Evolution of white matter hyperintensity segmentation methods and implementation over the past two decades; an incomplete shift towards deep learning.

This systematic review examines the prevalence, underlying mechanisms, cohort characteristics, evaluation criteria, and cohort types in white matter hyperintensity (WMH) pipeline and implementation literature spanning the last two decades. Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, we categorized WMH segmentation tools based on their methodologies from January 1, 2000, to November 18, 2022. Inclusion criteria involved articles using openly available techniques with detailed descriptions, focusing on WMH as a primary outcome. Our analysis identified 1007 visual rating scales, 118 pipeline development articles, and 509 implementation articles. These studies predominantly explored aging, dementia, psychiatric disorders, and small vessel disease, with aging and dementia being the most prevalent cohorts. Deep learning emerged as the most frequently developed segmentation technique, indicative of a heightened scrutiny in new technique development over the past two decades. We illustrate observed patterns and discrepancies between published and implemented WMH techniques. Despite increasingly sophisticated quantitative segmentation options, visual rating scales persist, with the SPM technique being the most utilized among quantitative methods and potentially serving as a reference standard for newer techniques. Our findings highlight the need for future standards in WMH segmentation, and we provide recommendations based on these observations.

Presenilin-1 mutation position influences amyloidosis, small vessel disease, and dementia with disease stage.

INTRODUCTION: Amyloidosis, including cerebral amyloid angiopathy, and markers of small vessel disease (SVD) vary across dominantly inherited Alzheimer's disease (DIAD) presenilin-1 (PSEN1) mutation carriers. We investigated how mutation position relative to codon 200 (pre-/postcodon 200) influences these pathologic features and dementia at different stages. METHODS: Individuals from families with known PSEN1 mutations (n = 393) underwent neuroimaging and clinical assessments. We cross-sectionally evaluated regional Pittsburgh compound B-positron emission tomography uptake, magnetic resonance imaging markers of SVD (diffusion tensor imaging-based white matter injury, white matter hyperintensity volumes, and microhemorrhages), and cognition. RESULTS: Postcodon 200 carriers had lower amyloid burden in all regions but worse markers of SVD and worse Clinical Dementia Rating® scores compared to precodon 200 carriers as a function of estimated years to symptom onset. Markers of SVD partially mediated the mutation position effects on clinical measures. DISCUSSION: We demonstrated the genotypic variability behind spatiotemporal amyloidosis, SVD, and clinical presentation in DIAD, which may inform patient prognosis and clinical trials. HIGHLIGHTS: Mutation position influences Aß burden, SVD, and dementia. PSEN1 pre-200 group had stronger associations between Aß burden and disease stage. PSEN1 post-200 group had stronger associations between SVD markers and disease stage. PSEN1 post-200 group had worse dementia score than pre-200 in late disease stage. Diffusion tensor imaging-based SVD markers mediated mutation position effects on dementia in the late stage.

Accuracy of TrUE-Net in comparison to established white matter hyperintensity segmentation methods: An independent validation study.

White matter hyperintensities (WMH) are nearly ubiquitous in the aging brain, and their topography and overall burden are associated with cognitive decline. Given their numerosity, accurate methods to automatically segment WMH are needed. Recent developments, including the availability of challenge data sets and improved deep learning algorithms, have led to a new promising deep-learning based automated segmentation model called TrUE-Net, which has yet to undergo rigorous independent validation. Here, we compare TrUE-Net to six established automated WMH segmentation tools, including a semi-manual method. We evaluated the techniques at both global and regional level to compare their ability to detect the established relationship between WMH burden and age. We found that TrUE-Net was highly reliable at identifying WMH regions with low false positive rates, when compared to semi-manual segmentation as the reference standard. TrUE-Net performed similarly or favorably when compared to the other automated techniques. Moreover, TrUE-Net was able to detect relationships between WMH and age to a similar degree as the reference standard semi-manual segmentation at both the global and regional level. These results support the use of TrUE-Net for identifying WMH at the global or regional level, including in large, combined datasets.

Increasing hub disruption parallels dementia severity in autosomal dominant Alzheimer disease.

Hub regions in the brain, recognized for their roles in ensuring efficient information transfer, are vulnerable to pathological alterations in neurodegenerative conditions, including Alzheimer Disease (AD). Given their essential role in neural communication, disruptions to these hubs have profound implications for overall brain network integrity and functionality. Hub disruption, or targeted impairment of functional connectivity at the hubs, is recognized in AD patients. Computational models paired with evidence from animal experiments hint at a mechanistic explanation, suggesting that these hubs may be preferentially targeted in neurodegeneration, due to their high neuronal activity levels-a phenomenon termed "activity-dependent degeneration". Yet, two critical issues were unresolved. First, past research hasn't definitively shown whether hub regions face a higher likelihood of impairment (targeted attack) compared to other regions or if impairment likelihood is uniformly distributed (random attack). Second, human studies offering support for activity-dependent explanations remain scarce. We applied a refined hub disruption index to determine the presence of targeted attacks in AD. Furthermore, we explored potential evidence for activity-dependent degeneration by evaluating if hub vulnerability is better explained by global connectivity or connectivity variations across functional systems, as well as comparing its timing relative to amyloid beta deposition in the brain. Our unique cohort of participants with autosomal dominant Alzheimer Disease (ADAD) allowed us to probe into the preclinical stages of AD to determine the hub disruption timeline in relation to expected symptom emergence. Our findings reveal a hub disruption pattern in ADAD aligned with targeted attacks, detectable even in pre-clinical stages. Notably, the disruption's severity amplified alongside symptomatic progression. Moreover, since excessive local neuronal activity has been shown to increase amyloid deposition and high connectivity regions show high level of neuronal activity, our observation that hub disruption was primarily tied to regional differences in global connectivity and sequentially followed changes observed in Aß PET cortical markers is consistent with the activity-dependent degeneration model. Intriguingly, these disruptions were discernible 8 years before the expected age of symptom onset. Taken together, our findings not only align with the targeted attack on hubs model but also suggest that activity-dependent degeneration might be the cause of hub vulnerability. This deepened understanding could be instrumental in refining diagnostic techniques and developing targeted therapeutic strategies for AD in the future.

White matter hyperintensity longitudinal morphometric analysis in association with Alzheimer disease.

INTRODUCTION: Vascular damage in Alzheimer's disease (AD) has shown conflicting findings particularly when analyzing longitudinal data. We introduce white matter hyperintensity (WMH) longitudinal morphometric analysis (WLMA) that quantifies WMH expansion as the distance from lesion voxels to a region of interest boundary. METHODS: WMH segmentation maps were derived from 270 longitudinal fluid-attenuated inversion recovery (FLAIR) ADNI images. WLMA was performed on five data-driven WMH patterns with distinct spatial distributions. Amyloid accumulation was evaluated with WMH expansion across the five WMH patterns. RESULTS: The preclinical group had significantly greater expansion in the posterior ventricular WM compared to controls. Amyloid significantly associated with frontal WMH expansion primarily within AD individuals. WLMA outperformed WMH volume changes for classifying AD from controls primarily in periventricular and posterior WMH. DISCUSSION: These data support the concept that localized WMH expansion continues to proliferate with amyloid accumulation throughout the entirety of the disease in distinct spatial locations.

Longitudinal Relationships of White Matter Hyperintensities and Alzheimer Disease Biomarkers Across the Adult Life Span.

BACKGROUND AND OBJECTIVES: White matter hyperintensities (WMH) correlate with Alzheimer disease (AD) biomarkers cross-sectionally and modulate AD pathogenesis. Longitudinal changes have been reported for AD biomarkers, including concentrations of CSF ß-amyloid (Aß) 42, Aß40, total tau and phosphorylated tau181, standardized uptake value ratio from the molecular imaging of cerebral fibrillar Aß with PET using [11C] Pittsburgh Compound-B, MRI-based hippocampal volume, and cortical thickness. Correlations between established AD biomarkers and the longitudinal change for WMH have not been fully evaluated, especially among cognitively normal individuals across the adult life span. METHODS: We jointly analyzed the longitudinal data of WMH volume and each of the established AD biomarkers and cognition from 371 cognitively normal individuals whose baseline age spanned from 19.6 to 88.20 years from 4 longitudinal studies of aging and AD. A 2-stage algorithm was applied to identify the inflection point of baseline age whereby older participants had an accelerated longitudinal change in WMH volume, in comparison with the younger participants. The longitudinal correlations between WMH volume and AD biomarkers were estimated from the bivariate linear mixed-effects models. RESULTS: A longitudinal increase in WMH volume was associated with a longitudinal increase in PET amyloid uptake and a decrease in MRI hippocampal volume, cortical thickness, and cognition. The inflection point of baseline age in WMH volume was identified at 60.46 (95% CI 56.43-64.49) years, with the annual increase for the older participants (83.12 [SE = 10.19] mm3 per year) more than 13 times faster (p < 0.0001) than that for the younger participants (6.35 [SE = 5.63] mm3 per year). Accelerated rates of change among the older participants were similarly observed in almost all the AD biomarkers. Longitudinal correlations of WMH volume with MRI, PET amyloid biomarkers, and cognition seemed to be numerically stronger for the younger participants, but not significantly different from those for the older participants. Carrying APOE ε4 alleles did not alter the longitudinal correlations between WMH and AD biomarkers. DISCUSSION: Longitudinal increases in WMH volume started to accelerate around a baseline age of 60.46 years and correlated with the longitudinal change in PET amyloid uptake, MRI structural outcomes, and cognition.

Neuroinflammation and amyloid deposition in the progression of mixed Alzheimer and vascular dementia.

BACKGROUND: Alzheimer's disease (AD) and vascular contributions to cognitive impairment and dementia (VCID) pathologies coexist in patients with cognitive impairment. Abnormal amyloid beta (Aß) deposition is the hallmark pathologic biomarker for AD. Neuroinflammation may be a pathophysiological mechanism in both AD and VCID. In this study, we aimed to understand the role of neuroinflammation and Aß deposition in white matter hyperintensities (WMH) progression and cognitive decline over a decade in patients with mixed AD and VCID pathologies. METHODS: Twenty-four elderly participants (median [interquartile range] age 78 [64.8, 83] years old, 14 female) were recruited from the Knight Alzheimer Disease Research Center. 11C-PK11195 standard uptake value ratio (SUVR) and 11C-PiB mean cortical binding potential (MCBP) were used to evaluate neuroinflammation and Aß deposition in-vivo, respectively. Fluid-attenuated inversion recovery MR images were acquired to obtain baseline WMH volume and its progression over 11.5 years. Composite cognitive scores (global, processing speed and memory) were computed at baseline and follow-up over 7.5 years. Multiple linear regression models evaluated the association between PET biomarkers (11C-PK11195 SUVR and 11C-PiB MCBP) and baseline WMH volume and cognitive function. Moreover, linear mixed-effects models evaluated whether PET biomarkers predicted greater WMH progression or cognitive decline over a decade. RESULTS: Fifteen participants (62.5%) had mixed AD (positive PiB) and VCID (at least one vascular risk factor) pathologies. Elevated 11C-PK11195 SUVR, but not 11C-PiB MCBP, was associated with greater baseline WMH volume and predicted greater WMH progression. Elevated 11C-PiB MCBP was associated with baseline memory and global cognition. Elevated 11C-PK11195 SUVR and elevated 11C-PiB MCBP independently predicted greater global cognition and processing speed declines. No association was found between 11C-PK11195 SUVR and 11C-PiB MCBP. CONCLUSIONS: Neuroinflammation and Aß deposition may represent two distinct pathophysiological pathways, and both independently contributed to the progression of cognitive impairment in mixed AD and VCID pathologies. Neuroinflammation, but not Aß deposition, contributed to WMH volume and progression.

Brain aerobic glycolysis and resilience in Alzheimer disease.

The distribution of brain aerobic glycolysis (AG) in normal young adults correlates spatially with amyloid-beta (Aß) deposition in individuals with symptomatic and preclinical Alzheimer disease (AD). Brain AG decreases with age, but the functional significance of this decrease with regard to the development of AD symptomatology is poorly understood. Using PET measurements of regional blood flow, oxygen consumption, and glucose utilization-from which we derive AG-we find that cognitive impairment is strongly associated with loss of the typical youthful pattern of AG. In contrast, amyloid positivity without cognitive impairment was associated with preservation of youthful brain AG, which was even higher than that seen in cognitively unimpaired, amyloid negative adults. Similar findings were not seen for blood flow nor oxygen consumption. Finally, in cognitively unimpaired adults, white matter hyperintensity burden was found to be specifically associated with decreased youthful brain AG. Our results suggest that AG may have a role in the resilience and/or response to early stages of amyloid pathology and that age-related white matter disease may impair this process.

Brain network decoupling with increased serum neurofilament and reduced cognitive function in Alzheimer's disease.

Neurofilament light chain, a putative measure of neuronal damage, is measurable in blood and CSF and is predictive of cognitive function in individuals with Alzheimer's disease. There has been limited prior work linking neurofilament light and functional connectivity, and no prior work has investigated neurofilament light associations with functional connectivity in autosomal dominant Alzheimer's disease. Here, we assessed relationships between blood neurofilament light, cognition, and functional connectivity in a cross-sectional sample of 106 autosomal dominant Alzheimer's disease mutation carriers and 76 non-carriers. We employed an innovative network-level enrichment analysis approach to assess connectome-wide associations with neurofilament light. Neurofilament light was positively correlated with deterioration of functional connectivity within the default mode network and negatively correlated with connectivity between default mode network and executive control networks, including the cingulo-opercular, salience, and dorsal attention networks. Further, reduced connectivity within the default mode network and between the default mode network and executive control networks was associated with reduced cognitive function. Hierarchical regression analysis revealed that neurofilament levels and functional connectivity within the default mode network and between the default mode network and the dorsal attention network explained significant variance in cognitive composite scores when controlling for age, sex, and education. A mediation analysis demonstrated that functional connectivity within the default mode network and between the default mode network and dorsal attention network partially mediated the relationship between blood neurofilament light levels and cognitive function. Our novel results indicate that blood estimates of neurofilament levels correspond to direct measurements of brain dysfunction, shedding new light on the underlying biological processes of Alzheimer's disease. Further, we demonstrate how variation within key brain systems can partially mediate the negative effects of heightened total serum neurofilament levels, suggesting potential regions for targeted interventions. Finally, our results lend further evidence that low-cost and minimally invasive blood measurements of neurofilament may be a useful marker of brain functional connectivity and cognitive decline in Alzheimer's disease.

Disseminated blastomycosis with cutaneous involvement in a 57-year-old woman: a case report and review of management.

Blastomycosis is an infectious disease produced by the fungal organisms, Blastomyces dermatiditis and Blastomyces gilchristi. We present a 57-year-old woman with pulmonary blastomycosis and secondary cutaneous involvement. Her diagnosis was facilitated by dermatology consultation after approximately one year of delay. In endemic areas including Canada and the USA, individuals are at risk for blastomycosis when non-motile fungal spores are inhaled, thus producing pulmonary disease. The organism may disseminate over time, affecting a variety of extrapulmonary organ systems including the skin. In endemic regions of blastomycosis, this important cutaneous manifestation of disease should be considered with a high index of suspicion as to avoid delayed resolution and adverse outcomes.

Abnormal Magnetic Resonance Image Signature in Virologically Stable HIV Individuals.

BACKGROUND: With implementation of combination antiretroviral therapy (cART), changes to brain integrity in people with HIV (PWH) are subtle compared to those observed in the pre-cART era. T1-weighted/T2-weighted (T1w/T2w) ratio has been proposed as a measure of cortical myelin. This study examines T1w/T2w values between virologically controlled PWH and persons without HIV (PWoH). METHODS: Virologically well-controlled PWH (n = 164) and PWoH (n = 120) were compared on global and regional T1w/T2w values. T1w/T2w values were associated with HIV disease variables (nadir and current CD4 T-cell count, and CNS penetration effectiveness of cART regimen) in PWH, and as a function of age for both PWoH and PWH. RESULTS: PWH had reduced global and regional T1w/T2w values compared to PWoH in the posterior cingulate cortex, caudal anterior cingulate cortex, and insula. T1w/T2w values did not correlate with HIV variables except for a negative relationship with CNS penetration effectiveness. Greater cardiovascular disease risk and older age were associated with lower T1w/T2w values only for PWH. CONCLUSIONS: T1w/T2w values obtained from commonly acquired MRI protocols differentiates virologically well-controlled PWH from PWoH. Changes in T1w/T2w ratio do not correlate with typical HIV measures. Future studies are needed to determine the biological mechanisms underlying this measure.

Association of Data-Driven White Matter Hyperintensity Spatial Signatures With Distinct Cerebral Small Vessel Disease Etiologies.

OBJECTIVES: Topographical distribution of white matter hyperintensities (WMH) are hypothesized to vary by cerebrovascular risk factors. We used an unbiased pattern discovery approach to identify distinct WMH spatial patterns and investigate their association with different WMH etiologies. METHODS: We performed a cross-sectional study on participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI) to identify spatially distinct WMH distribution patterns using voxel-based spectral clustering analysis of aligned WMH probability maps. We included all participants from the ADNI Grand Opportunity/ADNI 2 study with available baseline 2D-FLAIR MRI scans, without prior history of stroke or presence of infarction on imaging. We evaluated the associations of these WMH spatial patterns with vascular risk factors, amyloid-ß PET, and imaging biomarkers of cerebral amyloid angiopathy (CAA), characterizing different forms of cerebral small vessel disease (CSVD) using multivariable regression. We also used linear regression models to investigate whether WMH spatial distribution influenced cognitive impairment. RESULTS: We analyzed MRI scans of 1,046 ADNI participants with mixed vascular and amyloid-related risk factors (mean age 72.9, 47.7% female, 31.4% hypertensive, 48.3% with abnormal amyloid PET). We observed unbiased partitioning of WMH into five unique spatial patterns: deep frontal, periventricular, juxtacortical, parietal, and posterior. Juxtacortical WMH were independently associated with probable CAA, deep frontal WMH were associated with risk factors for arteriolosclerosis (hypertension and diabetes), and parietal WMH were associated with brain amyloid accumulation, consistent with an Alzheimer's disease (AD) phenotype. Juxtacortical, deep frontal, and parietal WMH spatial patterns were associated with cognitive impairment. Periventricular and posterior WMH spatial patterns were unrelated to any disease phenotype or cognitive decline. DISCUSSION: Data-driven WMH spatial patterns reflect discrete underlying etiologies including arteriolosclerosis, CAA, AD, and normal aging. Global measures of WMH volume may miss important spatial distinctions. WMH spatial signatures may serve as etiology-specific imaging markers, helping to resolve WMH heterogeneity, identify the dominant underlying pathological process, and improve prediction of clinical-relevant trajectories that influence cognitive decline.

Covariance-based vs. correlation-based functional connectivity dissociates healthy aging from Alzheimer disease.

Prior studies of aging and Alzheimer disease have evaluated resting state functional connectivity (FC) using either seed-based correlation (SBC) or independent component analysis (ICA), with a focus on particular functional systems. SBC and ICA both are insensitive to differences in signal amplitude. At the same time, accumulating evidence indicates that the amplitude of spontaneous BOLD signal fluctuations is physiologically meaningful. We systematically compared covariance-based FC, which is sensitive to amplitude, vs. correlation-based FC, which is not, in affected individuals and controls drawn from two cohorts of participants including autosomal dominant Alzheimer disease (ADAD), late onset Alzheimer disease (LOAD), and age-matched controls. Functional connectivity was computed over 222 regions of interest and group differences were evaluated in terms of components projected onto a space of lower dimension. Our principal observations are: (1) Aging is associated with global loss of resting state fMRI signal amplitude that is approximately uniform across resting state networks. (2) Thus, covariance FC measures decrease with age whereas correlation FC is relatively preserved in healthy aging. (3) In contrast, symptomatic ADAD and LOAD both lead to loss of spontaneous activity amplitude as well as severely degraded correlation structure. These results demonstrate a double dissociation between age vs. Alzheimer disease and the amplitude vs. correlation structure of resting state BOLD signals. Modeling results suggest that the AD-associated loss of correlation structure is attributable to a relative increase in the fraction of locally restricted as opposed to widely shared variance.

Machine Learning Quantifies Accelerated White-Matter Aging in Persons With HIV.

BACKGROUND: Persons with HIV (PWH) undergo white matter changes, which can be quantified using the brain-age gap (BAG), the difference between chronological age and neuroimaging-based brain-predicted age. Accumulation of microstructural damage may be accelerated in PWH, especially with detectable viral load (VL). METHODS: In total, 290 PWH (85% with undetectable VL) and 165 HIV-negative controls participated in neuroimaging and cognitive testing. BAG was measured using a Gaussian process regression model trained to predict age from diffusion magnetic resonance imaging in publicly available normative controls. To test for accelerated aging, BAG was modeled as an age × VL interaction. The relationship between BAG and global neuropsychological performance was examined. Other potential predictors of pathological aging were investigated in an exploratory analysis. RESULTS: Age and detectable VL had a significant interactive effect: PWH with detectable VL accumulated +1.5 years BAG/decade versus HIV-negative controls (P = .018). PWH with undetectable VL accumulated +0.86 years BAG/decade, although this did not reach statistical significance (P = .052). BAG was associated with poorer global cognition only in PWH with detectable VL (P < .001). Exploratory analysis identified Framingham cardiovascular risk as an additional predictor of pathological aging (P = .027). CONCLUSIONS: Aging with detectable HIV and cardiovascular disease may lead to white matter pathology and contribute to cognitive impairment.

The Structural and Functional Correlates of Frailty in Persons With Human Immunodeficiency Virus.

BACKGROUND: Persons with HIV (PWH) are at increased risk of frailty, a clinically recognizable state of increased vulnerability resulting from aging-associated decline in multiple physiologic systems. Frailty is often defined by the Fried criteria, which includes subjective and objective standards concerning health resiliency. However, these frailty metrics do not incorporate cognitive performance or neuroimaging measures. METHODS: We compared structural (diffusion tensor imaging [DTI]) and functional (cerebral blood flow [CBF]) neuroimaging markers in PWH with frailty and cognitive performance. Virologically controlled PWH were dichotomized as either frail (≥3) or nonfrail (<3) using the Fried criteria. Cognitive Z-scores, both domain (executive, psychomotor speed, language, and memory) and global, were derived from a battery of tests. We identified three regions of reduced CBF, based on a voxel-wise comparison of frail PWH compared with nonfrail PWH. These clusters (bilateral frontal and posterior cingulate) were subsequently used as seed regions of interest (ROIs) for DTI probabilistic white matter tractography. RESULTS: White matter integrity connecting the ROIs was significantly decreased in frail compared with nonfrail PWH. No differences in cognition were observed between frail and nonfrail PWH. However, reductions in white matter integrity among these ROIs was significantly associated with worse psychomotor speed and executive function across the entire cohort. CONCLUSIONS: We conclude that frailty in PWH can lead to structural and functional brain changes, including subtle changes that are not detectable by standard neuropsychological tests. Multimodal neuroimaging in conjunction with frailty assessment could identify pathological brain changes observed in PWH.

CSF Tau phosphorylation at Thr205 is associated with loss of white matter integrity in autosomal dominant Alzheimer disease.

BACKGROUND: Hyperphosphorylation of tau leads to conformational changes that destabilize microtubules and hinder axonal transport in Alzheimer's disease (AD). However, it remains unknown whether white matter (WM) decline due to AD is associated with specific Tau phosphorylation site(s). METHODS: In autosomal dominant AD (ADAD) mutation carriers (MC) and non-carriers (NC) we compared cerebrospinal fluid (CSF) phosphorylation at tau sites (pT217, pT181, pS202, and pT205) and total tau with WM measures, as derived from diffusion tensor imaging (DTI), and cognition. A WM composite metric, derived from a principal component analysis, was used to identify spatial decline seen in ADAD. RESULTS: The WM composite explained over 70% of the variance in MC. WM regions that strongly contributed to the spatial topography were located in callosal and cingulate regions. Loss of integrity within the WM composite was strongly associated with AD progression in MC as defined by the estimated years to onset (EYO) and cognitive decline. A linear regression demonstrated that amyloid, gray matter atrophy and phosphorylation at CSF tau site pT205 each uniquely explained a reduction in the WM composite within MC that was independent of vascular changes (white matter hyperintensities), and age. Hyperphosphorylation of CSF tau at other sites and total tau did not significantly predict WM composite loss. CONCLUSIONS: We identified a site-specific relationship between CSF phosphorylated tau and WM decline within MC. The presence of both amyloid deposition and Tau phosphorylation at pT205 were associated with WM composite loss. These findings highlight a primary AD-specific mechanism for WM dysfunction that is tightly coupled to symptom manifestation and cognitive decline.

Cardiorespiratory Fitness Is Associated With Better White Matter Integrity in Persons Living With HIV.

BACKGROUND: Despite improved survival rates, neurocognitive impairment persists in persons living with HIV (PLWH). An active lifestyle is linked to improved cognition among PLWH, yet the neural substrates remain unclear. Diffusion tensor imaging and diffusion basis spectrum imaging measure HIV-related changes in brain white matter integrity. We used these measures of structural brain integrity to assess white matter changes, physical fitness, and cognition in a cross-sectional study of PLWH. METHODS: Forty-four virologically well-controlled PLWH were recruited (average age of 56 years, a median recent CD4+ count of 682 cells/mm3). Diffusion tensor imaging -derived fractional anisotropy (FA) and diffusion basis spectrum imaging-derived axonal density were calculated. Cardiorespiratory fitness [maximal volume of oxygen consumption (VO2 max)] was measured by performing indirect calorimetry during exercise to volitional exhaustion. Cardiovascular risk was assessed by the Framingham risk score. Neuropsychological performance (NP) testing evaluated learning, memory, psychomotor/processing speed, and executive function. Partial correlations assessed the relationships among cardiorespiratory fitness, neuroimaging, NP, and HIV clinical metrics (CD4+ count and time since diagnosis). RESULTS: Higher VO2 max was associated with higher FA and higher axonal density in multiple white matter tracts, including the corticospinal tract and superior longitudinal fasciculus. Better NP in the motor/psychomotor domain was positively associated with FA and axonal density in diverse tracts including those associated with motor and visuospatial processing. However, higher VO2 max was not associated with NP or HIV clinical metrics. CONCLUSIONS: An active lifestyle promoting cardiorespiratory fitness may lead to better white matter integrity and decreased susceptibility to cognitive decline in virologically well-controlled PLWH.

Certolizumab Pegol in Plaque Psoriasis: Considerations for Pregnancy.

Psoriasis is a chronic, immune-mediated skin condition which commonly affects women of childbearing age. Certolizumab pegol (CZP) is an anti-tumor necrosis factor-alpha (anti-TNFα) agent that has demonstrated long-term safety and efficacy in treating moderate-to-severe plaque psoriasis. Previously, there has been limited safety data surrounding its use in pregnancy. The objective of this article is to review pivotal clinical trial data for CZP and explore safety considerations for this agent in pregnancy. This review demonstrates that CZP offers a safe and effective treatment option for women during childbearing years based on pharmacokinetics and available safety data. The observed occurrence of major congenital malformations and miscarriages appears to be no greater than the background occurrence of those in the general population, and risks to the mother are minimal based on its known safety profile. The use of CZP for treatment of plaque psoriasis should be considered and discussed with patients considering childbearing or whom are currently pregnant or breastfeeding.

Modeling autosomal dominant Alzheimer's disease with machine learning.

INTRODUCTION: Machine learning models were used to discover novel disease trajectories for autosomal dominant Alzheimer's disease. METHODS: Longitudinal structural magnetic resonance imaging, amyloid positron emission tomography (PET), and fluorodeoxyglucose PET were acquired in 131 mutation carriers and 74 non-carriers from the Dominantly Inherited Alzheimer Network; the groups were matched for age, education, sex, and apolipoprotein ε4 (APOE ε4). A deep neural network was trained to predict disease progression for each modality. Relief algorithms identified the strongest predictors of mutation status. RESULTS: The Relief algorithm identified the caudate, cingulate, and precuneus as the strongest predictors among all modalities. The model yielded accurate results for predicting future Pittsburgh compound B (R2  = 0.95), fluorodeoxyglucose (R2  = 0.93), and atrophy (R2  = 0.95) in mutation carriers compared to non-carriers. DISCUSSION: Results suggest a sigmoidal trajectory for amyloid, a biphasic response for metabolism, and a gradual decrease in volume, with disease progression primarily in subcortical, middle frontal, and posterior parietal regions.