scholarly journals Apathy, but not depression, predicts all-cause dementia in cerebral small vessel disease

2020 ◽  
Vol 91 (9) ◽  
pp. 953-959
Author(s):  
Jonathan Tay ◽  
Robin G Morris ◽  
Anil M Tuladhar ◽  
Masud Husain ◽  
Frank-Erik de Leeuw ◽  
...  
Keyword(s):  
Predictive Models ◽  
Diffusion Tensor ◽  
Small Vessel Disease ◽  
Cerebral Small Vessel Disease ◽  
Model Fit ◽  
Small Vessel ◽  
Prodromal Symptom ◽  
Vessel Disease ◽  
Prospective Cohort Studies ◽  
Improved Model

ObjectiveTo determine whether apathy or depression predicts all-cause dementia in small vessel disease (SVD) patients.MethodsAnalyses used two prospective cohort studies of SVD: St. George’s Cognition and Neuroimaging in Stroke (SCANS; n=121) and Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort (RUN DMC; n=352). Multivariate Cox regressions were used to predict dementia using baseline apathy and depression scores in both datasets. Change in apathy and depression was used to predict dementia in a subset of 104 participants with longitudinal data from SCANS. All models were controlled for age, education and cognitive function.ResultsBaseline apathy scores predicted dementia in SCANS (HR 1.49, 95% CI 1.05 to 2.11, p=0.024) and RUN DMC (HR 1.05, 95% CI 1.01 to 1.09, p=0.007). Increasing apathy was associated with dementia in SCANS (HR 1.53, 95% CI 1.08 to 2.17, p=0.017). In contrast, baseline depression and change in depression did not predict dementia in either dataset. Including apathy in predictive models of dementia improved model fit.ConclusionsApathy, but not depression, may be a prodromal symptom of dementia in SVD, and may be useful in identifying at-risk individuals.

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

Diagnostics ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 720
Author(s):  
Larisa A. Dobrynina ◽  
Zukhra Sh. Gadzhieva ◽  
Kamila V. Shamtieva ◽  
Elena I. Kremneva ◽  
Bulat M. Akhmetzyanov ◽  
...  
Keyword(s):  
Blood Flow ◽  
Cognitive Impairment ◽  
White Matter ◽  
Diffusion Tensor ◽  
Small Vessel Disease ◽  
Cerebral Small Vessel Disease ◽  
Small Vessel ◽  
Venous Blood Flow ◽  
Csf Flow ◽  
Vessel Disease

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.

scholarly journals White Matter Microstructural Damage on Diffusion Tensor Imaging in Cerebral Small Vessel Disease

Stroke ◽  
2016 ◽  
Vol 47 (6) ◽  
pp. 1679-1684 ◽  
Author(s):  
Marco Pasi ◽  
Inge W.M. van Uden ◽  
Anil M. Tuladhar ◽  
Frank-Erik de Leeuw ◽  
Leonardo Pantoni
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Small Vessel Disease ◽  
Cerebral Small Vessel Disease ◽  
Small Vessel ◽  
Vessel Disease ◽  
Microstructural Damage

scholarly journals Diffusion tensor imaging and MR spectroscopy in hypertension and presumed cerebral small vessel disease

2008 ◽  
Vol 59 (3) ◽  
pp. 528-534 ◽  
Author(s):  
Arani Nitkunan ◽  
Rebecca A. Charlton ◽  
Dominick J.O. McIntyre ◽  
Thomas R. Barrick ◽  
Franklyn A. Howe ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Mr Spectroscopy ◽  
Diffusion Tensor ◽  
Small Vessel Disease ◽  
Cerebral Small Vessel Disease ◽  
Small Vessel ◽  
Vessel Disease

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

Stroke ◽  
2019 ◽  
Vol 50 (10) ◽  
pp. 2775-2782 ◽  
Author(s):  
Owen A. Williams ◽  
Eva A. Zeestraten ◽  
Philip Benjamin ◽  
Christian Lambert ◽  
Andrew J. Lawrence ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Diffusion Tensor ◽  
Small Vessel Disease ◽  
Cerebral Small Vessel Disease ◽  
Small Vessel ◽  
Diffusion Tensor Image ◽  
Vessel Disease ◽  
Segmentation Technique

scholarly journals Nonlinear temporal dynamics of cerebral small vessel disease

Neurology ◽  
2017 ◽  
Vol 89 (15) ◽  
pp. 1569-1577 ◽  
Author(s):  
Esther M.C. van Leijsen ◽  
Ingeborg W.M. van Uden ◽  
Mohsen Ghafoorian ◽  
Mayra I. Bergkamp ◽  
Valerie Lohner ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Diffusion Tensor ◽  
Small Vessel Disease ◽  
Cerebral Small Vessel Disease ◽  
Small Vessel ◽  
Quadratic Term ◽  
Vessel Disease ◽  
Semiautomatic Segmentation ◽  
Over Time

Objective:To investigate the temporal dynamics of cerebral small vessel disease (SVD) by 3 consecutive assessments over a period of 9 years, distinguishing progression from regression.Methods:Changes in SVD markers of 276 participants of the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Imaging Cohort (RUN DMC) cohort were assessed at 3 time points over 9 years. We assessed white matter hyperintensities (WMH) volume by semiautomatic segmentation and rated lacunes and microbleeds manually. We categorized baseline WMH severity as mild, moderate, or severe according to the modified Fazekas scale. We performed mixed-effects regression analysis including a quadratic term for increasing age.Results:Mean WMH progression over 9 years was 4.7 mL (0.54 mL/y; interquartile range 0.95–5.5 mL), 20.3% of patients had incident lacunes (2.3%/y), and 18.9% had incident microbleeds (2.2%/y). WMH volume declined in 9.4% of the participants during the first follow-up interval, but only for 1 participant (0.4%) throughout the whole follow-up. Lacunes disappeared in 3.6% and microbleeds in 5.7% of the participants. WMH progression accelerated over time: including a quadratic term for increasing age during follow-up significantly improved the model (p < 0.001). SVD progression was predominantly seen in participants with moderate to severe WMH at baseline compared to those with mild WMH (odds ratio [OR] 35.5, 95% confidence interval [CI] 15.8–80.0, p < 0.001 for WMH progression; OR 5.7, 95% CI 2.8–11.2, p < 0.001 for incident lacunes; and OR 2.9, 95% CI 1.4–5.9, p = 0.003 for incident microbleeds).Conclusions:SVD progression is nonlinear, accelerating over time, and a highly dynamic process, with progression interrupted by reduction in some, in a population that on average shows progression.

[P2-411]: PREDICTING DEMENTIA IN CEREBRAL SMALL-VESSEL DISEASE USING AN AUTOMATIC DIFFUSION TENSOR IMAGE SEGMENTATION TECHNIQUE

2017 ◽  
Vol 13 (7S_Part_16) ◽  
pp. P789-P790
Author(s):  
Owen A. Williams ◽  
Eva Zeestraten ◽  
Philip Benjamin ◽  
Christian Lambert ◽  
Andrew J. Lawrence ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Diffusion Tensor ◽  
Small Vessel Disease ◽  
Cerebral Small Vessel Disease ◽  
Small Vessel ◽  
Diffusion Tensor Image ◽  
Vessel Disease ◽  
Segmentation Technique

scholarly journals Using DTI to assess white matter microstructure in cerebral small vessel disease (SVD) in multicentre studies

2017 ◽  
Vol 131 (12) ◽  
pp. 1361-1373 ◽  
Author(s):  
Iain D. Croall ◽  
Valerie Lohner ◽  
Barry Moynihan ◽  
Usman Khan ◽  
Ahamad Hassan ◽  
...  
Keyword(s):  
White Matter ◽  
Diffusion Tensor ◽  
Small Vessel Disease ◽  
Mean Diffusivity ◽  
Peak Height ◽  
Cerebral Small Vessel Disease ◽  
Small Vessel ◽  
Single Centre ◽  
Vessel Disease ◽  
Multicentre Studies

Diffusion tensor imaging (DTI) metrics such as fractional anisotropy (FA) and mean diffusivity (MD) have been proposed as clinical trial markers of cerebral small vessel disease (SVD) due to their associations with outcomes such as cognition. However, studies investigating this have been predominantly single-centre. As clinical trials are likely to be multisite, further studies are required to determine whether associations with cognition of similar strengths can be detected in a multicentre setting. One hundred and nine patients (mean age =68 years) with symptomatic lacunar infarction and confluent white matter hyperintensities (WMH) on MRI was recruited across six sites as part of the PRESERVE DTI substudy. After handling missing data, 3T-MRI scanning was available from five sites on five scanner models (Siemens and Philips), alongside neuropsychological and quality of life (QoL) assessments. FA median and MD peak height were extracted from DTI histogram analysis. Multiple linear regressions were performed, including normalized brain volume, WMH lesion load, and n° lacunes as covariates, to investigate the association of FA and MD with cognition and QoL. DTI metrics from all white matter were significantly associated with global cognition (standardized β =0.268), mental flexibility (β =0.306), verbal fluency (β =0.376), and Montreal Cognitive Assessment (MoCA) (β =0.273). The magnitudes of these associations were comparable with those previously reported from single-centre studies found in a systematic literature review. In this multicentre study, we confirmed associations between DTI parameters and cognition, which were similar in strength to those found in previous single-centre studies. The present study supports the use of DTI metrics as biomarkers of disease progression in multicentre studies.

scholarly journals Diffusion tensor tractography in cerebral small vessel disease: correlation with cognitive function

2017 ◽  
Vol 31 (1) ◽  
pp. 83-89 ◽  
Author(s):  
Maria M D’Souza ◽  
SP Gorthi ◽  
Kunal Vadwala ◽  
Richa Trivedi ◽  
C Vijayakumar ◽  
...  
Keyword(s):  
Cognitive Function ◽  
White Matter ◽  
Diffusion Tensor ◽  
Small Vessel Disease ◽  
Surrogate Marker ◽  
Mean Diffusivity ◽  
Cerebral Small Vessel Disease ◽  
Small Vessel ◽  
White Matter Damage ◽  
Vessel Disease

Background Patients with cerebral small vessel disease may suffer from varying levels of cognitive deficit and may progress on to vascular dementia. The extent of involvement, as seen on conventional magnetic resonance (MR) measures, correlates poorly with the level of cognitive decline. The purpose of this study was to investigate the utility of diffusion tensor imaging (DTI) as a marker for white matter damage in small vessel disease and to assess its correlation with cognitive function. Methods Thirty consecutive patients with cerebral small vessel disease underwent conventional MR imaging, DTI, and neuropsychological assessment. Results On tractographic analysis, fractional anisotropy was significantly reduced while mean diffusivity significantly increased in several white matter tracts. The alteration in DTI indices correlated well with cognitive function. No significant correlation was identified between T2 lesion load and cognitive performance. Conclusions Tractographic analysis of white matter integrity is a useful measure of disease severity and correlates well with cognitive function. It may have a significant potential in monitoring disease progression and may serve as a surrogate marker for treatment trials.

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