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Slowed processing speed is considered a hallmark feature of cognitive decline in cerebral small vessel disease (SVD); however, it is unclear whether SVD’s association with slowed processing might be due to its association with overall declining general cognitive ability. We quantified the total MRI-visible SVD burden of 540 members of the Lothian Birth Cohort 1936 (age: 72.6 ± 0.7 years; 47% female). Using latent growth curve modelling, we tested associations between total SVD burden at mean age 73 and changes in general cognitive ability, processing speed, verbal memory and visuospatial ability, measured at age 73, 76, 79 and 82. Covariates included age, sex, vascular risk and childhood cognitive ability. In the fully adjusted models, greater SVD burden was associated with greater declines in general cognitive ability (standardised β: −0.201; 95% CI: [−0.36, −0.04]; pFDR = 0.022) and processing speed (−0.222; [−0.40, −0.04]; pFDR = 0.022). SVD burden accounted for between 4 and 5% of variance in declines of general cognitive ability and processing speed. After accounting for the covariance between tests of processing speed and general cognitive ability, only SVD’s association with greater decline in general cognitive ability remained significant, prior to FDR correction (−0.222; [−0.39, −0.06]; p = 0.008; pFDR = 0.085). Our findings do not support the notion that SVD has a specific association with declining processing speed, independent of decline in general cognitive ability (which captures the variance shared across domains of cognitive ability). The association between SVD burden and declining general cognitive ability supports the notion of SVD as a diffuse, whole-brain disease and suggests that trials monitoring SVD-related cognitive changes should consider domain-specific changes in the context of overall, general cognitive decline.

Brain iron deposits (IDs) are indicative of microvessel dysfunction which may predispose to small vessel disease (SVD) brain damage and worsen cognition later in life. Visible perivascular spaces in the centrum semiovale (CSO-PVS) are SVD features linked with microvessel dysfunction. We examined possible associations of CSO-PVS volume and count with brain IDs and cognitive abilities in 700 community-dwelling individuals from the Lothian Birth Cohort 1936 who underwent detailed cognitive testing and multimodal brain MRI at mean age 72.7 years. Brain IDs were assessed automatically followed by manual editing. PVS were automatically assessed in the centrum semiovale and deep corona radiata supraventricular. General factors of overall cognitive function (g), processing speed (g-speed) and memory (g-memory) were used in the analyses. Median (IQR) volumes of IDs and CSO-PVS expressed as a percentage of intracranial volume were 0.0021 (0.011) and 0.22 (0.13)% respectively. Median count of CSO-PVS was 410 (IQR = 201). Total volumes of CSO-PVS and ID, adjusted for head size, were correlated (Spearman ρ = 0.13, p

Multi‐scanner MRI studies are reliant on understanding the apparent differences in imaging measures between different scanners. We provide a comprehensive analysis of T1‐weighted and diffusion MRI (dMRI) structural brain measures between a 1.5 T GE Signa Horizon HDx and a 3 T Siemens Magnetom Prisma using 91 community‐dwelling older participants (aged 82 years). Although we found considerable differences in absolute measurements (global tissue volumes were measured as ~6–11% higher and fractional anisotropy [FA] was 33% higher at 3 T than at 1.5 T), between‐scanner consistency was good to excellent for global volumetric and dMRI measures (intraclass correlation coefficient [ICC] range: .612–.993) and fair to good for 68 cortical regions (FreeSurfer) and cortical surface measures (mean ICC: .504–.763). Between‐scanner consistency was fair for dMRI measures of 12 major white matter tracts (mean ICC: .475–.564), and the general factors of these tracts provided excellent consistency (ICC ≥ .769). Whole‐brain structural networks provided good to excellent consistency for global metrics (ICC ≥ .612). Although consistency was poor for individual network connections (mean ICCs: .275−.280), this was driven by a large difference in network sparsity (.599 vs. .334), and consistency was improved when comparing only the connections present in every participant (mean ICCs: .533–.647). Regression‐based k‐fold cross‐validation showed that, particularly for global volumes, between‐scanner differences could be largely eliminated (R 2 range .615–.991). We conclude that low granularity measures of brain structure can be reliably matched between the scanners tested, but caution is warranted when combining high granularity information from different scanners., In this comprehensive analysis, we compared T1‐weighted and diffusion MRI structural brain measures between a 1.5 and 3 T scanner using 91 participants (aged 82 years). We found that large‐scale brain structures (whole‐brain, ventricular and tissue volumes; global diffusion MRI measures; and global network metrics) can be reliably matched between these scanners, but caution is warranted when combining regional measures from different scanners. ​

Multi-scanner MRI studies are reliant on understanding the apparent differences in imaging measures between different scanners. We provide a comprehensive analysis of T1-weighted and diffusion MRI (dMRI) structural brain measures between a 1.5T GE Signa Horizon HDx and a 3T Siemens Magnetom Prisma using 91 community-dwelling older participants (aged 82 years). Although we found considerable differences in absolute measurements (global tissue volumes were measured as ∼6—11% higher and fractional anisotropy was 33% higher at 3T than at 1.5T), between-scanner consistency was good to excellent for global volumetric and dMRI measures (intraclass correlation coefficient [ICC] range: 0.612—0.993) and fair to good for 68 cortical regions (FreeSurfer) and cortical surface measures (mean ICC: 0.504—0.763). Between-scanner consistency was fair for dMRI measures of 12 major white matter tracts (mean ICC: 0.475—0.564), and the general factors of these tracts provided excellent consistency (ICC ≥ 0.769). Whole-brain structural networks provided good to excellent consistency for global metrics (ICC ≥ 0.612). Although consistency was poor for individual network connections (mean ICCs: 0.275 – 0.280), this was driven by a large difference in network sparsity (0.599 versus 0.334), and consistency was improved when comparing only the connections present in every participant (mean ICCs: 0.533—0.647). Regression-based k-fold cross-validation showed that, particularly for global volumes, between-scanner differences could be largely eliminated (R2range 0.615—0.991). We conclude that low granularity measures of brain structure can be reliably matched between the scanners tested, but caution is warranted when combining high granularity information from different scanners.

Highlights • Greater SVD burden associates with poorer abilities in all major cognitive domains. • SVD associates with memory and visuospatial due to covariance with general ability. • However, SVD’s association with processing speed is independent of general ability. • Continuous radiological variables improve fidelity of SVD burden quantification. • All major cognitive domains should be tested in SVD research and clinical settings., Cerebral small vessel disease (SVD) is a leading cause of vascular cognitive impairment, however the precise nature of SVD-related cognitive deficits, and their associations with structural brain changes, remain unclear. We combined computational volumes and visually-rated MRI markers of SVD to quantify total SVD burden, using data from the Lothian Birth Cohort 1936 (n = 540; age: 72.6 ± 0.7 years). We found negative associations between total SVD burden and general cognitive ability (standardized β: -0.363; 95%CI: [-0.49, -0.23]; p(FDR) < 0.001), processing speed (-0.371 [-0.50, -0.24]; p(FDR) < 0.001), verbal memory (-0.265; [-0.42, -0.11]; p(FDR) = 0.002), and visuospatial ability (-0.170; [-0.32, -0.02]; p(FDR) = 0.029). Only the association between SVD burden and processing speed remained after accounting for covariance with general cognitive ability (-0.325; [-0.61, -0.04]; p(FDR) = 0.029). This suggests that SVD's association with poorer processing speed is not driven by, but is independent of its association with poorer general cognitive ability. Tests of processing speed may be particularly sensitive to the cognitive impact of SVD, but all major cognitive domains should be tested to determine the full range of SVD-related cognitive characteristics.

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.

Perivascular spaces include a variety of passageways around arterioles, capillaries and venules in the brain, along which a range of substances can move. Although perivascular spaces were first identified over 150 years ago, they have come to prominence recently owing to advances in knowledge of their roles in clearance of interstitial fluid and waste from the brain, particularly during sleep, and in the pathogenesis of small vessel disease, Alzheimer disease and other neurodegenerative and inflammatory disorders. Experimental advances have facilitated in vivo studies of perivascular space function in intact rodent models during wakefulness and sleep, and MRI in humans has enabled perivascular space morphology to be related to cognitive function, vascular risk factors, vascular and neurodegenerative brain lesions, sleep patterns and cerebral haemodynamics. Many questions about perivascular spaces remain, but what is now clear is that normal perivascular space function is important for maintaining brain health. Here, we review perivascular space anatomy, physiology and pathology, particularly as seen with MRI in humans, and consider translation from models to humans to highlight knowns, unknowns, controversies and clinical relevance.

The retinal and cerebral microvasculatures share many morphological and physiological properties. In this pilot we study the strength of the associations between morphological measurements of the retinal vasculature, obtained from fundus camera images, and of features of Small Vessel Disease (SVD), as white matter hyperintensities (WMH) and perivascular spaces (PVS), obtained from MRI brain scans. We performed a 500-trial bootstrap analysis with Regularized Gaussian linear regression on a cohort of older community-dwelling subjects (Lothian Birth Cohort 1936, N = 866) in their eighth decade. Arteriolar bifurcation coefficients, vessel tortuosity and fractal dimension predicted WMH volume in 23% of the trials. Arteriolar widths, venular bifurcation coefficients, and venular tortuosity predicted PVS in up to 99.6% of the trials.

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.

Perivascular spaces are fluid-filled tubular spaces that follow the course of cerebral penetrating vessels, thought to be a key part in the brain’s circulation and glymphatic drainage system. Their enlargement and abundance have been found associated with cerebral small vessel disease. Thus, their quantification is essential for establishing their relationship with neurological diseases. Previous works in the field have designed visual rating scales for assessing the presence of perivascular spaces and proposed segmentation techniques to reduce flooring and ceiling effects of qualitative visual scales, processing times, and inter-observer variability. Nonetheless, their application depends on the acquisition quality. In this paper, we propose a framework for improving perivascular spaces quantification using both texture analysis and total variation filtering. Texture features were considered for evaluating the image quality and determining automatically whether filtering was needed. We tested our work using data from a cohort of patients with mild stroke (\(n=60\)) with different extents of small vessel disease features and image quality. Our results demonstrate the potential of our proposal for improving perivascular spaces assessments.

Background and PurposeVentricular enlargement, especially enlargement of the lateral ventricles, is thought to be positively associated with white matter hyperintensities (WMH). Possible mechanisms behind the association are unclear. Lateral ventricles might increase due to generalised brain tissue loss not specific to periventricular WMH. Alternatively, they may expand into areas of tissue loss related to WMH, take up space and grow in size.MethodsWe investigated relations between longitudinal lateral ventricle and WMH volume changes, alongside vascular risk factors, in community-dwelling older people. We assessed lateral ventricle and WMH volumes, accounting for total brain volume, blood pressure, medical assessments and self-reported history of stroke, cardiovascular disease, diabetes and smoking. We used longitudinal data at three time points, each three years apart, between ages 73 to 79, including MRI data from all available time points.ResultsLateral ventricle volume increased steadily with age in all participants, WMH volume change was more variable. Decrease of WMH volume was found in around 20% and increase in remaining subjects. Using a repeated-measurements linear mixed model we found that over 6 years, lateral ventricle volume increased by 3% per year of age, 0.1% per mm Hg increase in mean blood pressure, 3.2% per 1% decrease of total brain volume, and 4.5% per 1% increase of WMH volume. Over time, lateral ventricle volumes were 19% smaller in women than men. No associations were found with other variables.ConclusionsChanges in lateral ventricle volumes and WMH volumes over time are only modestly associated, independent of general brain atrophy.

Supplemental Digital Content is available in the text., Objective: The retina may provide readily accessible imaging biomarkers of global cardiovascular health. Increasing evidence suggests variation in retinal vascular traits is highly heritable. This study aimed to identify the genetic determinants of retinal vascular traits. Approach and Results: We conducted a meta-analysis of genome-wide association studies for quantitative retinal vascular traits derived using semi-automatic image analysis of digital retinal photographs from the GoDARTS (Genetics of Diabetes Audit and Research in Tayside; N=1736) and ORCADES (Orkney Complex Disease Study; N=1358) cohorts. We identified a novel genome-wide significant locus at 19q13 (ACTN4/CAPN12) for retinal venular tortuosity (TortV), and one at 13q34 (COL4A2) for retinal arteriolar tortuosity (TortA); these 2 loci were subsequently confirmed in 3 independent cohorts (Ntotal=1413). In the combined analysis of discovery and replication cohorts, the lead single-nucleotide polymorphism in ACTN4/CAPN12 was rs1808382 (βs.d.=-0.109; SE=0.015; P=2.39×10-13) and in COL4A2 was rs7991229 (βs.d.=0.103; SE=0.015; P=4.66×10-12). Notably, the ACTN4/CAPN12 locus associated with TortV is also associated with coronary artery disease, heart rate, and atrial fibrillation. Conclusions: Genetic determinants of retinal vascular tortuosity are also linked to cardiovascular health. These findings provide a molecular pathophysiological foundation for the use of retinal vascular traits as biomarkers for cardiovascular diseases.

Automatically classifying retinal blood vessels appearing in fundus camera imaging into arterioles and venules can be problematic due to variations between people as well as in image quality, contrast and brightness. Using the most dominant features for retinal vessel types in each image rather than predefining the set of characteristic features prior to classification may achieve better performance. In this paper, we present a novel approach to classifying retinal vessels extracted from fundus camera images which combines an Orthogonal Locality Preserving Projections for feature extraction and a Gaussian Mixture Model with Expectation-Maximization unsupervised classifier. The classification rate with 47 features (the largest dimension tested) using OLPP on our own ORCADES dataset and the publicly available DRIVE dataset was $90.56\%$ and $86.7\%$ respectively.

Highlights • Quantitative measurements of Perivascular Spaces (PVS) relates to retinal vascular changes in a large sample of elderly subjects (n = 381). • Higher PVS burden corresponds with narrower retinal arterioles and reduced fractal dimension. • The retinal fractal dimension is a possible indicator of the state of health of the brain vasculature., Background Perivascular Spaces (PVS) become increasingly visible with advancing age on brain MRI, yet their relationship to morphological changes in the underlying microvessels remains poorly understood. Retinal and cerebral microvessels share morphological and physiological properties. We compared computationally-derived PVS morphologies with retinal vessel morphologies in older people. Methods We analysed data from community-dwelling individuals who underwent multimodal brain MRI and retinal fundus camera imaging at mean age 72.55 years (SD=0.71). We assessed centrum semiovale PVS computationally to determine PVS total volume and count, and mean per-subject individual PVS length, width and size. We analysed retinal images using the VAMPIRE software suite, obtaining the Central Retinal Artery and Vein Equivalents (CRVE and CRAE), Arteriole-to-Venule ratio (AVR), and fractal dimension (FD) of both eyes. We investigated associations using general linear models, adjusted for age, gender, and major vascular risk factors. Results In 381 subjects with all measures, increasing total PVS volume and count were associated with decreased CRAE in the left eye (volume β=−0.170, count β=−0.184, p

Introduction We test whether measures of the retinal vasculature are associated with cognitive functioning and cognitive change. Methods Retinal images from a narrow-age cohort were analyzed using Vessel Assessment and Measurement Platform for Images of the Retina, producing a comprehensive range of quantitative measurements of the retinal vasculature, at mean age 72.5 years (SD = 0.7). Cognitive ability and change were measured using a battery of multiple measures of memory, visuospatial, processing speed, and crystallized cognitive abilities at mean ages 73, 76, and 79 years. We applied multivariate growth curve models to test the association between retinal vascular measurements with cognitive abilities and their changes. Results Almost all associations were nonsignificant. In our most parsimonious model, venular asymmetry factor was associated with speed at age 73. Discussion Our null findings suggest that the quantitative retinal parameters applied in this study are not significantly associated with cognitive functioning or cognitive change.

OBJECTIVES: To validate a retinal imaging software named VAMPIRE® (Vascular Assay and Measurement Platform for Images of the Retina) in feline patients and test the clinical utility in hypertensive cats. ANIMALS STUDIED: One hundred and five healthy cats were enrolled. They represented the normal dataset used in the validation (group 1). Forty‐three hypertensive cats with no noticeable retinal abnormalities were enrolled for the clinical validity of the software (group 2). PROCEDURES: Eleven points (4 veins, 4 arteries, and 3 arterial bifurcations) were measured for each digital image. Repeatability and reproducibility of measurements were assessed using two independent operators. Data were statistically analyzed by the Mann‐Whiney and Tukey box plot. Significance was considered when P

Background Perivascular spaces, visible on brain magnetic resonance imaging, are thought to be associated with small vessel disease, neuroinflammation, and to be important for cerebral hemodynamics and interstitial fluid drainage. Aims To benchmark current knowledge on perivascular spaces associations with risk factors, neurological disorders, and neuroimaging lesions, using systematic review and meta-analysis. Summary of review We searched three databases for perivascular spaces publications, calculated odds ratios with 95% confidence interval and performed meta-analyses to assess adjusted associations with perivascular spaces. We identified 116 relevant studies ( n = 36,108) but only 23 ( n = 12,725) were meta-analyzable. Perivascular spaces assessment, imaging and clinical definitions varied. Perivascular spaces were associated ( n; OR, 95%CI, p) with ageing (8395; 1.47, 1.28–1.69, p = 0.00001), hypertension (7872; 1.67, 1.20–2.31, p = 0.002), lacunes (4894; 3.56, 1.39–9.14, p = 0.008), microbleeds (5015; 2.26, 1.04–4.90, p = 0.04) but not WMH (4974; 1.54, 0.71–3.32, p = 0.27), stroke or cognitive impairment. There was between-study heterogeneity. Lack of appropriate data on other brain disorders and demographic features such as ethnicity precluded analysis. Conclusions Despite many studies, more are required to determine potential pathophysiological perivascular spaces involvement in cerebrovascular, neurodegenerative and neuroinflammatory disorders.

Highlights • We assessed Perivascular Spaces (PVS) computationally in the centrum semiovale. • We measured total PVS volume and count, and individual PVS length, width, size. • Computational PVS measures correlated positively with PVS ratings. • PVS were associated with hypertension stroke and white matter hyperintensities., 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 β = 0.66, 95% CI [0.59 to 0.74] and versus WMH volume β = 0.43, 95% CI [0.38 to 0.48]) than computational PVS count (WMH Fazekas score β = 0.21, 95% CI [0.11 to 0.3]; WMH volume β = 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., Graphical abstract Image, graphical abstract

Research has suggested that the retinal vasculature may act as a surrogate marker for diseased cerebral vessels. Retinal vascular parameters were measured using Vessel Assessment and Measurement Platform for Images of the Retina (VAMPIRE) software in two cohorts: (i) community-dwelling older subjects of the Lothian Birth Cohort 1936 (n = 603); and (ii) patients with recent minor ischaemic stroke of the Mild Stroke Study (n = 155). Imaging markers of small vessel disease (SVD) (white matter hyperintensities [WMH] on structural MRI, visual scores and volume; perivascular spaces; lacunes and microbleeds), and vascular risk measures were assessed in both cohorts. We assessed associations between retinal and brain measurements using structural equation modelling and regression analysis. In the Lothian Birth Cohort 1936 arteriolar fractal dimension accounted for 4% of the variance in WMH load. In the Mild Stroke Study lower arteriolar fractal dimension was associated with deep WMH scores (odds ratio [OR] 0.53; 95% CI, 0.32–0.87). No other retinal measure was associated with SVD. Reduced fractal dimension, a measure of vascular complexity, is related to SVD imaging features in older people. The results provide some support for the use of the retinal vasculature in the study of brain microvascular disease.

Structural variation in retinal blood vessels is associated with global vascular health in humans and may provide a readily accessible indicator of several diseases of vascular origin. Increasing evidence suggests variation in retinal vasculature is highly heritable. This study aimed to identify genetic determinants of retinal vascular traits. We reported a meta-analysis of genome-wide association studies (GWAS) for quantitative retinal vascular traits derived using semi-automatic image analysis of digital retinal photographs from the Genetics of Diabetes Audit and Research in Tayside (GoDARTS) (n=1736) and the Orkney Complex Disease Study (ORCADES) (n=1358) cohorts. We identified a novel genome-wide significant locus at 19q13 (ACTN4/CAPN12) for retinal venular tortuosity (TortV), and one at 13q34 (COL4A2) for retinal arteriolar tortuosity (TortA); these two loci were subsequently confirmed in three independent cohorts (n=1413). In the combined analysis in ACTN4/CAPN12 the lead single nucleotide polymorphism (SNP) was rs1808382 (n=4507; Beta=−0.109; standard error (SE) =0.015; P=2.39×10−13) and in COL4A2 it was rs7991229 (n=4507; Beta=0.103; SE=0.015; P=4.66×10−12). Notably, the ACTN4/CAPN12 locus associated with retinal TortV is also associated with coronary artery disease and heart rate. Our findings demonstrate the contribution of genetics in retinal tortuosity traits, and provide new insights into cardiovascular diseases.Author SummaryRetinal vascular features are associated with wide range of diseases related to vascular health and provide an opportunity to understand early structural changes in vasculature which may help to predict disease risk. Emerging evidence indicates that retinal tortuosity traits are both associated with vascular health and highly heritable. However, the genetic architecture of retinal vascular tortuosity has not been investigated. We therefore performed a genome-wide association study on retinal arteriolar tortuosity (TortA) and retinal venular tortuosity trait (TortV) using data from two independent discovery cohorts of 3094 individuals of European-heritage. We found a novel associations at 19q13 (ACTN4/CAPN12) for TortV, and one at 13q34 (COL4A2) for TortA at discovery stage and validated in three independent cohorts. A significant association was subsequently found between lead SNPs at 19q13 and coronary artery disease, cardiovascular vascular risk factors and heart rate. We also performed genome-wide association studies for retinal vascular calibres and optic disc radius (ODradius) and replicated previously reported locus at 10q21.3 for ODradius. Our findings highlight genetic impacts on retinal venular tortuosity and it is association with cardiovascular disease. This may provide a molecular pathophysiological foundation for use of retinal vascular traits as biomarkers for cardiovascular diseases.

Introduction\ud \ud Many 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.\ud \ud \ud \ud Methods\ud \ud Surveys, teleconferences, and an in-person workshop were used to identify gaps in knowledge and to develop tools for harmonizing imaging and analysis.\ud \ud \ud \ud Results\ud \ud A 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.\ud \ud \ud \ud Conclusions\ud \ud The HARNESS initiative provides resources to reduce variability in measurement in MRI studies of cerebral small vessel disease.

Locating the optic disc center and the fovea in digital fundus images is surprisingly difficult due to the variation range in color and contrast and the possible presence of pathologies creating bright spots or changing the appearance of retinal landmarks. These reasons make it difficult to find good templates of optic disc and fovea shape and color for pattern matching. In this paper we propose radial symmetry as the principal cue to locate both optic disc and macula centers. Centers of bright and dark circularly symmetrical regions with arbitrary radii, can be found robustly against changes in brightness and contrast by using the Fast Radial Symmetry transform. Detectors based on this transform coupled with a weak hypothesis on vessel density (optic disc intersects large vessels while the fovea lies in an avascular region), can provide a fast location of both OD and macula with accuracy similar or better than state-of-the-art methods. The approach has been chosen as the default technique for fast localization of the two landmarks in the VAMPIRE software suite.

La segmentación de los espacios perivasculares (EVP) de las imágenes de resonancia magnética (RM) del cerebro es importante para comprender el sistema linfático del cerebro y su relación con las enfermedades neurológicas. El filtro Frangi podría ser una herramienta valiosa para este propósito. Sin embargo, sus parámetros deben ajustarse en respuesta a la variabilidad en los parámetros del escáner y los protocolos de estudio. Conociendo las clasificaciones neurorradiológicas del PVS, utilizamos el modelo logit ordenado para optimizar los parámetros del filtro Frangi. El volumen de PVS obtenido se correlacionó de manera significativa y fuerte con las evaluaciones neurorradiológicas (ρ = 0.75, p

Retinal image analysis is emerging as a key source of biomarkers of chronic systemic conditions affecting the cardiovascular system and brain. The rapid development and increasing diversity of commercial retinal imaging systems present a challenge to image analysis software providers. In addition, clinicians are looking to extract maximum value from the clinical imaging taking place. We describe how existing and well-established retinal vasculature segmentation and measurement software for fundus camera images has been modulated to analyze scanning laser ophthalmoscope retinal images generated by the dual-modality Heidelberg SPECTRALIS(®) instrument, which also features optical coherence tomography.

Non-analytical reasoning is thought to play a key role in dermatology diagnosis. Considering its potential importance, surprisingly little work has been done to research whether similar identification processes can be supported in non-experts. We describe here a prototype diagnostic support software, which we have used to examine the ability of medical students (at the beginning and end of a dermatology attachment) and lay volunteers, to diagnose 12 images of common skin lesions. Overall, the non-experts using the software had a diagnostic accuracy of 98% (923/936) compared with 33% for the control group (215/648) (Wilcoxon p

Photographic supra-projection is a forensic process that aims to identify a missing person from a photograph and a skull found. One of the crucial tasks throughout all this process is the craniofacial superimposition which tries to find a good fit between a 3D model of the skull and the 2D photo of the face. This photographic supra-projection stage is usually carried out manually by forensic anthropologists. It is thus very time consuming and presents several difficulties. In this paper, we aim to demonstrate that real-coded evolutionary algorithms are suitable approaches to tackle craniofacial superimposition. To do so, we first formulate this complex task in forensic identification as a numerical optimization problem. Then, we adapt three different evolutionary algorithms to solve it: two variants of a real-coded genetic algorithm and the state of the art evolution strategy CMA-ES. We also consider an existing binary-coded genetic algorithm as a baseline. Results on several superimposition problems of real-world identification cases solved by the Physical Anthropology lab at the University of Granada (Spain) are considered to test our proposals.

A common way to determine tissue acceptance of biomaterials is to perform histomorphometrical analysis on histologically stained sections from retrieved samples with surrounding tissue, using various methods. The "time and money consuming" methods and techniques used are often "in house standards". We address light microscopic investigations of bone tissue reactions on un-decalcified cut and ground sections of threaded implants. In order to screen sections and generate results faster, the aim of this pilot project was to compare results generated with the in-house standard visual image analysis tool (i.e., quantifications and judgements done by the naked eye) with a custom made automatic image analysis program. The histomorphometrical bone area measurements revealed no significant differences between the methods but the results of the bony contacts varied significantly. The raw results were in relative agreement, i.e., the values from the two methods were proportional to each other: low bony contact values in the visual method corresponded to low values with the automatic method. With similar resolution images and further improvements of the automatic method this difference should become insignificant. A great advantage using the new automatic image analysis method is that it is time saving--analysis time can be significantly reduced.

Sarcopenia in older people is a major health issue and its early detection could help target interventions and improve health. Evidence suggests that poor muscle mass is associated with greater arterial stiffness and cardiovascular risk. Arterial stiffness in turn is associated with smaller retinal artery width. This study examined the association of muscle mass in older people with retinal vascular width, a non-invasive measure of vascular function. Methods Participants >65 years were recruited to a cross-sectional study. Exclusions: Inability to walk independently; diabetes mellitus; stroke (within 6 months), severe macular degeneration, glaucoma, retinal dystrophy; advanced cataract. Digital Retinal images of both eyes were analysed using the VAMPIRE software suite. Central Retinal Artery and Vein Equivalents (CRVE and CRAE) were measured. Body composition was measured using Dual Energy X ray Absorptimetry (DXA). Appendicular Skeletal Muscle Mass/Height2 was calculated. Physical function was measured: 6-min walk distance, Short Physical performance battery, handgrip strength and quadriceps strength. Results 79 participants with mean age 72 (SD 6) years were recruited. 44% were female. Digital Retinal images of sufficient quality for measuring CRAE and CRVE were available for 51/75 (68%) of participants. Regression analysis showed significant association between larger ASMM/H2 and smaller CRAE (β = −0.20, p = 0.001) and CRVE (β = −0.12, p = 0.05). Handgrip strength, body mass index and sex combined with CRAE explained 88% and with CRVE explained 86% of the variance in ASMM/H2. Conclusion Larger muscle mass was significantly associated with smaller retinal artery size in older people. This unexpected finding needs further investigation.

We describe a complete pipeline for the detection and accurate automatic segmentation of the optic disc in digital fundus images. This procedure provides separation of vascular information and accurate inpainting of vessel-removed images, symmetry-based optic disc localization, and fitting of incrementally complex contour models at increasing resolutions using information related to inpainted images and vessel masks. Validation experiments, performed on a large dataset of images of healthy and pathological eyes, annotated by experts and partially graded with a quality label, demonstrate the good performances of the proposed approach. The method is able to detect the optic disc and trace its contours better than the other systems presented in the literature and tested on the same data. The average error in the obtained contour masks is reasonably close to the interoperator errors and suitable for practical applications. The optic disc segmentation pipeline is currently integrated in a complete software suite for the semiautomatic quantification of retinal vessel properties from fundus camera images (VAMPIRE).

This paper summarizes three recent, novel algorithms developed within VAMPIRE, namely optic disc and macula detection, arteryvein classification, and enhancement of binary vessel masks, and their performance assessment. VAMPIRE is an international collaboration growing a suite of software tools to allow efficient quantification of morphological properties of the retinal vasculature in large collections of fundus camera images. VAMPIRE measurements are currently mostly used in biomarker research, i.e., investigating associations between the morphology of the retinal vasculature and a number of clinical and cognitive conditions.

This paper presents an algorithm for classification of non-melanoma skin lesions based on a novel hierarchical K-Nearest Neighbors (K-NN) classifier. The K-NN classifier is simple, quick and effective. The hierarchical structure decomposes the classification task into a set of simpler problems, one at each node of the classification. Feature selection is embedded in the hierarchical framework that chooses the most relevant feature subsets at each node of the hierarchy. Colour and texture features are extracted from skin lesions. The accuracy of the proposed hierarchical scheme is higher than 93% in discriminating cancer and pre-malignant lesions from benign lesions, and it reaches an overall classification accuracy of 74% over five common classes of skin lesions, including two non-melanoma cancer types. This is the most extensive published result on non-melanoma skin cancer classification from colour images acquired by a standard camera (non-dermoscopy).

We propose a system for describing skin lesions images based on a human perception model. Pigmented skin lesions including melanoma and other types of skin cancer as well as non-malignant lesions are used. Works on classification of skin lesions already exist but they mainly concentrate on melanoma. The novelty of our work is that our system gives to skin lesion images a semantic label in a manner similar to humans. This work consists of two parts: first we capture they way users perceive each lesion, second we train a machine learning system that simulates how people describe images. For the first part, we choose 5 attributes: colour (light to dark), colour uniformity (uniform to non-uniform), symmetry (symmetric to non-symmetric), border (regular to irregular), texture (smooth to rough). Using a web based form we asked people to pick a value of each attribute for each lesion. In the second part, we extract 93 features from each lesions and we trained a machine learning algorithm using such features as input and the values of the human attributes as output. Results are quite promising, especially for the colour related attributes, where our system classifies over 80% of the lesions into the same semantic classes as humans.

In this work we propose a new method to segment range images. It automatically extracts invariant features directly from point clouds. Points belonging to such features are used as the input to improve an evolutionary approach to 3D range image registration in forensic anthropology. We use such features in the automatic reconstruction of an accurate 3D model of the skull. Our reconstruction method includes a pre-alignment stage, that uses a subset of feature points, and a refinement stage. Results are presented over a set of instances of real problems.

Breast cancer is the most common form of cancer among women. The diagnosis is usually performed by the pathologist, that subjectively evaluates tissue samples. The aim of our research is to develop techniques for the automatic classification of cancerous tissue, by analyzing histological samples of intact tissue taken with a biopsy. In our study, we considered 200 images presenting four different conditions: normal tissue, fibroadenosis, ductal cancer and lobular cancer. Methods to extract features have been investigated and described. One method is based on granulometries, which are size-shape descriptors widely used in mathematical morphology. Applications of granulometries lead to distribution functions whose moments are used as features. A second method is based on fractal geometry, that seems very suitable to quantify biological structures. The fractal dimension of binary images has been computed using the euclidean distance mapping. Image classification has then been performed using the extracted features as input of a back-propagation neural network. A new method that combines genetic algorithms and morphological filters has been also investigated. In this case, the classification is based on a correlation measure. Very encouraging results have been obtained with pilot experiments using a small subset of images as training set. Experimental results indicate the effectiveness of the proposed methods. Cancerous tissue was correctly classified in 92.5% of the cases.

In this paper we apply genetic algorithms to morphological filter optimization. The validation of the method is illustrated by performing experiments with synthetic images, whose optimal filter is known. Applications to microscopic images of breast tissue are reported. The medical problem consists in the discrimination between cancerous tissue and normal one.

In this work a computational approach for detecting and quantifying diabetic retinopathy is proposed. Particular attention has been paid to the study of Foveal Avascular Zone (FAZ). In fact, retinal capillary occlusion produces a FAZ enlargement. Moreover, the FAZ is characterized by qualitative changes showing an irregular contour with notchings and indentations. Our study is mainly focused on the analysis of the FAZ and on the extraction of a proper set of features to quantify FAZ alterations in diabetic patients. We propose an automatic segmentation procedure to correctly identify the FAZ boundary. The method was derived from the theory of active contours, also known as snakes, along with genetic optimization. Then we tried to extract features which can capture not only the size of the object, but also its shape and spatial orientation. The theory of moments provides an interesting and useful way for representing the shape of objects. We used a set of region and boundary moments to obtain a FAZ description which is complete enough for diagnostic purposes and in order to assess the effectiveness of moment descriptors we performed several classification experiments to discriminate diabetic from non-diabetic subjects. We used a neural network-based classifier, optimized for the problem, which is able to perform feature selection at the same time as learning, in order to extract a subset of features. The theory of moments provided us with an interesting and useful tool for representing the shape characteristics. In this way we were able to transform the qualitative description of the FAZ used by ophthalmologists into quantitative measurements.

In this paper a method for noise reduction in ocular fundus image sequences is described. The eye is the only part of the human body where the capillary network can be observed along with the arterial and venous circulation using a non invasive technique. The study of the retinal vessels is very important both for the study of the local pathology (retinal disease) and for the large amount of information it offers on systematic haemodynamics, such as hypertension, arteriosclerosis, and diabetes. In this paper a method for image integration of ocular fundus image sequences is described. The procedure can be divided in two step: registration and fusion. First we describe an automatic alignment algorithm for registration of ocular fundus images. In order to enhance vessel structures, we used a spatially oriented bank of filters designed to match the properties of the objects of interest. To evaluate interframe misalignment we adopted a fast cross-correlation algorithm. The performances of the alignment method have been estimated by simulating shifts between image pairs and by using a cross-validation approach. Then we propose a temporal integration technique of image sequences so as to compute enhanced pictures of the overall capillary network. Image registration is combined with image enhancement by fusing subsequent frames of a same region. To evaluate the attainable results, the signal-to-noise ratio was estimated before and after integration. Experimental results on synthetic images of vessel-like structures with different kind of Gaussian additive noise as well as on real fundus images are reported.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Enlarged perivascular spaces (PVS) and white matter hyperintensities (WMH) are features of cerebral small vessel disease which can be seen in brain magnetic resonance imaging (MRI). Given the associations and proposed mechanistic link between PVS and WMH, they are hypothesised to also have topological proximity. However, this, and the influence of their spatial proximity on WMH progression are unknown. We analysed longitudinal MRI data from 29/32 participants (mean age at baseline = 71.9 years) in a longitudinal study of cognitive ageing, from three waves of data collection at 3-year intervals, alongside semi-automatic segmentation masks for PVS and WMH, to assess relationships. The majority of deep WMH clusters were found adjacent to or enclosing PVS (Wave – 1: 77%; 2: 76%; 3: 69%), especially in frontal, parietal and temporal regions. Of the WMH clusters in the deep white matter that increased between waves, most increased around PVS (Waves – 1-2: 73%; 2-3: 72%). Formal statistical comparisons of severity of each if these two SVD markers yielded no associations between deep WMH progression and PVS proximity. These findings may suggest deep WMH clusters preferentially form and grow around PVS, possibly reflecting the consequences of impaired interstitial fluid drainage via PVS. The utility of these relationships as predictors of WMH progression remains unclear.