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Abstract Background Secondary prevention clinical trials for Alzheimer’s disease (AD) target amyloid accumulation in asymptomatic, amyloid-positive individuals, but it is unclear to what extent other pathophysiological processes, such as small vessel cerebrovascular disease, account for participant performance on the primary cognitive outcomes in those trials. White matter hyperintensities are areas of increased signal on T2-weighted magnetic resonance imaging (MRI) that reflect small vessel cerebrovascular disease. They are associated with cognitive functioning in older adults and with clinical presentation and course of AD, particularly when distributed in posterior brain regions. The purpose of this study was to examine to what degree regional WMH volume is associated with performance on the primary cognitive outcome measure in the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s Disease (A4) study, a secondary prevention trial. Methods Data from 1791 participants (59.5% women, mean age (SD) 71.6 (4.74)) in the A4 study and the Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) companion study at the screening visit were used to quantify WMH volumes on T2-weighted fluid-attenuated inversion recovery (FLAIR) MR images. Cognition was assessed with the preclinical Alzheimer cognitive composite (PACC). We tested the association of total and regional WMH volumes with PACC performance, adjusting for age, education, and amyloid positivity status, with general linear models. We also considered interactions between WMH and amyloid positivity status. Results Increased frontal and parietal lobe WMH volume was associated with poorer performance on the PACC. While amyloid positivity was also associated with lower cognitive test scores, WMH volumes did not interact with amyloid positivity status. Conclusion These results highlight the potential of small vessel cerebrovascular disease to drive AD-related cognitive profiles. Measures of small vessel cerebrovascular disease should be considered when evaluating outcome in trials, both as potential effect modifiers and as a possible target for intervention or prevention.

Abstract Background To promote the development of effective therapies, there is an important need to characterize the full spectrum of neuropathological changes associated with Alzheimer’s disease. In line with this need, this study examined white matter abnormalities in individuals with early-onset autosomal dominant Alzheimer’s disease, in relation to age and symptom severity. Methods This is a cross-sectional analysis of data collected in members of a large kindred with a PSEN1 E280A mutation. Participants were recruited between September 2011 and July 2012 from the Colombian Alzheimer’s Prevention Initiative registry. The studied cohort comprised 50 participants aged between 20 and 55 years, including 20 cognitively unimpaired mutation carriers, 9 cognitively impaired mutation carriers, and 21 non-carriers. Participants completed an MRI, a lumbar puncture for cerebrospinal fluid collection, a florbetapir PET scan, and neurological and neuropsychological examinations. The volume of white matter hyperintensities (WMH) was compared between cognitively unimpaired carriers, cognitively impaired carriers, and non-carriers. Relationships between WMH, age, and cognitive performance were further examined in mutation carriers. Results The mean (SD) age of participants was 35.8 (9.6) years and 64% were women. Cardiovascular risk factors were uncommon and did not differ across groups. Cognitively impaired carriers [median, 6.37; interquartile range (IQR), 9.15] had an increased volume of WMH compared to both cognitively unimpaired carriers [median, 0.85; IQR, 0.79] and non-carriers [median, 1.07; IQR, 0.71]. In mutation carriers, the volume of WMH strongly correlated with cognition and age, with evidence for an accelerated rate of changes after the age of 43 years, 1 year earlier than the estimated median age of symptom onset. In multivariable regression models including cortical amyloid retention, superior parietal lobe cortical thickness, and cerebrospinal fluid phospho-tau, the volume of WMH was the only biomarker independently and significantly contributing to the total explained variance in cognitive performance. Conclusions The volume of WMH is increased among individuals with symptomatic autosomal-dominant Alzheimer’s disease, begins to increase prior to clinical symptom onset, and is an independent determinant of cognitive performance in this group. These findings suggest that WMH are a key component of autosomal-dominant Alzheimer’s disease that is closely related to the progression of clinical symptoms.

Abstract Background Systematic pelvic lymphadenectomy or whole pelvic irradiation is recommended for the patients with stage IB1 cervical cancer. However, the precise pattern of lymphatic tumor spread in cervical cancer is unknown. In the present study we evaluated the distribution of nodal metastases in stage IB1 cervical cancer to explore the possibilities for tailoring cancer treatment. Methods A total of 289 patients with cervical cancer of stage IB1, according to FIGO 2009, were retrospectively analyzed. All patients underwent laparoscopic radical hysterectomy (Querleu and Morrow type C2) and systematic pelvic lymphadenectomy with or without para-aortic lymphadenectomy (level 2 or level 3 according to Querleu and Morrow) from October 2014 to December 2017. Lymph nodes removed from 7 well-defined anatomical locations as well as other tissues were examined histopathologically, and typed, graded, and staged according to the WHO/IARC classification. Results Totally 8314 lymph nodes were analyzed with the average number of 31.88 ± 10.34 (Mean ± SD) lymph nodes per patient. Nodal metastases were present in 44 patients (15.22%). The incidence of lymphatic spread to different anatomic sites ranged from 0% (presacral) to 30.92% (obturator nodes). Tumor size above 2 cm, histologically proven lymphovascular space involvement (LVSI) and parametrial invasion were shown to be significantly correlated with the higher risk of lymphatic metastasis, while obesity (BMI ≥ 25) was independently negatively associated with lymphatic metastases. Conclusions The incidence of lymph node metastasis in patients with stage IB1 cervical cancer is low but prognostically relevant. Individual treatment could be considered for the selected low-risk patients who have smaller tumors and obesity and lack of the parametrial invasion or LVSI.

White matter hyperintensities (WMH) are common radiological findings among older adults and strong predictors of age-related cognitive decline. Recent work has implicated WMH in the pathogenesis and symptom presentation of Alzheimer's disease (AD), which is characterized clinically primarily by a deficit in memory. The severity of WMH volume is typically quantified globally or by lobe, whereas white matter itself is organized by tracts and fiber classes. We derived WMH volumes within white matter tract classes, including association, projection, and commissural tracts, in 519 older adults and tested whether WMH volume within specific fiber classes is related to memory performance. We found that increased association and projection tract defined WMH volumes were related to worse memory function but not to a global cognition summary score that excluded memory. We conclude that macrostructural damage to association and projection tracts, manifesting as WMH, may result in memory decline among older adults. Keywords: White matter hyperintensities, White matter fiber tracts, Memory, Alzheimer's disease

Cynthia Kay,1,2 Erica Wozniak,2 Alice Ching,1 Joanne Bernstein1 1Clement J Zablocki - Department of Medicine, 2Center for Patient Care and Outcomes Research, Medical College of Wisconsin, Milwaukee, WI, USA Purpose: Ambulatory resources such as telephone calls, secure messages, nurse visits, and telephone triage are vital to the management of patients on chronic opioid therapy (COT). They are also often overlooked as health care services and yet to be broadly studied. The aim of the present study was to describe the Veterans Affairs (VA) health care utilization by patients based on COT, type, and amount of opioids prescribed. Patients and methods: A retrospective chart review was done on 617 patients on COT at a VA primary care clinic. Instances of health care utilization (emergency department visits [EDVs], hospitalizations, clinic visits, telephone triage calls, telephone calls/secure messages/nurse visits) were obtained. Results: Patients were likely to have more telephone calls, secure messages, or nurse visits if they were prescribed a schedule II opioid or if they were on more than one opioid. Model-based results found that patients on COT were more likely to have EDVs, telephone triage calls, and clinic contact compared to patients who were not on chronic opioids. Conclusion: The results are despite having a Patient Aligned Care Team, which is the VA’s patient-centered medical home. This suggests that reducing health care utilization for patients on COT may not be possible with just a primary care involvement. Keywords: opioids, Veterans Affairs, primary care, chronic pain

Microstructural and macrostructural white matter damage occurs frequently with aging, is associated with negative health outcomes, and can be imaged non-invasively as fractional anisotropy (FA) and white matter hyperintensities (WMH), respectively. The extent to which diminished microstructure precedes or results from macrostructural white matter damage is poorly understood. This study evaluated the hypothesis that white matter areas with normatively lower microstructure in young adults are most susceptible to develop WMH in older adults. Forty-nine younger participants (age = 25.8 ± 2.8 years) underwent diffusion-weighted imaging (DWI), and 557 older participants (age = 73.9 ± 5.7 years) underwent DWI and T2-weighted magnetic resonance imaging (MRI). In older adults, WMH had a mostly periventricular distribution with higher frequency in frontal regions. We found lower FA in areas of frank WMH compared to normal-appearing white matter (NAWM) in older adults. Then, to determine if areas of normatively lower white matter microstructure spatially overlap with areas that frequently develop macrostructural damage in older age, we created a WMH frequency map in which each voxel represented the percentage of older adults with a WMH in that voxel. We found lower normative FA in young adults with regions frequently segmented as WMH in older adults. We conclude that low white matter microstructure is observed in areas of white matter macrostructural damage, but white matter microstructure is also normatively low (i.e., at ages 20–30) in regions with high WMH frequency, prior to white matter macrostructural damage.

Abstract Background RNA visualization software tools have traditionally presented a static visualization of RNA molecules with limited ability for users to interact with the resulting image once it is complete. Only a few tools allowed for dynamic structures. One such tool is jViz.RNA. Currently, jViz.RNA employs a unique method for the creation of the RNA molecule layout by mapping the RNA nucleotides into vertexes in a graph, which we call the detailed graph, and then utilizes a Newtonian mechanics inspired system of forces to calculate a layout for the RNA molecule. The work presented here focuses on improvements to jViz.RNA that allow the drawing of RNA secondary structures according to common drawing conventions, as well as dramatic run-time performance improvements. This is done first by presenting an alternative method for mapping the RNA molecule into a graph, which we call the compressed graph, and then employing advanced numerical integration methods for the compressed graph representation. Results Comparing the compressed graph and detailed graph implementations, we find that the compressed graph produces results more consistent with RNA drawing conventions. However, we also find that employing the compressed graph method requires a more sophisticated initial layout to produce visualizations that would require minimal user interference. Comparing the two numerical integration methods demonstrates the higher stability of the Backward Euler method, and its resulting ability to handle much larger time steps, a high priority feature for any software which entails user interaction. Conclusion The work in this manuscript presents the preferred use of compressed graphs to detailed ones, as well as the advantages of employing the Backward Euler method over the Forward Euler method. These improvements produce more stable as well as visually aesthetic representations of the RNA secondary structures. The results presented demonstrate that both the compressed graph representation, as well as the Backward Euler integrator, greatly enhance the run-time performance and usability. The newest iteration of jViz.RNA is available at https://jviz.cs.sfu.ca/download/download.html .

Previously, we have introduced an improved version of jViz.RNA which enabled faster and more stable RNA visualization by employing compressed tree graphs. However, the new RNA representation and visualization method required a sophisticated mechanism of pseudoknot visualization. In this work, we present our novel pseudoknot classification and implementation of pseudoknot visualization in the context of the new RNA graph model. We then compare our approach with other RNA visualization software, and demonstrate jViz.RNA 4.0's benefits compared to other software. Additionally, we introduce interactive editing functionality into jViz.RNA and demonstrate its benefits in exploring and building RNA structures. The results presented highlight the new high degree of utility jViz.RNA 4.0 now offers. Users are now able to visualize pseudoknotted RNA, manipulate the resulting automatic layouts to suit their individual needs, and change both positioning and connectivity of the RNA molecules examined. Care was taken to limit overlap between structural elements, particularly in the case of pseudoknots to ensure an intuitive and informative layout of the final RNA structure. Availability: The software is freely available at: https://jviz.cs.sfu.ca/.

ABSTRACT Microbial carbon degradation and methanogenesis in wetland soils generate a large proportion of atmospheric methane, a highly potent greenhouse gas. Despite their potential to mitigate greenhouse gas emissions, knowledge about methane-consuming methanotrophs is often limited to lower-resolution single-gene surveys that fail to capture the taxonomic and metabolic diversity of these microorganisms in soils. Here our objective was to use genome-enabled approaches to investigate methanotroph membership, distribution, and in situ activity across spatial and seasonal gradients in a freshwater wetland near Lake Erie. 16S rRNA gene analyses demonstrated that members of the methanotrophic Methylococcales were dominant, with the dominance largely driven by the relative abundance of four taxa, and enriched in oxic surface soils. Three methanotroph genomes from assembled soil metagenomes were assigned to the genus Methylobacter and represented the most abundant methanotrophs across the wetland. Paired metatranscriptomes confirmed that these Old Woman Creek (OWC) Methylobacter members accounted for nearly all the aerobic methanotrophic activity across two seasons. In addition to having the capacity to couple methane oxidation to aerobic respiration, these new genomes encoded denitrification potential that may sustain energy generation in soils with lower dissolved oxygen concentrations. We further show that Methylobacter members that were closely related to the OWC members were present in many other high-methane-emitting freshwater and soil sites, suggesting that this lineage could participate in methane consumption in analogous ecosystems. This work contributes to the growing body of research suggesting that Methylobacter may represent critical mediators of methane fluxes in freshwater saturated sediments and soils worldwide. IMPORTANCE Here we used soil metagenomics and metatranscriptomics to uncover novel members within the genus Methylobacter. We denote these closely related genomes as members of the lineage OWC Methylobacter. Despite the incredibly high microbial diversity in soils, here we present findings that unexpectedly showed that methane cycling was primarily mediated by a single genus for both methane production (“Candidatus Methanothrix paradoxum”) and methane consumption (OWC Methylobacter). Metatranscriptomic analyses revealed that decreased methanotrophic activity rather than increased methanogenic activity possibly contributed to the greater methane emissions that we had previously observed in summer months, findings important for biogeochemical methane models. Although members of this Methylococcales order have been cultivated for decades, multi-omic approaches continue to illuminate the methanotroph phylogenetic and metabolic diversity harbored in terrestrial and marine ecosystems.

Cerebrovascular disease is associated with symptoms and pathogenesis of Alzheimer's disease (AD) among adults with Down syndrome (DS). The cause of increased dementia-related cerebrovascular disease in DS is unknown. We explored whether protein markers of neuroinflammation are associated with markers of cerebrovascular disease among adults with DS. Participants from the Alzheimer's disease in Down syndrome (ADDS) study with magnetic resonance imaging (MRI) scans and blood biomarker data were included. Support vector machine (SVM) analyses examined the relationship of blood-based proteomic biomarkers with MRI-defined cerebrovascular disease among participants characterized as having cognitive decline (n = 36, mean age ± SD = 53 ± 6.2) and as being cognitively stable (n = 78, mean age = 49 ± 6.4). Inflammatory and AD markers were associated with cerebrovascular disease, particularly among symptomatic individuals. The pattern suggested relatively greater inflammatory involvement among cognitively stable individuals and greater AD involvement among those with cognitively decline. The findings help to generate hypotheses that both inflammatory and AD markers are implicated in cerebrovascular disease among those with DS and point to potential mechanistic pathways for further examination.

Wetland water depth influences microbial and plant communities, which can alter the above- and below-ground carbon cycling of a wetland. Wetland water depths are likely to change due to shifting precipitation patterns, which will affect projections of greenhouse gas emissions; however, these effects are rarely incorporated into wetland greenhouse gas models. Seeking to address this gap, we used a mechanistic model, ecosys, to simulate a range of water depth scenarios in a temperate wetland, and analyzed simulated predictions of carbon dioxide (CO2) and methane (CH4) fluxes over the 21st century. We tested our model using eddy covariance measurements of CO2 and CH4 fluxes collected at the Old Woman Creek National Estuarine Research Reserve (OWC) during 2015 and 2016. OWC is a lacustrine, estuarine, freshwater, mineral-soil marsh. An empirical model found that the wetland water depth is highly dependent on the water depth of the nearby Lake Erie. Future wetland surface water depths were modeled based on projection of Lake Erie's water depth using four separate NOAA projections, resulting in four wetland water-depth scenarios. Two of the four 21st century projections for Lake Erie water depths used in this study indicated that the water depth of the wetland would remain nearly steady; however, the other two indicated decreases in the wetland water depth. In our scenario where the wetland dries out, we project the wetland's climatological warming effect will decrease due to smaller CH4 fluxes to the atmosphere and larger CO2 uptake by the wetland. We also found that increased water level can lower emissions by shifting the site towards more open water areas, which have lower CH4 emissions. We found that decreased water depths would cause more widespread colonization of the wetland by macrophyte vegetation. Using an empirical relationship, we also found that further drying could result in other, non-wetland vegetation to emerge, dramatically altering soil carbon cycling. In three of our four projections, we found that in general the magnitude of CO2 and CH4 fluxes steadily increase over the next 100 years in response to higher temperatures. However, in our driest simulations, we projected a different response due to increased oxidation of soil carbon, with CH4 emissions decreasing substantially from an annual cumulative peak of 224.6 to a minimum of 104.7 gC m-2 year-1. In that same simulation, net cumulative flux of CO2 changed from being a sink of 56.5 gC m-2 year-1 to a source of 369.6 gC m-2 year-1 over the same period, despite a temperature increase from 13.7 °C to 14.2 °C. This temperature shift in our other three cases with greater water depths increased the source strength of CH4 and the sink strength of CO2. We conclude that the magnitude of wetland greenhouse-gas fluxes depended on the water depth primarily as it affected the areal percentage of the wetland available for plant colonization, but dramatic decreases in water depths could cause significant reductions in the wetland CH4 fluxes, while simultaneously altering the wetland vegetation.

We determined the extent to which obstructive sleep apnea (OSA) is associated with increased cerebrovascular disease and amyloid burden, and the relation of the two processes across clinical Alzheimer's disease (AD) diagnostic groups in adults with Down syndrome (DS). Adults with DS from the Biomarkers of Alzheimer's Disease in Down Syndrome (ADDS) study were included given available research MRI (n = 116; 50 ± 8 years; 42% women) and amyloid PET scans (n = 71; 50 ± 7 years; 39% women) at the time of analysis. Participants were characterized as cognitively stable (CS; 64%), with mild cognitive impairment-DS (MCI-DS; 23%), with possible AD dementia (5%), or with definite AD dementia (8%). OSA was determined via medical records and interviews. Models tested the effect of OSA on MRI-derived cerebrovascular biomarkers and PET-derived amyloid burden, and the moderating effect of OSA and AD diagnosis on biomarkers. OSA was reported in 39% of participants, which did not differ by clinical AD diagnostic group. OSA was not associated with cerebrovascular biomarkers but was associated with greater cortical amyloid burden. White matter hyperintensity (WMH) volume (primarily in the parietal lobe), enlarged perivascular spaces, and cortical and striatal amyloid burden were greater across clinical AD diagnostic groups (CS

IntroductionWe examined whether educational attainment differentially contributes to cognitive reserve (CR) across race/ethnicity.MethodsA total of 1553 non-Hispanic Whites (Whites), non-Hispanic Blacks (Blacks), and Hispanics in the Washington Heights-Inwood Columbia Aging Project (WHICAP) completed structural magnetic resonance imaging. Mixture growth curve modeling was used to examine whether the effect of brain integrity indicators (hippocampal volume, cortical thickness, and white matter hyperintensity [WMH] volumes) on memory and language trajectories was modified by education across racial/ethnic groups.ResultsHigher educational attainment attenuated the negative impact of WMH burden on memory (β = -0.03; 99% CI: -0.071, -0.002) and language decline (β = -0.024; 99% CI:- 0.044, -0.004), as well as the impact of cortical thinning on level of language performance for Whites, but not for Blacks or Hispanics.DiscussionEducational attainment does not contribute to CR similarly across racial/ethnic groups.

ObjectiveAdults with Down syndrome (DS) develop Alzheimer disease (AD) pathology by their 5th decade. Compared with the general population, traditional vascular risks in adults with DS are rare, allowing examination of cerebrovascular disease in this population and insight into its role in AD without the confound of vascular risk factors. We examined in vivo magnetic resonance imaging (MRI)-based biomarkers of cerebrovascular pathology in adults with DS, and determined their cross-sectional relationship with age, beta-amyloid pathology, and mild cognitive impairment or clinical AD diagnostic status.MethodsParticipants from the Biomarkers of Alzheimer's Disease in Down Syndrome study (n = 138, 50 ± 7 years, 39% women) with MRI data and a subset (n = 90) with amyloid positron emission tomography (PET) were included. We derived MRI-based biomarkers of cerebrovascular pathology, including white matter hyperintensities (WMH), infarcts, cerebral microbleeds, and enlarged perivascular spaces (PVS), as well as PET-based biomarkers of amyloid burden. Participants were characterized as cognitively stable (CS), mild cognitive impairment-DS (MCI-DS), possible AD dementia, or definite AD dementia based on in-depth assessments of cognition, function, and health status.ResultsThere were detectable WMH, enlarged PVS, infarcts, and microbleeds as early as the 5th decade of life. There was a monotonic increase in WMH volume, enlarged PVS, and presence of infarcts across diagnostic groups (CS < MCI-DS < possible AD dementia < definite AD dementia). Higher amyloid burden was associated with a higher likelihood of an infarct.InterpretationThe findings highlight the prevalence of cerebrovascular disease in adults with DS and add to a growing body of evidence that implicates cerebrovascular disease as a core feature of AD and not simply a comorbidity. ANN NEUROL 2020;88:1165-1177.

During the spring of 2020, due to the COVID-19 pandemic, it was necessary to rapidly translate a new human-centered design studio course for first-year biomedical engineering students from a face-to-face delivery mode to a remote delivery mode. In addition to disrupting plans for hands-on design prototyping experiences, stay-at-home orders associated with the pandemic disrupted plans for students to interact substantively and empathetically with potential users, which is the heart of human-centered design. The challenge was therefore to provide students without ready access to machine shops, 3D printing, or other people with some form of the educational experiences promised in the course syllabus.

Coronal mass ejections (CMEs) drive space weather effects at Earth and the heliosphere. Predicting their arrival is a major part of space weather forecasting. In 2013, the Community Coordinated Modeling Center started collecting predictions from the community, developing an Arrival Time Scoreboard (ATSB). Riley et al. (2018, https://doi.org/10.1029/2018sw001962) analyzed the first 5 years of the ATSB, finding a bias of a few hours and uncertainty of order 15 hr. These metrics have been routinely quoted since 2018, but have not been updated despite continued predictions. We revise analysis of the ATSB using a sample 3.5 times the size of that in the original study. We find generally the same overall metrics, a bias of −2.5 hr, mean absolute error of 13.2 hr, and standard deviation of 17.4 hr, with only a slight improvement comparing between the previously‐used and new sets. The most well‐established, frequently‐submitted model results tend to outperform those from seldomly‐contributed models. These "best" models show a slight improvement over the 11 year span, with more scatter between the models during early times and a convergence toward the same error metrics in recent years. We find little evidence of any correlations between the arrival time errors and any other properties. The one noticeable exception is a tendency for late predictions for short transit times and vice versa. We propose that any model‐driven systematic errors may be washed out by the uncertainties in CME reconstructions in characterization of the background solar wind, and suggest that improving these may be the key to better predictions. Plain Language Summary: Coronal mass ejections (CMEs) are huge explosions that erupt from the Sun and travel through the solar system. It is important to have warning of when they reach Earth, so many researchers model the arrival time (AT) of CMEs. Many predictions are collected in the AT Scoreboard (ATSB), and the general errors from the first 5 years of the ATSB were determined in 2018. These errors are very important as a measure of the uncertainty of predictions, but they have not been updated in over 6 years. Now the data set is over 3.5 times larger so we determine updated results but ultimately only see a small change in the errors. We find a bias of only a few hours, so no strong tendency for either early or late predictions. We find an average absolute error of 13.2 hr but a wide range about this value for individual cases. We do see some evidence that the most commonly used models have improved over time, but the change is very small and there are many factors affecting whether it is significant or not. We suggest that improving how we reconstruct CME properties and model the background solar wind may improve predictions. Key Points: From 1702 arrival time predictions we find a bias of −2.5 hr, mean absolute error of 13.2 hr, and standard deviation of 17.4 hrThe routinely‐submitted models all perform fairly similar but there is more variation in models with smaller data setsWe find evidence of late predictions for coronal mass ejections (CMEs) with short transit times, and early predictions for CMEs with long transit times [ABSTRACT FROM AUTHOR]

Background and Purpose: Brain arterial diameters are markers of cerebrovascular disease. Demographic and anatomical factors may influence arterial diameters. We hypothesize that age, sex, height, total cranial volume (TCV), and persistent fetal posterior cerebral artery (fPCA) correlate with brain arterial diameters across populations. Methods: Participants had a time-of-flight MRA from nine international cohorts. Arterial diameters of the cavernous internal carotid arteries (ICA), middle cerebral arteries (MCA), and basilar artery (BA) were measured using LAVA software. Regression models assessed the association between exposures and brain arterial diameters. Results: We included 6,518 participants (mean age: 70 ± 9 years; 41% men). Unilateral fPCA was present in 13.2% and bilateral in 3.2%. Larger ICA, MCA, and BA diameters correlated with older age (Weighted average [WA] per 10 years: 0.18 mm, 0.11 mm, and 0.12 mm), male sex (WA: 0.24 mm, 0.13 mm, and 0.21 mm), and TCV (WA: for one TCV standard deviation: 0.24 mm, 0.29 mm, and 0.18 mm). Unilateral and bilateral fPCAs showed a positive correlation with ICA diameters (WA: 0.39 mm and 0.73 mm) and negative correlation with BA diameters (WA: −0.88 mm and −1.73 mm). Regression models including age, sex, TCV, and fPCA explained on average 15%, 13%, and 25% of the ICA, MCA, and BA diameter interindividual variation, respectively. Using height instead of TCV as a surrogate of head size decreased the R-squared by 3% on average. Conclusion: Brain arterial diameters correlated with age, sex, TCV, and fPCA. These factors should be considered when defining abnormal diameter cutoffs across populations. [ABSTRACT FROM AUTHOR]