A 10-year follow-up of hippocampal volume on magnetic resonance imaging in early dementia and cognitive decline

Neural underpinnings of fine motor skills under stress and anxiety: A review

This review offers a comprehensive examination of how stress and anxiety affect motor behavior, particularly focusing on fine motor skills and gait adaptability. We explore the role of several neurochemicals, including brain-derived neurotrophic factor (BDNF) and dopamine, in modulating neural plasticity and motor control under these affective states. The review highlights the importance of developing therapeutic strategies that enhance motor performance by leveraging the interactions between key neurochemicals. Additionally, we investigate the complex interplay between emotional-cognitive states and sensorimotor behaviors, showing how stress and anxiety disrupt neural integration, leading to impairments in skilled movements and negatively impacting quality of life. Synthesizing evidence from human and rodent studies, we provide a detailed understanding of the relationships among stress, anxiety, and motor behavior. Our findings reveal neurophysiological pathways, behavioral outcomes, and potential therapeutic targets, emphasizing the intricate connections between neurobiological mechanisms, environmental factors, and motor performance.

The Effects of Computerized Cognitive Training in Older Adults' Cognitive Performance and Biomarkers of Structural Brain Aging

OBJECTIVES

Cognitive training (CT) has been investigated as a means of delaying age-related cognitive decline in older adults. However, its impact on biomarkers of age-related structural brain atrophy has rarely been investigated, leading to a gap in our understanding of the linkage between improvements in cognition and brain plasticity. This study aimed to explore the impact of CT on cognitive performance and brain structure in older adults.

METHODS

One hundred twenty-four cognitively normal older adults recruited from 2 study sites were randomly assigned to either an adaptive CT (n = 60) or a casual game training (active control, AC, n = 64).

RESULTS

After 10 weeks of training, CT participants showed greater improvements in the overall cognitive composite score (Cohen's d = 0.66, p < .01) with nonsignificant benefits after 6 months from the completion of training (Cohen's d = 0.36, p = .094). The CT group showed significant maintenance of the caudate volume as well as significant maintained fractional anisotropy in the left internal capsule and in left superior longitudinal fasciculus compared to the AC group. The AC group displayed an age-related decrease in these metrics of brain structure.

DISCUSSION

Results from this multisite clinical trial demonstrate that the CT intervention improves cognitive performance and helps maintain caudate volume and integrity of white matter regions that are associated with cognitive control, adding to our understanding of the changes in brain structure contributing to changes in cognitive performance from adaptive CT.

CLINICAL TRIAL REGISTRATION

NCT03197454.

Dementia, dementia's risk factors and premorbid brain structure are concentrated in disadvantaged areas: National register and birth-cohort geographic analyses

INTRODUCTION

Dementia risk may be elevated in socioeconomically disadvantaged neighborhoods. Reasons for this remain unclear, and this elevation has yet to be shown at a national population level.

METHODS

We tested whether dementia was more prevalent in disadvantaged neighborhoods across the New Zealand population (N = 1.41 million analytic sample) over a 20-year observation. We then tested whether premorbid dementia risk factors and MRI-measured brain-structure antecedents were more prevalent among midlife residents of disadvantaged neighborhoods in a population-representative NZ-birth-cohort (N = 938 analytic sample).

RESULTS

People residing in disadvantaged neighborhoods were at greater risk of dementia (HR per-quintile-disadvantage-increase = 1.09, 95% confidence interval [CI]:1.08-1.10) and, decades before clinical endpoints typically emerge, evidenced elevated dementia-risk scores (CAIDE, LIBRA, Lancet, ANU-ADRI, DunedinARB; β's 0.31-0.39) and displayed dementia-associated brain structural deficits and cognitive difficulties/decline.

DISCUSSION

Disadvantaged neighborhoods have more residents with dementia, and decades before dementia is diagnosed, residents have more dementia-risk factors and brain-structure antecedents. Whether or not neighborhoods causally influence risk, they may offer scalable opportunities for primary dementia prevention.

Brain Healthcare Quotient as a Tool for Standardized Approach in Brain Healthcare Interventions

In addressing the challenge of assessing healthy brain aging across diverse interventions, this study introduces the use of MRI-derived Brain Healthcare Quotients (BHQ) for comprehensive evaluation. We analyzed BHQ changes in 319 participants aged 24-69, who were allocated into dietary (collagen peptide, euglena, matcha, isohumulone, xanthophyll) and physical activity (hand massage with lavender oil, handwriting, office stretching, pink lens, clinical art) groups, alongside a control group, over a month. These interventions were specifically chosen to test the efficacy of varying health strategies on brain health, measured through BHQ indices: GM-BHQ for gray matter volume, and FA-BHQ for white matter integrity. Notably, significant improvements in FA-BHQ were observed in the collagen peptide group, with marginal increases in the hand massage and office stretching groups. These findings highlight BHQ's potential as a sensitive tool for detecting brain health changes, offering evidence that low-intensity, easily implemented interventions can have beneficial effects on brain health. Moreover, BHQ allows for the systematic evaluation of such interventions using standard statistical approaches, suggesting its value in future brain healthcare research.

Prediction of dementia risk from multimodal repeated measures: The added value of brain MRI biomarkers

Abstract

The utility of brain magnetic resonance imaging (MRI) for predicting dementia is debated. We evaluated the added value of repeated brain MRI, including atrophy and cerebral small vessel disease markers, for dementia prediction. We conducted a landmark competing risk analysis in 1716 participants of the French population-based Three-City Study to predict the 5-year risk of dementia using repeated measures of 41 predictors till year 4 of follow-up. Brain MRI markers improved significantly the individual prediction of dementia after accounting for demographics, health measures, and repeated measures of cognition and functional dependency (area under the ROC curve [95% CI] improved from 0.80 [0.79 to 0.82] to 0.83 [0.81 to 0.84]). Nonetheless, accounting for the change over time through repeated MRIs had little impact on predictive abilities. These results highlight the importance of multimodal analysis to evaluate the added predictive abilities of repeated brain MRI for dementia and offer new insights into the predictive performances of various MRI markers.

Highlights

We evaluated whether repeated brain volumes and cSVD markers improve dementia prediction.The 5-year prediction of dementia is slightly improved when considering brain MRI markers.Measures of hippocampus volume are the main MRI predictors of dementia.Adjusted on cognition, repeated MRI has poor added value over single MRI for dementia prediction.We utilized a longitudinal analysis that considers error-and-missing-prone predictors, and competing death.

Transition to healthier lifestyle associated with reduced risk of incident dementia and decreased hippocampal atrophy

BACKGROUND

Research has estimated the associations of lifestyle at one-time point with the risk of dementia and hippocampal volume, but the impact of lifestyle transition on dementia and hippocampal volume remains unclear. This study aims to examine the associations of lifestyle transition with the risk of dementia and hippocampal volume.

METHODS

Based on data from the UK Biobank, a weighted lifestyle score was constructed by incorporating six lifestyle factors. Within each baseline lifestyle group (i.e., healthy, intermediate, and unhealthy), lifestyle transition was classified into decline, maintenance, and improvement. Cox proportional hazard regression was used to estimate the association of lifestyle transition and incident dementia (N = 16,305). A multiple linear regression model was used to estimate the association between lifestyle transition and hippocampal volume (N = 5849).

RESULTS

During a median follow-up period of 8.6 years, 120 (0.7 %) dementia events were documented. Among participants with healthy baseline lifestyles, the improvement group had a lower risk of incident dementia (HR: 0.18, 95 % CI: 0.04-0.81) and a larger hippocampal volume (β = 111.69, P = 0.026) than the decline group. Similar results were observed among participants with intermediate baseline lifestyles regarding dementia risk but not hippocampal volume. No benefits were observed in the improvement group among those with unhealthy baseline lifestyles.

LIMITATIONS

A lower incidence of dementia than other cohort study and this may have resulted in an underestimation of the risk of dementia.

CONCLUSIONS

Earlier transitions to healthier lifestyle were associated with reduced risk of incident dementia and decreased hippocampal atrophy.

The prevalence of mild cognitive impairment in Gulf War veterans: a follow-up study

Introduction

Gulf War Illness (GWI), also called Chronic Multisymptom Illness (CMI), is a multi-faceted condition that plagues an estimated 250,000 Gulf War (GW) veterans. Symptoms of GWI/CMI include fatigue, pain, and cognitive dysfunction. We previously reported that 12% of a convenience sample of middle aged (median age 52 years) GW veterans met criteria for mild cognitive impairment (MCI), a clinical syndrome most prevalent in older adults (e.g., ≥70 years). The current study sought to replicate and extend this finding.

Methods

We used the actuarial neuropsychological criteria and the Montreal Cognitive Assessment (MoCA) to assess the cognitive status of 952 GW veterans. We also examined regional brain volumes in a subset of GW veterans (n = 368) who had three Tesla magnetic resonance images (MRIs).

Results

We replicated our previous finding of a greater than 10% rate of MCI in four additional cohorts of GW veterans. In the combined sample of 952 GW veterans (median age 51 years at time of cognitive testing), 17% met criteria for MCI. Veterans classified as MCI were more likely to have CMI, history of depression, and prolonged (≥31 days) deployment-related exposures to smoke from oil well fires and chemical nerve agents compared to veterans with unimpaired and intermediate cognitive status. We also replicated our previous finding of hippocampal atrophy in veterans with MCI, and found significant group differences in lateral ventricle volumes.

Discussion

Because MCI increases the risk for late-life dementia and impacts quality of life, it may be prudent to counsel GW veterans with cognitive dysfunction, CMI, history of depression, and high levels of exposures to deployment-related toxicants to adopt lifestyle habits that have been associated with lowering dementia risk. With the Food and Drug Administration's recent approval of and the VA's decision to cover the cost for anti-amyloid β (Aβ) therapies, a logical next step for this research is to determine if GW veterans with MCI have elevated Aβ in their brains.

Increased Likelihood of Dementia with Coexisting Atrophy of Multiple Regions of Interest

BACKGROUND

Brain volume is associated with cognitive decline in later life, and cortical brain atrophy exceeding the normal range is related to inferior cognitive and behavioral outcomes in later life.

OBJECTIVE

To investigate the likelihood of cognitive decline, mild cognitive impairment (MCI), or dementia, when regional atrophy is present in participants' magnetic resonance imaging (MRI).

METHODS

Multi-center MRI data of 2,545 adults were utilized to measure regional volumes using NEUROPHET AQUA. Four lobes (frontal, parietal, temporal, and occipital), four Alzheimer's disease-related regions (entorhinal, fusiform, inferior temporal, and middle temporal area), and the hippocampus in the left and right hemispheres were measured and analyzed. The presence of regional atrophy from brain MRI was defined as ≤1.5 standard deviation (SD) compared to the age- and sex-matched cognitively normal population. The risk ratio for cognitive decline was investigated for participants with regional atrophy in contrast to those without regional atrophy.

RESULTS

The risk ratio for cognitive decline was significantly higher when hippocampal atrophy was present (MCI, 1.84, p < 0.001; dementia, 4.17, p < 0.001). Additionally, participants with joint atrophy in multiple regions showed a higher risk ratio for dementia, e.g., 9.6 risk ratio (95% confidence interval, 8.0-11.5), with atrophy identified in the frontal, temporal, and hippocampal gray matter, than those without atrophy.

CONCLUSIONS

Our study showed that individuals with multiple regional atrophy (either lobar or AD-specific regions) have a higher likelihood of developing dementia compared to the age- and sex-matched population without atrophy. Thus, further consideration is needed when assessing MRI findings.

Is Hippocampal Volume a Relevant Early Marker of Dementia?

OBJECTIVE

Hippocampal volume (HV) is a key imaging marker to improve Alzheimer's disease risk prediction. However, longitudinal studies are rare, and hippocampus may also be implicated in the subtle aging-related cognitive decline observed in dementia-free individuals. Our aim was to determine whether HV, measured by manual or automatic segmentation, is associated with dementia risk and cognitive decline in participants with and without incident dementia.

METHODS

At baseline, 510 dementia-free participants from the French longitudinal ESPRIT cohort underwent magnetic resonance imaging. HV was measured by manual and by automatic segmentation (FreeSurfer 6.0). The presence of dementia and cognitive functions were investigated at each follow-up (2, 4, 7, 10, 12, and 15 years). Cox proportional hazards models and linear mixed models were used to assess the association of HV with dementia risk and with cognitive decline, respectively.

RESULTS

During the 15-years follow-up, 42 participants developed dementia. Reduced HV (regardless of the measurement method) was significantly associated with higher dementia risk and cognitive decline in the whole sample. However, only the automatically measured HV was associated with cognitive decline in dementia-free participants.

CONCLUSION

These results suggest that HV can be used to predict the long-term risk of dementia but also cognitive decline in a dementia-free population. This raises the question of the relevance of HV measurement as an early marker of dementia in the general population.

Evaluation of 'Normal' Cognitive Functions and Correlation With MRI Volumetry: Towards a Definition of Vascular Cognitive Impairment

Introduction It is important to establish criteria to define vascular cognitive impairment (VCI) in India as VCI is an image-based diagnosis and magnetic resonance imaging (MRI) changes resulting from age with prevalent vascular risk factors may confound MRI interpretation. The objective of this study was to establish normative community data for MRI volumetry including white matter hyperintensity volume (WMHV), correlated with age-stratified cognitive scores and vascular risk factors (VRFs), in adults aged 40 years and above.  Methods We screened 2651 individuals without known neurological morbidity, living in Mumbai and nearby rural areas, using validated Marathi translations of Kolkata Cognitive Battery (KCB) and geriatric depression score (GDS). We stratified 1961 persons with GDS ≤9 by age and cognitive score, and randomly selected 10% from each subgroup for MRI brain volumetry. Crude volumes were standardized to reflect percentage of intracranial volume.  Results MRI volumetry studies were done in 199 individuals (F/M = 90/109; 73 with body mass index (BMI) ≥25; 44 hypertensives; 29 diabetics; mean cognitive score 76.3). Both grey and white matter volumes decreased with increasing age. WMHV increased with age and hypertension. Grey matter volume (GMV) decreased with increasing WMHV. Positive predictors of cognition included standardized hippocampal volume (HCV), urban living, education, and BMI, while WMHV and age were negative predictors. Urban dwellers had higher cognitive scores than rural, and, paradoxically, smaller HCV.  Conclusion In this study of MRI volumetry correlated with age, cognitive scores and VRFs, increasing age and WMHV predicted lower cognitive scores, whereas urban living and hippocampal volume predicted higher scores. Age and WMHV also correlated with decreasing GMV. Further study is warranted into sociodemographic and biological factors that mutually influence cognition and brain volumes, including nutritional and endocrine factors, especially at lower cognitive score bands. In this study, at the lower KCB score bins, the lack of laboratory data pertaining to nutritional and endocrine deficiencies is a drawback that reflects the logistical limitations of screening large populations at the community level. Our volumetric data which is age and cognition stratified, and takes into account the vascular risk factors associated, nevertheless constitutes important baseline data for the Indian population. Our findings could possibly contribute to the formulation of baseline criteria for defining VCI in India and could help in early diagnosis and control of cognitive decline and its key risk factors.

Hippocampal sclerosis of aging at post-mortem is evident on MRI more than a decade prior

INTRODUCTION

Hippocampal sclerosis of aging (HS) is an important component of combined dementia neuropathology. However, the temporal evolution of its histologically-defined features is unknown. We investigated pre-mortem longitudinal hippocampal atrophy associated with HS, as well as with other dementia-associated pathologies.

METHODS

We analyzed hippocampal volumes from magnetic resonance imaging (MRI) segmentations in 64 dementia patients with longitudinal MRI follow-up and post-mortem neuropathological evaluation, including HS assessment in the hippocampal head and body.

RESULTS

Significant HS-associated hippocampal volume changes were observed throughout the evaluated timespan, up to 11.75 years before death. These changes were independent of age and Alzheimer's disease (AD) neuropathology and were driven specifically by CA1 and subiculum atrophy. AD pathology, but not HS, was associated significantly with the rate of hippocampal atrophy.

DISCUSSION

HS-associated volume changes are detectable on MRI earlier than 10 years before death. Based on these findings, volumetric cutoffs could be derived for in vivo differentiation between HS and AD.

HIGHLIGHTS

Hippocampal atrophy was found in HS+ patients earlier than 10 years before death. These early pre-mortem changes were driven by reduced CA1 and subiculum volumes. Rates of hippocampus and subfield volume decline were independent of HS. In contrast, steeper atrophy rates were associated with AD pathology burden. Differentiation between AD and HS could be facilitated based on these MRI findings.

Metabolomic Signatures of Alzheimer's Disease Indicate Brain Region-Specific Neurodegenerative Progression

Pathological mechanisms contributing to Alzheimer's disease (AD) are still elusive. Here, we identified the metabolic signatures of AD in human post-mortem brains. Using 1H NMR spectroscopy and an untargeted metabolomics approach, we identified (1) metabolomic profiles of AD and age-matched healthy subjects in post-mortem brain tissue, and (2) region-common and region-unique metabolome alterations and biochemical pathways across eight brain regions revealed that BA9 was the most affected. Phenylalanine and phosphorylcholine were mainly downregulated, suggesting altered neurotransmitter synthesis. N-acetylaspartate and GABA were upregulated in most regions, suggesting higher inhibitory activity in neural circuits. Other region-common metabolic pathways indicated impaired mitochondrial function and energy metabolism, while region-unique pathways indicated oxidative stress and altered immune responses. Importantly, AD caused metabolic changes in brain regions with less well-documented pathological alterations that suggest degenerative progression. The findings provide a new understanding of the biochemical mechanisms of AD and guide biomarker discovery for personalized risk prediction and diagnosis.

Predictive factors for Alzheimer's disease progression: a comprehensive retrospective analysis of 3,553 cases with 211 months follow-up

Background

There is conflicting data regarding the predictors of Alzheimer's Disease (AD), the most common form of dementia. The main objective of the study is to evaluate potential predictors of AD progression using a comprehensive follow-up dataset that includes functional/cognitive assessments, clinical and neuropsychiatric evaluations, and neuroimaging biomarkers such as hippocampal atrophy or white matter intensities (WMIs).

Method

A total of 161 AD cases were recruited from a dementia database consisting of individuals who consulted the Dementia Outpatient Clinic of the Neurology Department at Mersin University Medical Faculty between 2000 and 2022, under the supervision of the same senior author have at least 3 full evaluation follow-up visit including functional, clinical, biochemical, neuropsychological, and radiological screening. Data were exported and analyzed by experts accordingly.

Results

Mean follow-up duration of study sample was 71.66 ± 41.98, min 15 to max 211 months. The results showed a fast and slow progressive subgroup of our AD cases with a high sensitivity (Entropy = 0.836), with a close relationship with several cofactors and the level of disability upon admittance. Hippocampal atrophy and WMIs grading via Fazekas were found to be underestimated predictors of AD progression, and functional capacity upon admittance was also among the main stakeholders.

Conclusion

The study highlights the importance of evaluating multiple potential predictors for AD progression, including functional capacity upon admittance, hippocampal atrophy, and WMIs grading via Fazekas. Our findings provide insight into the complexity of AD progression and may contribute to the development of effective strategies for managing and treating AD.

Predicting mild cognitive impairment progression to Alzheimer's disease based on machine learning analysis of cortical morphological features

PURPOSE

To establish a model for predicting mild cognitive impairment (MCI) progression to Alzheimer's disease (AD) using morphological features extracted from a joint analysis of voxel-based morphometry (VBM) and surface-based morphometry (SBM).

METHODS

We analyzed data from 121 MCI patients from the Alzheimer's Disease Neuroimaging Initiative, 32 of whom progressed to AD during a 4-year follow-up period and were classified as the progression group, while the remaining 89 were classified as the non-progression group. Patients were divided into a training set (n = 84) and a testing set (n = 37). Morphological features measured by VBM and SBM were extracted from the cortex of the training set and dimensionally reduced to construct morphological biomarkers using machine learning methods, which were combined with clinical data to build a multimodal combinatorial model. The model's performance was evaluated using receiver operating characteristic curves on the testing set.

RESULTS

The Alzheimer's Disease Assessment Scale (ADAS) score, apolipoprotein E (APOE4), and morphological biomarkers were independent predictors of MCI progression to AD. The combinatorial model based on the independent predictors had an area under the curve (AUC) of 0.866 in the training set and 0.828 in the testing set, with sensitivities of 0.773 and 0.900 and specificities of 0.903 and 0.747, respectively. The number of MCI patients classified as high-risk for progression to AD was significantly different from those classified as low-risk in the training set, testing set, and entire dataset, according to the combinatorial model (P < 0.05).

CONCLUSION

The combinatorial model based on cortical morphological features can identify high-risk MCI patients likely to progress to AD, potentially providing an effective tool for clinical screening.

Visit-to-visit HbA1c variability, dementia, and hippocampal atrophy among adults without diabetes

OBJECTIVES

Adults without diabetes are not completely healthy; they are probably heterogeneous with several potential health problems. The management of hemoglobin A1c (HbA1c) is crucial among patients with diabetes; but whether similar management strategy is needed for adults without diabetes is unclear. Thus, this study aimed to investigate the associations of visit-to-visit HbA1c variability with incident dementia and hippocampal volume among middle-aged and older adults without diabetes, providing potential insights into this question.

METHODS

We conducted a prospective analysis for incident dementia in 10,792 participants (mean age 58.9 years, 47.8 % men) from the UK Biobank. A subgroup of 3793 participants (mean age 57.8 years, 48.6 % men) was included in the analysis for hippocampal volume. We defined HbA1c variability as the difference in HbA1c divided by the mean HbA1c over the 2 sequential visits ([latter - former]/mean). Dementia was identified using hospital inpatient records with ICD-9 codes. T1-structural brain magnetic resonance imaging was conducted to derive hippocampal volume (normalized for head size). The nonlinear and linear associations were examined using restricted cubic spline (RCS) models, Cox regression models, and multiple linear regression models.

RESULTS

During a mean follow-up (since the second round) of 8.4 years, 90 (0.8 %) participants developed dementia. The RCS models suggested no significant nonlinear associations of HbA1c variability with incident dementia and hippocampal volume, respectively (All P > 0.05). Above an optimal cutoff of HbA1c variability at 0.08, high HbA1c variability (increment in HbA1c) was associated with an increased risk of dementia (Hazard Ratio, 1.88; 95 % Confidence Interval, 1.13 to 3.14, P = 0.015), and lower hippocampal volume (coefficient, -96.84 mm3, P = 0.037), respectively, in models with adjustment of covariates including age, sex, etc. Similar results were found for a different cut-off of 0. A series of sensitivity analyses verified the robustness of the findings.

CONCLUSIONS

Among middle-aged and older adults without diabetes, increasing visit-to-visit HbA1c variability was associated with an increased dementia risk and lower hippocampal volume. The findings highlight the importance of monitoring and controlling HbA1c fluctuation in apparently healthy adults without diabetes.

A Graph Convolutional Network Based on Univariate Neurodegeneration Biomarker for Alzheimer's Disease Diagnosis

OBJECTIVE

Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease that is not easily detectable in the early stage. This study proposed an efficient method of applying a graph convolutional network (GCN) on the early prediction of AD.

METHODS

We proposed a univariate neurodegeneration biomarker (UNB) based GCN semi-supervised classification framework. We generated UNB by comparing the similarity of individual morphological atrophy pattern and the atrophy pattern of [Formula: see text] AD group according to the brain morphological abnormalities induced by AD. For the GCN semi-supervised classification model, we took the UNBs of individuals as the features of nodes and constructed the weight of edges according to the similarity of phenotypic information between individuals, which explored the essential features of individuals through spectral graph convolution. The attention module was constructed and embedded into the GCN framework, which may refine the input morphological features to highlight the main impact of AD on the cerebral cortex and weaken the instability caused by individual diversities, thereby identifying the significant ROIs affected by AD and improving the classification accuracy.

RESULTS

We tested the UNB-GCN framework on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The estimated minimum sample sizes were 156, 349 and 423 for the longitudinal [Formula: see text] AD, [Formula: see text] mild cognitive impairment (MCI) and [Formula: see text] cognitively unimpaired (CU) groups, respectively. And the proposed UNB-GCN framework combined with the attention module can effectively improve the classification performance with 93.90% classification accuracy for AD vs. CU and 82.05% for AD vs. MCI on the validation set.

CONCLUSION

The proposed UNB measures were superior to the conventional volume measures in describing the AD-induced cerebral cortex morphological changes. And the UNB-GCN framework combined with attention module may effectively improve the classification performance between MCI subjects and AD patients. Clinical and Translational Impact Statement: This study aims to predict the early AD patients, so as to help clinicians develop effective interventions to delay the deterioration of AD symptoms.

The Relationship Between Coronary Artery Calcification and Carotid Intima Media Thickness and Hippocampal Volume: An Analysis From the Dallas Heart Study

BACKGROUND

Higher rates of dementia are reported in people with a history of coronary artery disease. Smaller hippocampal volume (HV) is a risk factor for the development of dementia.

OBJECTIVE

This study assessed whether coronary artery calcification (CAC) and carotid intima media thickness (CIMT) are associated with HV in participants from the Dallas Heart Study, a community-based study of Dallas County, Texas, residents.

METHODS

Data from a total of n = 1821 participants in the Dallas Heart Study with brain magnetic resonance imaging, CAC, and CIMT information were included in the present study, after excluding those with a history of myocardial infarction or stroke. To evaluate the effect of CAC and CIMT on total HV, 4 linear regression analyses were conducted in which the primary predictor was (1) CAC as a continuous metric; (2) CAC as a binary metric (CAC = 0 vs. CAC ≥ 1); (3) CAC as a continuous metric but only for those with CAC >0; and (4) CIMT as a continuous metric. Demographic and cardiovascular disease risk factors, as well as intracranial volume, were entered into the model as covariates.

RESULTS

Participants were largely women (58.2%) with a mean age of 49.7 ± 10.3 years. Forty-six percent of the sample reported being Black, and approximately 14% reported being Hispanic. All 3 variations of the CAC effect were nonsignificant predictors of total HV (β = -0.013, P = 0.602; β = -0.011, P = 0.650; β = 0.036, P = 0.354, respectively), as was the effect of CIMT (β = 0.009, P = 0.686).

CONCLUSIONS

Current findings suggest nonsignificant relationships between both CAC and CIMT and between CAC and total HV, while controlling for other related factors in a large, diverse, community-based sample of people without a history of myocardial infarction or stroke. In the context of existing evidence that both coronary artery disease and smaller HV are associated with the development of dementia, the present findings suggest that neither marker of the cardiovascular disease examined here is associated with a reduction in HV in the population studied. Longitudinal studies are needed to assess relationships between CAC and CIMT and between CAC and HV over time.

Hippocampal sclerosis of aging at post-mortem is evident on MRI more than a decade prior

INTRODUCTION

Hippocampal sclerosis of aging (HS) is an important component of combined dementia neuropathology. However, the temporal evolution of its histologically-defined features is unknown. We investigated pre-mortem longitudinal hippocampal atrophy associated with HS, as well as with other dementia-associated pathologies.

METHODS

We analyzed hippocampal volumes from MRI segmentations in 64 dementia patients with longitudinal MRI follow-up and post-mortem neuropathological evaluation, including HS assessment in the hippocampal head and body.

RESULTS

Significant HS-associated hippocampal volume changes were observed thoughout the evaluated timespan, up to 11.75 years before death. These changes were independent of age and Alzheimer’s Disease (AD) burden, and specifically driven by CA1 and subiculum. AD burden, but not HS, significantly associated with the rate of hippocampal atrophy.

DISCUSSION

HS-associated volume changes are detectable on MRI earlier than 10 years before death. These findings could contribute to the derivation of volumetric cut-offs for in vivo differentiation between HS and AD.

Association of white matter lesions and brain atrophy with the development of dementia in a community: the Hisayama Study

AIM

To investigate the association of white matter lesions volume (WMLV) levels with dementia risk and the association between dementia risk and the combined measures of WMLV and either total brain atrophy or dementia-related gray matter atrophy in a general older population.

METHODS

One thousand one hundred fifty-eight Japanese dementia-free community-residents aged ≥65 years who underwent brain magnetic resonance imaging were followed for 5.0 years. WMLV were segmented using the Lesion Segmentation Toolbox. Total brain volume (TBV) and regional gray matter volume were estimated by voxel-based morphometry. The WMLV-to-intracranial brain volume ratio (WMLV/ICV) was calculated, and its association with dementia risk was estimated using Cox proportional hazard models. Total brain atrophy, defined as the TBV-to-ICV ratio (TBV/ICV), and dementia-related regional brain atrophy defined based on our previous report were calculated. The association between dementia risk and the combined measures of WMLV/ICV and either total brain atrophy or the number of atrophied regions was also tested.

RESULTS

During the follow-up, 113 participants developed dementia. The risks of dementia increased significantly with higher WMLV/ICV levels. In addition, dementia risk increased additively both in participants with higher WMLV/ICV levels and lower TBV/ICV levels and in those with higher WMLV/ICV levels and a higher number of dementia-related brain regional atrophy.

CONCLUSION

The risk of dementia increased significantly with higher WMLV/ICV levels. An additive increment in dementia risk was observed with higher WMLV/ICV levels and lower TBV/ICV levels or a higher number of dementia-related brain regional atrophy, suggesting the importance of prevention or control of cardiovascular risk factors.

The Mediating Roles of Neurobiomarkers in the Relationship Between Education and Late-Life Cognition

BACKGROUND

The mediating roles of neuropathologies and neurovascular damage in the relationship between early-life education and later-life cognitive function are unknown.

OBJECTIVE

To examine whether Alzheimer's and neurovascular biomarkers mediate the relationships between education and cognitive functions.

METHODS

Data were from 537 adults aged 55-94 in the Alzheimer's Disease Neuroimaging Initiative 3. We tested whether the relationships between education (continuous, years) and cognitive function (memory, executive functioning, and language composites) were mediated by neuroimaging biomarkers (hippocampal volumes, cortical gray matter volumes, meta-temporal tau PET standard uptake value ratio, and white matter hyperintensity volumes). Models were adjusted for age, race, sex/gender, cardiovascular history, body mass index, depression, and Apolipoprotein E-ɛ4 status.

RESULTS

Hippocampal volumes and white matter hyperintensities partially mediated the relationships between education and cognitive function across all domains (6.43% to 15.72% mediated). The direct effects of education on each cognitive domain were strong and statistically significant.

CONCLUSIONS

Commonly measured neurobiomarkers only partially mediate the relationships between education and multi-domain cognitive function.

Aerobic exercise training and neurocognitive function in cognitively normal older adults: A one-year randomized controlled trial

BACKGROUND

Current evidence is inconsistent on the benefits of aerobic exercise training for preventing or attenuating age-related cognitive decline in older adults.

OBJECTIVE

To investigate the effects of a 1-year progressive, moderate-to-high intensity aerobic exercise intervention on cognitive function, brain volume, and cortical thickness in sedentary but otherwise healthy older adults.

METHODS

We randomized 73 older adults to a 1-year aerobic exercise or stretching-and-toning (active control) program. The primary outcome was a cognitive composite score calculated from eight neuropsychological tests encompassing inductive reasoning, long-term and working memory, executive function, and processing speed. Secondary outcomes were brain volume and cortical thickness assessed by MRI, and cardiorespiratory fitness measured by peak oxygen uptake (VO2 ).

RESULTS

One-year aerobic exercise increased peak VO2 by ∼10% (p < 0.001) while it did not change with stretching (p = 0.241). Cognitive composite scores increased in both the aerobic and stretching groups (p < 0.001 for time effect), although no group difference was observed. Total brain volume (p < 0.001) and mean cortical thickness (p = 0.001) decreased in both groups over time, while the reduction in hippocampal volume was smaller in the stretching group compared with the aerobic group (p = 0.040 for interaction). Across all participants, improvement in peak VO2 was positively correlated with increases in cognitive composite score (r = 0.282, p = 0.042) and regional cortical thickness at the inferior parietal lobe (p = 0.016).

CONCLUSIONS

One-year aerobic exercise and stretching interventions improved cognitive performance but did not prevent age-related brain volume loss in sedentary healthy older adults. Cardiorespiratory fitness gain was positively correlated with cognitive performance and regional cortical thickness.

Increase in Cerebral Blood Flow After Catheter Ablation of Atrial Fibrillation

BACKGROUND

Recent studies have found that atrial fibrillation (AF) is a risk factor for cognitive impairment. Brain hypoperfusion is hypothesized as an underlying mechanism of cognitive decline in AF patients.

OBJECTIVES

This study sought to assess changes in cerebral blood flow (CBF) and brain volume after catheter ablation of AF.

METHODS

Patients undergoing catheter ablation of AF were enrolled in this prospective study. AF patients being treated with pharmaceuticals alone served as a control group. Brain magnetic resonance imaging was performed before and 6 months after catheter ablation. CBF was assessed by 2-dimensional phase-contrast magnetic resonance angiography. Brain volume and bilateral hippocampal volume were measured using FreeSurfer software.

RESULTS

Of the 57 study patients (age 64 ± 11 years; 45 men; paroxysmal AF: n = 22; nonparoxysmal AF: n = 35), 48 patients were freed from tachyarrhythmia recurrence beyond a 3-month blanking period. Changes in CBF and brain perfusion over 6 months were significantly greater in the study patients than control (CBF: 39.26 vs -34.86 mL; P = 0.01, ANCOVA; brain perfusion: 3.78 vs -3.02 mL/100 mL/min; P = 0.009, ANCOVA), while changes in total brain volume and bilateral hippocampal volume were similar between 2 groups (total brain volume: 2.57 vs -2.15 mL; P = 0.32, ANCOVA; bilateral hippocampal volume: 0.03 vs 0.04 mL; P = 0.8, ANCOVA). Nonparoxysmal AF at baseline was an independent predictor of an increase in CBF of >32.6 mL/min.

CONCLUSIONS

Catheter ablation of AF has favorable effects on CBF, particularly in nonparoxysmal AF. Our results may partially explain the association between cognitive decline and AF.

Alzheimer's disease/dementia-associated brain pathology in aging DPP6-KO mice

We have previously reported that the single transmembrane protein Dipeptidyl Peptidase Like 6 (DPP6) impacts neuronal and synaptic development. DPP6-KO mice are impaired in hippocampal-dependent learning and memory and exhibit smaller brain size. Recently, we have described novel structures in hippocampal area CA1 in aging mice, apparently derived from degenerating presynaptic terminals, that are significantly more prevalent in DPP6-KO mice compared to WT mice of the same age and that these structures were observed earlier in development in DPP6-KO mice. These novel structures appear as clusters of large puncta that colocalize NeuN, synaptophysin, and chromogranin A, and also partially label for MAP2, amyloid β, APP, α-synuclein, and phosphorylated tau, with synapsin-1 and VGluT1 labeling on their periphery. In this current study, using immunofluorescence and electron microscopy, we confirm that both APP and amyloid β are prevalent in these structures; and we show with immunofluorescence the presence of similar structures in humans with Alzheimer's disease. Here we also found evidence that aging DPP6-KO mutants show additional changes related to Alzheimer's disease. We used in vivo MRI to show reduced size of the DPP6-KO brain and hippocampus. Aging DPP6-KO hippocampi contained fewer total neurons and greater neuron death and had diagnostic biomarkers of Alzheimer's disease present including accumulation of amyloid β and APP and increase in expression of hyper-phosphorylated tau. The amyloid β and phosphorylated tau pathologies were associated with neuroinflammation characterized by increases in microglia and astrocytes. And levels of proinflammatory or anti-inflammatory cytokines increased in aging DPP6-KO mice. We finally show that aging DPP6-KO mice display circadian dysfunction, a common symptom of Alzheimer's disease. Together these results indicate that aging DPP6-KO mice show symptoms of enhanced neurodegeneration reminiscent of dementia associated with a novel structure resulting from synapse loss and neuronal death. This study continues our laboratory's work in discerning the function of DPP6 and here provides compelling evidence of a direct role of DPP6 in Alzheimer's disease.

Improving risk indexes for Alzheimer's disease and related dementias for use in midlife

Knowledge of a person’s risk for Alzheimer’s disease and related dementias (ADRDs) is required to triage candidates for preventive interventions, surveillance, and treatment trials. ADRD risk indexes exist for this purpose, but each includes only a subset of known risk factors. Information missing from published indexes could improve risk prediction. In the Dunedin Study of a population-representative New Zealand-based birth cohort followed to midlife (N = 938, 49.5% female), we compared associations of four leading risk indexes with midlife antecedents of ADRD against a novel benchmark index comprised of nearly all known ADRD risk factors, the Dunedin ADRD Risk Benchmark (DunedinARB). Existing indexes included the Cardiovascular Risk Factors, Aging, and Dementia index (CAIDE), LIfestyle for BRAin health index (LIBRA), Australian National University Alzheimer’s Disease Risk Index (ANU-ADRI), and risks selected by the Lancet Commission on Dementia. The Dunedin benchmark was comprised of 48 separate indicators of risk organized into 10 conceptually distinct risk domains. Midlife antecedents of ADRD treated as outcome measures included age-45 measures of brain structural integrity [magnetic resonance imaging-assessed: (i) machine-learning-algorithm-estimated brain age, (ii) log-transformed volume of white matter hyperintensities, and (iii) mean grey matter volume of the hippocampus] and measures of brain functional integrity [(i) objective cognitive function assessed via the Wechsler Adult Intelligence Scale-IV, (ii) subjective problems in everyday cognitive function, and (iii) objective cognitive decline measured as residualized change in cognitive scores from childhood to midlife on matched Weschler Intelligence scales]. All indexes were quantitatively distributed and proved informative about midlife antecedents of ADRD, including algorithm-estimated brain age (β's from 0.16 to 0.22), white matter hyperintensities volume (β's from 0.16 to 0.19), hippocampal volume (β's from −0.08 to −0.11), tested cognitive deficits (β's from −0.36 to −0.49), everyday cognitive problems (β's from 0.14 to 0.38), and longitudinal cognitive decline (β's from −0.18 to −0.26). Existing indexes compared favourably to the comprehensive benchmark in their association with the brain structural integrity measures but were outperformed in their association with the functional integrity measures, particularly subjective cognitive problems and tested cognitive decline. Results indicated that existing indexes could be improved with targeted additions, particularly of measures assessing socioeconomic status, physical and sensory function, epigenetic aging, and subjective overall health. Existing premorbid ADRD risk indexes perform well in identifying linear gradients of risk among members of the general population at midlife, even when they include only a small subset of potential risk factors. They could be improved, however, with targeted additions to more holistically capture the different facets of risk for this multiply determined, age-related disease.

Association between cortisol and aging-related hippocampus volume changes in community-dwelling older adults: a 7-year follow-up study

BACKGROUND

Identifying peripheral biomarkers related to modifiable risk factors to prevent dementia at an early stage will be extremely beneficial. We have been studying how older adults can maintain their mental health and continue to live in a familiar community. The aim of this study is to investigate the association between serum cortisol levels and brain volume among older adults in rural Japan.

METHODS

This was a longitudinal study conducted in Kurokawa-cho, Imari, Saga Prefecture, Japan, among people aged 65 years and above, as reported previously. We conducted a survey twice. The first survey was conducted from October 2009 to March 2011 (Timepoint 1) and the second was conducted from November 2016 to September 2017 (Timepoint 2). Blood samples for serum cortisol levels analysis were collected from participants at Timepoint 1. Serum cortisol levels were measured using the enzyme-linked immunosorbent assay. The participants underwent brain MRI examinations, and Mini-Mental State Examination (MMSE) and Clinical Dementia Rating (CDR) for cognitive function assessment at Timepoint 1 and Timepoint 2. We obtained 70 participants (16 men, mean age 72.69 ± 3.18 years; 54 women, mean age 72.69 ± 4.60 years, at Timepoint 1) for analysis. Correlation analysis was performed between serum cortisol levels at baseline (Timepoint 1) and brain volume (Timepoint 1, Timepoint 2, and Timepoint 1-Timepoint 2 difference) using voxel-based morphometry method.

RESULTS

There was no significant difference in serum cortisol levels between men (72.32 ± 17.30 ng/ml) and women (76.60 ± 21.12 ng/ml) at baseline. Additionally, no effect of blood collection time on cortisol levels was observed in these participants. Small volume correction analysis at the cluster level by applying multiple comparison corrections (family-wise error; P < 0.05) showed a negative correlation between serum cortisol levels (Timepoint 1) and brain volume (Timepoint 2) within the region containing the left hippocampus.

CONCLUSIONS

Serum cortisol levels may serve as a peripheral biomarker of age-related volume changes involving the hippocampus in older adults aged 65 years and above.

Machine learning-based automatic estimation of cortical atrophy using brain computed tomography images

Cortical atrophy is measured clinically according to established visual rating scales based on magnetic resonance imaging (MRI). Although brain MRI is the primary imaging marker for neurodegeneration, computed tomography (CT) is also widely used for the early detection and diagnosis of dementia. However, they are seldom investigated. Therefore, we developed a machine learning algorithm for the automatic estimation of cortical atrophy on brain CT. Brain CT images (259 Alzheimer’s dementia and 55 cognitively normal subjects) were visually rated by three neurologists and used for training. We constructed an algorithm by combining the convolutional neural network and regularized logistic regression (RLR). Model performance was then compared with that of neurologists, and feature importance was measured. RLR provided fast and reliable automatic estimations of frontal atrophy (75.2% accuracy, 93.6% sensitivity, 67.2% specificity, and 0.87 area under the curve [AUC]), posterior atrophy (79.6% accuracy, 87.2% sensitivity, 75.9% specificity, and 0.88 AUC), right medial temporal atrophy (81.2% accuracy, 84.7% sensitivity, 79.6% specificity, and 0.88 AUC), and left medial temporal atrophy (77.7% accuracy, 91.1% sensitivity, 72.3% specificity, and 0.90 AUC). We concluded that RLR-based automatic estimation of brain CT provided a comprehensive rating of atrophy that can potentially support physicians in real clinical settings.

Multimodal magnetic resonance imaging reveals distinct sensitivity of hippocampal subfields in asymptomatic stage of Alzheimer’s disease

While hippocampal atrophy and its regional susceptibility to Alzheimer’s disease (AD) are well reported at late stages of AD, studies of the asymptomatic stage of AD are limited but could elucidate early stage pathophysiology as well as provide predictive biomarkers. In this study, we performed multi-modal magnetic resonance imaging (MRI) to estimate morphometry, functional connectivity, and tissue microstructure of hippocampal subfields in cognitively normal adults including those with asymptomatic AD. High-resolution resting-state functional, diffusion and structural MRI, cerebral spinal fluid (CSF), and neuropsychological evaluations were performed in healthy young adults (HY: n = 40) and healthy older adults with negative (HO−: n = 47) and positive (HO+ : n = 25) CSF biomarkers of AD. Morphometry, functional connectivity, and tissue microstructure were estimated from the structural, functional, and diffusion MRI images, respectively. Our results indicated that normal aging affected morphometry, connectivity, and microstructure in all hippocampal subfields, while the subiculum and CA1-3 demonstrated the greatest sensitivity to asymptomatic AD pathology. Tau, rather than amyloid-β, was closely associated with imaging-derived synaptic and microstructural measures. Microstructural metrics were significantly associated with neuropsychological assessments. These findings suggest that the subiculum and CA1-3 are the most vulnerable in asymptomatic AD and tau level is driving these early changes.

Hippocampal avoidance prophylactic cranial irradiation (HA-PCI) for small cell lung cancer reduces hippocampal atrophy compared to conventional PCI

BACKGROUND

Reducing radiation dose to the hippocampus with hippocampal avoidance prophylactic cranial irradiation (HA-PCI) is proposed to prevent cognitive decline. It has, however, not been investigated whether hippocampal atrophy is actually mitigated by this approach. Here, we determined whether HA-PCI reduces hippocampal atrophy. Additionally, we evaluated neurotoxicity of (HA-)PCI to other brain regions. Finally, we evaluated associations of hippocampal atrophy and brain neurotoxicity with memory decline.

METHODS

High-quality research MRI scans were acquired in the multicenter, randomized phase 3 trial NCT01780675. Hippocampal atrophy was evaluated for 4 months (57 HA-PCI patients and 46 PCI patients) and 12 months (28 HA-PCI patients and 27 PCI patients) after (HA-)PCI. We additionally studied multimodal indices of brain injury. Memory was assessed with the Hopkins Verbal Learning Test-Revised (HVLT-R).

RESULTS

HA-PCI reduced hippocampal atrophy at 4 months (1.8% for HA-PCI and 3.0% for PCI) and at 12 months (3.0% for HA-PCI and 5.8% for PCI). Both HA-PCI and PCI were associated with considerable reductions in gray matter and normal-appearing white matter, increases in white matter hyperintensities, and brain aging. There were no significant associations between hippocampal atrophy and memory.

CONCLUSIONS

HA-PCI reduces hippocampal atrophy at 4 and 12 months compared to regular PCI. Both types of radiotherapy are associated with considerable brain injury. We did not find evidence for excessive brain injury after HA-PCI relative to PCI. Hippocampal atrophy was not associated with memory decline in this population as measured with HVLT-R. The usefulness of HA-PCI is still subject to debate.

Stress-Induced Depression and Alzheimer's Disease: Focus on Astrocytes

Neurodegenerative diseases and depression are multifactorial disorders with a complex and poorly understood physiopathology. Astrocytes play a key role in the functioning of neurons in norm and pathology. Stress is an important factor for the development of brain disorders. Here, we review data on the effects of stress on astrocyte function and evidence of the involvement of astrocyte dysfunction in depression and Alzheimer's disease (AD). Stressful life events are an important risk factor for depression; meanwhile, depression is an important risk factor for AD. Clinical data indicate atrophic changes in the same areas of the brain, the hippocampus and prefrontal cortex (PFC), in both pathologies. These brain regions play a key role in regulating the stress response and are most vulnerable to the action of glucocorticoids. PFC astrocytes are critically involved in the development of depression. Stress alters astrocyte function and can result in pyroptotic death of not only neurons, but also astrocytes. BDNF-TrkB system not only plays a key role in depression and in normalizing the stress response, but also appears to be an important factor in the functioning of astrocytes. Astrocytes, being a target for stress and glucocorticoids, are a promising target for the treatment of stress-dependent depression and AD.

AD Resemblance Atrophy Index of Brain Magnetic Resonance Imaging in Predicting the Progression of Mild Cognitive Impairment Carrying Apolipoprotein E-ε4 Allele

Background and Objective

Early identification is important for timely Alzheimer’s disease (AD) treatment. Apolipoprotein E ε4 allele (APOE-ε4) is an important genetic risk factor for sporadic AD. The AD-Resemblance Atrophy Index (RAI)—a structural magnetic resonance imaging-derived composite index—was found to predict the risk of progression from mild cognitive impairment (MCI) to AD. Therefore, we investigated whether the AD-RAI can predict cognitive decline and progression to AD in patients with MCI carrying APOE ε4.

Methods

We included 733 participants with MCI from the Alzheimer’s Disease Neuroimaging Initiative Database (ADNI). Their APOE genotypes, cognitive performance, and levels of AD-RAI were assessed at baseline and follow-up. Linear regression models were used to test the correlations between the AD-RAI and baseline cognitive measures, and linear mixed models with random intercepts and slopes were applied to investigate whether AD-RAI and APOE-ε4 can predict the level of cognitive decline. Cox proportional risk regression models were used to test the association of AD-RAI and APOE status with the progression from MCI to AD.

Results

The baseline AD-RAI was higher in the MCI converted to AD group than in the MCI stable group (P < 0.001). The AD-RAI was significantly correlated with cognition, and had a synergistic effect with APOE-ε4 to predict the rate of cognitive decline. The AD-RAI predicted the risk and timing of MCI progression to AD. Based on the MCI population carrying APOE-ε4, the median time to progression from MCI to AD was 24 months if the AD-RAI > 0.5, while the median time to progression from MCI to AD was 96 months for patients with an AD-RAI ≤ 0.5.

Conclusion

The AD-RAI can predict the risk of progression to AD in people with MCI carrying APOE ε4, is strongly correlated with cognition, and can predict cognitive decline.

The impact of Alzheimer's disease susceptibility loci on lateral ventricular surface morphology in older adults

The enlargement of ventricular volume is a general trend in the elderly, especially in patients with Alzheimer's disease (AD). Multiple susceptibility loci have been reported to have an increased risk for AD and the morphology of brain structures are affected by the variations in the risk loci. Therefore, we hypothesized that genes contributed significantly to the ventricular surface, and the changes of ventricular surface were associated with the impairment of cognitive functions. After the quality controls (QC) and genotyping, a lateral ventricular segmentation method was employed to obtain the surface features of lateral ventricle. We evaluated the influence of 18 selected AD susceptibility loci on both volume and surface morphology across 410 subjects from Alzheimer's Disease Neuroimaging Initiative (ADNI). Correlations were conducted between radial distance (RD) and Montreal Cognitive Assessment (MoCA) subscales. Only the C allele at the rs744373 loci in BIN1 gene significantly accelerated the atrophy of lateral ventricle, including the anterior horn, body, and temporal horn of left lateral ventricle. No significant effect on lateral ventricle was found at other loci. Our results revealed that most regions of the bilateral ventricular surface were significantly negatively correlated with cognitive scores, particularly in delayed recall. Besides, small areas of surface were negatively correlated with language, orientation, and visuospatial scores. Together, our results indicated that the genetic variation affected the localized areas of lateral ventricular surface, and supported that lateral ventricle was an important brain structure associated with cognition in the elderly.

Mnemonic scaffolds vary in effectiveness for serial recall

Memory champions remember vast amounts of information in order and at first encounter by associating each study item to an anchor within a scaffold - a pre-learned, structured memory. The scaffold provides direct-access retrieval cues. Dominated by the familiar-route scaffold (Method of Loci), researchers have little insight into what characteristics of scaffolds make them effective, nor whether individual differences might play a role. We compared participant-generated mnemonic scaffolds: (a) familiar routes (Loci), (b) autobiographical stories (Story), (c) parts of the human body (Body), and (d) routine activities (Routine Activity). Loci, Body, and Story Scaffolds benefited serial recall over Control (no scaffold). The Body and Loci Scaffold were equally superior to the other scaffolds. Measures of visual imagery aptitude and vividness and body responsiveness did not predict accuracy. A second experiment tested whether embodiment could be responsible for the high level of effectiveness of the Body Scaffold; this was not supported. In short, mnemonic scaffolds are not equally effective and embodied cognition may not directly contribute to memory success. The Body Scaffold may be a strong alternative to the Method of Loci and may enhance learning for most learners, including those who do not find the Method of Loci useful.

MRI-visible enlarged perivascular spaces: imaging marker to predict cognitive impairment in older chronic insomnia patients

OBJECTIVE

Perivascular spaces (PVS), components of the glymphatic system in the brain, have been known to be important conduits for clearing metabolic waste, and this process mainly increases during sleep. Sleep disruption might result in PVS dysfunction and cognitive impairment. In this study, we aim to explore whether MRI-visible enlarged perivascular spaces (EPVS) could be imaging markers to predict cognitive impairment in chronic insomnia patients.

METHOD

We obtained data from 156 patients with chronic insomnia and 79 age-matched healthy individuals. Using T2-weighted MRI images, visible EPVS in various brain regions were measured and analyzed. The associations between EPVS numbers and cerebrospinal fluid (CSF) β-amyloid 42 (Aβ42), total tau (t-tau), and phosphorylated tau (p-tau) level in chronic insomnia patients were evaluated.

RESULT

Our results showed that MRI-visible EPVS in the frontal cortex, centrum semiovale, basal ganglia, and hippocampus of chronic insomnia patients with impaired cognition (ICG) significantly increased than that in normal cognition (NCG) patients. The increased MRI-visible EPVS in the frontal cortex, centrum semiovale, and basal ganglia were also associated with the increased CSF Aβ42, t-tau, and p-tau level in ICG patients. MRI-visible EPVS in the basal ganglia and centrum semiovale had high sensitivity and specificity in distinguishing ICG chronic insomnia patients from those with NCG.

CONCLUSION

Our study indicated that MRI-visible EPVS in the basal ganglia and centrum semiovale might be valuable imaging markers to predict cognitive impairment in chronic insomnia patients. It will be meaningful to discern those cognitive decline patients in preclinical stage and take some measures to prevent disease progression.

KEY POINTS

• Increased MRI-visible EPVS were associated with the increased CSF Aβ42, t-tau, and p-tau level in older chronic insomnia patients with impaired cognition.

Diagnostic Utility of Hippocampal Volumetric Data in a Memory Disorder Clinic Setting

BACKGROUND

Hippocampal volumetric data are widely used in research but are rarely examined in clinical populations in regard to aiding diagnosis or correlating with objective memory test scores.

OBJECTIVE

To replicate and expand on the few prior clinical examinations of the utility of hippocampal volumetric data. We evaluated MRI volumetric data to determine (a) the degree of hippocampal loss across diagnostic groups compared with a cognitively intact group, (b) if total or lateralized hippocampal volumes predict diagnostic group membership, and (c) how total and lateralized volumes correlate with memory tests.

METHOD

We retrospectively examined hippocampal volumetric data and memory test scores for 294 individuals referred to a memory clinic.

RESULTS

Individuals with mild cognitive impairment or Alzheimer disease had smaller hippocampal volumes compared with cognitively intact individuals. The raw and normalized total and lateralized hippocampal volumes were essentially equal for predicting diagnostic group membership, and notably low hippocampal volumes evidenced greater specificity than sensitivity. All of the volumetric data correlated with the memory test scores, with the total and left hippocampal volumes accounting for the slightly more variance in the diagnostic groups.

CONCLUSION

The diagnostic groups exhibited hippocampal volume loss, which can be a potential biomarker for neurodegenerative disease in clinical practice. However, solely using hippocampal volumetric data to predict diagnostic group membership or memory test failure was not supported. While extreme hippocampal volume loss was rare in the cognitively intact group, the sensitivity of these volumetric data suggests a need for supplementation by other tools when making a diagnosis.

Multiple-region grey matter atrophy as a predictor for the development of dementia in a community: the Hisayama Study

OBJECTIVE

To assess the association of regional grey matter atrophy with dementia risk in a general older Japanese population.

METHODS

We followed 1158 dementia-free Japanese residents aged ≥65 years for 5.0 years. Regional grey matter volume (GMV) at baseline was estimated by applying voxel-based morphometry methods. The GMV-to-total brain volume ratio (GMV/TBV) was calculated, and its association with dementia risk was estimated using Cox proportional hazard models. We assessed whether the predictive ability of a model based on known dementia risk factors could be improved by adding the total number of regions with grey matter atrophy among dementia-related brain regions, where the cut-off value for grey matter atrophy in each region was determined by receiver operating characteristic curves.

RESULTS

During the follow-up, 113 participants developed all-cause dementia, including 83 with Alzheimer's disease (AD). Lower GMV/TBV of the medial temporal lobe, insula, hippocampus and amygdala were significantly/marginally associated with higher risk of all-cause dementia and AD (all p for trend ≤0.08). The risks of all-cause dementia and AD increased significantly with increasing total number of brain regions exhibiting grey matter atrophy (both p for trend <0.01). Adding the total number of regions with grey matter atrophy into a model consisting of known risk factors significantly improved the predictive ability for AD (Harrell's c-statistics: 0.765-0.802; p=0.02).

CONCLUSIONS

Our findings suggest that the total number of regions with grey matter atrophy among the medial temporal lobe, insula, hippocampus and amygdala is a significant predictor for developing dementia, especially AD, in the general older population.

Intracranial internal carotid artery calcification is not predictive of future cognitive decline

Background

Intracranial internal carotid artery (ICA) calcification is a common incidental finding in non-contrast head CT. We evaluated the predictive value of ICAC (ICAC) for future risk of cognitive decline and compared the results with conventional imaging biomarkers of dementia.

Methods

In a retrospective observational cohort, we included 230 participants with a PET-CT scan within 18 months of a baseline clinical assessment and longitudinal imaging assessments. Intracranial ICAC was quantified on baseline CT scans using the Agatson calcium score, and the association between baseline ICA calcium scores and the risk of conversion from a CDR of zero in baseline to a persistent CDR > 0 at any follow-up visit, as well as longitudinal changes in cognitive scores, were evaluated through linear and mixed regression models. We also evaluated the association of conventional imaging biomarkers of dementia with longitudinal changes in cognitive scores and a potential indirect effect of ICAC on cognition through these biomarkers.

Results

Baseline ICA calcium score could not distinguish participants who converted to CDR > 0. ICA calcium score was also unable to predict longitudinal changes in cognitive scores, imaging biomarkers of small vessel disease such as white matter hyperintensities (WMH) volume, or AD such as hippocampal volume, AD cortical signature thickness, and amyloid burden. Severity of intracranial ICAC increased with age and in men. Higher WMH volume and amyloid burden as well as lower hippocampal volume and AD cortical signature thickness at baseline predicted lower Mini-Mental State Exam scores at longitudinal follow-up. Baseline ICAC was indirectly associated with longitudinal cognitive decline, fully mediated through WMH volume.

Conclusions

In elderly and preclinical AD populations, atherosclerosis of large intracranial vessels as demonstrated through ICAC is not directly associated with a future risk of cognitive impairment, or progression of imaging biomarkers of AD or small vessel disease.

Cognitive Aging and the Promise of Physical Activity

Is the field of cognitive aging irretrievably concerned with decline and deficits, or is it shifting to emphasize the hope of preservation and enhancement of cognitive function in late life? A fragment of an answer comes from research attempting to understand the reasons for individual variability in the extent and rate of cognitive decline. This body of work has created a sense of optimism based on evidence that there are some health behaviors that amplify cognitive performance or mitigate the rate of age-related cognitive decline. In this context, we discuss the role of physical activity on neurocognitive function in late adulthood and summarize how it can be conceptualized as a constructive approach both for the maintenance of cognitive function and as a therapeutic for enhancing or optimizing cognitive function in late life. In this way, physical activity research can be used to shape perceptions of cognitive aging. Expected final online publication date for the Annual Review of Clinical Psychology, Volume 18 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Head impact exposure, grey matter volume, and moderating effects of estimated IQ and educational attainment in former athletes at midlife

Repetitive head impact (RHI) exposure has been associated with differences in brain structure among younger active athletes, most often within the hippocampus. Studies of former athletes at early-midlife are limited. We investigated the association between RHI exposure and grey matter structure, as well as moderating factors, among former athletes in early-midlife. Former collegiate football players (N=55; age=37.9+1.5 years) completed magnetic resonance imaging to quantify grey matter morphometry and extensive structured interviews of RHI history (Head Impact Exposure Estimate). Linear regression models tested the association between RHI exposure and GM structures of interest. Interactions were tested for moderators: two estimates of IQ (single word reading and picture vocabulary) and education history. Greater RHI exposure was associated with smaller hippocampal volume, β=-.36, p=.004. Conversely, RHI exposure was not significantly associated with other GM outcomes ps>.05. Education history significantly moderated the association between RHI exposure and hippocampal volume, β=.69, p=.047. Among those with a bachelor's degree, greater RHI exposure was significantly associated with smaller hippocampal volumes, β=-.58, p<.001. For those with graduate/professional degrees, the association between RHI and hippocampal volume was not significant, β=-.33, p=.134. Consistent with studies involving younger, active athletes, smaller hippocampal volumes were selectively associated with greater RHI exposure among former collegiate football players at midlife. This relationship was moderated by higher levels of education. Future longitudinal studies are needed to investigate the course of possible changes that can occur between early-midlife to older ages, as well as the continued protective effect of education and other potential influential factors.

Cortisol Reactivity to a physical stressor in Patients with Depression and Alzheimer's disease

Some prevalent mental disorders in the elderly, such as Alzheimer's disease (AD) and major depression disorder (MDD), are associated with chronic stress and consequently with possible dysregulation of hypothalamic–pituitary–adrenal (HPA) axis and cortisol levels in basal conditions or in the reactivity of an acute stressor. However, evidence of cortisol behavior after a physical stressor in patients with AD and MDD is scarce.

Inter- and Intra-Scanner Variability of Automated Brain Volumetry on Three Magnetic Resonance Imaging Systems in Alzheimer's Disease and Controls

Magnetic Resonance Imaging (MRI) has become part of the clinical routine for diagnosing neurodegenerative disorders. Since acquisitions are performed at multiple centers using multiple imaging systems, detailed analysis of brain volumetry differences between MRI systems and scan-rescan acquisitions can provide valuable information to correct for different MRI scanner effects in multi-center longitudinal studies. To this end, five healthy controls and five patients belonging to various stages of the AD continuum underwent brain MRI acquisitions on three different MRI systems (Philips Achieva dStream 1.5T, Philips Ingenia 3T, and GE Discovery MR750w 3T) with harmonized scan parameters. Each participant underwent two subsequent MRI scans per imaging system, repeated on three different MRI systems within 2 h. Brain volumes computed by icobrain dm (v5.0) were analyzed using absolute and percentual volume differences, Dice similarity (DSC) and intraclass correlation coefficients, and coefficients of variation (CV). Harmonized scans obtained with different scanners of the same manufacturer had a measurement error closer to the intra-scanner performance. The gap between intra- and inter-scanner comparisons grew when comparing scans from different manufacturers. This was observed at image level (image contrast, similarity, and geometry) and translated into a higher variability of automated brain volumetry. Mixed effects modeling revealed a significant effect of scanner type on some brain volumes, and of the scanner combination on DSC. The study concluded a good intra- and inter-scanner reproducibility, as illustrated by an average intra-scanner (inter-scanner) CV below 2% (5%) and an excellent overlap of brain structure segmentation (mean DSC > 0.88).

Hemodynamic and structural brain measures in high and low sedentary older adults

Due to its cardiovascular effects sedentary behaviour might impact cerebrovascular function in the long term, affecting cerebrovascular regulatory mechanisms and perfusion levels. Consequently this could underly potential structural brain abnormalities associated with cognitive decline. We therefore assessed the association between sedentary behaviour and brain measures of cerebrovascular perfusion and structural abnormalities in community-dwelling older adults. Using accelerometery (GENEActiv) data from The Irish Longitudinal Study on Ageing (TILDA) we categorised individuals by low- and high-sedentary behaviour (≤8 vs >8 hours/day). We examined prefrontal haemoglobin oxygenation levels using Near-Infrared Spectroscopy during rest and after an orthostatic challenge in 718 individuals (66 ± 8 years, 52% female). Global grey matter cerebral blood flow, total grey and white matter volume, total and subfield hippocampal volumes, cortical thickness, and white matter hyperintensities were measured using arterial spin labelling, T1, and FLAIR MRI in 86 individuals (72 ± 6 years, 55% female). While no differences in prefrontal or global cerebral hemodynamics were found between groups, high-sedentary individuals showed lower hippocampal volumes and increased white matter hyperintensities compared to their low-sedentary counterparts. Since these structural cerebral abnormalities are associated with cognitive decline and Alzheimer's disease, future work exploring the causal pathways underlying these differences is needed.

Synergistic Effects of APOE and CLU May Increase the Risk of Alzheimer's Disease: Acceleration of Atrophy in the Volumes and Shapes of the Hippocampus and Amygdala

BACKGROUND

The volume loss of the hippocampus and amygdala in non-demented individuals has been reported to increase the risk of developing Alzheimer's disease (AD). Many neuroimaging genetics studies mainly focused on the individual effects of APOE and CLU on neuroimaging to understand their neural mechanisms, whereas their synergistic effects have been rarely studied.

OBJECTIVE

To assess whether APOE and CLU have synergetic effects, we investigated the epistatic interaction and combined effects of the two genetic variants on morphological degeneration of hippocampus and amygdala in the non-demented elderly at baseline and 2-year follow-up.

METHODS

Besides the widely-used volume indicator, the surface-based morphometry method was also adopted in this study to evaluate shape alterations.

RESULTS

Our results showed a synergistic effect of homozygosity for the CLU risk allele C in rs11136000 and APOEɛ4 on the hippocampal and amygdalar volumes during a 2-year follow-up. Moreover, the combined effects of APOEɛ4 and CLU C were stronger than either of the individual effects in the atrophy progress of the amygdala.

CONCLUSION

These findings indicate that brain morphological changes are caused by more than one gene variant, which may help us to better understand the complex endogenous mechanism of AD.

Hippocampus-Avoidance Whole-Brain Radiation Therapy Is Efficient in the Long-Term Preservation of Hippocampal Volume

Background and Purpose

With improved life expectancy, preventing neurocognitive decline after cerebral radiotherapy is gaining more importance. Hippocampal damage has been considered the main culprit for cognitive deficits following conventional whole-brain radiation therapy (WBRT). Here, we aimed to determine to which extent hippocampus-avoidance WBRT (HA-WBRT) can prevent hippocampal atrophy compared to conventional WBRT.

Methods and Materials

Thirty-five HA-WBRT and 48 WBRT patients were retrospectively selected, comprising a total of 544 contrast-enhanced T1-weighted magnetic resonance imaging studies, longitudinally acquired within 24 months before and 48 months after radiotherapy. HA-WBRT patients were treated analogously to the ongoing HIPPORAD-trial (DRKS00004598) protocol with 30 Gy in 12 fractions and dose to 98% of the hippocampus ≤ 9 Gy and to 2% ≤ 17 Gy. WBRT was mainly performed with 35 Gy in 14 fractions or 30 Gy in 10 fractions. Anatomical images were segmented and the hippocampal volume was quantified using the Computational Anatomy Toolbox (CAT), including neuroradiological expert review of the segmentations.

Results

After statistically controlling for confounding variables such as age, gender, and total intracranial volume, hippocampal atrophy was found after both WBRT and HA-WBRT (p < 10^-6). However, hippocampal decline across time following HA-WBRT was approximately three times lower than following conventional WBRT (p < 10^-6), with an average atrophy of 3.1% versus 8.5% in the first 2 years after radiation therapy, respectively.

Conclusion

HA-WBRT is a therapeutic option for patients with multiple brain metastases, which can effectively and durably minimize hippocampal atrophy compared to conventional WBRT.

The effect of body fatness on regional brain imaging markers and cognitive function in healthy elderly mediated by impaired glucose metabolism

Brain atrophy is related to vascular risk factors and can increase cognitive dysfunction risk. This community-based, cross-sectional study investigated whether glucose metabolic disorders due to body fatness are linked to regional changes in brain structure and a decline in neuropsychological function in cognitively healthy older adults. From 2016 to 2019, 429 participants underwent measurements for cortical thickness and subcortical volume using 3 T magnetic resonance imaging and for cognitive function using the neuropsychological screening battery. The effects of body fatness mediated by impaired glucose metabolism on neuroimaging markers and cognitive function was investigated using partial least square structural equation modeling. Total grey matter volume (β = -0.020; bias-corrected (BC) 95% confidence interval (CI) = -0.047 to -0.006), frontal (β = -0.029; BC 95% CI = -0.063 to -0.005) and temporal (β = -0.022; BC 95% CI = -0.051 to -0.004) lobe cortical thickness, and hippocampal volume (β = -0.029; BC 95% CI = -0.058 to -0.008) were indirectly related to body fatness. Further, frontal/temporal lobe thinning was associated with recognition memory (β = -0.005; BC 95% CI = -0.012 to -0.001/β = -0.005; BC 95% CI = -0.013 to -0.001) and delayed recall for visual information (β = -0.005; BC 95% CI = -0.013 to -0.001/β = -0.005; BC 95% CI = -0.013 to -0.001). Additionally, the smaller the hippocampal volume, the lower the score in recognition memory (β = -0.005; BC 95% CI = -0.012 to -0.001), delayed recall for visual information (β = -0.005; BC 95% CI = -0.012 to -0.001), and verbal learning (β = -0.008; BC 95% CI = -0.017 to -0.002). Our findings indicate that impaired glucose metabolism caused by excess body fatness affects memory decline as well as regional grey matter atrophy in elderly individuals with no neurological disease.

Differences in structural and functional default mode network connectivity in amyloid positive mild cognitive impairment: a longitudinal study

PURPOSE

Default mode network (DMN) has emerged as a potential biomarker of Alzheimer's disease (AD); however, it is not clear whether it can differentiate amnestic mild cognitive impairment with altered amyloid (aMCI-Aβ +) who will evolve to AD. We evaluated if structural and functional connectivity (FC), hippocampal volumes (HV), and cerebrospinal fluid biomarkers (CSF-Aβ₄₂, p-Tau, and t-Tau) can differentiate aMCI-Aβ + converters from non-converters.

METHODS

Forty-eight individuals (18 normal controls and 30 aMCI subjects in the AD continuum - with altered Aβ₄₂ in the CSF) were followed up for an average of 13 months. We used MultiAtlas, UF²C, and Freesurfer software to evaluate diffusion tensor imaging, FC, and HV, respectively, INNOTEST® kits to measure CSF proteins, and neuropsychological tests. Besides, we performed different MANOVAs with further univariate analyses to differentiate groups.

RESULTS

During follow-up, 8/30 aMCI-Aβ + converted (26.6%) to AD dementia. There were no differences in multivariate analysis between groups in CSF biomarkers (p = 0.092) or at DMN functional connectivity (p = 0.814). aMCI-Aβ + converters had smaller right HV than controls (p = 0.013), and greater right cingulum parahippocampal bundle radial diffusivity than controls (p < 0.001) and non-converters (p = 0.036).

CONCLUSION

In this exploratory study, structural, but not functional, DMN connectivity alterations may differentiate aMCI-Aβ + subjects who converted to AD dementia.

Risk of early-onset dementia among persons with tinnitus: a retrospective case-control study

Higher rates of poor cognitive performance are known to prevail among persons with tinnitus in all age groups. However, no study has explored the association between tinnitus and early-onset dementia. We hypothesize that tinnitus may precede or occur concurrently with subclinical or early onset dementia in adults younger than 65 years of age. This case–control study used data from the Taiwan National Health Insurance Research Database, identifying 1308 patients with early-onset dementia (dementia diagnosed before 65 years of age) and 1308 matched controls. We used multivariable logistic regressions to estimate odds ratios (ORs) for prior tinnitus among patients with dementia versus controls. Among total 2616 sample participants, the prevalence of prior tinnitus was 18%, 21.5% among cases and 14.5% among controls (p < 0.001). Multivariable logistic regression showed and adjusted OR for prior tinnitus of 1.6 for cases versus controls (95% CI: 1.3 ~ 2.0). After adjusting for sociodemographic characteristics and medical co-morbidities, patients with early-onset dementia had a 67% higher likelihood of having prior tinnitus (OR = 1.628; 95% CI = 1.321–2.006). Our findings showed that pre-existing tinnitus was associated with a 68% increased risk of developing early-onset dementia among young and middle-aged adults. The results call for greater awareness of tinnitus as a potential harbinger of future dementia in this population.

Altered hippocampal functional connectivity patterns in patients with cognitive impairments following ischaemic stroke: A resting-state fMRI study

BACKGROUND

Ischemic stroke with cognitive impairment is a considerable risk factor for developing dementia. Identifying imaging markers of cognitive impairment following ischemic stroke will help to develop prevention strategies against post-stroke dementia.

METHODS

We investigated the hippocampal functional connectivity (FC) pattern following ischemic stroke, using resting-state fMRI (rs-fMRI). Thirty-three cognitively impaired patients after ischemic stroke and sixteen age-matched controls with no known history of neurological disorder were recruited for the study. No patient had a direct ischaemic insult to hippocampus on the examination of brain imaging. Seven subfields of hippocampus were used as seeds region for FC analyses.

RESULTS

Across all hippocampal subfields, FC with the inferior parietal lobule was reduced in stroke patients as compared with healthy controls. This decreased FC included both supramarginal gyrus and angular gyrus. The FC of hippocampal subfields with cerebellum was increased. Importantly, the degree of the altered FC between hippocampal subfields and inferior parietal lobule was associated with their impaired memory function.

CONCLUSION

Our results demonstrated that decreased hippocampal-inferior parietal lobule connectivity was associated with cognitive impairment in patients with ischemic stroke. These findings provide novel insights into the role of hippocampus in cognitive impairment following ischemic stroke.

Impact of Mesial Temporal Lobe Resection on Brain Structure in Medically Refractory Epilepsy

OBJECTIVE

Surgical resection can decrease seizure frequency in medically intractable temporal lobe epilepsy. However, the functional and structural consequences of this intervention on brain circuitry are poorly understood. We investigated structural changes that occur in brain circuits after mesial temporal lobe resection for refractory epilepsy. Specifically, we used neuroimaging techniques to evaluate changes in 1) contralesional hippocampal and bilateral mammillary body volume and 2) brain-wide cortical thickness.

METHODS

Serial T1-weighted brain magnetic resonance images were acquired before and after surgery (1.6 ± 0.5 year interval) in 21 patients with temporal lobe epilepsy (9 women, 12 men; mean age, 39.4 ± 11.5 years) who had undergone unilateral temporal lobe resection (14 anterior temporal lobectomy; 7 selective amygdalohippocampectomy). Blinded manual segmentation of the unresected hippocampal formation and bilateral mammillary bodies was performed using the Pruessner and Copenhaver protocols, respectively. Brain-wide cortical thickness estimates were computed using the CIVET pipeline.

RESULTS

Surgical resection was associated with a 5% reduction in contralesional hippocampal volume (P < 0.01) and a 9.5% reduction in mammillary body volume (P = 0.03). In addition, significant changes in cortical thickness were observed in contralesional anterior and middle cingulate gyrus and insula (P_{false discovery rate} < 0.01) as well as in other temporal, frontal, and occipital regions (P_{false discovery rate} < 0.05). Postoperative verbal memory function was significantly associated with cortical thickness change in contralesional inferior temporal gyrus (R² = 0.39; P = 0.03).

CONCLUSIONS

These results indicate that mesial temporal lobe resection is associated with both volume loss in spared Papez circuitry and changes in cortical thickness across the brain.

MRI-based Alzheimer's disease-resemblance atrophy index in the detection of preclinical and prodromal Alzheimer's disease

Alzheimer's Disease-resemblance atrophy index (AD-RAI) is an MRI-based machine learning derived biomarker that was developed to reflect the characteristic brain atrophy associated with AD. Recent study showed that AD-RAI (≥0.5) had the best performance in predicting conversion from mild cognitive impairment (MCI) to dementia and from cognitively unimpaired (CU) to MCI. We aimed to validate the performance of AD-RAI in detecting preclinical and prodromal AD. We recruited 128 subjects (MCI=50, CU=78) from two cohorts: CU-SEEDS and ADNI. Amyloid (A+) and tau (T+) status were confirmed by PET (¹¹C-PIB, ¹⁸F-T807) or CSF analysis. We investigated the performance of AD-RAI in detecting preclinical and prodromal AD (i.e. A+T+) among MCI and CU subjects and compared its performance with that of hippocampal measures. AD-RAI achieved the best metrics among all subjects (sensitivity 0.74, specificity 0.91, accuracy 85.94%) and among MCI subjects (sensitivity 0.92, specificity 0.81, accuracy 86.00%) in detecting A+T+ subjects over other measures. Among CU subjects, AD-RAI yielded the best specificity (0.95) and accuracy (85.90%) over other measures, while hippocampal volume achieved a higher sensitivity (0.73) than AD-RAI (0.47) in detecting preclinical AD. These results showed the potential of AD-RAI in the detection of early AD, in particular at the prodromal stage.

Predicting future cognitive decline with hyperbolic stochastic coding

Hyperbolic geometry has been successfully applied in modeling brain cortical and subcortical surfaces with general topological structures. However, such approaches, similar to other surface-based brain morphology analysis methods, usually generate high dimensional features. It limits their statistical power in cognitive decline prediction research, especially in datasets with limited subject numbers. To address the above limitation, we propose a novel framework termed as hyperbolic stochastic coding (HSC). We first compute diffeomorphic maps between general topological surfaces by mapping them to a canonical hyperbolic parameter space with consistent boundary conditions and extracts critical shape features. Secondly, in the hyperbolic parameter space, we introduce a farthest point sampling with breadth-first search method to obtain ring-shaped patches. Thirdly, stochastic coordinate coding and max-pooling algorithms are adopted for feature dimension reduction. We further validate the proposed system by comparing its classification accuracy with some other methods on two brain imaging datasets for Alzheimer's disease (AD) progression studies. Our preliminary experimental results show that our algorithm achieves superior results on various classification tasks. Our work may enrich surface-based brain imaging research tools and potentially result in a diagnostic and prognostic indicator to be useful in individualized treatment strategies.