Systematic review and meta-analysis of automated methods for quantifying enlarged perivascular spaces in the brain.

Research into magnetic resonance imaging (MRI)-visible perivascular spaces (PVS) has recently increased, as results from studies in different diseases and populations are cementing their association with sleep, disease phenotypes, and overall health indicators. With the establishment of worldwide consortia and the availability of large databases, computational methods that allow to automatically process all this wealth of information are becoming increasingly relevant. Several computational approaches have been proposed to assess PVS from MRI, and efforts have been made to summarise and appraise the most widely applied ones. We systematically reviewed and meta-analysed all publications available up to September 2023 describing the development, improvement, or application of computational PVS quantification methods from MRI. We analysed 67 approaches and 60 applications of their implementation, from 112 publications. The two most widely applied were the use of a morphological filter to enhance PVS-like structures, with Frangi being the choice preferred by most, and the use of a U-Net configuration with or without residual connections. Older adults or population studies comprising adults from 18 years old onwards were, overall, more frequent than studies using clinical samples. PVS were mainly assessed from T2-weighted MRI acquired in 1.5T and/or 3T scanners, although combinations using it with T1-weighted and FLAIR images were also abundant. Common associations researched included age, sex, hypertension, diabetes, white matter hyperintensities, sleep and cognition, with occupation-related, ethnicity, and genetic/hereditable traits being also explored. Despite promising improvements to overcome barriers such as noise and differentiation from other confounds, a need for joined efforts for a wider testing and increasing availability of the most promising methods is now paramount.

Comparison of structural MRI brain measures between 1.5 and 3 T: Data from the Lothian Birth Cohort 1936.

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 (R2 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.

Structural, Functional, and Metabolic Brain Differences as a Function of Gender Identity or Sexual Orientation: A Systematic Review of the Human Neuroimaging Literature.

This review systematically explored structural, functional, and metabolic features of the cisgender brain compared with the transgender brain before hormonal treatment and the heterosexual brain compared to the homosexual brain from the analysis of the neuroimaging literature up to 2018, and identified and discussed subsequent studies published up to March 2021. Our main aim was to help identifying neuroradiological brain features that have been related to human sexuality to contribute to the understanding of the biological elements involved in gender identity and sexual orientation. We analyzed 39 studies on gender identity and 24 on sexual orientation. Our results suggest that some neuroanatomical, neurophysiological, and neurometabolic features in transgender individuals resemble those of their experienced gender despite the majority resembling those from their natal sex. In homosexual individuals the majority resemble those of their same-sex heterosexual population rather than their opposite-sex heterosexual population. However, it is always difficult to interpret findings with noninvasive neuroimaging. Given the gross nature of these measures, it is possible that more differences too subtle to measure with available tools yet contributing to gender identity and sexual orientation could be found. Conflicting results contributed to the difficulty of identifying specific brain features which consistently differ between cisgender and transgender or between heterosexual and homosexual groups. The small number of studies, the small-to-moderate sample size of each study, and the heterogeneity of the investigations made it impossible to meta-analyze all the data extracted. Further studies are necessary to increase the understanding of the neurological substrates of human sexuality.

Novel Genetic Locus Influencing Retinal Venular Tortuosity Is Also Associated With Risk of Coronary Artery Disease.

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 (ßs.d.=-0.109; SE=0.015; P=2.39×10-13) and in COL4A2 was rs7991229 (ßs.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.

VAMPIRE® fundus image analysis algorithms: Validation and diagnostic relevance in hypertensive cats.

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 < 0.05. RESULTS: Two hundred and ten retinal images were analyzed for a total of 2310 measurements. Total mean was 9.1 and 6.1 pixels for veins and arteries, respectively. First, second, and third arteriolar bifurcations angles were 73.6°, 76.9°, and 85.4°, respectively. A comparison between groups 1 and 2 showed a statistically significant reduction in arteriolar diameter (mean 3.3 pixels) and branch angle (55°, 47.8° and 59.9°) associated with increasing vein diameter (mean 24.15 pixels). CONCLUSIONS: Current image analysis techniques used in human medicine were investigated in terms of extending their use to veterinary medicine. The VAMPIRE® algorithm proved useful for an objective diagnosis of retinal vasculature changes secondary to systemic hypertension in cats, and could be an additional diagnostic test for feline systemic hypertension.

Detectability and accuracy of computational measurements of in-silico and physical representations of enlarged perivascular spaces from magnetic resonance images.

BACKGROUND: Magnetic Resonance Imaging (MRI) visible perivascular spaces (PVS) have been associated with age, decline in cognitive abilities, interrupted sleep, and markers of small vessel disease. But the limits of validity of their quantification have not been established. NEW METHOD: We use a purpose-built digital reference object to construct an in-silico phantom for addressing this need, and validate it using a physical phantom. We use cylinders of different sizes as models for PVS. We also evaluate the influence of 'PVS' orientation, and different sets of parameters of the two vesselness filters that have been used for enhancing tubular structures, namely Frangi and RORPO filters, in the measurements' accuracy. RESULTS: PVS measurements in MRI are only a proxy of their true dimensions, as the boundaries of their representation are consistently overestimated. The success in the use of the Frangi filter relies on a careful tuning of several parameters. Alpha= 0.5, beta= 0.5 and c= 500 yielded the best results. RORPO does not have these requirements and allows detecting smaller cylinders in their entirety more consistently in the absence of noise and confounding artefacts. The Frangi filter seems to be best suited for voxel sizes equal or larger than 0.4 mm-isotropic and cylinders larger than 1 mm diameter and 2 mm length. 'PVS' orientation did not affect measurements in data with isotropic voxels. COMPARISON WITH EXISTENT METHODS: Does not apply. CONCLUSIONS: The in-silico and physical phantoms presented are useful for establishing the validity of quantification methods of tubular small structures.

Influence of threshold selection and image sequence in in-vivo segmentation of enlarged perivascular spaces.

BACKGROUND: Growing interest surrounds perivascular spaces (PVS) as a clinical biomarker of brain dysfunction given their association with cerebrovascular risk factors and disease. Neuroimaging techniques allowing quick and reliable quantification are being developed, but, in practice, they require optimisation as their limits of validity are usually unspecified. NEW METHOD: We evaluate modifications and alternatives to a state-of-the-art (SOTA) PVS segmentation method that uses a vesselness filter to enhance PVS discrimination, followed by thresholding of its response, applied to brain magnetic resonance images (MRI) from patients with sporadic small vessel disease acquired at 3 T. RESULTS: The method is robust against inter-observer differences in threshold selection, but separate thresholds for each region of interest (i.e., basal ganglia, centrum semiovale, and midbrain) are required. Noise needs to be assessed prior to selecting these thresholds, as effect of noise and imaging artefacts can be mitigated with a careful optimisation of these thresholds. PVS segmentation from T1-weighted images alone, misses small PVS, therefore, underestimates PVS count, may overestimate individual PVS volume especially in the basal ganglia, and is susceptible to the inclusion of calcified vessels and mineral deposits. Visual analyses indicated the incomplete and fragmented detection of long and thin PVS as the primary cause of errors, with the Frangi filter coping better than the Jerman filter. COMPARISON WITH EXISTING METHODS: Limits of validity to a SOTA PVS segmentation method applied to 3 T MRI with confounding pathology are given. CONCLUSIONS: Evidence presented reinforces the STRIVE-2 recommendation of using T2-weighted images for PVS assessment wherever possible. The Frangi filter is recommended for PVS segmentation from MRI, offering robust output against variations in threshold selection and pathology presentation.

Retinal microvascular phenotypes can track small vessel disease burden and CPAP treatment effectiveness in obstructive sleep apnoea.

Optical coherence tomography angiography (OCT-A) retinal imaging enables in vivo visualization of the retinal microvasculature that is developmentally related to the brain and can offer insight on cerebrovascular health. We investigated retinal phenotypes and neuroimaging markers of small vessel disease (SVD) in individuals with obstructive sleep apnoea (OSA). We enrolled 44 participants (mean age 50.1 ± SD 9.1 years) and performed OCT-A imaging before and after continuous positive airway pressure (CPAP) therapy. Pre-treatment analyses using a generalized estimating equations model adjusted for relevant covariates, revealed perivascular spaces (PVS) volume in basal ganglia associated with greater foveal vessel density (fVD) (p-value < 0.001), and smaller foveal avascular zone area (p-value = 0.01), whereas PVS count in centrum semiovale associated with lower retinal vessel radius (p-value = 0.02) and higher vessel tortuosity (p-value = 0.01). A reduction in retinal vessel radius was also observed with increased OSA severity (p-value = 0.05). Post-treatment analyses showed greater CPAP usage was associated with a decrease in fVD (p-value = 0.02), and increased retinal vessel radius (p-value = 0.01). The findings demonstrate for the first time the potential use of OCT-A to monitor CPAP treatment and its possible impact on both retinal and brain vascular health.

Effects of pupil dilation with topical 0.5% tropicamide on retinal vascular parameters assessed by VAMPIRE® software in healthy cats.

Our study investigates the effects of mydriasis obtained with topical 0.5% tropicamide on retinal vascular parameters evaluated in cats using the retinal imaging software: Vascular Assessment and Measurement Platform for Images of the Retina (VAMPIRE®). Forty client-owned healthy adult cats were included in the study. Topical 0.5% tropicamide was applied to dilate only the right pupil. The left eye was used as a control. Before dilation (T0), infrared pupillometry of both pupils was performed and fundus oculi images were taken from both eyes. Right eye fundus images were then captured 30 min after topical application of tropicamide (T30), when mydriasis was achieved. The retinal vessel widths (3 arteries and 3 veins) were measured with VAMPIRE® in four standard measurement areas (SMA) identified with the letters A, B, C, D. Average value of the 3 vessel widths was used. After normality assessment, the t-test was used to analyse the mean difference in vascular parameters of the left and right eyes at T0 and T30, with p set <0.05. The two eyes showed no statistical differences in pupil and vascular parameter measurements at T0. At T30, only one artery measurement of the right eye (SMA A-peripapillary area) showed a small but statistically significant mean vasoconstriction of approximately 4%. The results indicate that local application of 0.5% tropicamide seems to be associated with a small retinal arteriolar vasoconstriction as assessed by VAMPIRE® in cats. However, this change is minimal, and should not affect the interpretation of the results when VAMPIRE® is used.

Sleep quality, perivascular spaces and brain health markers in ageing - A longitudinal study in the Lothian Birth Cohort 1936.

BACKGROUND: Sleep is thought to play a major role in brain health and general wellbeing. However, few longitudinal studies have explored the relationship between sleep habits and imaging markers of brain health, particularly markers of brain waste clearance such as perivascular spaces (PVS), of neurodegeneration such as brain atrophy, and of vascular disease, such as white matter hyperintensities (WMH). We explore these associations using data collected over 6 years from a birth cohort of older community-dwelling adults in their 70s. METHOD: We analysed brain MRI data from ages 73, 76 and 79 years, and self-reported sleep duration, sleep quality and vascular risk factors from community-dwelling participants in the Lothian Birth Cohort 1936 (LBC1936) study. We calculated sleep efficiency (at age 76), quantified PVS burden (at age 73), and WMH and brain volumes (age 73 to 79), calculated the white matter damage metric, and used structural equation modelling (SEM) to explore associations and potential causative pathways between indicators related to brain waste cleaning (i.e., sleep and PVS burden), brain and WMH volume changes during the 8th decade of life. RESULTS: Lower sleep efficiency was associated with a reduction in normal-appearing white matter (NAWM) volume (ß = 0.204, P = 0.009) from ages 73 to 79, but not concurrent volume (i.e. age 76). Increased daytime sleep correlated with less night-time sleep (r = -0.20, P < 0.001), and with increasing white matter damage metric (ß = -0.122, P = 0.018) and faster WMH growth (ß = 0.116, P = 0.026). Shorter night-time sleep duration was associated with steeper 6-year reduction of NAWM volumes (ß = 0.160, P = 0.011). High burden of PVS at age 73 (volume, count, and visual scores), was associated with faster deterioration in white matter: reduction of NAWM volume (ß = -0.16, P = 0.012) and increasing white matter damage metric (ß = 0.37, P < 0.001) between ages 73 and 79. On SEM, centrum semiovale PVS burden mediated 5% of the associations between sleep parameters and brain changes. CONCLUSION: Sleep impairments, and higher PVS burden, a marker of impaired waste clearance, were associated with faster loss of healthy white matter and increasing WMH in the 8th decade of life. A small percentage of the effect of sleep in white matter health was mediated by the burden of PVS consistent with the proposed role for sleep in brain waste clearance.

Retinal capillary microvessel morphology changes are associated with vascular damage and dysfunction in cerebral small vessel disease.

Cerebral small vessel disease (SVD) is a cause of stroke and dementia. Retinal capillary microvessels revealed by optical coherence tomography angiography (OCTA) are developmentally related to brain microvessels. We quantified retinal vessel density (VD) and branching complexity, investigating relationships with SVD lesions, white matter integrity on diffusion tensor imaging (DTI) and cerebrovascular reactivity (CVR) to CO2 in patients with minor stroke. We enrolled 123 patients (mean age 68.1 ± SD 9.9 years), 115 contributed retinal data. Right (R) and left (L) eyes are reported. After adjusting for age, eye disease, diabetes, blood pressure and image quality, lower VD remained associated with higher mean diffusivity (MD) (standardized ß; R -0.16 [95%CI -0.32 to -0.01]) and lower CVR (L 0.17 [0.03 to 0.31] and R 0.19 [0.02 to 0.36]) in normal appearing white matter (NAWM). Sparser branching remained associated with sub-visible white matter damage shown by higher MD (R -0.24 [-0.08 to -0.40]), lower fractional anisotropy (FA) (L 0.17 [0.01 to 0.33]), and lower CVR (R 0.20 [0.02 to 0.38]) in NAWM. OCTA-derived metrics provide evidence of microvessel abnormalities that may underpin SVD lesions in the brain.

Assessment of perivascular space filtering methods using a three-dimensional computational model.

Growing interest surrounds the assessment of perivascular spaces (PVS) on magnetic resonance imaging (MRI) and their validation as a clinical biomarker of adverse brain health. Nonetheless, the limits of validity of current state-of-the-art segmentation methods are still unclear. Here, we propose an open-source three-dimensional computational framework comprising 3D digital reference objects and evaluate the performance of three PVS filtering methods under various spatiotemporal imaging considerations (including sampling, motion artefacts, and Rician noise). Specifically, we study the performance of the Frangi, Jerman and RORPO filters in enhancing PVS-like structures to facilitate segmentation. Our findings were three-fold. First, as long as voxels are isotropic, RORPO outperforms the other two filters, regardless of imaging quality. Unlike the Frangi and Jerman filters, RORPO's performance does not deteriorate as PVS volume increases. Second, the performance of all "vesselness" filters is heavily influenced by imaging quality, with sampling and motion artefacts being the most damaging for these types of analyses. Third, none of the filters can distinguish PVS from other hyperintense structures (e.g. white matter hyperintensities, stroke lesions, or lacunes) effectively, the area under precision-recall curve dropped substantially (Frangi: from 94.21 [IQR 91.60, 96.16] to 43.76 [IQR 25.19, 63.38]; Jerman: from 94.51 [IQR 91.90, 95.37] to 58.00 [IQR 35.68, 64.87]; RORPO: from 98.72 [IQR 95.37, 98.96] to 71.87 [IQR 57.21, 76.63] without and with other hyperintense structures, respectively). The use of our computational model enables comparing segmentation methods and identifying their advantages and disadvantages, thereby providing means for testing and optimising pipelines for ongoing and future studies.

Topological relationships between perivascular spaces and progression of white matter hyperintensities: A pilot study in a sample of the Lothian Birth Cohort 1936.

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 hypothesized to also have topological proximity. However, this and the influence of their spatial proximity on WMH progression are unknown. We analyzed longitudinal MRI data from 29 out of 32 participants (mean age at baseline = 71.9 years) in a longitudinal study of cognitive aging, 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 (waves-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 of these two SVD markers yielded no associations between deep WMH progression and PVS proximity. These findings may suggest some deep WMH clusters may 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.

Contribution of white matter hyperintensities to ventricular enlargement in older adults.

Lateral ventricles might increase due to generalized tissue loss related to brain atrophy. Alternatively, they may expand into areas of tissue loss related to white matter hyperintensities (WMH). We assessed longitudinal associations between lateral ventricle and WMH volumes, accounting for total brain volume, blood pressure, history of stroke, cardiovascular disease, diabetes and smoking at ages 73, 76 and 79, in participants from the Lothian Birth Cohort 1936, including MRI data from all available time points. Lateral ventricle volume increased steadily with age, WMH volume change was more variable. WMH volume decreased in 20% and increased in remaining subjects. Over 6 years, lateral ventricle volume increased by 3% per year of age, 0.1% per mm Hg increase in 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. Ventricular and WMH volume changes are modestly associated and independent of general brain atrophy, suggesting that their underlying processes do not fully overlap.

Utility of non-rule-based visual matching as a strategy to allow novices to achieve skin lesion diagnosis.

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 < 0.0001). We have demonstrated, within the constraints of a simplified clinical model, that novices' diagnostic scores are significantly increased by the use of a structured image database coupled with matching of index and referent images. The novices achieve this high degree of accuracy without any use of explicit definitions of likeness or rule-based strategies.

Novice identification of melanoma: not quite as straightforward as the ABCDs.

The "ABCD" mnemonic to assist non-experts' diagnosis of melanoma is widely promoted; however, there are good reasons to be sceptical about public education strategies based on analytical, rule-based approaches--such as ABCD (i.e. Asymmetry, Border Irregularity, Colour Uniformity and Diameter). Evidence suggests that accurate diagnosis of skin lesions is achieved predominately through non-analytical pattern recognition (via training examples) and not by rule-based algorithms. If the ABCD are to function as a useful public education tool they must be used reliably by untrained novices, with low inter-observer and intra-diagnosis variation, but with maximal inter-diagnosis differences. The three subjective properties (the ABCs of the ABCD) were investigated experimentally: 33 laypersons scored 40 randomly selected lesions (10 lesions × 4 diagnoses: benign naevi, dysplastic naevi, melanomas, seborrhoeic keratoses) for the three properties on visual analogue scales. The results (n = 3,960) suggest that novices cannot use the ABCs reliably to discern benign from malignant lesions.

Rationale and design of a longitudinal study of cerebral small vessel diseases, clinical and imaging outcomes in patients presenting with mild ischaemic stroke: Mild Stroke Study 3.

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 in the centrum semiovale at the beginning of the 8th decade of life: effect on cognition and associations with mineral deposition.

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 < 0.001). CSO-PVS volume, despite being correlated with all three cognitive measures, was only associated with g-memory (B = -114.5, SE = 48.35, p = 0.018) in general linear models, adjusting for age, sex, vascular risk factors, childhood intelligence and white matter hyperintensity volume. The interaction of CSO-PVS count with diabetes (B = -0.0019, SE = 0.00093, p = 0.041) and volume with age (B = 1.57, SE = 0.67, p = 0.019) were also associated with g-memory. Linear regression models did not replicate these associations. Therefore, it does not seem that CSO-PVS burden is directly associated with general cognitive ability in older age.

Dietary patterns, cognitive function, and structural neuroimaging measures of brain aging.

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 (ß = 0.121, P = 0.002). Associations with global cognitive function (ß = 0.094, P = 0.043), visuospatial ability (ß = 0.113, P = 0.019), and memory (ß = 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 (ß = -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.

Computational quantification of brain perivascular space morphologies: Associations with vascular risk factors and white matter hyperintensities. A study in the Lothian Birth Cohort 1936.

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 ß = 0.66, 95% CI [0.59 to 0.74] and versus WMH volume ß = 0.43, 95% CI [0.38 to 0.48]) than computational PVS count (WMH Fazekas score ß = 0.21, 95% CI [0.11 to 0.3]; WMH volume ß = 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.