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Background and Objectives: Patients with cerebral small vessel disease (SVD) show a heterogenous clinical course. The aim of the current study was to investigate the longitudinal course of cognitive and motor function in patients who developed parkinsonism, dementia, both, or none., Methods: Participants were from the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort study, a prospective cohort of patients with SVD. Parkinsonism and dementia were, respectively, diagnosed according to the UK Parkinson's Disease Society brain bank criteria and the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, criteria for major neurocognitive disorder. Linear and generalized linear mixed-effect analyses were used to study the longitudinal course of motor and cognitive tasks., Results: After a median follow-up of 12.8 years (interquartile range 10.2-15.3), 132 of 501 (26.3%) participants developed parkinsonism, dementia, or both. Years before diagnosis of these disorders, participants showed distinct clinical trajectories from those who developed none: Participant who developed parkinsonism had an annual percentage of 22% (95% CI 18%-27%) increase in motor part of the Unified Parkinson's Disease Rating Scale score. This was significantly higher than the 16% (95% CI 14%-18%) of controls, mainly because of a steep increase in bradykinesia and posture and gait disturbances. When they developed dementia as well, the increase in Timed Up and Go Test time of 0.73 seconds per year (95% CI 0.58-0.87) was significantly higher than the 0.20 seconds per year increase (95% CI 0.16-0.23) of controls. All groups, including the participants who developed parkinsonism without dementia, showed a faster decline in executive function compared with controls: Annual decline in Z -score was -0.07 (95% CI -0.10 to -0.05), -0.09 (95% CI -0.11 to -0.08), and -0.11 (95% CI -0.14 to -0.08) for participants who developed, respectively, parkinsonism, dementia, and both parkinsonism and dementia. These declines were all significantly faster than the annual decline in Z -score of 0.07 (95% CI -0.10 to -0.05) of controls., Discussion: A distinct pattern in deterioration of clinical markers is visible in patients with SVD, years before the diagnosis of parkinsonism and dementia. This knowledge aids early identification of patients with a high risk of developing these disorders.

Background: Small hyperintense lesions are found on diffusion-weighted imaging (DWI) in patients with sporadic small vessel disease (SVD). Their exact role in SVD progression remains unclear due to their asymptomatic and transient nature. The main objective is to investigate the role of DWI+lesions in the radiological progression of SVD and their relationship with clinical outcomes., Methods: Participants with SVD were included from the Radboud University Nijmegen Diffusion tensor MRI Cohort. DWI+lesions were assessed on four time points over 14 years. Outcome measures included neuroimaging markers of SVD, cognitive performance and clinical outcomes, including stroke, all-cause dementia and all-cause mortality. Linear mixed-effect models and Cox regression models were used to examine the outcome measures in participants with a DWI+lesion (DWI+) and those without a DWI+lesion (DWI-)., Results: DWI+lesions were present in 45 out of 503 (8.9%) participants (mean age: 66.7 years (SD=8.3)). Participants with DWI+lesions and at least one follow-up (n=33) had higher white matter hyperintensity progression rates (β=0.36, 95% CI=0.05 to 0.68, p = 0.023), more incident lacunes (incidence rate ratio=2.88, 95% CI=1.80 to 4.67, p<0.001) and greater cognitive decline (β=-0.03, 95% CI=-0.05 to -0.01, p=0.006) during a median follow-up of 13.2 (IQR: 8.8-13.8) years compared with DWI- participants. No differences were found in risk of all-cause mortality, stroke or dementia., Conclusion: Presence of a DWI+lesion in patients with SVD is associated with greater radiological progression of SVD and cognitive decline compared with patients without DWI+lesions., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Cerebral small vessel disease (cSVD) is a major cause of stroke and dementia. Previous studies on the prevalence of cSVD are mostly based on single geographically defined cohorts in high-income countries. Studies investigating the prevalence of cSVD in low- and middle-income countries (LMICs) are expanding but have not been systematically assessed., Aim: This study aims to systematically review the prevalence of cSVD in LMICs., Results: Articles were searched from the Ovid MEDLINE and EMBASE databases from 1 January 2000 to 31 March 2022, without language restrictions. Title/abstract screening, full-text review, and data extraction were performed by two to seven independent reviewers. The prevalence of cSVD and study sample size were extracted by pre-defined world regions and health status. The Risk of Bias for Non-randomized Studies tool was used. The protocol was registered on PROSPERO (CRD42022311133). A meta-analysis of proportion was performed to assess the prevalence of different magnetic resonance imaging markers of cSVD, and a meta-regression was performed to investigate associations between cSVD prevalence and type of study, age, and male: female ratio. Of 2743 studies identified, 42 studies spanning 12 global regions were included in the systematic review. Most of the identified studies were from China (n = 23). The median prevalence of moderate-to-severe white matter hyperintensities (WMHs) was 20.5%, 40.5%, and 58.4% in the community, stroke, and dementia groups, respectively. The median prevalence of lacunes was 0.8% and 33.5% in the community and stroke groups. The median prevalence of cerebral microbleeds (CMBs) was 10.7% and 22.4% in the community and stroke groups. The median prevalence of moderate-to-severe perivascular spaces was 25.0% in the community. Meta-regression analyses showed that the weighted median age (51.4 ± 0.0 years old; range: 36.3-80.2) was a significant predictor of the prevalence of moderate-to-severe WMH and lacunes, while the type of study was a significant predictor of the prevalence of CMB. The heterogeneity of studies was high (>95%). Male participants were overrepresented., Conclusions: This systematic review and meta-analysis provide data on cSVD prevalence in LMICs and demonstrated the high prevalence of the condition. cSVD research in LMICs is being published at an increasing rate, especially between 2010 and 2022. More data are particularly needed from Sub-Saharan Africa and Central Europe, Eastern Europe, and Central Asia.

Cerebral small vessel disease is a major cause of vascular cognitive impairment and dementia. There are few treatments, largely reflecting limited understanding of the underlying pathophysiology. Metabolomics can be used to identify novel risk factors to better understand pathogenesis and to predict disease progression and severity. We analysed data from 624 patients with symptomatic cerebral small vessel disease from two prospective cohort studies. Serum samples were collected at baseline and patients underwent MRI scans and cognitive testing at regular intervals with up to 14 years of follow-up. Using ultra-performance liquid chromatography-mass spectrometry and nuclear magnetic resonance spectroscopy, we obtained metabolic and lipidomic profiles from 369 annotated metabolites and 54 764 unannotated features and examined their association with respect to disease severity, assessed using MRI small vessel disease markers, cognition and future risk of all-cause dementia. Our analysis identified 28 metabolites that were significantly associated with small vessel disease imaging markers and cognition. Decreased levels of multiple glycerophospholipids and sphingolipids were associated with increased small vessel disease load as evidenced by higher white matter hyperintensity volume, lower mean diffusivity normalized peak height, greater brain atrophy and impaired cognition. Higher levels of creatine, FA(18:2(OH)) and SM(d18:2/24:1) were associated with increased lacune count, higher white matter hyperintensity volume and impaired cognition. Lower baseline levels of carnitines and creatinine were associated with higher annualized change in peak width of skeletonized mean diffusivity, and 25 metabolites, including lipoprotein subclasses, amino acids and xenobiotics, were associated with future dementia incidence. Our results show multiple distinct metabolic signatures that are associated with imaging markers of small vessel disease, cognition and conversion to dementia. Further research should assess causality and the use of metabolomic screening to improve the ability to predict future disease severity and dementia risk in small vessel disease. The metabolomic profiles may also provide novel insights into disease pathogenesis and help identify novel treatment approaches., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Objectives: Given the strong association between systemic inflammation and cognitive decline, we aimed to determine whether nonneurologic infections are associated with accelerated cognitive decline and structural changes in the brain using pre- and post-infection neuropsychologic assessments and repeated brain MR images., Design: Additional analysis of the prospective observational Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort study., Setting: Single-center study at the Radboud university medical center, Nijmegen, The Netherlands, between January 2006 and September 2015., Patients: Five-hundred three participants (50-85 yr old) with cerebral small vessel disease were included and followed for 9 years., Measurements and Main Results: Participants underwent repeated cognitive measurements and brain MRI. Infectious events were collected. Sepsis episodes were analyzed, and additionally, patients were stratified in three groups: having had a severe infectious episode (e.g., sepsis or hospitalization for infection), a mild, or no infectious episode. Development of dementia, trajectories of cognition, and structural brain changes on MRI in the subsequent follow-up periods were compared between the groups. Complete infectious data were available from 331 patients (mean age 64 ± 8 yr, 57% males). Twenty-nine participants (9%) suffered from a sepsis episode, 69 (21%) from a severe, 201 (61%) from a mild, and 61 (18%) had no infectious episode during follow-up. After correction for age, baseline cognition, and brain volume, each sepsis episode remained associated with an 82% increased risk to develop dementia within the follow-up period (hazard ratio, 1.82; 95% CI, 1.07-3.10; p = 0.027). Infections had no effect on the trajectory of structural changes to the brain after correction for baseline differences., Conclusions: In this 9-year observational follow-up study, sepsis episodes were associated with subsequent development of dementia. Nonneurologic infections had no effect on the trajectory of structural cerebral changes., Competing Interests: Drs. Meijer-van Leijsen and de Leeuw disclosed work for hire. Dr. de Leeuw received funding from a clinical established investigator grant from the Dutch Heart Foundation (2014T060) and by a Vidi innovational grant from The Netherlands ZonMw (grant number 016126351). Dr. Tuladhar received funding from the Dutch Heart Foundation (grant number 2016T044). Dr. Abdo received funding from a research grant from the Netherlands Organization for Health Research and Development (ZonMw Clinical Fellowship Grant 90715610). The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2022 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.)

Objectives: It has been suggested that diffusion tensor imaging (DTI) measures sensitive to white matter (WM) damage may predict future dementia risk not only in cerebral small vessel disease (SVD), but also in mild cognitive impairment. To determine whether DTI measures were associated with cognition cross-sectionally and predicted future dementia risk across the full range of SVD severity, we established the International OPtimising mulTImodal MRI markers for use as surrogate markers in trials of Vascular Cognitive Impairment due to cerebrAl small vesseL disease collaboration which included six cohorts., Methods: Among the six cohorts, prospective data with dementia incidences were available for three cohorts. The associations between six different DTI measures and cognition or dementia conversion were tested. The additional contribution to prediction of other MRI markers of SVD was also determined., Results: The DTI measure mean diffusivity (MD) median correlated with cognition in all cohorts, demonstrating the contribution of WM damage to cognition. Adding MD median significantly improved the model fit compared to the clinical risk model alone and further increased in all single-centre SVD cohorts when adding conventional MRI measures. Baseline MD median predicted dementia conversion. In a study with severe SVD (SCANS) change in MD median also predicted dementia conversion. The area under the curve was best when employing a multimodal MRI model using both DTI measures and other MRI measures., Conclusions: Our results support a central role for WM alterations in dementia pathogenesis in all cohorts. DTI measures such as MD median may be a useful clinical risk predictor. The contribution of other MRI markers varied according to disease severity., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: DTI is sensitive to white matter (WM) microstructural damage and has been suggested as a surrogate marker for phase 2 clinical trials in cerebral small vessel disease (SVD). The study's objective is to establish the best way to analyse the diffusion-weighted imaging data in SVD for this purpose. The ideal method would be sensitive to change and predict dementia conversion, but also straightforward to implement and ideally automated. As part of the OPTIMAL collaboration, we evaluated five different DTI analysis strategies across six different cohorts with differing SVD severity., Methods: Those 5 strategies were: (1) conventional mean diffusivity WM histogram measure (MD median), (2) a principal component-derived measure based on conventional WM histogram measures (PC1), (3) peak width skeletonized mean diffusivity (PSMD), (4) diffusion tensor image segmentation θ (DSEG θ) and (5) a WM measure of global network efficiency (Geff). The association between each measure and cognitive function was tested using a linear regression model adjusted by clinical markers. Changes in the imaging measures over time were determined. In three cohort studies, repeated imaging data together with data on incident dementia were available. The association between the baseline measure, change measure and incident dementia conversion was examined using Cox proportional-hazard regression or logistic regression models. Sample size estimates for a hypothetical clinical trial were furthermore computed for each DTI analysis strategy., Results: There was a consistent cross-sectional association between the imaging measures and impaired cognitive function across all cohorts. All baseline measures predicted dementia conversion in severe SVD. In mild SVD, PC1, PSMD and Geff predicted dementia conversion. In MCI, all markers except Geff predicted dementia conversion. Baseline DTI was significantly different in patients converting to vascular dementia than to Alzheimer' s disease. Significant change in all measures was associated with dementia conversion in severe but not in mild SVD. The automatic and semi-automatic measures PSMD and DSEG θ required the lowest minimum sample sizes for a hypothetical clinical trial in single-centre sporadic SVD cohorts., Conclusion: DTI parameters obtained from all analysis methods predicted dementia, and there was no clear winner amongst the different analysis strategies. The fully automated analysis provided by PSMD offers advantages particularly for large datasets., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Objective: To determine whether apathy or depression predicts all-cause dementia in small vessel disease (SVD) patients., Methods: Analyses 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., Results: Baseline 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., Conclusions: Apathy, but not depression, may be a prodromal symptom of dementia in SVD, and may be useful in identifying at-risk individuals., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)

Objective: To determine whether a simple small vessel disease (SVD) score, which uses information available on rapid visual assessment of clinical MRI scans, predicts risk of cognitive decline and dementia, above that provided by simple clinical measures., Methods: Three prospective longitudinal cohort studies (SCANS [St George's Cognition and Neuroimaging in Stroke], RUN DMC [Radboud University Nijmegen Diffusion Imaging and Magnetic Resonance Imaging Cohort], and the ASPS [Austrian Stroke Prevention Study]), which covered a range of SVD severity from mild and asymptomatic to severe and symptomatic, were included. In all studies, MRI was performed at baseline, cognitive tests repeated during follow-up, and progression to dementia recorded prospectively. Outcome measures were cognitive decline and onset of dementia during follow-up. We determined whether the SVD score predicted risk of cognitive decline and future dementia. We also determined whether using the score to select a group of patients with more severe disease would reduce sample sizes for clinical intervention trials., Results: In a pooled analysis of all 3 cohorts, the score improved prediction of dementia (area under the curve [AUC], 0.85; 95% confidence interval [CI], 0.81-0.89) compared with that from clinical risk factors alone (AUC, 0.76; 95% CI, 0.71-0.81). Predictive performance was higher in patients with more severe SVD. Power calculations showed selecting patients with a higher score reduced sample sizes required for hypothetical clinical trials by 40%-66% depending on the outcome measure used., Conclusions: A simple SVD score, easily obtainable from clinical MRI scans and therefore applicable in routine clinical practice, aided prediction of future dementia risk., (Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

This expert working group report proposes an updated approach to subtype definition of vascular parkinsonism (VaP) based on a review of the existing literature. The persistent lack of consensus on clear terminology and inconsistent conceptual definition of VaP formed the impetus for the current expert recommendation report. The updated diagnostic approach intends to provide a comprehensive tool for clinical practice. The preamble for this initiative is that VaP can be diagnosed in individual patients with possible prognostic and therapeutic consequences and therefore should be recognized as a clinical entity. The diagnosis of VaP is based on the presence of clinical parkinsonism, with variable motor and non-motor signs that are corroborated by clinical, anatomic or imaging findings of cerebrovascular disease. Three VaP subtypes are presented: (1) The acute or subacute post-stroke VaP subtype presents with acute or subacute onset of parkinsonism, which is typically asymmetric and responds to dopaminergic drugs; (2) The more frequent insidious onset VaP subtype presents with progressive parkinsonism with prominent postural instability, gait impairment, corticospinal, cerebellar, pseudobulbar, cognitive and urinary symptoms and poor responsiveness to dopaminergic drugs. A higher-level gait disorder occurs frequently as a dominant manifestation in the clinical spectrum of insidious onset VaP, and (3) With the emergence of molecular imaging biomarkers in clinical practice, our diagnostic approach also allows for the recognition of mixed or overlapping syndromes of VaP with Parkinson's disease or other neurodegenerative parkinsonisms. Directions for future research are also discussed., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Objective: We prospectively investigated the role of depressive symptoms (DS) on all-cause dementia in a population with small vessel disease (SVD), considering onset age of DS and cognitive performance., Methods: The RUN DMC study (Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort) is a prospective cohort study among 503 older adults with SVD on MRI without dementia at baseline (2006), with a follow-up of 5 years (2012). Kaplan-Meier curves stratified for DS and dementia risk were compared using log-rank test. We calculated hazard ratios using Cox regression analyses., Results: Follow-up was available for 496 participants (mean baseline age 65.6 years [SD 8.8]; mean follow-up time 5.2 years). All-cause dementia developed in 41 participants. The 5.5-year dementia risk was higher in those with DS (hazard ratio 2.7, 95% confidence interval 1.4-5.2), independent of confounders. This was driven by those with late-onset DS. Five-year cumulative risk difference for dementia was higher in participants with depressive symptoms who had high baseline cognitive performance (no DS 0.0% vs DS 6.9%, log-rank p < 0.001) compared with those who had low cognitive performance at baseline., Conclusions: Late-onset DS increases dementia risk, independent of SVD. Especially in those with relatively high cognitive performance, DS indicate a higher risk. In contrast to current practice, clinicians should monitor those with DS who also show relatively good cognitive test scores., (© 2016 American Academy of Neurology.)

Objective: To examine whether structural network connectivity at baseline predicts incident all-cause dementia in a prospective hospital-based cohort of elderly participants with MRI evidence of small vessel disease (SVD)., Methods: A total of 436 participants from the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort (RUN DMC), a prospective hospital-based cohort of elderly without dementia with cerebral SVD, were included in 2006. During follow-up (2011-2012), dementia was diagnosed. The structural network was constructed from baseline diffusion tensor imaging followed by deterministic tractography and measures of efficiency using graph theory were calculated. Cox proportional regression analyses were conducted., Results: During 5 years of follow-up, 32 patients developed dementia. MRI markers for SVD were strongly associated with network measures. Patients with dementia showed lower total network strength and global and local efficiency at baseline as compared with the group without dementia. Lower global network efficiency was independently associated with increased risk of incident all-cause dementia (hazard ratio 0.63, 95% confidence interval 0.42-0.96, p = 0.032); in contrast, individual SVD markers including lacunes, white matter hyperintensities volume, and atrophy were not independently associated., Conclusions: These results support a role of network disruption playing a pivotal role in the genesis of dementia in SVD, and suggest network analysis of the connectivity of white matter has potential as a predictive marker in the disease., (© 2016 American Academy of Neurology.)

Background: The relationship between cerebral small vessel disease (SVD) and dementia has been studied without considering white matter (WM) volume, the microstructural integrity of the WM surrounding the SVD, and grey matter (GM)., Objective: We prospectively investigated the relationship between these structures and the risk of dementia, and formed a prediction model to investigate which characteristics (macro- or microstructural) explained most of the variance., Methods: The RUN DMC study is a prospective cohort study among 503 non-demented participants with an age between 50 and 85 years at baseline, with baseline assessment in 2006 and follow-up assessment in 2012. Two were lost to follow-up (yielding a 99.6% response-rate). Cox regression analysis was used, to calculate hazard ratios for dementia, of baseline MRI characteristics. Tract-Based Spatial Statistics (TBSS) analysis was used to assess the added value of microstructural integrity of the WM., Results: Mean age at baseline was 65.6 years (SD 8.8) and 56.8% was male. 43 participants developed dementia (8.6%), resulting in a 5.5-year cumulative risk of 11.1% (95% CI 7.7-14.6). Low WM and hippocampal volume are significant predictors for dementia. WM, WM hyperintensities, and hippocampal volume explained most of the variance. TBSS analyses showed no additional value of diffusion parameters., Conclusions: WM and hippocampal volume were the main predictors for the development of incident dementia at 5-year follow-up in elderly with SVD. There was no additional diagnostic value of the diffusion tensor imaging parameters on top of the macrostructural characteristics.

The relation between blood pressure level and degree of global brain atrophy is equivocal. We evaluated past and present blood pressure levels and change in blood pressure over 20 years in relation to the degree of cortical atrophy on magnetic resonance imaging (MRI). In 1995-1996, we measured blood pressure and performed MRI in 1077 nondemented elderly (age 60-90 years). For 513 of these, we had information on a blood pressure level 20 years before. The degree of cortical atrophy was semi-quantitatively scored (range 0-15). In late life, a high (>/=90 mmHg) and low (<65 mmHg) diastolic blood pressure were associated with more cortical atrophy than a diastolic blood pressure level between 65-74 mmHg (adjusted difference 0.60 units (95% confidence interval (CI), 0.18-1.02) and 0.77 units (0.28-1.25), respectively). Persons whose diastolic blood pressure had declined more than 10 mmHg over 20 years had more cortical atrophy than those with stable blood pressure levels (adjusted difference 0.53 units, 0.05-1.02). Both high and declining diastolic blood pressure levels are associated with more global brain atrophy on MRI.

IntroductionMany consequences of cerebrovascular disease are identifiable by magnetic resonance imaging (MRI), but variation in methods limits multicenter studies and pooling of data. The European Union Joint Program on Neurodegenerative Diseases (EU JPND) funded the HARmoNizing Brain Imaging MEthodS for VaScular Contributions to Neurodegeneration (HARNESS) initiative, with a focus on cerebral small vessel disease.MethodsSurveys, teleconferences, and an in-person workshop were used to identify gaps in knowledge and to develop tools for harmonizing imaging and analysis.ResultsA framework for neuroimaging biomarker development was developed based on validating repeatability and reproducibility, biological principles, and feasibility of implementation. The status of current MRI biomarkers was reviewed. A website was created at www.harness-neuroimaging.org with acquisition protocols, a software database, rating scales and case report forms, and a deidentified MRI repository.ConclusionsThe HARNESS initiative provides resources to reduce variability in measurement in MRI studies of cerebral small vessel disease.

Cerebral microinfarcts (CMIs) are small ischemic lesions invisible to the naked eye at brain autopsy, while the larger ones (0.5–4 mm in diameter) have been visualized in-vivo on magnetic resonance imaging (MRI). CMIs can be detected on diffusion-weighted imaging (DWI) as incidental small DWI-positive lesions (ISDPLs) and on structural MRI for those confined to the cortex and in the chronic phase. ISDPLs may evolve into old cortical-CMIs, white matter hyperintensities or disappear depending on their location and size. Novel techniques in neuropathology and neuroimaging facilitate the detection of CMIs, which promotes understanding of these lesions. CMIs have heterogeneous causes, involving both cerebral small- and large-vessel disease as well as heart diseases such as atrial fibrillation and congestive heart failure. The underlying mechanisms incorporate vascular remodeling, inflammation, blood–brain barrier leakage, penetrating venule congestion, cerebral hypoperfusion, and microembolism. CMIs lead to clinical outcomes, including cognitive decline, a higher risk of stroke and mortality, and accelerated neurobehavioral disturbances. It has been suggested that CMIs can impair brain function and connectivity beyond the microinfarct core and are also associated with perilesional and global cortical atrophy. This review aims to summarize recent progress in studies involving both cortical-CMIs and ISDPLs since 2017, including their detection, etiology, risk factors, MRI correlates, and clinical consequences. [ABSTRACT FROM AUTHOR]

Cerebral small vessel disease is a major cause of vascular cognitive impairment and dementia. There are few treatments, largely reflecting limited understanding of the underlying pathophysiology. Metabolomics can be used to identify novel risk factors to better understand pathogenesis and to predict disease progression and severity. We analysed data from 624 patients with symptomatic cerebral small vessel disease from two prospective cohort studies. Serum samples were collected at baseline and patients underwent MRI scans and cognitive testing at regular intervals with up to 14 years of follow-up. Using ultra-performance liquid chromatography-mass spectrometry and nuclear magnetic resonance spectroscopy, we obtained metabolic and lipidomic profiles from 369 annotated metabolites and 54 764 unannotated features and examined their association with respect to disease severity, assessed using MRI small vessel disease markers, cognition and future risk of all-cause dementia. Our analysis identified 28 metabolites that were significantly associated with small vessel disease imaging markers and cognition. Decreased levels of multiple glycerophospholipids and sphingolipids were associated with increased small vessel disease load as evidenced by higher white matter hyperintensity volume, lower mean diffusivity normalized peak height, greater brain atrophy and impaired cognition. Higher levels of creatine, FA(18:2(OH)) and SM(d18:2/24:1) were associated with increased lacune count, higher white matter hyperintensity volume and impaired cognition. Lower baseline levels of carnitines and creatinine were associated with higher annualized change in peak width of skeletonized mean diffusivity, and 25 metabolites, including lipoprotein subclasses, amino acids and xenobiotics, were associated with future dementia incidence. Our results show multiple distinct metabolic signatures that are associated with imaging markers of small vessel disease, cognition and conversion to dementia. Further research should assess causality and the use of metabolomic screening to improve the ability to predict future disease severity and dementia risk in small vessel disease. The metabolomic profiles may also provide novel insights into disease pathogenesis and help identify novel treatment approaches. [ABSTRACT FROM AUTHOR]

Cerebral small vessel disease (SVD) is considered the most important vascular contributor to the development of dementia. Comprehensive characterization of the time course of disease progression will result in better understanding of aetiology and clinical consequences of SVD. SVD progression has been studied extensively over the years, usually describing change in SVD markers over time using neuroimaging at two time points. As a consequence, SVD is usually seen as a rather linear, continuously progressive process. This assumption of continuous progression of SVD markers was recently challenged by several studies that showed regression of SVD markers. Here, we provide a review on disease progression in sporadic SVD, thereby taking into account both progression and regression of SVD markers with emphasis on white matter hyperintensities (WMH), lacunes and microbleeds. We will elaborate on temporal dynamics of SVD progression and discuss the view of SVD progression as a dynamic process, rather than the traditional view of SVD as a continuous progressive process, that might better fit evidence from longitudinal neuroimaging studies. We will discuss possible mechanisms and clinical implications of a dynamic time course of SVD, with both progression and regression of SVD markers. [ABSTRACT FROM AUTHOR]

Purpose: White matter hyperintensities (WMH) are seen on FLAIR-MRI in several neurological disorders, including multiple sclerosis, dementia, Parkinsonism, stroke and cerebral small vessel disease (SVD). WMHs are often used as biomarkers for prognosis or disease progression in these diseases, and additionally longitudinal quantification of WMHs is used to evaluate therapeutic strategies. Human readers show considerable disagreement and inconsistency on detection of small lesions. A multitude of automated detection algorithms for WMHs exists, but since most of the current automated approaches are tuned to optimize segmentation performance according to Jaccard or Dice scores, smaller WMHs often go undetected in these approaches. In this paper, the authors propose a method to accurately detect all WMHs, large as well as small. Methods: A two-stage learning approach was used to discriminate WMHs from normal brain tissue. Since small and larger WMHs have quite a different appearance, the authors have trained two probabilistic classifiers: one for the small WMHs (≤3 mm effective diameter) and one for the larger WMHs (>3 mm in-plane effective diameter). For each size-specific classifier, an Adaboost is trained for five iterations, with random forests as the basic classifier. The feature sets consist of 22 features including intensities, location information, blob detectors, and second order derivatives. The outcomes of the two first-stage classifiers were combined into a single WMH likelihood by a second-stage classifier. Their method was trained and evaluated on a dataset with MRI scans of 362 SVD patients (312 subjects for training and validation annotated by one and 50 for testing annotated by two trained raters). To analyze performance on the separate test set, the authors performed a free-response receiving operating characteristic (FROC) analysis, instead of using segmentation based methods that tend to ignore the contribution of small WMHs. Results: Experimental results based on FROC analysis demonstrated a close performance of the proposed computer aided detection (CAD) system to human readers. While an independent reader had 0.78 sensitivity with 28 false positives per volume on average, their proposed CAD system reaches a sensitivity of 0.73 with the same number of false positives. Conclusions: The authors have developed a CAD system with all its ingredients being optimized for a better detection of WMHs of all size, which shows performance close to an independent reader. [ABSTRACT FROM AUTHOR]

Background: Cerebral small vessel disease (SVD) is a frequent finding on CT and MRI scans of elderly people and is related to vascular risk factors and cognitive and motor impairment, ultimately leading to dementia or parkinsonism in some. In general, the relations are weak, and not all subjects with SVD become demented or get parkinsonism. This might be explained by the diversity of underlying pathology of both white matter lesions (WML) and the normal appearing white matter (NAWM). Both cannot be properly appreciated with conventional MRI. Diffusion tensor imaging (DTI) provides alternative information on microstructural white matter integrity. The association between SVD, its microstructural integrity, and incident dementia and parkinsonism has never been investigated. Methods/Design: The RUN DMC study is a prospective cohort study on the risk factors and cognitive and motor consequences of brain changes among 503 non-demented elderly, aged between 50-85 years, with cerebral SVD. First follow up is being prepared for July 2011. Participants alive will be included and invited to the research centre to undergo a structured questionnaire on demographics and vascular risk factors, and a cognitive, and motor, assessment, followed by a MRI protocol including conventional MRI, DTI and resting state fMRI. Discussion: The follow up of the RUN DMC study has the potential to further unravel the causes and possibly better predict the consequences of changes in white matter integrity in elderly with SVD by using relatively new imaging techniques. When proven, these changes might function as a surrogate endpoint for cognitive and motor function in future therapeutic trials. Our data could furthermore provide a better understanding of the pathophysiology of cognitive and motor disturbances in elderly with SVD. The execution and completion of the follow up of our study might ultimately unravel the role of SVD on the microstructural integrity of the white matter in the transition from "normal" aging to cognitive and motor decline and impairment and eventually to incident dementia and parkinsonism. [ABSTRACT FROM AUTHOR]

Background: Vascular factors are recognized as important risk factors for Alzheimer’s disease, although it is unknown whether these factors directly lead to the typical degenerative pathology such as medial temporal lobe atrophy. We set out to investigate the relation between blood pressure and medial temporal lobe atrophy in patients with senile and presenile Alzheimer’s disease with or without white matter lesions. Methods: We determined the relation between blood pressure and pulse pressure and medial temporal lobe atrophy on MRI in 159 patients with Alzheimer’s disease, stratified on white matter lesions and age at onset of dementia. Results: There was a linear relation between systolic blood pressure and pulse pressure (both in tertiles) and the severity of medial temporal lobe atrophy (ptrend = 0.05 and ptrend 0.03, respectively). A significant relation was found between pulse pressure [β = 0.08 (95% CI: 0.00–0.15; p = 0.05) per 10 mm Hg] and (borderline significant) systolic blood pressure [β = 0.05 (95% CI: –0.01 to 0.11; p = 0.1) per 10 mm Hg] and medial temporal lobe atrophy. White matter lesions and age-stratified analysis revealed a significant association between systolic blood pressure and pulse pressure and medial temporal lobe atrophy, only in the subsample with white matter lesions and in the subsample with a senile onset of dementia. The relations were independent of severity of dementia and diabetes mellitus. Conclusions: Systolic blood pressure and pulse pressure are associated with medial temporal lobe atrophy in Alzheimer’s disease, especially in the presence of white matter lesions and in patients with a late onset of dementia. Our finding may be another step in providing a rationale on how vascular factors could ultimately result in Alzheimer’s disease. Copyright © 2005 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Stroke is a leading cause of disability, not only because of motor limitations, but also because of the frequent occurrence of post-stroke cognitive impairment. This is illustrated by the fact that the risk of post-stroke dementia is reportedly higher than a recurrent stroke. The loss of subcortical and cortical functions in the post-stroke cognitive dysfunction spectrum is usually well explained by the size and location of the infarction. However, this does not apply for post-stroke memory dysfunction (especially episodic memory dysfunction), as there is almost never an infarction in the medial temporal lobe. Involvement of the medial temporal lobe in post-stroke memory dysfunction seems likely since this structure is essential for memory encoding and retrieval. For a proper episodic memory function, the medial temporal lobe depends on intact connections with virtually the whole brain. Disconnection from other brain areas due to the infarction could lead to a reduced medial temporal lobe function and the attendant reduced episodic memory function. We investigated medial temporal lobe functionality in 28 ‘first-ever’ stroke patients and 22 healthy controls with the aid of functional magnetic resonance imaging. Stroke patients with a reduced episodic memory function 6–8 weeks after infarction had reduced medial temporal lobe functionality. Post-stroke reduced medial temporal lobe functionality may be responsible for the frequent observation of impaired post-stroke episodic memory function. Insight into this mechanism could be helpful in identifying which stroke patients may be at increased risk for developing post-stroke dementia and those who could benefit from early cognitive rehabilitation. [ABSTRACT FROM AUTHOR]

Cerebral small vessel disease (SVD) is commonly observed on neuroimaging among elderly individuals and is recognized as a major vascular contributor to dementia, cognitive decline, gait impairment, mood disturbance and stroke. However, clinical symptoms are often highly inconsistent in nature and severity among patients with similar degrees of SVD on brain imaging. Here, we provide a new framework based on new advances in structural and functional neuroimaging that aims to explain the remarkable clinical variation in SVD. First, we discuss the heterogeneous pathology present in SVD lesions despite an identical appearance on imaging and the perilesional and remote effects of these lesions. We review effects of SVD on structural and functional connectivity in the brain, and we discuss how network disruption by SVD can lead to clinical deficits. We address reserve and compensatory mechanisms in SVD and discuss the part played by other age-related pathologies. Finally, we conclude that SVD should be considered a global rather than a focal disease, as the classically recognized focal lesions affect remote brain structures and structural and functional network connections. The large variability in clinical symptoms among patients with SVD can probably be understood by taking into account the heterogeneity of SVD lesions, the effects of SVD beyond the focal lesions, the contribution of neurodegenerative pathologies other than SVD, and the interaction with reserve mechanisms and compensatory mechanisms. [ABSTRACT FROM AUTHOR]

Abstract: Cerebral small vessel disease (SVD), including white matter lesions (WML) and lacunar infarcts, is related to objective cognitive impairment but also to subjective cognitive failures (SCF). SCF have reported to be an early predictor of dementia. Cerebral microbleeds (MB) are another manifestation of SVD and have been related to cognitive impairment, but the role of MB in SCF has never been studied. We therefore investigated whether MB are related to SCF among non-demented elderly individuals with SVD, independent of coexisting WML and lacunar infarcts. The RUN DMC study is a prospective cohort study among 503 older persons with cerebral SVD between 50 and 85 years of age. All participants underwent FLAIR and T2* scanning. SCF, subjective memory failures (SMF), and subjective executive failures (SEF) were assessed. The relation between SCF and the presence, number and location of MB was assessed by linear regression analyses adjusted for age, sex, education, depressive symptoms, cognitive function, total brain volume, normalized hippocampal volume, territorial infarcts, WML, and lacunar infarcts. MB were present in 11%. We found a relation between the presence, total number and lobar located MB, and SCF, SMF, and SEF and the reported progression of these failures, especially in participants with good objective cognitive function. In conclusion, MB are related to SCF independent of co-existing WML and lacunar infarcts, especially in those with good objective cognitive performance. These results suggest that MB are associated with the earliest manifestations of cognitive impairment. MB may help us to understand the role of the ever-expanding spectrum of SVD in cognitive impairment. [Copyright &y& Elsevier]