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Alzheimer's disease (AD) is a devastating, age-associated neurodegenerative disorder and the most common cause of dementia. The clinical continuum of AD spans from preclinical disease to subjective cognitive decline, mild cognitive impairment, and dementia stages (mild, moderate, and severe). Neuropathologically, AD is defined by the accumulation of amyloid ß (Aß) into extracellular plaques in the brain parenchyma and in the cerebral vasculature, and by abnormally phosphorylated tau that accumulates intraneuronally forming neurofibrillary tangles (NFTs). Development of treatment approaches that prevent or even reduce the cognitive decline because of AD has been slow compared to other major causes of death. Recently, the United States Food and Drug Administration gave full approval to 2 different Aß-targeting monoclonal antibodies. However, this breakthrough disease modifying approach only applies to a limited subset of patients in the AD continuum and there are stringent eligibility criteria. Furthermore, these approaches do not prevent progression of disease, because other AD-related pathologies, such as NFTs, are not directly targeted. A non-mutually exclusive alternative is to address lifestyle interventions that can help reduce the risk of AD and AD-related dementias (ADRD). It is estimated that addressing such modifiable risk factors could potentially delay up to 40% of AD/ADRD cases. In this review, we discuss some of the many modifiable risk factors that may be associated with prevention of AD/ADRD and/or increasing brain resilience, as well as other factors that may interact with these modifiable risk factors to influence AD/ADRD progression. ANN NEUROL 2024.
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Anxiety is highly prevalent in Alzheimer's disease (AD), correlating with CSF/PET biomarkers and disease progression. Relationships to plasma biomarkers are unclear. Herein, we compare levels of plasma biomarkers in research participants with and without anxiety at cognitively normal, mild cognitive impairment, and AD dementia stages. We observed significantly higher plasma tau/Aß42 ratio in AD participants with anxiety versus those without, but did not observe differences at other stages or plasma biomarkers. No such relationships were evident with depression. These results support a unique pathophysiological relationship between anxiety and AD that can be reflected in plasma biomarkers, suggestive of heightened neurodegeneration.
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BACKGROUND: Subjective cognitive decline (SCD), considered a preclinical dementia stage, is less understood in Hispanics, a high-risk group for dementia. We investigated SCD to mild cognitive impairment (MCI) progression risk, as well as baseline and longitudinal features of depressive symptoms, SCD complaints, and objective cognitive performance among Hispanics compared to non-Hispanic Whites (NHW). METHODS: Hispanic (n = 23) and NHW (n = 165) SCD participants were evaluated at baseline and 2-year follow-up. Evaluations assessed function, depressive symptoms, SCD, and objective cognitive performance. RESULTS: Hispanics were at increased risk of progression to MCI (OR: 6.10, 95% CI 1.09-34.20, P = .040). Hispanic participants endorsed more depressive symptoms at baseline (P = .048) that worsened more longitudinally (OR: 3.16, 95% CI 1.18-8.51, P = .023). Hispanic participants had increased SCD complaints on the Brief Cognitive Rating Scale (BCRS) (ß = .40 SE: .17, P = .023), and in specific BCRS domains: concentration (ß = .13, SE: .07, P = .047), past memory (ß = .13, SE: .06, P = .039) and functional abilities (ß = .10, SE: .05, P = .037). In objective cognitive performance, Hispanic ethnicity associated with decline in MMSE (ß = -.27, SE: .13, P = .039), MoCA (ß = -.80 SE: .34, P = .032), Trails A (ß = 2.75, SE: .89, P = .002), Trails B (ß = 9.18, SE: 2.71, P = .001) and Guild Paragraph Recall Delayed (ß = -.80 SE: .28, P = .005). Conclusions: Hispanic ethnicity associated with a significantly increased risk of 2-year progression of SCD to MCI compared to NHW. This increased risk associated with increased depressive symptoms, distinctive SCD features, and elevated amnestic and non-amnestic objective cognitive decline. This supports further research to refine the assessment of preclinical dementia in this high-risk group.
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Magnetization transfer MRI is sensitive to semi-solid macromolecules, including amyloid beta, and has previously been used to discriminate Alzheimer's disease (AD) patients from controls. Here, we fit an unconstrained 2-pool quantitative MT (qMT) model, i.e., without constraints on the longitudinal relaxation rate R 1 s of semi-solids, and investigate the sensitivity of the estimated parameters to amyloid accumulation in preclinical subjects. We scanned 15 cognitively normal volunteers, of which 9 were amyloid positive by [18F]Florbetaben PET. A 12 min hybrid-state qMT scan with an effective resolution of 1.24 mm isotropic and whole-brain coverage was acquired to estimate the unconstrained 2-pool qMT parameters. Group comparisons and correlations with Florbetaben PET standardized uptake value ratios were analyzed at the lobar level. We find that the exchange rate and semi-solid pool's R 1 s were sensitive to the amyloid concentration, while morphometric measures of cortical thickness derived from structural MRI were not. Changes in the exchange rate are consistent with previous reports in clinical AD, while changes in R 1 s have not been reported previously as its value is typically constrained in the literature. Our results demonstrate that qMT MRI may be a promising surrogate marker of amyloid beta without the need for contrast agents or radiotracers.
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Introduction: Alzheimer's Disease (AD) typically starts in the medial temporal lobe, then develops into a neurodegenerative cascade which spreads to other brain regions. People with subjective cognitive decline (SCD) are more likely to develop dementia, especially in the presence of amyloid pathology. Thus, we were interested in the white matter microstructure of the medial temporal lobe in SCD, specifically the lower cingulum bundle that leads into the hippocampus. Diffusion tensor imaging (DTI) has been shown to differentiate SCD participants who will progress to mild cognitive impairment from those who will not. However, the biology underlying these DTI metrics is unclear, and results in the medial temporal lobe have been inconsistent. Methods: To better characterize the microstructure of this region, we applied DTI to cognitively normal participants in the Cam-CAN database over the age of 55 with cognitive testing and diffusion MRI available (N = 325, 127 SCD). Diffusion MRI was processed to generate regional and voxel-wise diffusion tensor values in bilateral lower cingulum white matter, while T1-weighted MRI was processed to generate regional volume and cortical thickness in the medial temporal lobe white matter, entorhinal cortex, temporal pole, and hippocampus. Results: SCD participants had thinner cortex in bilateral entorhinal cortex and right temporal pole. No between-group differences were noted for any of the microstructural metrics of the lower cingulum. However, correlations with delayed story recall were significant for all diffusion microstructure metrics in the right lower cingulum in SCD, but not in controls, with a significant interaction effect. Additionally, the SCD group showed an accelerated aging effect in bilateral lower cingulum with MD, AxD, and RD. Discussion: The diffusion profiles observed in both interaction effects are suggestive of a mixed neuroinflammatory and neurodegenerative pathology. Left entorhinal cortical thinning correlated with decreased FA and increased RD, suggestive of demyelination. However, right entorhinal cortical thinning also correlated with increased AxD, suggestive of a mixed pathology. This may reflect combined pathologies implicated in early AD. DTI was more sensitive than cortical thickness to the associations between SCD, memory, and age. The combined effects of mixed pathology may increase the sensitivity of DTI metrics to variations with age and cognition.
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BACKGROUND: We examined drivers of self and study partner reports of memory loss in mild cognitive impairment (MCI) from Alzheimer (AD-MCI) and vascular disease (Va-MCI). METHODS: We performed retrospective cross-sectional analyses of participants with AD-MCI (n=2874) and Va-MCI (n=376) from the National Alzheimer Coordinating Center data set. Statistical analysis utilized 2-sided t test or the Fisher exact test. RESULTS: Compared with AD-MCI, Va-MCI subjects (24.5% vs. 19.7%, P =0.031) and study partners (31.4% vs. 21.6%, P <0.0001) were more likely to deny memory loss. Black/African Americans were disproportionately represented in the group denying memory loss in AD-MCI (20.0% vs. 13.2%, P <0.0001) and Va-MCI (33.7% vs. 18.0%, P =0.0022). Study partners of participants with these features also disproportionately denied memory loss: female (AD-MCI: 60.1% vs. 51.7%, P =0.0002; Va-MCI: 70.3% vs. 52.3%, P =0.0011), Black/African American (AD-MCI: 23.5% vs. 11.98%, P <0.0001; Va-MCI: 48.8% vs. 26.5%, P =0.0002), and <16 years of education (AD-MCI only: 33.9% vs. 16.3%, P =0.0262). In AD-MCI and Va-MCI, participants with anxiety were disproportionately represented in the group endorsing memory loss (AD: 28.2% vs. 17.4%, P <0.0001; Va: 31.5% vs. 16.1%, P =0.0071), with analogous results with depression. CONCLUSION: The findings would suggest extra vigilance in interview-based MCI detection of persons at-risk for self-based or informant-based misreport.
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Doença de Alzheimer , Disfunção Cognitiva , Transtornos da Memória , Doenças Vasculares , Humanos , Feminino , Masculino , Idoso , Estudos Transversais , Transtornos da Memória/diagnóstico , Estudos Retrospectivos , Doenças Vasculares/complicações , Idoso de 80 Anos ou maisRESUMO
Early identification of Alzheimer's disease (AD) and AD-related dementias (ADRD) has high clinical significance, both because of the potential to slow decline through initiating FDA-approved therapies and managing modifiable risk factors, and to help persons living with dementia and their families to plan before cognitive loss makes doing so challenging. However, substantial racial and ethnic disparities in early diagnosis currently lead to additional inequities in care, urging accurate and inclusive risk assessment programs. In this study, we trained an artificial intelligence foundation model to represent the electronic health records (EHR) data with a vast cohort of 1.2 million patients within a large health system. Building upon this foundation EHR model, we developed a predictive Transformer model, named TRADE, capable of identifying risks for AD/ADRD and mild cognitive impairment (MCI), by analyzing the past sequential visit records. Amongst individuals 65 and older, our model was able to generate risk predictions for various future timeframes. On the held-out validation set, our model achieved an area under the receiver operating characteristic (AUROC) of 0.772 (95% CI: 0.770, 0.773) for identifying the AD/ADRD/MCI risks in 1 year, and AUROC of 0.735 (95% CI: 0.734, 0.736) in 5 years. The positive predictive values (PPV) in 5 years among individuals with top 1% and 5% highest estimated risks were 39.2% and 27.8%, respectively. These results demonstrate significant improvements upon the current EHR-based AD/ADRD/MCI risk assessment models, paving the way for better prognosis and management of AD/ADRD/MCI at scale.
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Synaptic spine loss is an early pathophysiologic hallmark of Alzheimer disease (AD) that precedes overt loss of dendritic architecture and frank neurodegeneration. While spine loss signifies a decreased engagement of postsynaptic neurons by presynaptic targets, the degree to which loss of spines and their passive components impacts the excitability of postsynaptic neurons and responses to surviving synaptic inputs is unclear. Using passive multicompartmental models of CA1 pyramidal neurons (PNs), implicated in early AD, we find that spine loss alone drives a boosting of remaining inputs to their proximal and distal dendrites, targeted by CA3 and entorhinal cortex (EC), respectively. This boosting effect is higher in distal versus proximal dendrites and can be mediated by spine loss restricted to the distal compartment, enough to impact synaptic input integration and somatodendritic backpropagation. This has particular relevance to very early stages of AD in which pathophysiology extends from EC to CA1.
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GABAergic inhibitory neurons are the principal source of inhibition in the brain. Traditionally, their role in maintaining the balance of excitation-inhibition has been emphasized. Beyond homeostatic functions, recent circuit mapping and functional manipulation studies have revealed a wide range of specific roles that GABAergic circuits play in dynamically tilting excitation-inhibition coupling across spatio-temporal scales. These span from gating of compartment- and input-specific signaling, gain modulation, shaping input-output functions and synaptic plasticity, to generating signal-to-noise contrast, defining temporal windows for integration and rate codes, as well as organizing neural assemblies, and coordinating inter-regional synchrony. GABAergic circuits are thus instrumental in controlling single-neuron computations and behaviorally-linked network activity. The activity dependent modulation of sensory and mnemonic information processing by GABAergic circuits is pivotal for the formation and maintenance of episodic memories in the hippocampus. Here, we present an overview of the local and long-range GABAergic circuits that modulate the dynamics of excitation-inhibition and disinhibition in the main output area of the hippocampus CA1, which is crucial for episodic memory. Specifically, we link recent findings pertaining to GABAergic neuron molecular markers, electrophysiological properties, and synaptic wiring with their function at the circuit level. Lastly, given that area CA1 is particularly impaired during early stages of Alzheimer's disease, we emphasize how these GABAergic circuits may contribute to and be involved in the pathophysiology.
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Doença de Alzheimer , Humanos , Hipocampo/fisiologia , Memória , Neurônios GABAérgicos/fisiologia , EncéfaloRESUMO
Alzheimer's disease (AD) is the most common cause of age-associated dementia and will exponentially rise in prevalence in the coming decades, supporting the parallel development of the early stage detection and disease-modifying strategies. While primarily considered as a cognitive disorder, AD also features motor symptoms, primarily gait dysfunction. Such gait abnormalities can be phenotyped across classic clinical syndromes as well as by quantitative kinematic assessments to address subtle dysfunction at preclinical and prodromal stages. As such, certain measures of gait can predict the future cognitive and functional decline. Moreover, cross-sectional and longitudinal studies have associated gait abnormalities with imaging, biofluid, and genetic markers of AD across all stages. This suggests that gait assessment is an important tool in the clinical assessment of patients across the AD spectrum, especially to help identify at-risk individuals.
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Doença de Alzheimer , Transtornos Cognitivos , Disfunção Cognitiva , Humanos , Doença de Alzheimer/complicações , Estudos Transversais , MarchaRESUMO
OBJECTIVES: Subjective cognitive decline (SCD) is a preclinical stage of AD. White matter hyperintensities (WMH), an MRI marker of cerebral small vessel disease, associate with AD biomarkers and progression. The impact of WMH on SCD phenotype is unclear. METHODS/DESIGN: A retrospective, cross-sectional analysis was conducted on a diverse cohort with SCD evaluated at the NYU Alzheimer's Disease Research Center between January 2017 and November 2021 (n = 234). The cohort was dichotomized into none-to-mild (n = 202) and moderate-to-severe (n = 32) WMH. Differences in SCD and neurocognitive assessments were evaluated via Wilcoxon or Fisher exact tests, with p-values adjusted for demographics using multivariable logistic regression. RESULTS: Moderate-to-severe WMH participants reported more difficulty with decision making on the Cognitive Change Index (1.5 SD 0.7 vs. 1.2 SD 0.5, p = 0.0187) and worse short-term memory (2.2 SD 0.4 vs. 1.9 SD 0.3, p = 0.0049) and higher SCD burden (9.5 SD 1.6 vs. 8.7 SD 1.7, p = 0.0411) on the Brief Cognitive Rating Scale. Moderate-to-severe WMH participants scored lower on the Mini-Mental State Examination (28.0 SD 1.6 vs. 28.5 SD 1.9, p = 0.0491), and on delayed paragraph (7.2 SD 2.0 vs. 8.8 SD 2.9, p = 0.0222) and designs recall (4.5 SD 2.3 vs. 6.1 SD 2.5, p = 0.0373) of the Guild Memory Test. CONCLUSIONS: In SCD, WMH impact overall symptom severity, specifically in executive and memory domains, as well as objective performance on global and domain-specific tests in verbal memory and visual working/associative memory.
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Doença de Alzheimer , Disfunção Cognitiva , Substância Branca , Humanos , Substância Branca/diagnóstico por imagem , Estudos Retrospectivos , Estudos Transversais , Doença de Alzheimer/genética , Imageamento por Ressonância Magnética , Fenótipo , Testes NeuropsicológicosRESUMO
Introduction: Alzheimer's disease (AD) and Lewy body disease (LBD) are the two most common neurodegenerative dementias and can occur in combination (AD+LBD). Due to overlapping biomarkers and symptoms, clinical differentiation of these subtypes could be difficult. However, it is unclear how the magnitude of diagnostic uncertainty varies across dementia spectra and demographic variables. We aimed to compare clinical diagnosis and post-mortem autopsy-confirmed pathological results to assess the clinical subtype diagnosis quality across these factors. Methods: We studied data of 1,920 participants recorded by the National Alzheimer's Coordinating Center from 2005 to 2019. Selection criteria included autopsy-based neuropathological assessments for AD and LBD, and the initial visit with Clinical Dementia Rating (CDR) stage of normal, mild cognitive impairment, or mild dementia. Longitudinally, we analyzed the first visit at each subsequent CDR stage. This analysis included positive predictive values, specificity, sensitivity and false negative rates of clinical diagnosis, as well as disparities by sex, race, age, and education. If autopsy-confirmed AD and/or LBD was missed in the clinic, the alternative clinical diagnosis was analyzed. Findings: In our findings, clinical diagnosis of AD+LBD had poor sensitivities. Over 61% of participants with autopsy-confirmed AD+LBD were diagnosed clinically as AD. Clinical diagnosis of AD had a low sensitivity at the early dementia stage and low specificities at all stages. Among participants diagnosed as AD in the clinic, over 32% had concurrent LBD neuropathology at autopsy. Among participants diagnosed as LBD, 32% to 54% revealed concurrent autopsy-confirmed AD pathology. When three subtypes were missed by clinicians, "No cognitive impairment" and "primary progressive aphasia or behavioral variant frontotemporal dementia" were the leading primary etiologic clinical diagnoses. With increasing dementia stages, the clinical diagnosis accuracy of black participants became significantly worse than other races, and diagnosis quality significantly improved for males but not females. Discussion: These findings demonstrate that clinical diagnosis of AD, LBD, and AD+LBD are inaccurate and suffer from significant disparities on race and sex. They provide important implications for clinical management, anticipatory guidance, trial enrollment and applicability of potential therapies for AD, and promote research into better biomarker-based assessment of LBD pathology.
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INTRODUCTION: Mild to moderate exercise may decrease Alzheimer's disease (AD) risk, but the effects of vigorous, regular physical exercise remain unclear. METHODS: Two patients with initial diagnoses of amnestic mild cognitive impairment (MCI) demonstrated positive AD biomarkers throughout 16 and 8 years of follow-up, with final diagnoses of mild AD and amnestic MCI, respectively. RESULTS: Patient 1 was diagnosed with amnestic MCI at age 64. Neuropsychological testing, magnetic resonance imaging (MRI), fluorodeoxyglucose-positron emission tomography (FDG-PET), amyloid imaging PET, and cerebrospinal fluid (CSF) biomarkers during follow-ups remained consistent with AD. By age 80, progression was minimal with Montreal Cognitive Assessment (MoCA) 26 of 30. Patient 2 was diagnosed with amnestic MCI at age 72. Neuropsychological testing, MRI, FDG-PET, and amyloid imaging PET during follow-ups remained consistent with AD. At age 80, MoCA was 27 of 30 with no clinical progression. Both patients regularly performed vigorous, regular exercise that increased after retirement/work reduction. DISCUSSION: Vigorous, regular exercise may slow disease progression in biomarker-positive amnestic MCI and mild AD.
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Doença de Alzheimer , Disfunção Cognitiva , Humanos , Pessoa de Meia-Idade , Idoso , Idoso de 80 Anos ou mais , Doença de Alzheimer/patologia , Fluordesoxiglucose F18 , Progressão da Doença , Tomografia por Emissão de Pósitrons/métodos , Imageamento por Ressonância Magnética , Biomarcadores/líquido cefalorraquidiano , Disfunção Cognitiva/diagnóstico , Exercício Físico , Peptídeos beta-Amiloides/líquido cefalorraquidiano , Testes NeuropsicológicosRESUMO
BACKGROUND: We examined the association between asymptomatic intracranial artery stenosis (aICAS) and cortical thickness using brain magnetic resonance morphometry in two cohorts. METHODS: This cross-sectional study included stroke-free participants from the Northern Manhattan Study (NOMAS) and the National Alzheimer's Coordinating Center (NACC). We represented the predictor aICAS in NOMAS as a continuous global stenosis score reflecting an overall burden of stenosis (possible range 0-44) assessed by magnetic resonance angiography and in NACC as a dichotomous autopsy-determined Circle of Willis (CoW) atherosclerosis (none-mild vs moderate-severe). The primary outcome of interest was total cortical thickness. We analyzed each dataset separately using multivariable linear regression. RESULTS: The analysis included 1209 NOMAS (46% had any stenosis, 5% had ≥70% stenosis of at least one vessel; stenosis score range 0-11) and 392 NACC (36% moderate-severe CoW atherosclerosis) participants. We found an inverse relationship between stenosis score and total cortical thickness (ß-estimate [95% confidence interval (CI)]: -2.98 [-5.85, -0.11]) in adjusted models. We replicated these results in NACC (ß-estimate [95% CI]: -0.06 [-0.11, -0.003]). Post-hoc, we segregated stenosis scores by location and only posterior circulation stenosis score was associated with total cortical thickness (anterior ß-estimate [95% CI]: -0.90 [-5.16, 3.36], posterior ß-estimate [95% CI]: -7.25 [-14.30, -0.20]). CONCLUSION: We found both radiographically and neuropathologically determined aICAS to be associated with global cortical thinning. Interestingly, posterior circulation stenoses appeared to drive this association with global cortical thinning, raising the possibility of pathophysiologic mechanisms for cortical thinning other than impaired hemodynamics.
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Aterosclerose , Estenose das Carótidas , Arteriosclerose Intracraniana , Noma , Acidente Vascular Cerebral , Humanos , Constrição Patológica/diagnóstico por imagem , Estudos Transversais , Afinamento Cortical Cerebral , Acidente Vascular Cerebral/diagnóstico por imagem , Imageamento por Ressonância Magnética , Artérias/patologia , Arteriosclerose Intracraniana/complicações , Arteriosclerose Intracraniana/diagnóstico por imagemRESUMO
Demyelination is observed in both healthy aging and age-related neurodegenerative disorders. While the significance of myelin within the cortex is well acknowledged, studies focused on intracortical demyelination and depth-specific structural alterations in normal aging are lacking. Using the recently available Human Connectome Project Aging dataset, we investigated intracortical myelin in a normal aging population using the T1w/T2w ratio. To capture the fine changes across cortical depths, we employed a surface-based approach by constructing cortical profiles traveling perpendicularly through the cortical ribbon and sampling T1w/T2w values. The curvatures of T1w/T2w cortical profiles may be influenced by differences in local myeloarchitecture and other tissue properties, which are known to vary across cortical regions. To quantify the shape of these profiles, we parametrized the level of curvature using a nonlinearity index (NLI) that measures the deviation of the profile from a straight line. We showed that NLI exhibited a steep decline in aging that was independent of local cortical thinning. Further examination of the profiles revealed that lower T1w/T2w near the gray-white matter boundary and superficial cortical depths were major contributors to the apparent NLI variations with age. These findings suggest that demyelination and changes in other T1w/T2w related tissue properties in normal aging may be depth-specific and highlight the potential of NLI as a unique marker of microstructural alterations within the cerebral cortex.
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Imageamento por Ressonância Magnética , Bainha de Mielina , Humanos , Idoso , Substância Cinzenta , Córtex Cerebral/diagnóstico por imagem , EncéfaloRESUMO
Early diagnosis of Alzheimer's disease plays a pivotal role in patient care and clinical trials. In this study, we have developed a new approach based on 3D deep convolutional neural networks to accurately differentiate mild Alzheimer's disease dementia from mild cognitive impairment and cognitively normal individuals using structural MRIs. For comparison, we have built a reference model based on the volumes and thickness of previously reported brain regions that are known to be implicated in disease progression. We validate both models on an internal held-out cohort from The Alzheimer's Disease Neuroimaging Initiative (ADNI) and on an external independent cohort from The National Alzheimer's Coordinating Center (NACC). The deep-learning model is accurate, achieved an area-under-the-curve (AUC) of 85.12 when distinguishing between cognitive normal subjects and subjects with either MCI or mild Alzheimer's dementia. In the more challenging task of detecting MCI, it achieves an AUC of 62.45. It is also significantly faster than the volume/thickness model in which the volumes and thickness need to be extracted beforehand. The model can also be used to forecast progression: subjects with mild cognitive impairment misclassified as having mild Alzheimer's disease dementia by the model were faster to progress to dementia over time. An analysis of the features learned by the proposed model shows that it relies on a wide range of regions associated with Alzheimer's disease. These findings suggest that deep neural networks can automatically learn to identify imaging biomarkers that are predictive of Alzheimer's disease, and leverage them to achieve accurate early detection of the disease.
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Doença de Alzheimer , Disfunção Cognitiva , Aprendizado Profundo , Doença de Alzheimer/diagnóstico por imagem , Biomarcadores , Disfunção Cognitiva/diagnóstico por imagem , Progressão da Doença , Diagnóstico Precoce , Humanos , Imageamento por Ressonância Magnética/métodos , Neuroimagem/métodosRESUMO
High-resolution susceptibility weighted imaging (SWI) provides unique contrast to small venous vasculature. The conspicuity of these mesoscopic veins, such as deep medullary veins in white matter, is subject to change from SWI venography when venous oxygenation in these veins is altered due to oxygenated blood susceptibility changes. The changes of visualization in small veins shows potential to depict regional changes of oxygen utilization and/or vascular density changes in the aging brain. The goal of this study was to use WM venous density to quantify small vein visibility in WM and investigate its relationship with neurodegenerative features, white matter hyperintensities (WMHs), and cognitive/functional status in elderly subjects (N = 137). WM venous density was significantly associated with neurodegeneration characterized by brain atrophy (ß = 0.046± 0.01, p < 0.001), but no significant association was found between WM venous density and WMHs lesion load (p = 0.3963). Further analysis of clinical features revealed a negative trend of WM venous density with the sum-of-boxes of Clinical Dementia Rating and a significant association with category fluency (1-min animal naming). These results suggest that WM venous density on SWI can be used as a sensitive marker to characterize cerebral oxygen metabolism and different stages of cognitive and functional status in neurodegenerative diseases.