Dataset Information

Nonlinear temporal dynamics of cerebral small vessel disease: The RUN DMC study.

ABSTRACT: 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.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.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).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.

SUBMITTER: van Leijsen EMC

PROVIDER: S-EPMC5634663 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Nonlinear temporal dynamics of cerebral small vessel disease: The RUN DMC study.

van Leijsen Esther M C EMC van Uden Ingeborg W M IWM Ghafoorian Mohsen M Bergkamp Mayra I MI Lohner Valerie V Kooijmans Eline C M ECM van der Holst Helena M HM Tuladhar Anil M AM Norris David G DG van Dijk Ewoud J EJ Rutten-Jacobs Loes C A LCA Platel Bram B Klijn Catharina J M CJM de Leeuw Frank-Erik FE

Neurology 20170906 15

<h4>Objective</h4>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.<h4>Methods</h4>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 la ...[more]

PMID: 28878046

Similar Datasets

Project description:ImportanceNeuropathology studies show a high prevalence of cortical microinfarcts (CMIs) in aging individuals, especially in patients with cerebrovascular disease and dementia. However, most, are invisible on T1- and T2-weighted magnetic resonance imaging (MRI), raising the question of how to explain this mismatch. Studies on small acute infarcts, detected on diffusion-weighted imaging (DWI), suggest that infarcts are largest in their acute phase and reduce in size thereafter. Therefore, we hypothesized that a subset of the CMI that are invisible on MRI can be detected on MRI in their acute phase. However, to our knowledge, a serial imaging study investigating the temporal dynamics of acute CMI (A-CMI) is lacking.ObjectiveTo determine the prevalence of chronic CMI (C-CMI) and the cumulative incidence and temporal dynamics of A-CMI in individuals with cerebral small vessel disease (SVD).Design, setting, participants and exposuresThe RUN DMC-Intense study is a single-center hospital-based prospective cohort study on SVD performed between March 2016 and November 2017 and comprising 10 monthly 3-T MRI scans, including high-resolution DWI, 3-dimensional T1, 3-dimensional fluid-attenuated inversion recovery, and T2. One hundred six individuals from the previous longitudinal RUN DMC study were recruited based on the presence of progression of white matter hyperintensities on MRI between 2006 and 2015 and exclusion of causes of cerebral ischemia other than SVD. Fifty-four individuals (50.9%) participated. The median total follow-up duration was 39.5 weeks (interquartile range, 37.8-40.3). Statistical data analysis was performed between May and October 2019.Main outcomes and measuresWe determined the prevalence of C-CMI using the baseline T1, fluid-attenuated inversion recovery, and T2 scans. Monthly high-resolution DWI scans (n = 472) were screened to determine the cumulative incidence of A-CMI. The temporal dynamics of A-CMI were determined based on the MRI scans collected during the first follow-up visit after A-CMI onset and the last available follow-up visit.ResultsThe median age of the cohort at baseline MRI was 69 years (interquartile range, 66-74 years) and 34 participants (63%) were men. The prevalence of C-CMI was 35% (95% CI, 0.24-0.49). Monthly DWI detected 21 A-CMI in 7 of 54 participants, resulting in a cumulative incidence of 13% (95% CI, 0.06-0.24). All A-CMI disappeared on follow-up MRI.Conclusions and relevanceAcute CMI never evolved into chronically MRI-detectable lesions. We suggest that these A-CMI underlie part of the submillimeter C-CMI encountered on neuropathological examination and thereby provide a source for the high CMI burden on neuropathology.

Project description:BackgroundThe aim of this study is to investigate the temporal dynamics of small vessel disease (SVD) and the effect of vascular risk factors and baseline SVD burden on progression of SVD with 4 neuroimaging assessments over 14 years in patients with SVD.MethodsFive hundred three patients with sporadic SVD (50-85 years) from the ongoing prospective cohort study (RUN DMC [Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort]) underwent baseline assessment in 2006 and follow-up in 2011, 2015, and 2020. Vascular risk factors and magnetic resonance imaging markers of SVD were evaluated. Linear mixed-effects model and negative binomial regression model were used to examine the determinants of temporal dynamics of SVD markers.ResultsA total of 382 SVD patients (mean [SD] 64.1 [8.4]; 219 men and 163 women) who underwent at least 2 serial brain magnetic resonance imaging scans were included, with mean (SD) follow-up of 11.15 (3.32) years. We found a highly variable temporal course of SVD. Mean (SD) WMH progression rate was 0.6 (0.74) mL/y (range, 0.02-4.73 mL/y) and 13.6% of patients had incident lacunes (1.03%/y) over the 14-year follow-up. About 4% showed net WMH regression over 14 years, whereas 38 out of 361 (10.5%), 5 out of 296 (2%), and 61 out of 231 (26%) patients showed WMH regression for the intervals 2006 to 2011, 2011 to 2015, and 2015 to 2020, respectively. Of these, 29 (76%), 5 (100%), and 57 (93%) showed overall progression across the 14-year follow-up, and the net overall WMH change between first and last scan considering all participants was a net average WMH progression over the 14-year period. Older age was a strong predictor for faster WMH progression and incident lacunes. Patients with mild baseline WMH rarely progressed to severe WMH. In addition, both baseline burden of SVD lesions and vascular risk factors independently and synergistically predicted WMH progression, whereas only baseline SVD burden predicted incident lacunes over the 14-year follow-up.ConclusionsSVD shows pronounced progression over time, but mild WMH rarely progresses to clinically severe WMH. WMH regression is noteworthy during some magnetic resonance imaging intervals, although it could be overall compensated by progression over the long follow-up.

Project description:Background and Objective: Studies on relations between arterial stiffness and full spectrum of radiological features of cerebral small vessel disease (CSVD) are scarce. We aim to investigate the association of arterial stiffness with lacunes, white matter hyperintensities (WMH), microbleeds (CMBs), dilated perivascular spaces (PVS), and brain atrophy in a community-based sample. Methods: A total of 953 participants (55.7 ± 9.4 years) who underwent brachial-ankle pulse wave velocity (baPWV) and brain magnetic resonance imaging were included. Lacunes, CMBs, and PVS were visually rated. Brain structure and WMH were automatically segmented. Brain parenchyma fraction (BPF), a surrogate index of brain atrophy, was calculated as a ratio of brain parenchyma volume to total intracranial volume. Multivariable logistic and linear regressions were used to investigate the associations between baPWV and CSVD. Subsequently, we explored these associations in strata of age. Results: Increased baPWV was associated with severe PVS in white matter (OR, 1.09; 95%CI, 1.01-1.17; p = 0.022), larger WMH volume (β, 0.08; 95%CI, 0.04-0.12; p < 0.001), lower BPF (β, -0.09; 95%CI, -0.15- -0.03; p = 0.007), and marginally associated with strictly lobar CMBs (OR, 1.11; 95%CI, 1.00-1.23; p = 0.055), but not with lacunes. WMH volume mediated the relation between baPWV and BPF. In age subgroup analysis, the association of baPWV with PVS in white matter was stronger among those aged <55 years, whereas the association with brain atrophy was more prominent among those aged ≥55 years. Increased baPWV was associated with larger WMH volume in both younger and older individuals. Conclusions: Increased arterial stiffness was associated with most of imaging markers of CSVD, including PVS in white matter, larger WMH volume, strictly lobar CMBs, and brain atrophy, but not lacunes. The mechanisms underlying these associations and their potential clinical significances warrant further investigations.

Dataset Information

Nonlinear temporal dynamics of cerebral small vessel disease: The RUN DMC study.

Publications

Nonlinear temporal dynamics of cerebral small vessel disease: The RUN DMC study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets