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BACKGROUND AND PURPOSE: Incidental findings on brain MR and variation of the circle of Willis (CoW) are relatively common among the general population. Ethnic differences have been described before, but few studies have explored the prevalence of incidental intracranial cerebrovascular findings and CoW variants in the setting of a single multi-ethnic cohort. The purpose of this investigation is to describe both incidental cerebrovascular findings and the morphology of the CoW on high-resolution 3T time-of-flight MR angiography (ToF MRA) in a UK tri-ethnic population-based cohort and to present updated prevalence estimates and morphologic reference values. MATERIALS AND METHODS: We studied participants from the UK Southall and Brent Revisited (SABRE) study who underwent 3T brain MRI between 2014-2018. ToF MRA images were assessed for the presence of incidental cerebrovascular imaging findings and used to determine CoW anatomy. RESULTS: 750 participants (mean age: 71.28 ± 6.46 years, range [46-90], 337 female), 322 White Europeans, 253 South Asians, and 175 African Caribbeans, were included. Incidental cerebrovascular findings were observed in 84 subjects (11.2%, 95% CI [9.0-13.7]; 38 women, 45.24%, 95% CI [34.34-56.48]), cerebral aneurysms being the most frequent, followed by intracranial arterial stenoses (ICAS) with highest prevalence among South Asians compared to White European (OR: 2.72, 95% CI [1.22-6.08], p = .015) and African Caribbean subjects (OR: 2.79, 95% CI [1.00-7.82], p = .051). Other findings included arteriovenous malformations and infundibula. The CoW was found to be more often complete in women than in men (25.22% compared to 18.41%, p = .024), and in African Caribbean (34.86%), compared to White European (19.19%), and South Asian (14.23%) subjects (p <0.001 each). CONCLUSIONS: ICAS were independently associated with ethnicity after adjusting for vascular risk factors, having the highest prevalence among South Asians. The prevalence of aneurysms was higher than in previous population-based studies. We observed anatomical differences in the CoW configuration between women, men, and ethnicities. ABBREVIATIONS: BP = Blood pressure; ICAS = Intracranial arterial stenoses; CoW = Circle of Willis; CVM = Cerebral vascular malformations; OR = Odds ratio; ToF MRA = Time-of-flight MR angiography.
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We propose a novel approach to the estimation of multiple Graphical Models to analyse temporal patterns of association among a set of metabolites over different groups of patients. Our motivating application is the Southall And Brent REvisited (SABRE) study, a tri-ethnic cohort study conducted in the UK. We are interested in identifying potential ethnic differences in metabolite levels and associations as well as their evolution over time, with the aim of gaining a better understanding of different risk of cardio-metabolic disorders across ethnicities. Within a Bayesian framework, we employ a nodewise regression approach to infer the structure of the graphs, borrowing information across time as well as across ethnicities. The response variables of interest are metabolite levels measured at two time points and for two ethnic groups, Europeans and South-Asians. We use nodewise regression to estimate the high-dimensional precision matrices of the metabolites, imposing sparsity on the regression coefficients through the dynamic horseshoe prior, thus favouring sparser graphs. We provide the code to fit the proposed model using the software Stan, which performs posterior inference using Hamiltonian Monte Carlo sampling, as well as a detailed description of a block Gibbs sampling scheme.
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Imaging markers of cerebral small vessel disease provide valuable information on brain health, but their manual assessment is time-consuming and hampered by substantial intra- and interrater variability. Automated rating may benefit biomedical research, as well as clinical assessment, but diagnostic reliability of existing algorithms is unknown. Here, we present the results of the VAscular Lesions DetectiOn and Segmentation (Where is VALDO?) challenge that was run as a satellite event at the international conference on Medical Image Computing and Computer Aided Intervention (MICCAI) 2021. This challenge aimed to promote the development of methods for automated detection and segmentation of small and sparse imaging markers of cerebral small vessel disease, namely enlarged perivascular spaces (EPVS) (Task 1), cerebral microbleeds (Task 2) and lacunes of presumed vascular origin (Task 3) while leveraging weak and noisy labels. Overall, 12 teams participated in the challenge proposing solutions for one or more tasks (4 for Task 1-EPVS, 9 for Task 2-Microbleeds and 6 for Task 3-Lacunes). Multi-cohort data was used in both training and evaluation. Results showed a large variability in performance both across teams and across tasks, with promising results notably for Task 1-EPVS and Task 2-Microbleeds and not practically useful results yet for Task 3-Lacunes. It also highlighted the performance inconsistency across cases that may deter use at an individual level, while still proving useful at a population level.