and significant functional morbidity. White matter hyperintensities and brain atrophy, seen on magnetic resonance imaging, are correlated with increasing disease severity. However, how the two are related remains an open question. To better define the relationship between white matter hyperintensity growth and brain atrophy, we applied a semi-automated magnetic resonance imaging segmentation analysis pipeline to a 3-year longitudinal cohort of 99 subjects with symptomatic small vessel disease, who were followed-up for ≥1 years. Using a novel two-stage warping pipeline with tissue repair step, voxel-by-voxel rate of change maps were calculated for each tissue class (grey matter, white matter, white matter hyperintensities and lacunes) for each individual. These maps capture both the distribution of disease and spatial information showing local rates of growth and atrophy. These were analysed to answer three primary questions: first, is there a relationship between whole brain atrophy and magnetic resonance imaging markers of small vessel disease (white matter hyperintensities or lacune volume)? Second, is there regional variation within the cerebral white matter in the rate of white matter hyperintensity progression? Finally, are there regionally specific relationships between the rates of white matter hyperintensity progression and cortical grey matter atrophy? We demonstrate that the rates of white matter hyperintensity expansion and grey matter atrophy are strongly correlated (Pearson's R = -0.69, P < 1 × 10(-7)), and significant grey matter loss and whole brain atrophy occurs annually (P < 0.05). Additionally, the rate of white matter hyperintensity growth was heterogeneous, occurring more rapidly within long association fasciculi. Using voxel-based quantification (family-wise error corrected P < 0.05), we show the rate of white matter hyperintensity progression is associated with increases in cortical grey matter atrophy rates, in the medial-frontal, orbito-frontal, parietal and occipital regions. Conversely, increased rates of global grey matter atrophy are significantly associated with faster white matter hyperintensity growth in the frontal and parietal regions. Together, these results link the progression of white matter hyperintensities with increasing rates of regional grey matter atrophy, and demonstrate that grey matter atrophy is the major contributor to whole brain atrophy in symptomatic cerebral small vessel disease. These measures provide novel insights into the longitudinal pathogenesis of small vessel disease, and imply that therapies aimed at reducing progression of white matter hyperintensities via end-arteriole damage may protect against secondary brain atrophy and consequent functional morbidity

Longitudinal decline in structural networks predicts dementia in cerebral small vessel disease.

OBJECTIVE: To determine whether longitudinal change in white matter structural network integrity predicts dementia and future cognitive decline in cerebral small vessel disease (SVD). To investigate whether network disruption has a causal role in cognitive decline and mediates the association between conventional MRI markers of SVD with both cognitive decline and dementia. METHODS: In the prospective longitudinal SCANS (St George's Cognition and Neuroimaging in Stroke) Study, 97 dementia-free individuals with symptomatic lacunar stroke were followed with annual MRI for 3 years and annual cognitive assessment for 5 years. Conversion to dementia was recorded. Structural networks were constructed from diffusion tractography using a longitudinal registration pipeline, and network global efficiency was calculated. Linear mixed-effects regression was used to assess change over time. RESULTS: Seventeen individuals (17.5%) converted to dementia, and significant decline in global cognition occurred (p = 0.0016). Structural network measures declined over the 3-year MRI follow-up, but the degree of change varied markedly between individuals. The degree of reductions in network global efficiency was associated with conversion to dementia (B = -2.35, odds ratio = 0.095, p = 0.00056). Change in network global efficiency mediated much of the association of conventional MRI markers of SVD with cognitive decline and progression to dementia. CONCLUSIONS: Network disruption has a central role in the pathogenesis of cognitive decline and dementia in SVD. It may be a useful disease marker to identify that subgroup of patients with SVD who progress to dementia

Predicting Dementia in Cerebral Small Vessel Disease Using an Automatic Diffusion Tensor Image Segmentation Technique.

Background and Purpose- Cerebral small vessel disease (SVD) is the most common cause of vascular cognitive impairment, with a significant proportion of cases going on to develop dementia. We explore the extent to which diffusion tensor image segmentation technique (DSEG; which characterizes microstructural damage across the cerebrum) predicts both degree of cognitive decline and conversion to dementia, and hence may provide a useful prognostic procedure. Methods- Ninety-nine SVD patients (aged 43-89 years) underwent annual magnetic resonance imaging scanning (for 3 years) and cognitive assessment (for 5 years). DSEG-θ was used as a whole-cerebrum measure of SVD severity. Dementia diagnosis was based Diagnostic and Statistical Manual of Mental Disorders V criteria. Cox regression identified which DSEG measures and vascular risk factors were related to increased risk of dementia. Linear discriminant analysis was used to classify groups of stable versus subsequent dementia diagnosis individuals. Results- DSEG-θ was significantly related to decline in executive function and global cognition (P<0.001). Eighteen (18.2%) patients converted to dementia. Baseline DSEG-θ predicted dementia with a balanced classification rate=75.95% and area under the receiver operating characteristic curve=0.839. The best classification model included baseline DSEG-θ, change in DSEG-θ, age, sex, and premorbid intelligence quotient (balanced classification rate of 79.65%; area under the receiver operating characteristic curve=0.903). Conclusions- DSEG is a fully automatic technique that provides an accurate method for assessing brain microstructural damage in SVD from a single imaging modality (diffusion tensor imaging). DSEG-θ is an important tool in identifying SVD patients at increased risk of developing dementia and has potential as a clinical marker of SVD severity

Progression of MRI markers in cerebral small vessel disease: sample size considerations for clinical trials.

Detecting treatment efficacy using cognitive change in trials of cerebral small vessel disease (SVD) has been challenging, making the use of surrogate markers such as magnetic resonance imaging (MRI) attractive. We determined the sensitivity of MRI to change in SVD and used this information to calculate sample size estimates for a clinical trial. Data from the prospective SCANS (St George's Cognition and Neuroimaging in Stroke) study of patients with symptomatic lacunar stroke and confluent leukoaraiosis was used (n=121). Ninety-nine subjects returned at one or more time points. Multimodal MRI and neuropsychologic testing was performed annually over 3 years. We evaluated the change in brain volume, T2 white matter hyperintensity (WMH) volume, lacunes, and white matter damage on diffusion tensor imaging (DTI). Over 3 years, change was detectable in all MRI markers but not in cognitive measures. WMH volume and DTI parameters were most sensitive to change and therefore had the smallest sample size estimates. MRI markers, particularly WMH volume and DTI parameters, are more sensitive to SVD progression over short time periods than cognition. These markers could significantly reduce the size of trials to screen treatments for efficacy in SVD, although further validation from longitudinal and intervention studies is required.Journal of Cerebral Blood Flow & Metabolism advance online publication, 3 June 2015; doi:10.1038/jcbfm.2015.113

Lacunar Infarcts, but Not Perivascular Spaces, Are Predictors of Cognitive Decline in Cerebral Small-Vessel Disease.

BACKGROUND AND PURPOSE: Cerebral small-vessel disease is a major cause of cognitive impairment. Perivascular spaces (PvS) occur in small-vessel disease, but their relationship to cognitive impairment remains uncertain. One reason may be difficulty in distinguishing between lacunes and PvS. We determined the relationship between baseline PvS score and PvS volume with change in cognition over a 5-year follow-up. We compared this to the relationship between baseline lacune count and total lacune volume with cognition. In addition, we examined change in PvS volume over time. METHODS: Data from the prospective SCANS study (St Georges Cognition and Neuroimaging in Stroke) of patients with symptomatic lacunar stroke and confluent leukoaraiosis were used (n=121). Multimodal magnetic resonance imaging was performed annually for 3 years and neuropsychological testing annually for 5 years. Lacunes were manually identified and distinguished from PvS. PvS were rated using a validated visual rating scale, and PvS volumes calculated using T1-weighted images. Linear mixed-effect models were used to determine the impact of PvS and lacunes on cognition. RESULTS: Baseline PvS scores or volumes showed no association with cognitive indices. No change was detectable in PvS volumes over the 3 years. In contrast, baseline lacunes associated with all cognitive indices and predicted cognitive decline over the 5-year follow-up. CONCLUSIONS: Although a feature of small-vessel disease, PvS are not a predictor of cognitive decline, in contrast to lacunes. This study highlights the importance of carefully differentiating between lacunes and PvS in studies investigating vascular cognitive impairment

Mnemonic function in small vessel disease and associations with white matter tract microstructure.

Cerebral small vessel disease (SVD) is associated with deficits in working memory, with a relative sparing of long-term memory; function may be influenced by white matter microstructure. Working and long-term memory were examined in 106 patients with SVD and 35 healthy controls. Microstructure was measured in the uncinate fasciculi and cingula. Working memory was more impaired than long-term memory in SVD, but both abilities were reduced compared to controls. Regression analyses found that having SVD explained the variance in memory functions, with additional variance explained by the cingula (working memory) and uncinate (long-term memory). Performance can be explained in terms of integrity loss in specific white matter tract associated with mnemonic functions

Application of Diffusion Tensor Imaging Parameters to Detect Change in Longitudinal Studies in Cerebral Small Vessel Disease.

Cerebral small vessel disease (SVD) is the major cause of vascular cognitive impairment, resulting in significant disability and reduced quality of life. Cognitive tests have been shown to be insensitive to change in longitudinal studies and, therefore, sensitive surrogate markers are needed to monitor disease progression and assess treatment effects in clinical trials. Diffusion tensor imaging (DTI) is thought to offer great potential in this regard. Sensitivity of the various parameters that can be derived from DTI is however unknown. We aimed to evaluate the differential sensitivity of DTI markers to detect SVD progression, and to estimate sample sizes required to assess therapeutic interventions aimed at halting decline based on DTI data. We investigated 99 patients with symptomatic SVD, defined as clinical lacunar syndrome with MRI confirmation of a corresponding infarct as well as confluent white matter hyperintensities over a 3 year follow-up period. We evaluated change in DTI histogram parameters using linear mixed effect models and calculated sample size estimates. Over a three-year follow-up period we observed a decline in fractional anisotropy and increase in diffusivity in white matter tissue and most parameters changed significantly. Mean diffusivity peak height was the most sensitive marker for SVD progression as it had the smallest sample size estimate. This suggests disease progression can be monitored sensitively using DTI histogram analysis and confirms DTI's potential as surrogate marker for SVD

Identifying preclinical vascular dementia in symptomatic small vessel disease using MRI.

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