White matter hyperintensity lesion burden is associated with the infarct volume and 90-day outcome in small subcortical infarcts.
ABSTRACT: Small subcortical infarcts (SSI) frequently coexist with brain white matter hyperintensity (WMH) lesions. We sought to determine whether preexisting WMH burden relates to SSI volume, SSI etiology, and 90-day functional outcome.We retrospectively studied 80 consecutive patients with acute SSI. Infarct volume was determined on diffusion weighted imaging, and WMH burden was graded on fluid-attenuated inversion recovery sequences according to the Fazekas scale. SSI etiology was categorized as small vessel disease (SVD) vs non-SVD related. Multivariable linear and logistic regression models were constructed to determine whether WMH burden was independently associated with the SSI volume and a poor 90-day outcome (modified Rankin scale [mRS] score >2), respectively.In unadjusted analyses, patients with non-SVD-related SSI were older (P=.002) and more frequently had multiple infarcts (P<.001) than patients with SVD-related SSI. In the fully adjusted model, WMH severity (Coefficient 0.07; 95%-CI 0.029-0.117; P=.002) but not SSI etiology (P>.1) was independently associated with the SSI volume. On multivariable logistic regression, worse WMH (OR 2.28; 95%-CI 1.04-4.99; P=.040), SSI etiology (OR 9.20; 95%-CI 1.04-81.39; P=.046), preadmission mRS (OR 8.96; 95%-CI 2.65-30.27; P<.001), and SSI volume (OR 1.98; 95%-CI 1.14-3.44; P=.016) were associated with a poor 90-day outcome.Greater WMH burden is independently associated with a larger SSI volume and a worse 90-day outcome.
Project description:Background: Cerebral small vessel disease (SVD) is generally considered as a cause of stroke, disability, gait disturbances, vascular cognitive impairment, and dementia. The aim of this study was to investigate whether the total SVD burden can be used to predict functional outcome in patients with acute ischemic stroke. Methods: From April 2017 to January 2018, consecutive patients with acute ischemic stroke who underwent baseline MRI scan were evaluated. The functional outcome was assessed using the modified Rankin Scale (mRS) at 90 days and defined as i) excellent outcome (mRS ? 1) and ii) good outcome (mRS ? 2). Brain MRI was performed and assessed for lacunes, white matter hyperintensities (WMH), and enlarged perivascular spaces (EPVS). The total SVD burden was calculated based on lacunes, WMH, and EPVS and then summed up to generate an ordinal "total SVD burden" (range 0-3). Bivariate logistic regression models were used to identify the association between SVD and functional outcome. Results: A total of 416 patients were included in the final analysis; 44.0, 33.4, 19.2, and 3.4% of the patients had 0, 1, 2, and 3 features of SVD, respectively. In regard to individual SVD feature, lacunes (OR: 0.48, 95% CI: 0.32-0.71; OR: 0.49, 95% CI: 0.31-0.77) and WMH (OR: 0.53, 95% CI: 0.34-0.82; OR: 0.53, 95% CI: 0.33-0.85) were negatively associated with excellent outcome and good outcome. As to the total burden of SVD, three SVD features had strongest negative associations with functional outcomes (excellent outcome, OR: 0.13, 95% CI: 0.03-0.48; good outcome, OR: 0.18, 95% CI: 0.06-0.54). After adjustment for potential confounders, a high SVD burden (3 features, OR: 0.07, 95% CI: 0.01-0.41) and the score of total SVD burden (OR: 0.64, 95% CI: 0.44-0.93) remained negatively associated with excellent outcome. Conclusion: Total SVD burden negatively associated with functional outcome at 3 months in patients with acute ischemic stroke and is superior to individual SVD feature in prediction of functional outcome. MRI-based assessment of total SVD burden is highly valuable in clinical management of stroke victims and could help guide the allocation of resources to improve outcome.
Project description:Cerebrovascular disease (CVD) may contribute to mild cognitive impairment (MCI). We sought to determine the relation of white matter hyperintensity (WMH) volume and infarcts in brain MRI to MCI in a community-based sample.A total of 679 elderly persons without dementia underwent brain MRI. WMH and infarcts were quantified using research methods. WMH was adjusted for total cranial volume. The Petersen criteria were used to define MCI. MCI was further subclassified into amnestic and non-amnestic. We used logistic regression to relate WMH and infarcts to prevalent MCI.WMH were associated with amnestic MCI (odds ratio [OR] = 1.9; 95% confidence interval [CI] 1.1, 3.4) but not non-amnestic MCI (OR = 1.2; 95% CI 0.4, 1.6) after adjusting for age, gender, ethnic group, education, and APOE-epsilon4. Infarcts were more strongly associated with non-amnestic MCI (OR = 2.7; 95% CI 1.5, 4.8) than amnestic MCI (OR = 1.4; 95% CI 0.9, 2.3). In secondary analyses using continuous cognitive scores as outcomes, WMH, but not infarcts, were related to memory, while infarcts were more strongly related with non-amnestic domains.White matter hyperintensity (WMH) is more strongly related to amnestic mild cognitive impairment (MCI). Infarcts are more strongly related to non-amnestic MCI. The nature of WMH in amnestic MCI requires further study.
Project description:BACKGROUND AND PURPOSE:Perivascular Spaces (PVS), also known as Virchow-Robin spaces, seen on structural brain MRI, are important fluid drainage conduits and are associated with small vessel disease (SVD). Computational quantification of visible PVS may enable efficient analyses in large datasets and increase sensitivity to detect associations with brain disorders. We assessed the associations of computationally-derived PVS parameters with vascular factors and white matter hyperintensities (WMH), a marker of SVD. PARTICIPANTS:Community dwelling individuals (n = 700) from the Lothian Birth Cohort 1936 who had multimodal brain MRI at age 72.6 years (SD = 0.7). METHODS:We assessed PVS computationally in the centrum semiovale and deep corona radiata on T2-weighted images. The computationally calculated measures were the total PVS volume and count per subject, and the mean individual PVS length, width and size, per subject. We assessed WMH by volume and visual Fazekas scores. We compared PVS visual rating to PVS computational metrics, and tested associations between each PVS measure and vascular risk factors (hypertension, diabetes, cholesterol), vascular history (cardiovascular disease and stroke), and WMH burden, using generalized linear models, which we compared using coefficients, confidence intervals and model fit. RESULTS:In 533 subjects, the computational PVS measures correlated positively with visual PVS ratings (PVS count r = 0.59; PVS volume r = 0.61; PVS mean length r = 0.55; PVS mean width r = 0.52; PVS mean size r = 0.47). PVS size and width were associated with hypertension (OR 1.22, 95% CI [1.03 to 1.46] and 1.20, 95% CI [1.01 to 1.43], respectively), and stroke (OR 1.34, 95% CI [1.08 to 1.65] and 1.36, 95% CI [1.08 to 1.71], respectively). We found no association between other PVS measures and diabetes, hypercholesterolemia or cardiovascular disease history. Computational PVS volume, length, width and size were more strongly associated with WMH (PVS mean size versus WMH Fazekas score ? = 0.66, 95% CI [0.59 to 0.74] and versus WMH volume ? = 0.43, 95% CI [0.38 to 0.48]) than computational PVS count (WMH Fazekas score ? = 0.21, 95% CI [0.11 to 0.3]; WMH volume ? = 0.14, 95% CI [0.09 to 0.19]) or visual score. Individual PVS size showed the strongest association with WMH. CONCLUSIONS:Computational measures reflecting individual PVS size, length and width were more strongly associated with WMH, stroke and hypertension than computational count or visual PVS score. Multidimensional computational PVS metrics may increase sensitivity to detect associations of PVS with risk exposures, brain lesions and neurological disease, provide greater anatomic detail and accelerate understanding of disorders of brain fluid and waste clearance.
Project description:To investigate the relation between baseline cerebral small vessel disease (SVD) and the risk of incident parkinsonism using different MRI and diffusion tensor imaging (DTI) measures.In the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort (RUN DMC) study, a prospective cohort study, 503 elderly participants with SVD and without parkinsonism were included in 2006. During follow-up (2011-2012), parkinsonism was diagnosed according to UK Brain Bank criteria. Cox regression analysis was used to investigate the association between baseline imaging measures and incident all-cause parkinsonism and vascular parkinsonism (VP). Tract-based spatial statistics analysis was used to identify differences in baseline DTI measures of white matter (WM) tracts between participants with VP and without parkinsonism.Follow-up was available from 501 participants (mean age 65.6 years; mean follow-up duration 5.2 years). Parkinsonism developed in 20 participants; 15 were diagnosed with VP. The 5-year risk of (any) parkinsonism was increased for those with a high white matter hyperintensity (WMH) volume (hazard ratio [HR] 1.8 per SD increase, 95% confidence interval [CI] 1.3-2.4) and a high number of lacunes (HR 1.4 per number increase, 95% CI 1.1-1.8) at baseline. For VP, this risk was also increased by the presence of microbleeds (HR 5.7, 95% CI 1.9-16.8) and a low gray matter volume (HR 0.4 per SD increase, 95% CI 0.2-0.8). Lower fractional anisotropy values in bifrontal WM tracts involved in movement control were observed in participants with VP compared to participants without parkinsonism.SVD at baseline, especially a high WMH volume and a high number of lacunes, is associated with incident parkinsonism. Our findings favor a role of SVD in the etiology of parkinsonism.
Project description: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.
Project description:BACKGROUND:Research in older adults with subjective cognitive decline (SCD) has mainly focused on Alzheimer's disease (AD)-related MRI markers, such as hippocampal volume. However, small vessel disease (SVD) is currently established as serious comorbidity in dementia and its preliminary stages. It is therefore important to examine SVD markers in addition to AD markers in older adults presenting with SCD. OBJECTIVE:The aim of our study was to elucidate the role of SVD markers in late middle-aged to older adults with and without SCD in addition to the commonly found role of AD markers (hippocampal volume). METHODS:67 healthy late middle-aged to older adults participated in this study (mean age 68 years); 25 participants with SCD and 42 participants without SCD. We evaluated quantitative as well as qualitative AD markers (i.e., hippocampal volume and medial temporal lobe atrophy (MTA) scale) and SVD markers (i.e., white matter hyperintensities (WMH) volume, Fazekas scale, microbleeds, and lacunar infarcts), and neuropsychological function and amount of memory complaints. RESULTS:We found a significant effect of SCD on hippocampal atrophy, as assessed using the MTA scale, but not on hippocampal volume. In addition, we found a significant effect of SCD, and amount of memory complaints, on WMH volume and Fazekas score, suggesting larger WMH volumes in participants with SCD. CONCLUSION:SVD MRI markers are related to amount of memory complaints, in addition to the commonly observed AD MRI markers, as demonstrated by the greater WMHs in healthy late middle-aged to older adults with SCD.
Project description:BACKGROUND AND PURPOSE:Serum neurofilament light (NfL)-chain is a circulating marker for neuroaxonal injury and is also associated with severity of cerebral small vessel disease (SVD) cross-sectionally. Here we explored the association of serum-NfL with imaging and cognitive measures in SVD longitudinally. METHODS:From 503 subjects with SVD, baseline and follow-up magnetic resonance imaging (MRI) was available for 264 participants (follow-up 8.7±0.2 years). Baseline serum-NfL was measured by an ultrasensitive single-molecule-assay. SVD-MRI-markers including white matter hyperintensity (WMH)-volume, mean diffusivity (MD), lacunes, and microbleeds were assessed at both timepoints. Cognitive testing was performed in 336 participants, including SVD-related domains as well as global cognition and memory. Associations with NfL were assessed using linear regression analyses and analysis of covariance (ANCOVA). RESULTS:Serum-NfL was associated with baseline WMH-volume, MD-values and presence of lacunes and microbleeds. SVD-related MRI- and cognitive measures showed progression during follow-up. NfL-levels were associated with future MRI-markers of SVD, including WMH, MD and lacunes. For the latter, this association was independent of baseline lacunes. Furthermore, NfL was associated with incident lacunes during follow-up (P=0.040). NfL-levels were associated with future SVD-related cognitive impairment (processing speed: ?=-0.159; 95% confidence interval [CI], -0.242 to -0.068; P=0.001; executive function ?=-0.095; 95% CI, -0.170 to -0.007; P=0.033), adjusted for age, sex, education, and depression. Dementia-risk increased with higher NfL-levels (hazard ratio, 5.0; 95% CI, 2.6 to 9.4; P<0.001), however not after adjusting for age. CONCLUSIONS:Longitudinally, serum-NfL is associated with markers of SVD, especially with incident lacunes, and future cognitive impairment affecting various domains. NfL may potentially serve as an additional marker for disease monitoring and outcome in SVD, potentially capturing both vascular and neurodegenerative processes in the elderly.
Project description:OBJECTIVE:To determine the contribution of acute infarcts, evidenced by diffusion-weighted imaging positive (DWI+) lesions, to progression of white matter hyperintensities (WMH) and other cerebral small vessel disease (SVD) markers. METHODS:We performed monthly 3T magnetic resonance imaging (MRI) for 10 consecutive months in 54 elderly individuals with SVD. MRI included high-resolution multishell DWI, and 3-dimensional fluid-attenuated inversion recovery, T1, and susceptibility-weighted imaging. We determined DWI+ lesion evolution, WMH progression rate (ml/mo), and number of incident lacunes and microbleeds, and calculated for each marker the proportion of progression explained by DWI+ lesions. RESULTS:We identified 39 DWI+ lesions on 21 of 472 DWI scans in 9 of 54 subjects. Of the 36 DWI+ lesions with follow-up MRI, 2 evolved into WMH, 4 evolved into a lacune (3 with cavity <3mm), 3 evolved into a microbleed, and 27 were not detectable on follow-up. WMH volume increased at a median rate of 0.027 ml/mo (interquartile range = 0.005-0.073), but was not significantly higher in subjects with DWI+ lesions compared to those without (p = 0.195). Of the 2 DWI+ lesions evolving into WMH on follow-up, one explained 23% of the total WMH volume increase in one subject, whereas the WMH regressed in the other subject. DWI+ lesions preceded 4 of 5 incident lacunes and 3 of 10 incident microbleeds. INTERPRETATION:DWI+ lesions explain only a small proportion of the total WMH progression. Hence, WMH progression seems to be mostly driven by factors other than acute infarcts. DWI+ lesions explain the majority of incident lacunes and small cavities, and almost one-third of incident microbleeds, confirming that WMH, lacunes, and microbleeds, although heterogeneous on MRI, can have a common initial appearance on MRI. ANN NEUROL 2019;86:582-592.
Project description:Cerebral small vessel disease (SVD) is a heterogeneous group of pathological disorders that affect the small vessels of the brain and are an important cause of cognitive impairment. The ischaemic consequences of this disease can be detected using MRI, and include white matter hyperintensities (WMH), lacunar infarcts and microhaemorrhages. The relationship between SVD disease severity, as defined by WMH volume, in sporadic age-related SVD and cortical thickness has not been well defined. However, regional cortical thickness change would be expected due to associated phenomena such as underlying ischaemic white matter damage, and the observation that widespread cortical thinning is observed in the related genetic condition CADASIL (Righart et al., 2013). Using MRI data, we have developed a semi-automated processing pipeline for the anatomical analysis of individuals with cerebral small vessel disease and applied it cross-sectionally to 121 subjects diagnosed with this condition. Using a novel combined automated white matter lesion segmentation algorithm and lesion repair step, highly accurate warping to a group average template was achieved. The volume of white matter affected by WMH was calculated, and used as a covariate of interest in a voxel-based morphometry and voxel-based cortical thickness analysis. Additionally, Gaussian Process Regression (GPR) was used to assess if the severity of SVD, measured by WMH volume, could be predicted from the morphometry and cortical thickness measures. We found significant (Family Wise Error corrected p < 0.05) volumetric decline with increasing lesion load predominately in the parietal lobes, anterior insula and caudate nuclei bilaterally. Widespread significant cortical thinning was found bilaterally in the dorsolateral prefrontal, parietal and posterio-superior temporal cortices. These represent distinctive patterns of cortical thinning and volumetric reduction compared to ageing effects in the same cohort, which exhibited greater changes in the occipital and sensorimotor cortices. Using GPR, the absolute WMH volume could be significantly estimated from the grey matter density and cortical thickness maps (Pearson's coefficients 0.80 and 0.75 respectively). We demonstrate that SVD severity is associated with regional cortical thinning. Furthermore a quantitative measure of SVD severity (WMH volume) can be predicted from grey matter measures, supporting an association between white and grey matter damage. The pattern of cortical thinning and volumetric decline is distinctive for SVD severity compared to ageing. These results, taken together, suggest that there is a phenotypic pattern of atrophy associated with SVD severity.
Project description:Background: Enlarged perivascular spaces (ePVS) are common finding on magnetic resonance imaging (MRI) in elderly. ePVS are thought to be associated with cerebral small vessel disease (SVD) such as white matter hyperintensities (WMH), lacunes, and cerebral microbleeds (CMBs). However, the different location of SVD and its relationship to ePVS distribution requires further investigation. Objective: To study the association between location and severity of SVD with ePVS from memory clinic and population-based settings. Methods: This study includes patients from an ongoing memory clinic based case-control study and participants from the population-based: Epidemiology of Dementia in Singapore study (EDIS). All participants underwent a comprehensive standardized evaluation including physical, medical and neuropsychological assessment and a brain MRI. CMBs and lacune location were categorized into strictly lobar, strictly deep and mixed, and ePVS location into centrum semiovale and basal ganglia. WMH volume was automatically segmented and was classified into anterior and posterior distribution. Negative binomial regression models were constructed to analyse associations between SVD and ePVS and the rate ratios (RR) and 95% confidence intervals (CI) were reported. Results: Of 375 patients (median age = 73 years) from memory clinic and 583 participants (median age = 70 years) from EDIS, the median total ePVS count was 17.0 and 7.0, respectively. Increased severity of SVD was not associated with total ePVS counts in both memory clinic and EDIS study. Analysis with the location of SVD and ePVS also showed similar results. However, in EDIS study, presence of ?2 lacunes [RR = 1.61, 95% CI = 1.3, 2.30, p = 0.009], presence of ?2 CMBs [RR = 1.40, 95% CI = 1.08, 1.83, p = 0.012], and higher volume of WMH [RR = 1.41, 95% CI = 1.10, 1.81, p = 0.006] were associated with basal ganglia ePVS independent of age, gender and vascular risk factors. Conclusion: In this study, we found that the ePVS were not associated with the location and severity of SVD in the memory-clinic patients. However, only severity of SVD was associated with basal ganglia ePVS in the population-based setting. Our findings will need to be studied further in different cohorts so as to understand the mechanism underlying different SVD types in subclinical and clinical phases as well as for predicting cognitive decline.