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Introduction Small vessel disease (SVD) commonly causes stroke and dementia. Early clinical predictors of disease progression are lacking. We aimed to determine whether informant reports of chronic cognitive/functional decline, prerequisites for dementia diagnosis, are associated with (a)baseline SVD burden, measured by Fazekas scores and (b)SVD change, measured by incident subcortical Diffusion-weighted Imaging (DWI) lesions. Method We prospectively recruited patients with mild ischaemic stroke, performed diagnostic MRI, and invited participants to repeat MRI 3- to 6-monthly. Informants completed the Informant Questionnaire for Cognitive Decline in the Elderly (IQCODE) prior to baseline visit, a 16-item questionnaire which assesses patients’ cognitive and functional decline in the preceding ten years. Scores range from 1–5: a score above 3.3 has high sensitivity/specificity for dementia post-stroke. We conducted linear regression with IQCODE as the dependent variable, adjusting for age, sex, baseline MoCA, disability (modified Rankin Scale). Results We recruited 106 participants (mean age 67 years;range 40–86;33% female). Ninety-three informant questionnaires were returned. IQCODE associated with baseline Fazekas score; Fazekas 6 (β = 0.28, p = 0.04) vs. Fazekas 3 (β = 0.03, p = 0.67), R2 = 0.11, adjusted for age, sex, baseline MoCA, disability. Incident DWI lesions were common (15/106; 14/15 subcortical; no active embolic sources; median 67 days post-stroke). Four were asymptomatic, two reported stroke-like symptoms and nine had neuropsychiatric/non-focal symptoms. IQCODE was higher in those with a new lesion vs. without (β = 0.21, p = 0.02), R2 = 0.09, while age (β = −0.004, p = 0.19), MoCA (β = −0.006, p = 0.56) and disability (β = 0.06, p = 0.2) were not. Conclusions Higher SVD burden and incident, mostly “silent” stroke lesions associate more strongly with informant concerns of cognitive/functional decline than age or objective cognitive tests. These findings are novel in an ischaemic stroke population and the first to assess IQCODE/SVD progression. Future work should determine whether combining informant reports with imaging features of small vessel disease improves early detection of dementia.

Objective This work investigates network organisation of brain structural connectivity in systemic lupus erythematosus (SLE) relative to healthy controls and its putative association with lesion distribution and disease indicators. Methods White matter hyperintensity (WMH) segmentation and connectomics were performed in 47 patients with SLE and 47 healthy age-matched controls from structural and diffusion MRI data. Network nodes were divided into hierarchical tiers based on numbers of connections. Results were compared between patients and controls to assess for differences in brain network organisation. Voxel-based analyses of the spatial distribution of WMH in relation to network measures and SLE disease indicators were conducted. Results Despite inter-individual differences in brain network organization observed across the study sample, the connectome networks of SLE patients had larger proportion of connections in the peripheral nodes. SLE patients had statistically larger numbers of links in their networks with generally larger fractional anisotropy weights (i.e. a measure of white matter integrity) and less tendency to aggregate than those of healthy controls. The voxels exhibiting connectomic differences were coincident with WMH clusters, particularly the left hemisphere’s intersection between the anterior limb of the internal and external capsules. Moreover, these voxels also associated more strongly with disease indicators. Conclusion Our results indicate network differences reflective of compensatory reorganization of the neural circuits, reflecting adaptive or extended neuroplasticity in SLE.

Raised signal in cerebrospinal fluid (CSF) on fluid-attenuated inversion recovery (FLAIR) may indicate raised CSF protein or debris and is seen in inferior frontal sulci on routine MRI. To explore its clinical relevance, we assessed the association of inferior frontal sulcal hyperintensities (IFSH) on FLAIR with demographics, risk factors, and small vessel disease markers in three cohorts (healthy volunteers, n=44; mild stroke patients, n=105; older community-dwelling participants from Lothian birth cohort 1936, n=101). We collected detailed clinical data, scanned all subjects on the same 3T MRI scanner and 3-dimensional FLAIR sequence and developed a scale to rate IFSH. In adjusted analyses, the IFSH score increased with age (per 10-year increase; OR 1.69; 95% CI, 1.42-2.02), and perivascular spaces score in centrum semiovale in stroke patients (OR 1.73; 95% CI, 1.13-2.69). Since glymphatic CSF clearance declines with age and drains partially via the cribriform plate to the nasal lymphatics, IFSH on 3T MRI may be a non-invasive biomarker of altered CSF clearance and justifies further research in larger, more diverse samples.

Purpose: Dynamic contrast-enhanced (DCE) -MRI with Patlak model analysis is increasingly used to quantify low-level blood-brain barrier (BBB) leakage in studies of pathophysiology. We aimed to investigate systematic errors due to physiological, experimental, and modeling factors influencing quantification of the permeability-surface area product PS and blood plasma volume v p, and to propose modifications to reduce the errors so that subtle differences in BBB permeability can be accurately measured. Methods: Simulations were performed to predict the effects of potential sources of systematic error on conventional PS and v p quantification: restricted BBB water exchange, reduced cerebral blood flow, arterial input function (AIF) delay and (Formula presented.) error. The impact of targeted modifications to the acquisition and processing were evaluated, including: assumption of fast versus no BBB water exchange, bolus versus slow injection of contrast agent, exclusion of early data from model fitting and (Formula presented.) correction. The optimal protocol was applied in a cohort of recent mild ischaemic stroke patients. Results: Simulation results demonstrated substantial systematic errors due to the factors investigated (absolute PS error ≤ 4.48 × 10 −4 min −1). However, these were reduced (≤0.56 × 10 −4 min −1) by applying modifications to the acquisition and processing pipeline. Processing modifications also had substantial effects on in-vivo normal-appearing white matter PS estimation (absolute change ≤ 0.45 × 10 −4 min −1). Conclusion: Measuring subtle BBB leakage with DCE-MRI presents unique challenges and is affected by several confounds that should be considered when acquiring or interpreting such data. The evaluated modifications should improve accuracy in studies of neurodegenerative diseases involving subtle BBB breakdown.

IntroductionMultiple sclerosis (MS) is a chronic neuroinflammatory and neurodegenerative disease. MS prevalence varies geographically and is notably high in Scotland. Disease trajectory varies significantly between individuals and the causes for this are largely unclear. Biomarkers predictive of disease course are urgently needed to allow improved stratification for current disease modifying therapies and future targeted treatments aimed at neuroprotection and remyelination. MRI can detect disease activity and underlying damage non-invasively in vivo at the micro and macrostructural level. FutureMS is a prospective Scottish longitudinal multi-centre cohort study, which focuses on deeply phenotyping patients with recently diagnosed relapsing-remitting MS (RRMS). Neuroimaging is a central component of the study and provides two main primary endpoints for disease activity and neurodegeneration. FutureMS aims to reduce uncertainty around disease course and allow for targeted treatment in RRMS by exploring the role of conventional and advanced MRI measures as biomarkers of disease severity and progression. This paper provides an overview of MRI data acquisition, management and processing in FutureMS.Methods and analysisMRI is acquired at baseline (N=431) and 1-year follow-up, in Dundee, Glasgow and Edinburgh (3T Siemens) and in Aberdeen (3T Philips), and managed and processed in Edinburgh. The core structural MRI protocol comprises T1-weighted, T2-weighted, FLAIR and proton density images. Primary imaging outcome measures are new/enlarging white matter lesions (WML) and reduction in brain volume over one year. Secondary imaging outcome measures comprise WML volume as an additional quantitative structural MRI measure, rim lesions on susceptibility-weighted imaging, and microstructural MRI measures, including diffusion tensor imaging and neurite orientation dispersion and density imaging metrics, relaxometry, magnetisation transfer (MT) ratio, MT saturation and derived g-ratio measures.Ethics and disseminationThe study received ethical approval from the South East Scotland Research Ethics Committee 02 (reference 15/SS/0233). Results will be made available to study participants and funders.STRENGTHS AND LIMITATIONS OF THE STUDYBrain imaging acquired within six months after relapsing-remitting multiple sclerosis (RRMS) diagnosis allows for detection of abnormalities at a very early stage of disease.Longitudinal structural and microstructural brain MRI are integrated with multi-modal clinical, blood biomarker, genetic and retinal imaging data to allow comprehensive evaluation of early RRMS stratifiers.MR protocol optimization was implemented mid-study to improved image quality and protocol harmonization, resulting in some between-subject protocol variation.Multiplatform MRI acquisition required to allow access for a large MS population across Scotland introduces inevitable inter-site data variance.Contrast enhanced MRI was not acquired, limiting imaging evaluation of active inflammatory lesions.

Research involving brain imaging is important for understanding common brain diseases. Study endpoints can include features and measures derived from imaging modalities, providing a benchmark against which other phenotypical data can be assessed. In trials, imaging data provides objective evidence of beneficial and adverse outcomes. Multi-centre studies increase generalizability and statistical power. However, there is a lack of practical guidelines for the set-up and conduct of large neuroimaging studies. We address this deficit by describing aspects of study design and other essential practical considerations that will help researchers avoid common pitfalls and data loss. The recommendations are grouped as: 1. Get help from experts in the field and plan the study, 2. Define the imaging endpoints, develop an imaging manual and have a system in place to manage the workflow, 3. Perform a dummy run test scan and test the analysis methods, 4. Acquire the scans, 5. Data anonymisation and transfer, 6. Quality control, 7. Data sharing. Implementing these steps will lead to valuable and usable data and help avoid imaging data wastage. Additionally, we highlight the importance of data sharing to maximize the benefits of the research to society by making the data available to other researchers.

Objective To examine the cross-sectional associations between dietary patterns and cognitive and neuroimaging indices of brain health concurrently in the same sample of healthy older adults. Methods Dietary patterns were derived from a 130-item food frequency questionnaire for 511 individuals in the Lothian Birth Cohort 1936 (mean age 79.3 ± 0.6 years). Composite scores for global cognitive function, visuospatial ability, processing speed, memory, and verbal ability were assessed. Brain volumes and white matter microstructure were assessed in participants (n = 358) who also underwent structural magnetic resonance imaging. Results A Mediterranean-style dietary pattern and a processed dietary pattern were identified using principal component analysis of food frequency questionnaire items. In fully-adjusted linear regression models, adherence to the Mediterranean-style pattern was associated with better verbal ability (β = 0.121, P = 0.002). Associations with global cognitive function (β = 0.094, P = 0.043), visuospatial ability (β = 0.113, P = 0.019), and memory (β = 0.105, P = 0.029) did not survive correction for multiple comparisons. Associations between the processed pattern and lower cognitive scores were attenuated by around 50% following adjustment for prior (childhood) cognitive ability; only an association with verbal ability remained (β = −0.130, P = 0.001). Neither dietary pattern was associated with brain volumes or white matter microstructure. Specific Mediterranean diet features—green leafy vegetables and a low intake of red meat—were associated with better cognitive functioning. Conclusions These observational findings suggest that adherence to a Mediterranean-style diet is associated with better cognitive functioning, but not better brain structural integrity, in older adults.

Objective To investigate brain structural connectivity in relation to cognitive abilities and systemic damage in systemic lupus erythematosus (SLE). Methods Structural and diffusion MRI data were acquired from 47 patients with SLE. Brains were segmented into 85 cortical and subcortical regions and combined with whole brain tractography to generate structural connectomes using graph theory. Global cognitive abilities were assessed using a composite variable g, derived from the first principal component of three common clinical screening tests of neurological function. SLE damage ( LD) was measured using a composite of a validated SLE damage score and disease duration. Relationships between network connectivity metrics, cognitive ability and systemic damage were investigated. Hub nodes were identified. Multiple linear regression, adjusting for covariates, was employed to model the outcomes g and LD as a function of network metrics. Results The network measures of density (standardised ß = 0.266, p = 0.025) and strength (standardised ß = 0.317, p = 0.022) were independently related to cognitive abilities. Strength (standardised ß = –0.330, p = 0.048), mean shortest path length (standardised ß = 0.401, p = 0.020), global efficiency (standardised ß = –0.355, p = 0.041) and clustering coefficient (standardised ß = –0.378, p = 0.030) were independently related to systemic damage. Network metrics were not related to current disease activity. Conclusion Better cognitive abilities and more SLE damage are related to brain topological network properties in this sample of SLE patients, even those without neuropsychiatric involvement and after correcting for important covariates. These data show that connectomics might be useful for understanding and monitoring cognitive function and white matter damage in SLE.

Rodero et al. report the direct quantification of IFNα protein in monogenic interferonopathies, autoimmunity, and infectious disease states, made possible by the combination of digital ELISA and high-affinity autoantibodies isolated from APECED patients, revealing differential levels and cellular sources dependent on underlying pathology., Type I interferons (IFNs) are essential mediators of antiviral responses. These cytokines have been implicated in the pathogenesis of autoimmunity, most notably systemic lupus erythematosus (SLE), diabetes mellitus, and dermatomyositis, as well as monogenic type I interferonopathies. Despite a fundamental role in health and disease, the direct quantification of type I IFNs has been challenging. Using single-molecule array (Simoa) digital ELISA technology, we recorded attomolar concentrations of IFNα in healthy donors, viral infection, and complex and monogenic interferonopathies. IFNα protein correlated well with functional activity and IFN-stimulated gene expression. High circulating IFNα levels were associated with increased clinical severity in SLE patients, and a study of the cellular source of IFNα protein indicated disease-specific mechanisms. Measurement of IFNα attomolar concentrations by digital ELISA will enhance our understanding of IFN biology and potentially improve the diagnosis and stratification of pathologies associated with IFN dysregulation.

Background Cerebral small vessel disease is a major cause of dementia and stroke, visible on brain magnetic resonance imaging. Recent data suggest that small vessel disease lesions may be dynamic, damage extends into normal-appearing brain and microvascular dysfunctions include abnormal blood–brain barrier leakage, vasoreactivity and pulsatility, but much remains unknown regarding underlying pathophysiology, symptoms, clinical features and risk factors of small vessel disease. Patients and Methods: The Mild Stroke Study 3 is a prospective observational cohort study to identify risk factors for and clinical implications of small vessel disease progression and regression among up to 300 adults with non-disabling stroke. We perform detailed serial clinical, cognitive, lifestyle, physiological, retinal and brain magnetic resonance imaging assessments over one year; we assess cerebrovascular reactivity, blood flow, pulsatility and blood–brain barrier leakage on magnetic resonance imaging at baseline; we follow up to four years by post and phone. The study is registered ISRCTN 12113543. Summary Factors which influence direction and rate of change of small vessel disease lesions are poorly understood. We investigate the role of small vessel dysfunction using advanced serial neuroimaging in a deeply phenotyped cohort to increase understanding of the natural history of small vessel disease, identify those at highest risk of early disease progression or regression and uncover novel targets for small vessel disease prevention and therapy.

International audience; Recombinant interferon alpha is used to treat several immunological, oncological, and infectious diseases,1 and various serious side-effects have been associated with its therapeutic use. We want to bring attention to the development of neuromyelitis optica spectrum disorder (NMOSD) [...]

The structural network of the human brain has a rich topology which many have sought to characterise using standard network science measures and concepts. However, this characterisation remains incomplete and the non-obvious features of this topology have confounded attempts to model it constructively. This calls for new perspectives. Hierarchical complexity is an emerging paradigm of complex network topology based on the observation that complex systems are composed of hierarchies within which the roles of hierarchically equivalent nodes display highly variable connectivity patterns. Here we test the hierarchical complexity of the human structural connectomes of a group of seventy-nine healthy adults. Binary connectomes are found to be more hierarchically complex than three null models-random graphs, random geometric graphs, and edge-randomised connectomes. This presents important new insights into the structure of the human brain, indicating a rich variety of connectivity patterns within hierarchically equivalent nodes. That random models fail to show such behaviour suggests that the generative mechanisms of brain structure may even insist on such dissimilarity. This also provides the strongest evidence to date in support of the hierarchical complexity paradigm of complex brain networks- both ordered and random systems are inherently more predictable. Dividing the connectomes into four tiers based on degree magnitudes indicates that the most complex nodes are neither those with the highest nor lowest degrees but are instead found in the third and second tiers. Spatial mapping of the brain regions in each hierarchical tier reveals consistency with the current anatomical, functional and neuropsychological knowledge of the human brain. The most complex tier (tier 3) involves regions believed to bridge high-order cognitive (tier 1) and low-order sensorimotor processing (tier 2), revealing a strikingly large diversity of connectivity patterns elicited in the integration of these processes.

We present a complete study of limited one-time sampling irregularity map (LOTS-IM), a fully automatic unsupervised approach to extract brain tissue irregularities in magnetic resonance images (MRI), including its application and evaluation for quantitative assessment of white matter hyperintensities (WMH) of presumed vascular origin and assessing multiple sclerosis (MS) lesion progression. LOTS-IM is unique compared to similar other methods because it yields irregularity map (IM) which represents WMH as irregularity values, not probability values, and retains the original MRI’s texture information. We tested and compared the usage of IM for WMH segmentation on T2-FLAIR MRI with various methods, including the well established unsupervised WMH segmentation Lesion Growth Algorithm from the public toolbox Lesion Segmentation Toolbox (LST-LGA), conventional supervised machine learning schemes andstate-of-the-artsupervised deep neural networks. In our experiments, LOTS-IM outperformed unsupervised method LST-LGA, both in performance and processing speed, thanks to the limited one-time sampling scheme and its implementation on GPU. Our method also outperformed supervised conventional machine learning algorithms (i.e., support vector machine (SVM) and random forest (RF)) and deep neural networks algorithms (i.e., deep Boltzmann machine (DBM) and convolutional encoder network (CEN)), while yielding comparable results to the convolutional neural network schemes that rank top of the algorithms developed up to date for this purpose (i.e., UResNet and UNet). The high sensitivity of IM on depicting signal change deems suitable for assessing MS progression, although care must be taken with signal changes not reflective of a true pathology.

Objective The objective of this study was to investigate fatigue and cognitive impairments in systemic lupus erythematous (SLE) in relation to diffuse white matter microstructural brain damage. Methods Diffusion tensor MRI, used to generate biomarkers of brain white matter microstructural integrity, was obtained in patients with SLE and age-matched controls. Fatigue and cognitive function were assessed and related to SLE activity, clinical data and plasma biomarkers of inflammation and endothelial dysfunction. Results Fifty-one patients with SLE (mean age 48.8 ± 14.3 years) were included. Mean diffusivity (MD) was significantly higher in all white matter fibre tracts in SLE patients versus age-matched healthy controls ( p Conclusion Patients with SLE have more microstructural brain white matter damage for age than the general population, but this does not explain increased fatigue or lower cognition in SLE. The association between raised IL-6 and worse current cognitive function in SLE should be explored in larger datasets.

Background and Purpose— White matter hyperintensities (WMH) and perivascular spaces (PVS) are features of small vessel disease, found jointly on MRI of older people. Inflammation is a prominent pathological feature of small vessel disease. We examined the association between inflammation, PVS, and WMH in the Lothian Birth Cohort 1936 (N=634). Methods— We measured plasma fibrinogen, C-reactive protein, and interleukin-6 and rated PVS in 3 brain regions. We measured WMH volumetrically and visually using the Fazekas scale. We derived latent variables for PVS, WMH , and Inflammation from measured PVS, WMH, and inflammation markers and modelled associations using structural equation modelling. Results— After accounting for age, sex, stroke, and vascular risk factors, PVS were significantly associated with WMH (β=0.47; P Inflammation was weakly but significantly associated with PVS (β=0.12; P =0.048), but not with WMH (β=0.02; P =NS). Conclusions— Circulating inflammatory markers are weakly associated with MR-visible PVS, but not directly with WMH. Longitudinal studies should examine whether visible PVS predate WMH progression and whether inflammation modulators can prevent small vessel disease.

Background and Purpose— Some rheumatic diseases are associated with stroke. Less is known about associations with stroke subtypes or stroke risk by age. We quantified the association between stroke, its subtypes, and rheumatic diseases and identified when stroke risk is greatest. Methods— Searches of EMBASE (from 1980) and MEDLINE (from inception) to end 2014 and manual search of reference lists for studies of stroke and stroke subtypes in rheumatic diseases as well as studies measuring cerebrovascular disease from magnetic resonance imaging. Results— Prior published meta-analyses and new pooled analyses of any stroke in rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis, gout, and psoriasis show an excess risk of stroke over the general population with odds ratio (OR) ranging from 1.51 (95% confidence interval: 1.39–1.62) to 2.13 (1.53–2.98). New meta-analyses of stroke subtypes in rheumatoid arthritis [ischemic: OR, 1.64 (1.32–2.05); hemorrhagic: OR, 1.68 (1.11–2.53)] and systemic lupus erythematosus [ischemic: OR, 2.11 (1.66–2.67); hemorrhagic: OR, 1.82 (1.07–3.09)] show an excess risk of stroke over the general population. Stroke risk across rheumatic diseases is highest in those aged 65 years: OR, 1.14 (0.94–1.38); difference P Conclusions— Risk of any stroke is higher in most rheumatic diseases than in the general population, particularly

Background: The cause of cerebral small vessel disease is not fully understood, yet it is important, accounting for about 25% of all strokes. It also increases the risk of having another stroke and contributes to about 40% of dementias. Various processes have been implicated, including microatheroma, endothelial dysfunction and inflammation. A previous review investigated endothelial dysfunction in lacunar stroke versus mostly non-stroke controls while another looked at markers of inflammation and endothelial damage in ischaemic stroke in general. We have focused on blood markers between clinically evident lacunar stroke and other subtypes of ischaemic stroke, thereby controlling for stroke in general. Summary: We systematically assessed the literature for studies comparing blood markers of coagulation, fibrinolysis, endothelial dysfunction and inflammation in lacunar stroke versus non-stroke controls or other ischaemic stroke subtypes. We assessed the quality of included papers and meta-analysed results. We split the analysis on time of blood draw in relation to the stroke. We identified 1,468 full papers of which 42 were eligible for inclusion, including 4,816 ischaemic strokes, of which 2,196 were lacunar and 2,500 non-stroke controls. Most studies subtyped stroke using TOAST. The definition of lacunar stroke varied between studies. Markers of coagulation/fibrinolysis (tissue plasminogen activator (tPA), plasminogen activator inhibitor (PAI), fibrinogen, D-dimer) were higher in lacunar stroke versus non-stroke although fibrinogen was no different to non-stroke in the acute phase. tPA and PAI were no different between lacunar and non-lacunar stroke. Fibrinogen and D-dimer were significantly lower in lacunar stroke compared to other ischaemic strokes, both acutely and chronically. Markers of endothelial dysfunction (homocysteine, von Willebrand Factor (vWF), E-selectin, P-selectin, intercellular adhesion molecule-1 (ICAM), vascular cellular adhesion molecule-1 (VCAM)) were higher or had insufficient or conflicting data (P-selectin, VCAM) in lacunar stroke versus non-stroke. Compared to other ischaemic stroke subtypes, homocysteine did not differ in lacunar stroke while vWF was significantly lower in lacunar stroke acutely [atherothrombotic standardized mean difference, SMD, -0.34 (-0.61, -0.08); cardioembolic SMD -0.38 (-0.62, -0.14)], with insufficient data chronically. Markers of inflammation (C-reactive protein (CRP), tumour necrosis factor-alpha (TNF-α), interleukin-6 (IL-6)) were higher in lacunar stroke versus non-stroke, although there were no studies measuring TNF-α chronically and the sole study measuring IL-6 chronically showed no difference between lacunar stroke and non-stroke. Compared to other ischaemic stroke subtypes, there was no difference (CRP) or insufficient or conflicting data (TNF-α) to lacunar stroke. IL-6 was significantly lower [atherothrombotic SMD -0.37 (-0.63, -0.10); cardioembolic SMD -0.52 (-0.82, -0.22)] in lacunar stroke acutely, with insufficient data chronically. Key Messages: Lacunar stroke is an important stroke subtype. More studies comparing lacunar stroke to non-lacunar stroke specifically, rather than to non-stroke controls, are needed. Prospective studies with measurements taken well after the acute event are more likely to be helpful in determining pathogenesis. The available data in this review were limited and do not exclude the possibility that peripheral inflammatory processes including endothelial dysfunction are associated with lacunar stroke and cerebral small vessel disease.

Supplemental Digital Content is available in the text., Background and Purpose— Perivascular spaces (PVS) around venules may help drain interstitial fluid from the brain. We examined relationships between suspected venules and PVS visible on brain magnetic resonance imaging. Methods— We developed a visual venular quantification method to examine the spatial relationship between venules and PVS. We recruited patients with lacunar stroke or minor nondisabling ischemic stroke and performed brain magnetic resonance imaging and retinal imaging. We quantified venules on gradient echo or susceptibility-weighted imaging and PVS on T2-weighted magnetic resonance imaging in the centrum semiovale and then determined overlap between venules and PVS. We assessed associations between venular count and patient demographic characteristics, vascular risk factors, small vessel disease features, retinal vessels, and venous sinus pulsatility. Results— Among 67 patients (69% men, 69.0±9.8 years), only 4.6% (range, 0%–18%) of venules overlapped with PVS. Total venular count increased with total centrum semiovale PVS count in 55 patients after accounting for venule-PVS overlap (β=0.468 [95% CI, 0.187–0.750]) and transverse sinus pulsatility (β=0.547 [95% CI, 0.309–0.786]) and adjusting for age, sex, and systolic blood pressure. Conclusions— Despite increases in both visible PVS and suspected venules, we found minimal spatial overlap between them in patients with sporadic small vessel disease, suggesting that most magnetic resonance imaging-visible centrum semiovale PVS are periarteriolar rather than perivenular.