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

Williams, Owen A.; Zeestraten, Eva; Benjamin, Philip; Lambert, Christian; Lawrence, Andrew J.; MacKinnon, Andrew D.; Morris, Robin G.; Markus, Hugh S.; Barrick, Thomas R.; Charlton, Rebecca A.

doi:10.1161/strokeaha.119.025843

Cited by 20 publications

(20 citation statements)

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“…In line with this hypothesis, our results suggest that disconnectivity plays a role already in the preclinical stages of dementia. The findings in this study also extend results from clinical studies in patients with cerebral small vessel disease to the general population, [14][15][16][17] suggesting that measures of FA/MD may improve prognostic accuracy of existing prediction models to identify persons at high risk of dementia in the community. Furthermore, knowledge of tract-specific effects on cognition and risk of dementia may allow clinicians to better understand why specific patients with only small, but strategically located brain infarcts develop cognitive impairment, and which patients after stroke are most likely to develop dementia.…”

Section: Discussionsupporting

confidence: 74%

“…13 In 4 longitudinal studies from 2 clinical cohorts of patients with small vessel disease, network disruption was related to accelerated decline in psychomotor speed and an increased risk of dementia. [14][15][16][17] However, patients with substantial small vessel disease on MRI represent a minority of the individuals at high risk of dementia in the community, and it remains undetermined whether prior findings extend to the wider population without severe small vessel disease, prior TIA, or stroke. In addition, study in persons with and without small vessel disease may better determine the effect of disconnectivity on dementia, above and beyond the burden of, for example, WMHs.…”

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confidence: 99%

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Structural disconnectivity and the risk of dementia in the general population

et al. 2020

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Objective:The ‘disconnectivity hypothesis’ postulates that partial loss of connecting white matter fibers between brain regions contributes to the development of dementia. Using diffusion-magnetic resonance imaging (MRI) to quantify global and tract-specific white matter microstructural integrity, we tested this hypothesis in a longitudinal population-based study.Methods:Global and tract-specific fractional anisotropy (FA) and mean diffusivity (MD) were obtained in 4,415 non-demented persons (mean age: 63.9 years, 55.0% women) from the prospective population-based Rotterdam Study with brain MRI between 2005-2011. We modelled the association of these diffusion measures with risk of dementia (follow-up until 2016), and with changes on repeated cognitive assessment after on average 5.4 years, adjusting for age, sex, education, macrostructural MRI markers, depressive symptoms, cardiovascular risk factors, and APOE genotype.Results:During a mean follow-up of 6.7 years, 101 participants had incident dementia, of whom 83 had clinical AD. Lower global values of FA and higher values of MD were associated with an increased risk of dementia (adjusted hazard ratio [95% confidence interval] per standard deviation increase – for MD: 1.79 [1.44-2.23], and FA: 0.65 [0.52;0.80]). Similarly, lower global values of FA and higher values of MD related to more cognitive decline in non-demented individuals (difference in global cognition per standard deviation increase in MD (95% CI) was: -0.04 (-0.07;-0.01)). Associations were most profound in the projection, association and limbic system tracts.Conclusions:Structural disconnectivity is associated with and an increased risk of dementia and more pronounced cognitive decline in the general population.

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Section: Discussionsupporting

confidence: 74%

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confidence: 99%

Structural disconnectivity and the risk of dementia in the general population

et al. 2020

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“…Furthermore, multi-shell diffusion MRI techniques (msdMRI), including the neurite orientation dispersion and density imaging (NODDI) model consisting of intracellular volume fraction (ICVF), orientation dispersion index (ODI), and isotropic volume fraction (ISO), have been shown to more sensitively evaluate neuritic microstructure alterations than DTI [ 7 ]. Using DTI, the association of white-matter fiber tract disorders with cognitive decline has been reported in vascular dementia, as well as small vessel diseases in hemodialysis patients [ 8 , 9 , 10 , 11 ], although no evidence is currently available for the analysis of white-matter fiber tracts using msdMRI techniques.…”

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confidence: 99%

Possible Neuroprotective Effects of l-Carnitine on White-Matter Microstructural Damage and Cognitive Decline in Hemodialysis Patients

et al. 2021

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Although l-carnitine alleviated white-matter lesions in an experimental study, the treatment effects of l-carnitine on white-matter microstructural damage and cognitive decline in hemodialysis patients are unknown. Using novel diffusion magnetic resonance imaging (dMRI) techniques, white-matter microstructural changes together with cognitive decline in hemodialysis patients and the effects of l-carnitine on such disorders were investigated. Fourteen hemodialysis patients underwent dMRI and laboratory and neuropsychological tests, which were compared across seven patients each in two groups according to duration of l-carnitine treatment: (1) no or short-term l-carnitine treatment (NSTLC), and (2) long-term l-carnitine treatment (LTLC). Ten age- and sex-matched controls were enrolled. Compared to controls, microstructural disorders of white matter were widely detected on dMRI of patients. An autopsy study of one patient in the NSTLC group showed rarefaction of myelinated fibers in white matter. With LTLC, microstructural damage on dMRI was alleviated along with lower levels of high-sensitivity C-reactive protein and substantial increases in carnitine levels. The LTLC group showed better achievement on trail making test A, which was correlated with amelioration of disorders in some white-matter tracts. Novel dMRI tractography detected abnormalities of white-matter tracts after hemodialysis. Long-term treatment with l-carnitine might alleviate white-matter microstructural damage and cognitive impairment in hemodialysis patients.

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“…RD offers better predictability of a reduction in executive function than AD [ 25 ]. Williams et al (2017, 2019) proposed a method for automatic DTI segmentation to obtain the coefficient of a surrogate measure of CSVD severity associated with executive dysfunction, the speed of information processing, global cognition, and predictive CI over several years of observation [ 26 , 27 ]. At the same time, the use of DTI methods that consider the distribution of changes reveals regional damage selectivity, which corresponds to impairments of specific cognitive functions [ 20 , 28 , 29 ] and allows the differentiation between vascular and degenerative dementia due to Alzheimer’s disease [ 30 ].…”

Section: Introductionmentioning

confidence: 99%

Microstructural Predictors of Cognitive Impairment in Cerebral Small Vessel Disease and the Conditions of Their Formation

et al. 2020

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Introduction: Cerebral small vessel disease (CSVD) is the leading cause of vascular and mixed degenerative cognitive impairment (CI). The variability in the rate of progression of CSVD justifies the search for sensitive predictors of CI. Materials: A total of 74 patients (48 women, average age 60.6 ± 6.9 years) with CSVD and CI of varying severity were examined using 3T MRI. The results of diffusion tensor imaging with a region of interest (ROI) analysis were used to construct a predictive model of CI using binary logistic regression, while phase-contrast magnetic resonance imaging and voxel-based morphometry were used to clarify the conditions for the formation of CI predictors. Results: According to the constructed model, the predictors of CI are axial diffusivity (AD) of the posterior frontal periventricular normal-appearing white matter (pvNAWM), right middle cingulum bundle (CB), and mid-posterior corpus callosum (CC). These predictors showed a significant correlation with the volume of white matter hyperintensity; arterial and venous blood flow, pulsatility index, and aqueduct cerebrospinal fluid (CSF) flow; and surface area of the aqueduct, volume of the lateral ventricles and CSF, and gray matter volume. Conclusion: Disturbances in the AD of pvNAWM, CB, and CC, associated with axonal damage, are a predominant factor in the development of CI in CSVD. The relationship between AD predictors and both blood flow and CSF flow indicates a disturbance in their relationship, while their location near the floor of the lateral ventricle and their link with indicators of internal atrophy, CSF volume, and aqueduct CSF flow suggest the importance of transependymal CSF transudation when these regions are damaged.

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

Abstract: Supplemental Digital Content is available in the text.

Cited by 20 publications

References 39 publications

Structural disconnectivity and the risk of dementia in the general population

Structural disconnectivity and the risk of dementia in the general population

Possible Neuroprotective Effects of l-Carnitine on White-Matter Microstructural Damage and Cognitive Decline in Hemodialysis Patients

Microstructural Predictors of Cognitive Impairment in Cerebral Small Vessel Disease and the Conditions of Their Formation

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