White matter alterations in early-stage Alzheimer's disease: A tract-specific study

Exploring Radial Asymmetry in MR Diffusion Tensor Imaging and Its Impact on the Interpretation of Glymphatic Mechanisms

BACKGROUND

Diffusion imaging holds great potential for the non-invasive assessment of the glymphatic system in humans. One technique, diffusion tensor imaging along the perivascular space (DTI-ALPS), has introduced the ALPS-index, a novel metric for evaluating diffusivity within the perivascular space. However, it still needs to be established whether the observed reduction in the ALPS-index reflects axonal changes, a common occurrence in neurodegenerative diseases.

PURPOSE

To determine whether axonal alterations can influence change in the ALPS-index.

STUDY TYPE

Retrospective.

POPULATION

100 participants (78 cognitively normal and 22 with mild cognitive impairments) aged 50-90 years old.

FIELD STRENGTH/SEQUENCE

3T; diffusion-weighted single-shot spin-echo echo-planar imaging sequence, T1-weighted images (MP-RAGE).

ASSESSMENT

The ratio of two radial diffusivities of the diffusion tensor (i.e., λ2/λ3) across major white matter tracts with distinct venous/perivenous anatomy that fulfill (ALPS-tracts) and do not fulfill (control tracts) ALPS-index anatomical assumptions were analyzed.

STATISTICAL TESTS

To investigate the correlation between λ2/λ3 and age/cognitive function (RAVLT) while accounting for the effect of age, linear regression was implemented to remove the age effect from each variable. Pearson correlation analysis was conducted on the residuals obtained from the linear regression. Statistical significance was set at p < 0.05.

RESULTS

λ2 was ~50% higher than λ3 and demonstrated a consistent pattern across both ALPS and control tracts. Additionally, in both ALPS and control tracts a reduction in the λ2/λ3 ratio was observed with advancing age (r = -0.39, r = -0.29, association and forceps tract, respectively) and decreased memory function (r = 0.24, r = 0.27, association and forceps tract, respectively).

DATA CONCLUSIONS

The results unveil a widespread radial asymmetry of white matter tracts that changes with aging and neurodegeration. These findings highlight that the ALPS-index may not solely reflect changes in the diffusivity of the perivascular space but may also incorporate axonal contributions.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Fixel-based and tensor-derived white matter abnormalities in relation to memory impairment and neurocognitive disorders

Aging-related neurocognitive disorders, including Alzheimer's disease (AD) and mild cognitive impairment (MCI), have been characterised by altered brain white matter (WM), relying widely on diffusion tensor imaging (DTI). DTI's limited accuracy in assessing crossing fibres prompted novel methods that distinguish fibres crossing through same voxel-spaces, such as fixel-based analysis (FBA), highlighting subtle macrostructural and microstructural alterations in AD and MCI. We examined the FBA and DTI's specificity in determining WM features relevant to memory in the neurocognitive aging spectrum. Diffusion-weighted images were analysed in 560 participants with various neurocognitive diagnoses from the Alzheimer's Disease Neuroimaging Initiative (F:297; mean age: 73.2 ± 8). Verbal memory was measured in 488 participants using the Rey Auditory Verbal Learning Test. FBA-derived measures of fibre density (FD), fibre-bundle cross-section (FC), and their combination (FDC), DTI fractional anisotropy (FA) and mean diffusivity (MD) were examined in relation to diagnoses and memory scores, controlling for age, sex, and intracranial volume. MCI and AD groups significantly differed from controls, with lower FD and FDC in the fornix and bilateral fibres extending to the medial temporal lobes (MTL). Memory was positively associated with FD and FDC in the fornix and MTL fibres, and FC in the anterior commissure (AC). Widespread FA reductions and MD increases were observed in AD and MCI and widely associated with memory. Fixel-wise measures highlight fibre tracts that are altered distinctly at the macroscopic and microscopic level in neurocognitive aging, and reveals structures associated with memory performance that are more specifically located than tensor-derived measures.

Diffusion magnetic resonance imaging of cerebrospinal fluid dynamics: Current techniques and future advancements

Cerebrospinal fluid (CSF) plays a critical role in metabolic waste clearance from the brain, requiring its circulation throughout various brain pathways, including the ventricular system, subarachnoid spaces, para-arterial spaces, interstitial spaces, and para-venous spaces. The complexity of CSF circulation has posed a challenge in obtaining noninvasive measurements of CSF dynamics. The assessment of CSF dynamics throughout its various circulatory pathways is possible using diffusion magnetic resonance imaging (MRI) with optimized sensitivity to incoherent water movement across the brain. This review presents an overview of both established and emerging diffusion MRI techniques designed to measure CSF dynamics and their potential clinical applications. The discussion offers insights into the optimization of diffusion MRI acquisition parameters to enhance the sensitivity and specificity of diffusion metrics on underlying CSF dynamics. Lastly, we emphasize the importance of cautious interpretations of diffusion-based imaging, especially when differentiating between tissue- and fluid-related changes or elucidating structural versus functional alterations.

White matter structure and derived network properties are used to predict the progression from mild cognitive impairment of older adults to Alzheimer's disease

OBJECTIVE

To identify white matter fiber injury and network changes that may lead to mild cognitive impairment (MCI) progression, then a joint model was constructed based on neuropsychological scales to predict high-risk individuals for Alzheimer's disease (AD) progression among older adults with MCI.

METHODS

A total of 173 MCI patients were included from the Alzheimer's Disease Neuroimaging Initiative(ADNI) database and randomly divided into training and testing cohorts. Forty-five progressed to AD during a 4-year follow-up period. Diffusion tensor imaging (DTI) techniques extracted relevant DTI quantitative features for each patient. In addition, brain networks were constructed based on white matter fiber bundles to extract network property features. Ensemble dimensionality reduction was applied to reduce both DTI quantitative features and network features from the training cohort, and machine learning algorithms were added to construct white matter signature. In addition, 52 patients from the National Alzheimer's Coordinating Center (NACC) database were used for external validation of white matter signature. A joint model was subsequently generated by combining with scale scores, and its performance was evaluated using data from the testing cohort.

RESULTS

Based on multivariate logistic regression, clinical dementia rating and Alzheimer's disease assessment scales (CDRS and ADAS, respectively) were selected as independent predictive factors. A joint model was constructed in combination with the white matter signature. The AUC, sensitivity, and specificity in the training cohort were 0.938, 0.937, and 0.91, respectively, and the AUC, sensitivity, and specificity in the test cohort were 0.905, 0.923, and 0.872, respectively. The Delong test showed a statistically significant difference between the joint model and CDRS or ADAS scores (P < 0.05), yet no significant difference between the joint model and the white matter signature (P = 0.341).

CONCLUSION

The present results demonstrate that a joint model combining neuropsychological scales can be constructed by using machine learning and DTI technology to identify MCI patients who are at high-risk of progressing to AD.

The mediating effect of the amygdala-frontal circuit on the association between depressive symptoms and cognitive function in Alzheimer's disease

Depressive symptoms occur commonly in Alzheimer's disease (AD). Although abnormalities in the amygdala-frontal circuit have been linked to emotional dysregulation and cognitive impairment, the neurological basis underlying these associations in AD patients with depressive symptoms (ADD) is unclear. We aimed to investigate the relationship between the amygdala-frontal circuit and depressive symptoms and cognitive function in ADD. We recruited 60 ADD, 60 AD patients without depressive symptoms (ADND), and 60 healthy controls (HC). Functional connectivity (FC) maps of the bilateral amygdala were compared. Fractional anisotropy (FA) of the amygdala-frontal circuit connected by the uncinate fasciculus (UF) was calculated using automated fiber quantification (AFQ). In addition, mediation analysis was performed to explore the effects of the amygdala-frontal circuit on the relationship between depressive symptoms and cognitive function. We found decreased bilateral amygdala FC with the inferior frontal gyrus (IFG) in the ADD group compared to the ADND and HC groups. Moreover, FA in the left frontal UF (nodes 64-97) was significantly lower in the ADD group than ADND group. Notably, amygdala-based FC with IFG and the left frontal UF FA mediated the relationship between depressive symptoms and cognitive function in ADD, with mediating effects ranging between 15 and 18%. Our study is the first to demonstrate the mediating effect of functional and microstructural abnormalities in the amygdala-frontal circuit in ADD. The findings suggest that the amygdala-frontal circuit may underlie emotional dysregulation in ADD, providing potential targets for treatment strategies.

Seeing beyond the symptoms: biomarkers and brain regions linked to cognitive decline in Alzheimer's disease

Objective

Early Alzheimer's disease (AD) diagnosis remains challenging, necessitating specific biomarkers for timely detection. This study aimed to identify such biomarkers and explore their associations with cognitive decline.

Methods

A cohort of 1759 individuals across cognitive aging stages, including healthy controls (HC), mild cognitive impairment (MCI), and AD, was examined. Utilizing nine biomarkers from structural MRI (sMRI), diffusion tensor imaging (DTI), and positron emission tomography (PET), predictions were made for Mini-Mental State Examination (MMSE), Clinical Dementia Rating Scale Sum of Boxes (CDRSB), and Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS). Biomarkers included four sMRI (e.g., average thickness [ATH]), four DTI (e.g., mean diffusivity [MD]), and one PET Amyloid-β (Aβ) measure. Ensemble regression tree (ERT) technique with bagging and random forest approaches were applied in four groups (HC/MCI, HC/AD, MCI/AD, and HC/MCI/AD).

Results

Aβ emerged as a robust predictor of cognitive scores, particularly in late-stage AD. Volumetric measures, notably ATH, consistently correlated with cognitive scores across early and late disease stages. Additionally, ADAS demonstrated links to various neuroimaging biomarkers in all subject groups, highlighting its efficacy in monitoring brain changes throughout disease progression. ERT identified key brain regions associated with cognitive scores, such as the right transverse temporal region for Aβ, left and right entorhinal cortex, left inferior temporal gyrus, and left middle temporal gyrus for ATH, and the left uncinate fasciculus for MD.

Conclusion

This study underscores the importance of an interdisciplinary approach in understanding AD mechanisms, offering potential contributions to early biomarker development.

Structural neuroimaging changes associated with subjective cognitive decline from a clinical sample

BACKGROUND

Alzheimer's disease (AD) is characterized by progressive deterioration of cognitive functions. Some individuals with subjective cognitive decline (SCD) are in the early phase of the disease and subsequently progress through the AD continuum. Although neuroimaging biomarkers could be used for the accurate and early diagnosis of preclinical AD, the findings in SCD samples have been heterogeneous. This study established the morphological differences in brain magnetic resonance imaging (MRI) findings between individuals with SCD and those without cognitive impairment based on a clinical sample of patients defined according to SCD-Initiative recommendations. Moreover, we investigated baseline structural changes in the brains of participants who remained stable or progressed to mild cognitive impairment or dementia.

METHODS

This study included 309 participants with SCD and 43 healthy controls (HCs) with high-quality brain MRI at baseline. Among the 99 subjects in the SCD group who were followed clinically, 32 progressed (SCDp) and 67 remained stable (SCDnp). A voxel-wise statistical comparison of gray and white matter (WM) volume was performed between the HC and SCD groups and between the HC, SCDp, and SCDnp groups. XTRACT ATLAS was used to define the anatomical location of WM tract damage. Region-of-interest (ROI) analyses were performed to determine brain volumetric differences. White matter lesion (WML) burden was established in each group.

RESULTS

Voxel-based morphometry (VBM) analysis revealed that the SCD group exhibited gray matter atrophy in the middle frontal gyri, superior orbital gyri, superior frontal gyri, right rectal gyrus, whole occipital lobule, and both thalami and precunei. Meanwhile, ROI analysis revealed decreased volume in the left rectal gyrus, bilateral medial orbital gyri, middle frontal gyri, superior frontal gyri, calcarine fissure, and left thalamus. The SCDp group exhibited greater hippocampal atrophy (p < 0.001) than the SCDnp and HC groups on ROI analyses. On VBM analysis, however, the SCDp group exhibited increased hippocampal atrophy only when compared to the SCDnp group (p < 0.001). The SCD group demonstrated lower WM volume in the uncinate fasciculus, cingulum, inferior fronto-occipital fasciculus, anterior thalamic radiation, and callosum forceps than the HC group. However, no significant differences in WML number (p = 0.345) or volume (p = 0.156) were observed between the SCD and HC groups.

CONCLUSIONS

The SCD group showed brain atrophy mainly in the frontal and occipital lobes. However, only the SCDp group demonstrated atrophy in the medial temporal lobe at baseline. Structural damage in the brain regions was anatomically connected, which may contribute to early memory decline.

Diffusion imaging markers of accelerated aging of the lower cingulum in subjective cognitive decline

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.

Assessing brain microstructural changes in chronic kidney disease: a diffusion imaging study using multiple models

Objectives

To explore the effectiveness of diffusion quantitative parameters derived from advanced diffusion models in detecting brain microstructural changes in patients with chronic kidney disease (CKD).

Methods

The study comprised 44 CKD patients (eGFR<59 mL/min/1.73 m2) and 35 age-and sex-matched healthy controls. All patients underwent diffusion spectrum imaging (DSI) and conventional magnetic resonance imaging. Reconstructed to obtain diffusion MRI models, including diffusion tensor imaging (DTI), neurite orientation dispersion and density imaging (NODDI) and Mean Apparent Propagator (MAP)-MRI, were processed to obtain multi-parameter maps. The Tract-Based Spatial Statistics (TBSS) analysis was utilized for detecting microstructural differences and Pearson correlation analysis assessed the relationship between renal metabolism markers and diffusion parameters in the brain regions of CKD patients. Receiver operating characteristic (ROC) curve analysis assessed the diagnostic performance of diffusion models, with AUC comparisons made using DeLong's method.

Results

Significant differences were noted in DTI, NODDI, and MAP-MRI parameters between CKD patients and controls (p < 0.05). DTI indicated a decrease in Fractional Anisotropy(FA) and an increase in Mean and Radial Diffusivity (MD and RD) in CKD patients. NODDI indicated decreased Intracellular and increased Extracellular Volume Fractions (ICVF and ECVF). MAP-MRI identified extensive microstructural changes, with elevated Mean Squared Displacement (MSD) and Q-space Inverse Variance (QIV) values, and reduced Non-Gaussianity (NG), Axial Non-Gaussianity (NGAx), Radial Non-Gaussianity (NGRad), Return-to-Origin Probability (RTOP), Return-to-Axis Probability (RTAP), and Return-to-Plane Probability (RTPP). There was a moderate correlation between serum uric acid (SUA) and diffusion parameters in six brain regions (p < 0.05). ROC analysis showed the AUC values of DTI_FA ranged from 0.70 to 0.793. MAP_NGAx in the Retrolenticular part of the internal capsule R reported a high AUC value of 0.843 (p < 0.05), which was not significantly different from other diffusion parameters (p > 0.05).

Conclusion

The advanced diffusion models (DTI, NODDI, and MAP-MRI) are promising for detecting brain microstructural changes in CKD patients, offering significant insights into CKD-affected brain areas.

Free water in gray matter linked to gut microbiota changes with decreased butyrate producers in Alzheimer's disease and mild cognitive impairment

Neuroinflammation contributes to the pathology and progression of Alzheimer's disease (AD), and it can be observed even with mild cognitive impairment (MCI), a prodromal phase of AD. Free water (FW) imaging estimates the extracellular water content and has been used to study neuroinflammation across several neurological diseases including AD. Recently, the role of gut microbiota has been implicated in the pathogenesis of AD. The relationship between FW imaging and gut microbiota was examined in patients with AD and MCI. Fifty-six participants underwent neuropsychological assessments, FW imaging, and gut microbiota analysis targeting the bacterial 16S rRNA gene. They were categorized into the cognitively normal control (NC) (n = 19), MCI (n = 19), and AD (n = 18) groups according to the neuropsychological assessments. The correlations of FW values, neuropsychological assessment scores, and the relative abundance of gut microbiota were analyzed. FW was higher in several white matter tracts and in gray matter regions, predominantly the frontal, temporal, limbic and paralimbic regions in the AD/MCI group than in the NC group. In the AD/MCI group, higher FW values in the temporal (superior temporal and temporal pole), limbic and paralimbic (insula, hippocampus and amygdala) regions were the most associated with worse neuropsychological assessment scores. In the AD/MCI group, FW values in these regions were negatively correlated with the relative abundances of butyrate-producing genera Anaerostipes, Lachnospiraceae UCG-004, and [Ruminococcus] gnavus group, which showed a significant decreasing trend in the order of the NC, MCI, and AD groups. The present study showed that increased FW in the gray matter regions related to cognitive impairment was associated with low abundances of butyrate producers in the AD/MCI group. These findings suggest an association between neuroinflammation and decreased levels of the short-chain fatty acid butyrate that is one of the major gut microbial metabolites having a potentially beneficial role in brain homeostasis.

Imaging Biomarker for Early-Stage Alzheimer Disease: Utility of Hippocampal Histogram Analysis of Diffusion Metrics

BACKGROUND AND PURPOSE

Biomarkers have been required for diagnosing early Alzheimer disease. We assessed the utility of hippocampal diffusion parameters for diagnosing Alzheimer disease pathology in mild cognitive impairment.

MATERIALS AND METHODS

Sixty-nine patients with mild cognitive impairment underwent both CSF measurement and multi-shell diffusion imaging at 3T. Based on the CSF biomarker level, patients were classified according to the presence (Alzheimer disease group, n = 35) or absence (non-Alzheimer disease group, n = 34) of Alzheimer disease pathology. Neurite orientation dispersion and density imaging and diffusion tensor imaging parametric maps were generated. Two observers independently created the hippocampal region of interest for calculating histogram features. Interobserver correlations were calculated. The statistical significance of intergroup differences was tested by using the Mann-Whitney U test. Logistic regression analyses, using both the clinical scale and the image data, were used to predict intergroup differences, after which group discriminations were performed.

RESULTS

Most intraclass correlation coefficient values were between 0.59 and 0.91. In the regions of interest of both observers, there were statistically significant intergroup differences for the left-side neurite orientation dispersion and density imaging-derived intracellular volume fraction, right-side diffusion tensor imaging-derived mean diffusivity, left-side diffusion tensor imaging-derived mean diffusivity, axial diffusivity, and radial diffusivity (P < .05). Logistic regression models revealed that diffusion parameters contributed the most to discriminating between the groups. The areas under the receiver operating characteristic curve for the regions of interest of observers A/B were 0.69/0.68, 0.69/0.68, 0.73/0.68, 0.71/0.68, and 0.68/0.68 for the left-side intracellular volume fraction (mean), right-side mean diffusivity (mean), left-side mean diffusivity (10th percentile), axial diffusivity (10th percentile), and radial diffusivity (mean).

CONCLUSIONS

Hippocampal diffusion parameters might be useful for the early diagnosis of Alzheimer disease.

White Matter Microstructure Analysis in Subjective Memory Complaints and Cognitive Impairment: Insights from Diffusion Kurtosis Imaging and Free-Water DTI

Background

Dementia is characterized by a cognitive decline in memory and other domains that lead to functional impairments. As people age, subjective memory complaints (SMC) become common, where individuals perceive cognitive decline without objective deficits on assessments. SMC can be an early sign and may precede amnestic mild cognitive impairment (MCI), which frequently advances to Alzheimer's disease (AD).

Objective

This study aims to investigate white matter microstructure in individuals with SMC, in cognitively impaired (CI) cohorts, and in cognitively normal individuals using diffusion kurtosis imaging (DKI) and free water imaging (FWI). The study also explores voxel-based correlations between DKI/FWI metrics and cognitive scores to understand the relationship between brain microstructure and cognitive function.

Methods

Twelve healthy controls (HCs), ten individuals with SMC, and eleven CI individuals (MCI or AD) were enrolled in this study. All participants underwent MRI 3T scan and the BNI Screen (BNIS) for Higher Cerebral Functions.

Results

The mean kurtosis tensor and anisotropy of the kurtosis tensor showed significant differences across the three groups, indicating altered white matter microstructure in CI and SMC individuals. The free water volume fraction (f) also revealed group differences, suggesting changes in extracellular water content. Notably, these metrics effectively discriminated between the CI and HC/SMC groups. Additionally, correlations between imaging metrics and BNIS scores were found for CI and SMC groups.

Conclusions

These imaging metrics hold promise in discriminating between individuals with CI and SMC. The observed differences indicate their potential as sensitive and specific biomarkers for early detection and differentiation of cognitive decline.

White matter integrity is associated with cognition and amyloid burden in older adult Koreans along the Alzheimer's disease continuum

BACKGROUND

White matter (WM) microstructural changes in the hippocampal cingulum bundle (CBH) in Alzheimer's disease (AD) have been described in cohorts of largely European ancestry but are lacking in other populations.

METHODS

We assessed the relationship between CBH WM integrity and cognition or amyloid burden in 505 Korean older adults aged ≥ 55 years, including 276 cognitively normal older adults (CN), 142 with mild cognitive impairment (MCI), and 87 AD patients, recruited as part of the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's disease (KBASE) at Seoul National University.

RESULTS

Compared to CN, AD and MCI subjects showed significantly higher RD, MD, and AxD values (all p-values < 0.001) and significantly lower FA values (left p ≤ 0.002, right p ≤ 0.015) after Bonferroni adjustment for multiple comparisons. Most tests of cognition and mood (p < 0.001) as well as higher medial temporal amyloid burden (p < 0.001) were associated with poorer WM integrity in the CBH after Bonferroni adjustment.

CONCLUSION

These findings are consistent with patterns of WM microstructural damage previously reported in non-Hispanic White (NHW) MCI/AD cohorts, reinforcing existing evidence from predominantly NHW cohort studies.

Disentangling in-vivo microstructural changes of white and gray matter in mild cognitive impairment and Alzheimer's disease: a systematic review and meta-analysis

The microstructural characteristics of white and gray matter in mild cognitive impairment (MCI) and the early-stage of Alzheimer's disease (AD) remain unclear. This study aimed to systematically identify the microstructural damages of MCI/AD in studies using neurite orientation dispersion and density imaging (NODDI), and explore their correlations with cognitive performance. Multiple databases were searched for eligible studies. The 10 eligible NODDI studies were finally included. Patients with MCI/AD showed overall significant reductions in neurite density index (NDI) of specific white matter structures in bilateral hemispheres (left hemisphere: -0.40 [-0.53, -0.27], P < 0.001; right: -0.33 [-0.47, -0.19], P < 0.001), involving the bilateral superior longitudinal fasciculus (SLF), uncinate fasciculus (UF), the left posterior thalamic radiation (PTR), and the left cingulum. White matter regions exhibited significant increased orientation dispersion index (ODI) (left: 0.25 [0.02, 0.48], P < 0.05; right: 0.27 [0.07, 0.46], P < 0.05), including the left cingulum, the right UF, and the bilateral parahippocampal cingulum (PHC), and PTR. Additionally, the ODI of gray matter showed significant reduction in bilateral hippocampi (left: -0.97 [-1.42, -0.51], P < 0.001; right: -0.90 [-1.35, -0.45], P < 0.001). The cognitive performance in MCI/AD was significantly associated with NDI (r = 0.50, P < 0.001). Our findings highlight the microstructural changes in MCI/AD were characterized by decreased fiber orientation dispersion in the hippocampus, and decreased neurite density and increased fiber orientation dispersion in specific white matter tracts, including the cingulum, UF, and PTR. Moreover, the decreased NDI may indicate the declined cognitive level of MCI/AD patients.

Diffusion Kurtosis Imaging in Evaluating the Mild Cognitive Impairment of Occupational Aluminum Workers

RATIONALE AND OBJECTIVES

To investigate whether diffusion kurtosis imaging (DKI) can distinguish mild cognitive impairment (MCI) from normal controls (NC) in aluminum (Al)-exposed workers, and to explore the association of DKI with cognitive performance and plasma Al concentration.

MATERIALS AND METHODS

28 patients with MCI and 25 NC at Al factory were enrolled in this study. All subjects underwent conventional MRI and DKI scans. The mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr), mean diffusivity (MD) and fractional anisotropy (FA) parameters of the hippocampus, substantia nigra, red nucleus, thalamus, anterior cingulate gyrus, genu and crus of the corpus callosum, frontal, parietal and temporal lobe were measured. To compare the parameters between the two groups, the Mann-Whitney rank sum test was used. The correlation of parameter values with cognitive performance and plasma Al concentration was analyzed using Spearman correlation analysis. The receiver operating characteristic (ROC) curve and the Z-scores were used to evaluate the diagnostic efficacy of each parameter.

RESULTS

Compared with the NC group, the MK, Ka, Kr, and FA values in the MCI group were significantly decreased, and the MD values were significantly increased (p<0.05). For the diagnosis of MCI, MK in the right hippocampus showed the largest AUC (0.924). The MK, Kr, MD and FA values were correlated with the Montreal Cognitive Assessment (MoCA) scores, and MK values in the right hippocampus showed the greatest correlation with MoCA scores (r=0.744, p <0.001). Plasma Al in the MCI group was higher than that in the NC group, although there was no significant difference in plasma Al between the two groups (p=0.057). There was no correlation between DKI parameters and plasma Al.

CONCLUSION

The DKI method might be a sensitive imaging biomarker to discriminate MCI from NC, and could preliminarily assess the severity of cognitive impairment in Al-exposed workers. MK in the right hippocampus appeared to be the best independent predictor. The mechanism of cognitive decline is an important content of aluminum exposure research. This study indicates that the DKI technique could provide valuable information for the diagnosis of MCI.

Influence of mild cognitive impairment and body mass index on white matter integrity assessed by diffusion tensor imaging

Mild cognitive impairment (MCI), a prodromal stage of Alzheimer's disease, is characterized by decreased memory and cognition, which are linked to degenerative changes in the brain. To assess whether white matter (WM) integrity is compromised in MCI, we collected diffusion-weighted images from 60 healthy older adults (OA) (69.16 ± 0.7) and 20 older adults with amnestic MCI (72.45 ± 1.9). WM integrity differences were examined using Tract-Based Spatial Statistics (TBSS). We hypothesized that those with MCI would have diminished WM integrity relative to OA. In a whole-brain comparison, those with MCI showed higher axial diffusivity in the splenium (SCC) and body of the corpus callosum (BCC), superior corona radiata (SCR), and the retrolenticular part of the internal capsule (RLIC) (p's < .05 TFCE-corrected). Additionally, significant between-group connectivity differences were observed using probabilistic tractography between the SCC, chosen from the TBSS results, and forceps major and minor (p-value's < .05). To further relate a physical health indicator to WM alterations, linear regression showed significant interactions between cognitive status and body mass index (BMI) on diffusivity outcome measures from probabilistic tractography (p-value-'s < .05). Additionally, we examined the association between relational memory, BMI, and WM integrity. WM integrity was positively associated with relational memory performance. These findings suggest that these regions may be more sensitive to early markers of neurodegenerative disease and health behaviors, suggesting that modifiable lifestyle factors may affect white matter integrity.

Nigral Pathology Contributes to Microstructural Integrity of Striatal and Frontal Tracts in Parkinson's Disease

BACKGROUND

Motor and cognitive impairment in Parkinson's disease (PD) is associated with dopaminergic dysfunction that stems from substantia nigra (SN) degeneration and concomitant α-synuclein accumulation. Diffusion magnetic resonance imaging (MRI) can detect microstructural alterations of the SN and its tracts to (sub)cortical regions, but their pathological sensitivity is still poorly understood.

OBJECTIVE

To unravel the pathological substrate(s) underlying microstructural alterations of SN, and its tracts to the dorsal striatum and dorsolateral prefrontal cortex (DLPFC) in PD.

METHODS

Combining post-mortem in situ MRI and histopathology, T1-weighted and diffusion MRI, and neuropathological samples of nine PD, six PD with dementia (PDD), five dementia with Lewy bodies (DLB), and 10 control donors were collected. From diffusion MRI, mean diffusivity (MD) and fractional anisotropy (FA) were derived from the SN, and tracts between the SN and caudate nucleus, putamen, and DLPFC. Phosphorylated-Ser129-α-synuclein and tyrosine hydroxylase immunohistochemistry was included to quantify nigral Lewy pathology and dopaminergic degeneration, respectively.

RESULTS

Compared to controls, PD and PDD/DLB showed increased MD of the SN and SN-DLPFC tract, as well as increased FA of the SN-caudate nucleus tract. Both PD and PDD/DLB showed nigral Lewy pathology and dopaminergic loss compared to controls. Increased MD of the SN and FA of SN-caudate nucleus tract were associated with SN dopaminergic loss. Whereas increased MD of the SN-DLPFC tract was associated with increased SN Lewy neurite load.

CONCLUSIONS

In PD and PDD/DLB, diffusion MRI captures microstructural alterations of the SN and tracts to the dorsal striatum and DLPFC, which differentially associates with SN dopaminergic degeneration and Lewy neurite pathology. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Axonal energy metabolism, and the effects in aging and neurodegenerative diseases

Human studies consistently identify bioenergetic maladaptations in brains upon aging and neurodegenerative disorders of aging (NDAs), such as Alzheimer's disease, Parkinson's disease, Huntington's disease, and Amyotrophic lateral sclerosis. Glucose is the major brain fuel and glucose hypometabolism has been observed in brain regions vulnerable to aging and NDAs. Many neurodegenerative susceptible regions are in the topological central hub of the brain connectome, linked by densely interconnected long-range axons. Axons, key components of the connectome, have high metabolic needs to support neurotransmission and other essential activities. Long-range axons are particularly vulnerable to injury, neurotoxin exposure, protein stress, lysosomal dysfunction, etc. Axonopathy is often an early sign of neurodegeneration. Recent studies ascribe axonal maintenance failures to local bioenergetic dysregulation. With this review, we aim to stimulate research in exploring metabolically oriented neuroprotection strategies to enhance or normalize bioenergetics in NDA models. Here we start by summarizing evidence from human patients and animal models to reveal the correlation between glucose hypometabolism and connectomic disintegration upon aging/NDAs. To encourage mechanistic investigations on how axonal bioenergetic dysregulation occurs during aging/NDAs, we first review the current literature on axonal bioenergetics in distinct axonal subdomains: axon initial segments, myelinated axonal segments, and axonal arbors harboring pre-synaptic boutons. In each subdomain, we focus on the organization, activity-dependent regulation of the bioenergetic system, and external glial support. Second, we review the mechanisms regulating axonal nicotinamide adenine dinucleotide (NAD+) homeostasis, an essential molecule for energy metabolism processes, including NAD+ biosynthetic, recycling, and consuming pathways. Third, we highlight the innate metabolic vulnerability of the brain connectome and discuss its perturbation during aging and NDAs. As axonal bioenergetic deficits are developing into NDAs, especially in asymptomatic phase, they are likely exaggerated further by impaired NAD+ homeostasis, the high energetic cost of neural network hyperactivity, and glial pathology. Future research in interrogating the causal relationship between metabolic vulnerability, axonopathy, amyloid/tau pathology, and cognitive decline will provide fundamental knowledge for developing therapeutic interventions.

Longitudinal Associations Between Blood Biomarkers and White Matter MRI in Sport-Related Concussion: A Study of the NCAA-DoD CARE Consortium

BACKGROUND AND OBJECTIVES

To study longitudinal associations between blood-based neural biomarkers (including total tau, neurofilament light [NfL], glial fibrillary acidic protein [GFAP], and ubiquitin C-terminal hydrolase-L1) and white matter neuroimaging biomarkers in collegiate athletes with sport-related concussion (SRC) from 24 hours postinjury to 1 week after return to play.

METHODS

We analyzed clinical and imaging data of concussed collegiate athletes in the Concussion Assessment, Research, and Education (CARE) Consortium. The CARE participants completed same-day clinical assessments, blood draws, and diffusion tensor imaging (DTI) at 3 time points: 24-48 hours postinjury, point of becoming asymptomatic, and 7 days after return to play. DTI probabilistic tractography was performed for each participant at each time point to render 27 participant-specific major white matter tracts. The microstructural organization of these tracts was characterized by 4 DTI metrics. Mixed-effects models with random intercepts were applied to test whether white matter microstructural abnormalities are associated with the blood-based biomarkers at the same time point. An interaction model was used to test whether the association varies across time points. A lagged model was used to test whether early blood-based biomarkers predict later microstructural changes.

RESULTS

Data from 77 collegiate athletes were included in the following analyses. Among the 4 blood-based biomarkers, total tau had significant associations with the DTI metrics across the 3 time points. In particular, high tau level was associated with high radial diffusivity (RD) in the right corticospinal tract (β = 0.25, SE = 0.07, p FDR-adjusted = 0.016) and superior thalamic radiation (β = 0.21, SE = 0.07, p FDR-adjusted = 0.042). NfL and GFAP had time-dependent associations with the DTI metrics. NfL showed significant associations only at the asymptomatic time point (|β|s > 0.12, SEs <0.09, psFDR-adjusted < 0.05) and GFAP showed a significant association only at 7 days after return to play (βs > 0.14, SEs <0.06, psFDR-adjusted < 0.05). The p values for the associations of early tau and later RD were not significant after multiple comparison adjustment, but were less than 0.1 in 7 white matter tracts.

DISCUSSION

This prospective study using data from the CARE Consortium demonstrated that in the early phase of SRC, white matter microstructural integrity detected by DTI neuroimaging was associated with elevated levels of blood-based biomarkers of traumatic brain injury. Total tau in the blood showed the strongest association with white matter microstructural changes.

Characterization of diffusion magnetic resonance imaging revealing relationships between white matter disconnection and behavioral disturbances in mild cognitive impairment: a systematic review

White matter disconnection is the primary cause of cognition and affection abnormality in mild cognitive impairment (MCI). Adequate understanding of behavioral disturbances, such as cognition and affection abnormality in MCI, can help to intervene and slow down the progression of Alzheimer's disease (AD) promptly. Diffusion MRI is a non-invasive and effective technique for studying white matter microstructure. This review searched the relevant papers published from 2010 to 2022. Sixty-nine studies using diffusion MRI for white matter disconnections associated with behavioral disturbances in MCI were screened. Fibers connected to the hippocampus and temporal lobe were associated with cognition decline in MCI. Fibers connected to the thalamus were associated with both cognition and affection abnormality. This review summarized the correspondence between white matter disconnections and behavioral disturbances such as cognition and affection, which provides a theoretical basis for the future diagnosis and treatment of AD.

White matter integrity is associated with cognition and amyloid burden in older adult Koreans along the Alzheimer's disease continuum

BACKGROUND

White matter (WM) microstructural changes in the hippocampal cingulum bundle (CBH) in Alzheimer's disease (AD) have been described in cohorts of largely European ancestry but are lacking in other populations.

METHODS

We assessed the relationship between CBH WM integrity and cognition or amyloid burden in 505 Korean older adults aged ≥55 years, including 276 cognitively normal older adults (CN), 142 mild cognitive impairment (MCI), and 87 AD, recruited as part of the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's disease (KBASE) at Seoul National University.

RESULTS

Compared to CN, AD and MCI subjects showed decreased WM integrity in the bilateral CBH. Cognition, mood, and higher amyloid burden were also associated with poorer WM integrity in the CBH.

CONCLUSION

These findings are consistent with patterns of WM microstructural damage previously reported in non-Hispanic White (NHW) MCI/AD cohorts, reinforcing existing evidence from predominantly NHW cohort studies.

Functional connectivity and mild behavioral impairment in dementia-free elderly

Background

Mild behavioral impairment (MBI) is a syndrome that uses later-life emergent and persistent neuropsychiatric symptoms (NPS) to identify a group at high risk for incident dementia. MBI is associated with neurodegenerative disease markers in advance of syndromic dementia. Functional connectivity (FC) correlates of MBI are understudied and could provide further insights into mechanisms early in the disease course. We used resting-state functional magnetic resonance imaging (rs-fMRI) to test the hypothesis that FC within the default mode network (DMN) and salience network (SN) of persons with MBI (MBI+) is reduced, relative to those without (MBI-).

Methods

From two harmonized dementia-free cohort studies, using a score of ≥6 on the MBI Checklist to define MBI status, 32 MBI+ and 63 MBI- individuals were identified (mean age: 71.7 years; 54.7% female). Seed-based connectivity analysis was implemented in each MBI group using the CONN fMRI toolbox (v20.b), with the posterior cingulate cortex (PCC) as the seed region within the DMN and anterior cingulate cortex (ACC) as the seed within the SN. The average time series from the PCC and ACC were used to determine FC with other regions within the DMN (medial prefrontal cortex, lateral inferior parietal cortex) and SN (anterior insula, supramarginal gyrus, rostral prefrontal cortex), respectively. Age, sex, years of education, and Montreal Cognitive Assessment scores were included as model covariates. The false discovery rate approach was used to correct for multiple comparisons, with a p-value of .05 considered significant.

Results

For the DMN, MBI+ individuals exhibited reduced FC between the PCC and the medial prefrontal cortex, compared to MBI-. For the SN, MBI+ individuals exhibited reduced FC between the ACC and left anterior insula.

Conclusion

MBI in dementia-free older adults is associated with reduced FC in networks known to be disrupted in dementia. Our results complement the evidence linking MBI with Alzheimer's disease biomarkers.

Highlights

Resting-state functional magnetic resonance imaging was completed in 95 dementia-free persons from FAVR and COMPASS-ND studies.Participants were stratified by informant-rated Mild Behavioral Impairment Checklist (MBI-C) score, ≥6 for MBI+.MBI+ participants showed reduced functional connectivity (FC) within the default mode network and salience network.These FC changes are consistent with those seen in early-stage Alzheimer's disease.MBI may help identify persons with early-stage neurodegenerative disease.

Leveraging genetic diversity in mice to inform individual differences in brain microstructure and memory

In human Alzheimer's disease (AD) patients and AD mouse models, both differential pre-disease brain features and differential disease-associated memory decline are observed, suggesting that certain neurological features may protect against AD-related cognitive decline. The combination of these features is known as brain reserve, and understanding the genetic underpinnings of brain reserve may advance AD treatment in genetically diverse human populations. One potential source of brain reserve is brain microstructure, which is genetically influenced and can be measured with diffusion MRI (dMRI). To investigate variation of dMRI metrics in pre-disease-onset, genetically diverse AD mouse models, we utilized a population of genetically distinct AD mice produced by crossing the 5XFAD transgenic mouse model of AD to 3 inbred strains (C57BL/6J, DBA/2J, FVB/NJ) and two wild-derived strains (CAST/EiJ, WSB/EiJ). At 3 months of age, these mice underwent diffusion magnetic resonance imaging (dMRI) to probe neural microanatomy in 83 regions of interest (ROIs). At 5 months of age, these mice underwent contextual fear conditioning (CFC). Strain had a significant effect on dMRI measures in most ROIs tested, while far fewer effects of sex, sex*strain interactions, or strain*sex*5XFAD genotype interactions were observed. A main effect of 5XFAD genotype was observed in only 1 ROI, suggesting that the 5XFAD transgene does not strongly disrupt neural development or microstructure of mice in early adulthood. Strain also explained the most variance in mouse baseline motor activity and long-term fear memory. Additionally, significant effects of sex and strain*sex interaction were observed on baseline motor activity, and significant strain*sex and sex*5XFAD genotype interactions were observed on long-term memory. We are the first to study the genetic influences of brain microanatomy in genetically diverse AD mice. Thus, we demonstrated that strain is the primary factor influencing brain microstructure in young adult AD mice and that neural development and early adult microstructure are not strongly altered by the 5XFAD transgene. We also demonstrated that strain, sex, and 5XFAD genotype interact to influence memory in genetically diverse adult mice. Our results support the usefulness of the 5XFAD mouse model and convey strong relationships between natural genetic variation, brain microstructure, and memory.

Posttraumatic Stress and Traumatic Brain Injury: Cognition, Behavior, and Neuroimaging Markers in Vietnam Veterans

BACKGROUND

Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) are common in Veterans and linked to behavioral disturbances, increased risk of cognitive decline, and Alzheimer's disease.

OBJECTIVE

We studied the synergistic effects of PTSD and TBI on behavioral, cognitive, and neuroimaging measures in Vietnam war Veterans.

METHODS

Data were acquired at baseline and after about one-year from male Veterans categorized into: PTSD, TBI, PTSD+TBI, and Veteran controls without PTSD or TBI. We applied manual tractography to examine white matter microstructure of three fiber tracts: uncinate fasciculus (N = 91), cingulum (N = 87), and inferior longitudinal fasciculus (N = 95). ANCOVAs were used to compare Veterans' baseline behavioral and cognitive functioning (N = 285), white matter microstructure, amyloid-β (N = 230), and tau PET (N = 120). Additional ANCOVAs examined scores' differences from baseline to follow-up.

RESULTS

Veterans with PTSD and PTSD+TBI, but not Veterans with TBI only, exhibited poorer behavioral and cognitive functioning at baseline than controls. The groups did not differ in baseline white matter, amyloid-β, or tau, nor in behavioral and cognitive functioning, and tau accumulation change. Progression of white matter abnormalities of the uncinate fasciculus in Veterans with PTSD compared to controls was observed; analyses in TBI and PTSD+TBI were not run due to insufficient sample size.

CONCLUSIONS

PTSD and PTSD+TBI negatively affect behavioral and cognitive functioning, while TBI does not contribute independently. Whether progressive decline in uncinate fasciculus microstructure in Veterans with PTSD might account for cognitive decline should be further studied. Findings did not support an association between PTSD, TBI, and Alzheimer's disease pathology based on amyloid and tau PET.

Structural connectivity mapping in human hippocampal-subfields using super-resolution hybrid diffusion imaging: a feasibility study

PURPOSE

The goal of the current study was to introduce a new methodology that holds a promise to be used in hippocampus-aging studies using sub-millimeter super-resolution hybrid diffusion imaging (HYDI) MRI.

METHODS

HYDI diffusion data were acquired in two groups of older and younger healthy participants recruited from the Indiana Alzheimer's Disease Research Center and community. These data were then transformed into super-resolution diffusion images before the hippocampal subfield analyses. We studied the correlation between the subjects' age and the structural connectivity involving the hippocampal subfields and the connectivity between the whole hippocampus and the cerebral cortex.

RESULTS

Structural integrity derived from the tractography streamlines between the hippocampal subfields was reduced in older than younger adults.

CONCLUSION

The findings offered a new promising framework, and they opened avenues for future studies to explore the relationship between the structural connectivity in the hippocampal area and different types of dementia.

White matter integrity and key structures affected in Alzheimer's disease characterized by diffusion tensor imaging

White matter (WM) degeneration is suggested to predict the early signs of Alzheimer's disease (AD). The exact structural regions of brain circuitry involved are not known. This study aims to examine the associations between WM tract integrity, represented by the diffusion tensor imaging (DTI) measures, and AD diagnosis and to denote the key substrates in predicting AD. It included DTI measures of mean diffusivity (MD), fractional anisotropy, radial diffusivity and axial diffusivity of 18 main WM tracts in 84 non-Hispanic white participants from the Alzheimer's Disease Neuroimaging Initiative dataset. The multivariable general linear model was used to examine the association of AD diagnosis with each DTI measure adjusting for age, gender and education. The corpus callosum, fornix, cingulum hippocampus, uncinate fasciculus, sagittal striatum, left posterior thalamic radiation and fornix-stria terminalis showed significant increases in MD, radial and axial diffusivity, whereas the splenium of corpus callosum and the fornix showed significant decreases in fractional anisotropy among AD patients. Variable cluster analysis identified that hippocampus volume, mini-mental state examination (MMSE), cingulate gyrus/hippocampus, inferior fronto-occipital fasciculus and uncinate fasciculus are highly correlated in one cluster with MD measures. In conclusion, there were significant differences in DTI measures between the brain WM of AD patients and controls. Age is the risk factor associated with AD, not gender or education. Right cingulum gyrus and right uncinate fasciculus are particularly affected, correlating well with a cognitive test MMSE and MD measures for dementia in AD patients and could be a region of focus for AD staging.

Histogram Analysis Based on Neurite Orientation Dispersion and Density MR Imaging for Differentiation Between Glioblastoma Multiforme and Solitary Brain Metastasis and Comparison of the Diagnostic Performance of Two ROI Placements

BACKGROUND

Preoperative differentiation of glioblastoma multiforme (GBM) and solitary brain metastasis (SBM) contributes to guide neurosurgical decision-making.

PURPOSE

To explore the value of histogram analysis based on neurite orientation dispersion and density imaging (NODDI) in differentiating between GBM and SBM and comparison of the diagnostic performance of two region of interest (ROI) placements.

STUDY TYPE

Retrospective.

POPULATION

In all, 109 patients with GBM (n = 57) or SBM (n = 52) were enrolled.

FIELD STRENGTH/SEQUENCE

A 3.0 T scanners. T₂ -dark-fluid sequence, contrast-enhanced T₁ magnetization-prepared rapid gradient echo sequence, and NODDI.

ASSESSMENT

ROIs were placed on the peritumoral edema area (ROI1) and whole tumor area (ROI2, included the cystic, necrotic, and hemorrhagic areas). Histogram parameters of each isotropic volume fraction (ISOVF), intracellular volume fraction (ICVF), and orientation dispersion index (ODI) from NODDI images for two ROIs were calculated, respectively.

STATISTICAL TESTS

Mann-Whitney U test, independent t-test, chi-square test, multivariate logistic regression analysis, DeLong's test.

RESULTS

For the ROI1 and ROI2, the ICVF_min and ODI_mean obtained the highest area under curve (AUC, AUC = 0.741 and 0.750, respectively) compared to other single parameters, and the AUC of the multivariate logistic regression model was 0.851 and 0.942, respectively. DeLong's test revealed significant difference in diagnostic performance between optimal single parameter and multivariate logistic regression model within the same ROI, and the multivariate logistic regression models between two different ROIs.

DATA CONCLUSION

The performance of multivariate logistic regression model is superior to optimal single parameter in both ROIs based on NODDI histogram analysis to distinguish SBM from GBM, and the ROI placed on the whole tumor area exhibited better diagnostic performance.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 2.

Diffusion Tensor Imaging Profiles Can Distinguish Diffusivity and Neural Properties of White Matter Injury in Hydrocephalus vs. Non-hydrocephalus Using a Strategy of a Periodic Table of DTI Elements

Background:

The aim of this study was to create a simplistic taxonomy to improve transparency and consistency in, and reduce complexity of, interpreting diffusion tensor imaging (DTI) profiles in white matter disruption. Using a novel strategy of a periodic table of DTI elements, we examined if DTI profiles could demonstrate neural properties of disruption sufficient to characterize white matter changes specific for hydrocephalus vs. non-hydrocephalus, and to distinguish between cohorts of neural injury by their differing potential for reversibility.

Methods

DTI datasets from three clinical cohorts representing pathological milestones from reversible to irreversible brain injury were compared to those of healthy controls at baseline, over time and with interventions. The final dataset comprised patients vs. controls in the following groupings: mild traumatic brain injury (mTBI), n = 24 vs. 27, normal pressure hydrocephalus (NPH), n = 16 vs. 9 and Alzheimer's disease (AD), n = 27 vs. 47. We generated DTI profiles from fractional anisotropy (FA) and mean, axial and radial diffusivity measures (MD, L1 and L2 and 3 respectively), and constructed an algorithm to map changes consistently to a periodic table of elements, which fully described their diffusivity and neural properties.

Results

Mapping tissue signatures to a periodic table of DTI elements rapidly characterized cohorts by their differing patterns of injury. At baseline, patients with mTBI displayed the most preserved tracts. In NPH, the magnitude of changes was dependent on “familial” DTI neuroanatomy, i.e., potential for neural distortion from risk of ventriculomegaly. With time, patients with Alzheimer's disease were significantly different to controls across multiple measures. By contrast, patients with mTBI showed both loss of integrity and pathophysiological processes of neural repair. In NPH, some patterns of injury, such as “stretch/compression” and “compression” were more reversible following intervention than others; these neural profile properties suggested “microstructural resilience” to injury.

Conclusion

Using the novel strategy of a periodic table of DTI elements, our study has demonstrated it is possible to distinguish between different cohorts along the spectrum of brain injury by describing neural profile properties of white matter disruption. Further work to contribute datasets of disease toward this proposed taxonomic framework would enhance the translatability of DTI profiles to the clinical-research interface.

Hippocampal-subfield microstructures and their relation to plasma biomarkers in Alzheimer's disease

Hippocampal subfields exhibit differential vulnerabilities to Alzheimer's disease-associated pathology including abnormal accumulation of amyloid-β deposition and neurofibrillary tangles. These pathological processes extensively impact on the structural and functional interconnectivities of the subfields and may explain the association between hippocampal dysfunction and cognitive deficits. In this study, we investigated the degree of alterations in the microstructure of hippocampal subfields across the clinical continuum of Alzheimer's disease. We applied a grey matter-specific multi-compartment diffusion model (Cortical-Neurite orientation dispersion and density imaging) to understand the differential effects of Alzheimer's disease pathology on the hippocampal subfield microstructure. A total of 119 participants were included in this cross-sectional study. Participants were stratified into three categories, cognitively normal (n = 47), mild cognitive impairment (n = 52), and Alzheimer's disease (n = 19). Diffusion MRI, plasma biomarkers and neuropsychological test scores were used to determine the association between the microstructural integrity and Alzheimer's disease-associated molecular indicators and cognition. For Alzheimer's disease-related plasma biomarkers, we studied amyloid-β, total tau and neurofilament light; for Alzheimer's disease-related neuropsychological tests, we included the Trail Making Test, Rey Auditory Verbal Learning Test, Digit Span and Montreal Cognitive Assessment. Comparisons between cognitively normal subjects and those with mild cognitive impairment showed significant microstructural alterations in the hippocampal cornu ammonis (CA) 4 and dentate gyrus region, whereas CA 1-3 was the most sensitive region for the later stages in the Alzheimer's disease clinical continuum. Among imaging metrics for microstructures, the volume fraction of isotropic diffusion for interstitial free water demonstrated the largest effect size in between-group comparisons. Regarding the plasma biomarkers, neurofilament light appeared to be the most sensitive biomarker for associations with microstructural imaging findings in CA4-dentate gyrus. CA 1-3 was the subfield which had stronger correlations between cognitive performance and microstructural metrics. Particularly, poor performance on the Rey Auditory Verbal Learning Test and Montreal Cognitive Assessment was associated with decreased intracellular volume fraction. Overall, our findings support the value of tissue-specific microstructural imaging for providing pathologically relevant information manifesting in the plasma biomarkers and neuropsychological outcomes across various stages of Alzheimer's disease.

Reduced Inter-Voxel Whiter Matter Integrity in Subjective Cognitive Decline: Diffusion Tensor Imaging With Tract-Based Spatial Statistics Analysis

Subjective cognitive decline (SCD), a self-reported worsening in cognition concurrent with normal performance on standardized neuropsychological tests, has gained much attention due to its high risks in the development of mild cognitive impairments or Alzheimer’s disease. The existing cross-sectional diffusion tensor imaging (DTI) studies in SCD have shown extremely controversial findings. Furthermore, all of these studies investigated diffusion properties within the voxel, such as fractional anisotropy, mean diffusivity, or axial diffusivity (DA). However, it remains unclear whether individuals with SCD demonstrate alterations of diffusion profile between voxels and their neighbors, as indexed by local diffusion homogeneity (LDH). We selected 30 healthy controls (HCs) and 23 SCD subjects to acquire their whole-brain DTI. Diffusion images were compared using the tract-based spatial statistics method. Diffusion indices with significant between-group tract clusters were extracted from each individual for further region-of-interest (ROI)-based comparisons. Our results showed that subjects with SCD demonstrated reduced LDH in the left superior frontal gyrus (SFG) and DA in the right anterior cingulate cortex compared with the HC group. In contrast, the SCD group showed higher LDH values in the left lingual gyrus (LG) compared with the HC group. Notably, LDH in the left SFG was significantly and negatively correlated with LDH in the left LG. In conclusion, white matter (WM) integrity in the left SFG, right ACC, and left LG is altered in SCD, suggesting that individuals with SCD exhibit detectable changes in WM tracts before they demonstrate objective cognitive deficits.

White matter damage due to vascular, tau, and TDP-43 pathologies and its relevance to cognition

Multi-compartment modelling of white matter microstructure using Neurite Orientation Dispersion and Density Imaging (NODDI) can provide information on white matter health through neurite density index and free water measures. We hypothesized that cerebrovascular disease, Alzheimer's disease, and TDP-43 proteinopathy would be associated with distinct NODDI readouts of white matter damage which would be informative for identifying the substrate for cognitive impairment. We identified two independent cohorts with multi-shell diffusion MRI, amyloid and tau PET, and cognitive assessments: specifically, a population-based cohort of 347 elderly randomly sampled from the Olmsted county, Minnesota, population and a clinical research-based cohort of 61 amyloid positive Alzheimer's dementia participants. We observed an increase in free water and decrease in neurite density using NODDI measures in the genu of the corpus callosum associated with vascular risk factors, which we refer to as the vascular white matter component. Tau PET signal reflective of 3R/4R tau deposition was associated with worsening neurite density index in the temporal white matter where we measured parahippocampal cingulum and inferior temporal white matter bundles. Worsening temporal white matter neurite density was associated with (antemortem confirmed) FDG TDP-43 signature. Post-mortem neuropathologic data on a small subset of this sample lend support to our findings. In the community-dwelling cohort where vascular disease was more prevalent, the NODDI vascular white matter component explained variability in global cognition (partial R2 of free water and neurite density = 8.3%) and MMSE performance (8.2%) which was comparable to amyloid PET (7.4% for global cognition and 6.6% for memory). In the AD dementia cohort, tau deposition was the greatest contributor to cognitive performance (9.6%), but there was also a non-trivial contribution of the temporal white matter component (8.5%) to cognitive performance. The differences observed between the two cohorts were reflective of their distinct clinical composition. White matter microstructural damage assessed using advanced diffusion models may add significant value for distinguishing the underlying substrate (whether cerebrovascular disease versus neurodegenerative disease caused by tau deposition or TDP-43 pathology) for cognitive impairment in older adults.

Neuroimaging of Mouse Models of Alzheimer’s Disease

Magnetic resonance imaging (MRI) and positron emission tomography (PET) have made great strides in the diagnosis and our understanding of Alzheimer’s Disease (AD). Despite the knowledge gained from human studies, mouse models have and continue to play an important role in deciphering the cellular and molecular evolution of AD. MRI and PET are now being increasingly used to investigate neuroimaging features in mouse models and provide the basis for rapid translation to the clinical setting. Here, we provide an overview of the human MRI and PET imaging landscape as a prelude to an in-depth review of preclinical imaging in mice. A broad range of mouse models recapitulate certain aspects of the human AD, but no single model simulates the human disease spectrum. We focused on the two of the most popular mouse models, the 3xTg-AD and the 5xFAD models, and we summarized all known published MRI and PET imaging data, including contrasting findings. The goal of this review is to provide the reader with broad framework to guide future studies in existing and future mouse models of AD. We also highlight aspects of MRI and PET imaging that could be improved to increase rigor and reproducibility in future imaging studies.

White matter changes in empirically derived incident MCI subtypes in the Mayo Clinic Study of Aging

INTRODUCTION

The aim of this study was to examine white matter hyperintensities (WMH) and fractional anisotropy (FA) in empirically derived incident mild cognitive impairment (MCI) subtypes.

METHODS

We evaluated 188 participants with incident MCI in the Mayo Clinic Study of Aging (MCSA) identified as having one of four cluster-derived subtypes: subtle cognitive impairment, amnestic, dysnomic, and dysexecutive. We used linear regression models to evaluate whole brain and regional WMH volumes. We examined fractional anisotropy (FA) on a subset of 63 participants with diffusion tensor imaging.

RESULTS

Amnestic and dysexecutive subtypes had higher WMH volumes in differing patterns than cognitively unimpaired; the dysexecutive subtype had higher WMH than subtle cognitive impairment. There was widespread WM degeneration in long association and commissural fibers in the amnestic, dysnomic, and dysexecutive subtypes, and corpus callosum FA accounted for significant variability in global cognition.

DISCUSSION

White matter changes likely contribute to cognitive symptoms in incident MCI.

Sleep and White Matter in Adults with Down Syndrome

Adults with Down syndrome are at a high risk for disordered sleep. These sleep problems could have marked effects on aging and Alzheimer's disease, potentially altering white matter integrity. This study examined the associations between disordered sleep assessed via an actigraph accelerometer worn on 7 consecutive nights, presence of diagnosis of obstructive sleep apnea, and diffusion tensor imaging indices of white matter integrity in 29 non-demented adults with Down Syndrome (48% female, aged 33-54 years). Average total sleep time was associated with lower mean diffusivity in the left superior longitudinal fasciculus (r = -0.398, p = 0.040). Average sleep efficiency, length of awakenings, and movement index were related to fractional anisotropy in the right inferior longitudinal fasciculus (r = -0.614 to 0.387, p ≤ 0.050). Diagnosis of obstructive sleep apnea was associated with fractional anisotropy in the right inferior longitudinal fasciculus (r = -0.373, p = 0.050). Findings suggest that more disrupted sleep is associated with lower white matter integrity in the major association tracts in middle-aged adults with Down syndrome. Longitudinal work is needed to confirm the directionally of associations. Sleep interventions could be an important component for promoting optimal brain aging in the Down syndrome population.

Tau deposition and structural connectivity demonstrate differential association patterns with neurocognitive tests

Tau neurofibrillary tangles have a central role in the pathogenesis of Alzheimer’s Disease (AD). Mounting evidence indicates that the propagation of tau is assisted by brain connectivity with weakened white-matter integrity along the propagation pathways. Recent advances in tau positron emission tomography tracers and diffusion magnetic resonance imaging allow the visualization of tau pathology and white-matter connectivity of the brain in vivo. The current study aims to investigate how tau deposition and structural connectivity are associated with memory function in prodromal AD. In this study, tau accumulation and structural connectivity data from 83 individuals (57 cognitively normal participants and 26 participants with mild cognitive impairment) were associated with neurocognitive test scores. Statistical analyses were performed in 70 cortical/subcortical brain regions to determine: 1. the level of association between tau and network metrics extracted from structural connectivity and 2. the association patterns of brain memory function with tau accumulation and network metrics. The results showed that tau accumulation and network metrics were correlated in early tau deposition regions. Furthermore, tau accumulation was associated with worse performance in almost all neurocognitive tests performance evaluated in the study. In comparison, decreased network connectivity was associated with declines in the delayed memory recall in Craft Stories and Benson Figure Copy. Interaction analysis indicates that tau deposition and dysconnectivity have a synergistic effect on the delayed Benson Figure Recall. Overall, our findings indicate that both tau deposition and structural dysconnectivity are associated with neurocognitive dysfunction. They also suggest that tau-PET may have better sensitivity to neurocognitive performance than diffusion MRI-derived measures of white-matter connectivity.

Brain neurometabolites differences in individuals with subjective cognitive decline plus: a quantitative single- and multi-voxel proton magnetic resonance spectroscopy study

Background

Subjective cognitive decline plus could be an extremely early phase of Alzheimer's disease; however, changes of N-acetylaspartate, myoinositol, and N-acetylaspartate/myoinositol is still unknown at this stage. This study aimed to explore brain neurometabolic alterations in patients with subjective cognitive decline plus using quantitative single-voxel and multi-voxel ¹H-magnetic resonance spectroscopy.

Methods

A total of 91 participants were enrolled and underwent a GE 3.0-T magnetic resonance imaging, including 33 elderly controls, 27 patients with subjective cognitive decline plus, and 31 patients with amnestic mild cognitive impairment (MCI). Single-voxel and multi-voxel ¹H-magnetic resonance spectroscopy were used to investigate the differences in neurometabolite levels among the three groups.

Results

Compared with elderly controls, patients with subjective cognitive decline plus showed significant decline in N-acetylaspartate and N-acetylaspartate/myoinositol values in multiple regions, and amnestic MCI participants demonstrated more significant decreased N-acetylaspartate and N-acetylaspartate/myoinositol levels in multiple regions. The combined concentrations of N-acetylaspartate with myoinositol showed an excellent discrimination between those with subjective cognitive decline plus and elderly controls as compared to that obtained using N-acetylaspartate/myoinositol ratios with the area under the receiver operating characteristic curve of 0.895 and 0.860, respectively. Likewise, the combined area under the curve for differentiating patients with subjective cognitive decline plus from amnestic MCI was obtained using the combined levels of N-acetylaspartate with myoinositol was 0.892. This was also higher than the combined area under the curve of 0.836 obtained using N-acetylaspartate/myoinositol ratios. Moreover, N-acetylaspartate levels in the left hippocampus and left posterior cingulate cortex (PCC) was positively related to the Auditory Verbal Learning Test delayed recall scores in patients with subjective cognitive decline plus, whereas only the N-acetylaspartate/myoinositol ratio was positively related to this scale scores in the left hippocampus.

Conclusions

Quantitative single-voxel and multi-voxel ¹H-magnetic resonance spectroscopy can provide valuable information to detect alterative brain neurometabolites characteristics in patients with subjective cognitive decline plus. N-acetylaspartate concentrations may be used as one of the earliest neuroimaging markers at this stage, while N-acetylaspartate/myoinositol ratio could be more suitable for monitoring Alzheimer's disease progression.

Neural correlates of the impulse dyscontrol domain of mild behavioral impairment

OBJECTIVES

Agitation and aggression are common in dementia and pre-dementia. The dementia risk syndrome mild behavioral impairment (MBI) includes these symptoms in the impulse dyscontrol domain. However, the neural circuitry associated with impulse dyscontrol in neurodegenerative disease is not well understood. The objective of this work was to investigate if regional micro- and macro-structural brain properties were associated with impulse dyscontrol symptoms in older adults with normal cognition, mild cognitive impairment, and Alzheimer's disease (AD).

METHODS

Clinical, neuropsychiatric, and T1-weighted and diffusion-tensor magnetic resonance imaging (DTI) data from 80 individuals with and 123 individuals without impulse dyscontrol were obtained from the AD Neuroimaging Initiative. Linear mixed effect models were used to assess if impulse dyscontrol was related to regional DTI and volumetric parameters.

RESULTS

Impulse dyscontrol was present in 17% of participants with NC, 43% with MCI, and 66% with AD. Impulse dyscontrol was associated with: (1) lower fractional anisotropy (FA), and greater mean, axial, and radial diffusivity in the fornix; (2) lesser FA and greater radial diffusivity in the superior fronto-occipital fasciculus; (3) greater axial diffusivity in the cingulum; (4) greater axial and radial diffusivity in the uncinate fasciculus; (5) gray matter atrophy, specifically, lower cortical thickness in the parahippocampal gyrus.

CONCLUSION

Our findings provide evidence that well-established atrophy patterns of AD are prominent in the presence of impulse dyscontrol, even when disease status is controlled for, and possibly in advance of dementia. Our findings support the growing evidence for impulse dyscontrol symptoms as an early manifestation of AD.

Diffusion models reveal white matter microstructural changes with ageing, pathology and cognition

White matter microstructure undergoes progressive changes during the lifespan, but the neurobiological underpinnings related to ageing and disease remains unclear. We used an advanced diffusion MRI, Neurite Orientation Dispersion and Density Imaging, to investigate the microstructural alterations due to demographics, common age-related pathological processes (amyloid, tau and white matter hyperintensities) and cognition. We also compared Neurite Orientation Dispersion and Density Imaging findings to the older Diffusion Tensor Imaging model-based findings. Three hundred and twenty-eight participants (264 cognitively unimpaired, 57 mild cognitive impairment and 7 dementia with a mean age of 68.3 ± 13.1 years) from the Mayo Clinic Study of Aging with multi-shell diffusion imaging, fluid attenuated inversion recovery MRI as well as amyloid and tau PET scans were included in this study. White matter tract level diffusion measures were calculated from Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging. Pearson correlation and multiple linear regression analyses were performed with diffusion measures as the outcome and age, sex, education/occupation, white matter hyperintensities, amyloid and tau as predictors. Analyses were also performed with each diffusion MRI measure as a predictor of cognitive outcomes. Age and white matter hyperintensities were the strongest predictors of all white matter diffusion measures with low associations with amyloid and tau. However, neurite density decrease from Neurite Orientation Dispersion and Density Imaging was observed with amyloidosis specifically in the temporal lobes. White matter integrity (mean diffusivity and free water) in the corpus callosum showed the greatest associations with cognitive measures. All diffusion measures provided information about white matter ageing and white matter changes due to age-related pathological processes and were associated with cognition. Neurite orientation dispersion and density imaging and diffusion tensor imaging are two different diffusion models that provide distinct information about variation in white matter microstructural integrity. Neurite Orientation Dispersion and Density Imaging provides additional information about synaptic density, organization and free water content which may aid in providing mechanistic insights into disease progression.

Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases

There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases.

Bundle-specific associations between white matter microstructure and Aβ and tau pathology in preclinical Alzheimer's disease

Beta-amyloid (Aβ) and tau proteins, the pathological hallmarks of Alzheimer's disease (AD), are believed to spread through connected regions of the brain. Combining diffusion imaging and positron emission tomography, we investigated associations between white matter microstructure specifically in bundles connecting regions where Aβ or tau accumulates and pathology. We focused on free-water-corrected diffusion measures in the anterior cingulum, posterior cingulum, and uncinate fasciculus in cognitively normal older adults at risk of sporadic AD and presymptomatic mutation carriers of autosomal dominant AD. In Aβ-positive or tau-positive groups, lower tissue fractional anisotropy and higher mean diffusivity related to greater Aβ and tau burden in both cohorts. Associations were found in the posterior cingulum and uncinate fasciculus in preclinical sporadic AD, and in the anterior and posterior cingulum in presymptomatic mutation carriers. These results suggest that microstructural alterations accompany pathological accumulation as early as the preclinical stage of both sporadic and autosomal dominant AD.

Microstructural white matter alterations in Alzheimer's disease and amnestic mild cognitive impairment and its diagnostic value based on diffusion kurtosis imaging: a tract-based spatial statistics study

This prospective study aimed to explore the white matter microstructural alterations in Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) using the Tract-based Spatial Statistics (TBSS) method of diffusion kurtosis imaging (DKI).Diffusion images were collected from 45 AD patients, 42 aMCI patients, and 35 healthy controls (HC). The differences of DKI-derived parameters, including kurtosis fractional anisotropy (KFA), mean kurtosis (MK), fractional anisotropy (FA), and mean diffusivity (MD), were compared across the three groups using the TBSS method. Correlation between the altered DKI-derived parameters and the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores were analyzed. A receiver operating characteristic curve (ROC) was used to evaluate the diagnostic performance of different white matter parameters with the strongest correlations. As a result, compared with the HC group, KFA values decreased significantly in the aMCI group. Compared with both the HC and aMCI groups, the FA, KFA, and MK values decreased significantly and the MD value increased significantly in the AD group. FA, MD, KFA, and MK values of many white matter fiber tracts were significantly correlated with MMSE and MoCA scores. The area under the ROC curve (AUC) for the splenium of corpus callosum KFA values were highest for the diagnosis of aMCI and AD patients. In conclusion, the compactness and complexity of white matter microstructures were reduced in AD and aMCI patients. DKI can provide information about the severity of AD progression, and KFA might be more sensitive for the detection of white matter microstructural alterations.

Midlife Cardiovascular Fitness Is Reflected in the Brain's White Matter

Disappointing results from clinical trials designed to delay structural brain decline and the accompanying increase in risk for dementia in older adults have precipitated a shift in testing promising interventions from late in life toward midlife before irreversible damage has accumulated. This shift, however, requires targeting midlife biomarkers that are associated with clinical changes manifesting only in late life. Here we explored possible links between one putative biomarker, distributed integrity of brain white matter, and two intervention targets, cardiovascular fitness and healthy lifestyle behaviors, in midlife. At age 45, fractional anisotropy (FA) derived from diffusion weighted MRI was used to estimate the microstructural integrity of distributed white matter tracts in a population-representative birth cohort. Age-45 cardiovascular fitness (VO₂Max; N = 801) was estimated from heart rates obtained during submaximal exercise tests; age-45 healthy lifestyle behaviors were estimated using the Nyberg Health Index (N = 854). Ten-fold cross-validated elastic net predictive modeling revealed that estimated VO₂Max was modestly associated with distributed FA. In contrast, there was no significant association between Nyberg Health Index scores and FA. Our findings suggest that cardiovascular fitness levels, but not healthy lifestyle behaviors, are associated with the distributed integrity of white matter in the brain in midlife. These patterns could help inform future clinical intervention research targeting ADRDs.

Systematic Assessment of the Impact of DTI Methodology on Fractional Anisotropy Measures in Alzheimer's Disease

White matter microstructural changes in Alzheimer's disease (AD) are often assessed using fractional anisotropy (FA) obtained from diffusion tensor imaging (DTI). FA depends on the acquisition and analysis methods, including the fitting algorithm. In this study, we compared FA maps from different acquisitions and fitting algorithms in AD, mild cognitive impairment (MCI), and healthy controls (HCs) using the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Three acquisitions from two vendors were compared (Siemens 30, GE 48, and Siemens 54 directions). DTI data were fit using nine fitting algorithms (four linear least squares (LLS), two weighted LLS (WLLS), and three non-linear LLS (NLLS) from four software tools (FSL, DSI-Studio, CAMINO, and AFNI). Different cluster volumes and effect-sizes were observed across acquisitions and fits, but higher consistency was observed as the number of diffusion directions increased. Significant differences were observed between HC and AD groups for all acquisitions, while significant differences between HC and MCI groups were only observed for GE48 and SI54. Using the intraclass correlation coefficient, AFNI-LLS and CAMINO-RESTORE were the least consistent with the other algorithms. By combining data across all three acquisitions and nine fits, differences between AD and HC/MCI groups were observed in the fornix and corpus callosum, indicating FA differences in these regions may be robust DTI-based biomarkers. This study demonstrates that comparisons of FA across aging populations could be confounded by variability in acquisitions and fit methodologies and that identifying the most robust DTI methodology is critical to provide more reliable DTI-based neuroimaging biomarkers for assessing microstructural changes in AD.

Microstructural and Cerebral Blood Flow Abnormalities in Subjective Cognitive Decline Plus: Diffusional Kurtosis Imaging and Three-Dimensional Arterial Spin Labeling Study

Objective: To explore microstructural and cerebral blood flow (CBF) abnormalities in individuals with subjective cognitive decline plus (SCD plus) using diffusional kurtosis imaging (DKI) and three-dimensional (3D) arterial spin labeling (ASL). Methods: Twenty-seven patients with SCD plus, 31 patients with amnestic mild cognitive impairment (aMCI), and 33 elderly controls (ECs) were recruited and underwent DKI and 3D ASL using a GE 3.0-T MRI. Mean kurtosis (MK), fractional anisotropy (FA), mean diffusivity (MD), and CBF values were acquired from 24 regions of interest (ROIs) in the brain, including the bilateral hippocampal (Hip) subregions (head, body, and tail), posterior cingulate cortex (PCC), precuneus, dorsal thalamus subregions (anterior nucleus, ventrolateral nucleus, and medial nucleus), lenticular nucleus, caput nuclei caudati, white matter (WM) of the frontal lobe, and WM of the occipital lobe. Pearson's correlation analysis was performed to assess the relationships among the DKI-derived parameters, CBF values, and key neuropsychological tests for SCD plus. Results: Compared with ECs, participants with SCD plus showed a significant decline in MK and CBF values, mainly in the Hip head and PCC, and participants with aMCI exhibited more significant abnormalities in the MK and CBF values than individuals with ECs and SCD plus in multiple regions. Combined MK values showed better discrimination between patients with SCD plus and ECs than that obtained using CBF levels, with areas under the receiver operating characteristic (ROC) curve (AUC) of 0.874 and 0.837, respectively. Similarly, the AUC in discriminating SCD plus from aMCI patients obtained using combined MK values was 0.823, which was also higher than the combined AUC of 0.779 obtained using CBF values. Moreover, MK levels in the left Hip (h) and left PCC positively correlated with the auditory verbal learning test-delayed recall (AVLT-DR) score in participants with SCD plus. By contrast, only the CBF value in the left Hip head positively correlated with the AVLT-DR score. Conclusions: Our results provide new evidence of microstructural and CBF changes in patients with SCD plus. MK may be used as an early potential neuroimaging biomarker and may be a more sensitive DKI parameter than CBF at the very early stage of Alzheimer's disease (AD).

Tau-related white-matter alterations along spatially selective pathways

Progressive accumulation of tau neurofibrillary tangles in the brain is a defining pathologic feature of Alzheimer’s disease (AD). Tau pathology exhibits a predictable spatiotemporal spreading pattern, but the underlying mechanisms of this spread are poorly understood. Although AD is conventionally considered a disease of the gray matter, it is also associated with pronounced and progressive deterioration of the white matter (WM). A link between abnormal tau and WM degeneration is suggested by findings from both animal and postmortem studies, but few studies demonstrated their interplay in vivo. Recent advances in diffusion magnetic resonance imaging and the availability of tau positron emission tomography (PET) have made it possible to evaluate the association of tau and WM degeneration (tau-WM) in vivo. In this study, we explored the spatial pattern of tau-WM associations across the whole brain to evaluate the hypothesis that tau deposition is associated with WM microstructural alterations not only in isolated tracts, but in continuous structural connections in a stereotypic pattern. Sixty-two participants, including 22 cognitively normal subjects, 22 individuals with subjective cognitive decline, and 18 with mild cognitive impairment were included in the study. WM characteristics were inferred by classic diffusion tensor imaging (DTI) and a complementary diffusion compartment model – neurite orientation dispersion and density imaging (NODDI) that provides a proxy for axonal density. A data-driven iterative searching (DDIS) approach, coupled with whole-brain graph theory analyses, was developed to continuously track tau-WM association patterns. Without applying prior knowledge of the tau spread, we observed a distinct spatial pattern that resembled the typical propagation of tau pathology in AD. Such association pattern was not observed between diffusion and amyloid-β PET signal. Tau-related WM degeneration is characterized by an increase in the mean diffusivity (with a dominant change in the radial direction) and a decrease in the intra-axonal volume fraction. These findings suggest that cortical tau deposition (as measured in tau PET) is associated with a lower axonal packing density and greater diffusion freedom. In conclusion, our in vivo findings using a data-driven method on cross-sectional data underline the important role of WM alterations in the AD pathological cascade with an association pattern similar to the postmortem Braak staging of AD. Future studies will focus on longitudinal analyses to provide in vivo evidence of tau pathology spreads along neuroanatomically connected brain areas.

Association between neurite metrics and tau/inflammatory pathology in Alzheimer's disease

INTRODUCTION

The molecular mechanism of neurodegeneration, including tau and neurite complexity, is an important topic in Alzheimer's disease (AD) research.

METHODS

We recruited 27 amyloid-positive individuals identified through 11C-Pittsburgh compound B (PiB) positron emission tomography (PET) and 31 amyloid-negative individuals with normal cognition. All participants underwent 11C-PiB and 18F-THK5351 PET and magnetic resonance imaging (MRI) with neurite orientation dispersion and density imaging (NODDI) protocol. The neurite density index (NDI), orientation dispersion index (ODI), and PET images were analyzed to calculate voxel-wise correlations among the imaging modalities and correlations with cognitions.

RESULTS

In the amyloid-positive participants, there were significant negative correlations between 18F-THK5351 and NDI and between 18F-THK5351 and ODI. The bilateral mesial and lateral temporal lobes were mainly involved. Regarding cognition, 18F-THK5351 showed more marked associations with all cognitive domains than the other modalities.

DISCUSSION

Tau and neuroinflammation in AD may reduce the neurite density and orientation dispersion, particularly in the mesial and lateral temporal lobes.

GABAergic Inhibitory Interneuron Deficits in Alzheimer's Disease: Implications for Treatment

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized clinically by severe cognitive deficits and pathologically by amyloid plaques, neuronal loss, and neurofibrillary tangles. Abnormal amyloid β-protein (Aβ) deposition in the brain is often thought of as a major initiating factor in AD neuropathology. However, gamma-aminobutyric acid (GABA) inhibitory interneurons are resistant to Aβ deposition, and Aβ decreases synaptic glutamatergic transmission to decrease neural network activity. Furthermore, there is now evidence suggesting that neural network activity is aberrantly increased in AD patients and animal models due to functional deficits in and decreased activity of GABA inhibitory interneurons, contributing to cognitive deficits. Here we describe the roles played by excitatory neurons and GABA inhibitory interneurons in Aβ-induced cognitive deficits and how altered GABA interneurons regulate AD neuropathology. We also comprehensively review recent studies on how GABA interneurons and GABA receptors can be exploited for therapeutic benefit. GABA interneurons are an emerging therapeutic target in AD, with further clinical trials urgently warranted.

Peak Width of Skeletonized Water Diffusion MRI in the Neonatal Brain

Preterm birth is closely associated with cognitive impairment and generalized dysconnectivity of neural networks inferred from water diffusion MRI (dMRI) metrics. Peak width of skeletonized mean diffusivity (PSMD) is a metric derived from histogram analysis of mean diffusivity across the white matter skeleton, and it is a useful biomarker of generalized dysconnectivity and cognition in adulthood. We calculated PSMD and five other histogram based metrics derived from diffusion tensor imaging (DTI) and neurite orientation and dispersion imaging (NODDI) in the newborn, and evaluated their accuracy as biomarkers of microstructural brain white matter alterations associated with preterm birth. One hundred and thirty five neonates (76 preterm, 59 term) underwent 3T MRI at term equivalent age. There were group differences in peak width of skeletonized mean, axial, and radial diffusivities (PSMD, PSAD, PSRD), orientation dispersion index (PSODI) and neurite dispersion index (PSNDI), all p < 10-4. PSFA did not differ between groups. PSNDI was the best classifier of gestational age at birth with an accuracy of 81±10%, followed by PSMD, which had 77±9% accuracy. Models built on both NODDI metrics, and on all dMRI metrics combined, did not outperform the model based on PSNDI alone. We conclude that histogram based analyses of DTI and NODDI parameters are promising new image markers for investigating diffuse changes in brain connectivity in early life.

The role of limbic structures in financial abilities of mild cognitive impairment patients

Mild Cognitive Impairment (MCI) patients experience problems in financial abilities that affect everyday functioning. To date, the neural correlates of decline in this domain are unclear. This study aims at examining the correlation between the pattern of brain atrophy of MCI patients and performance on financial abilities. Forty-four MCI patients and thirty-seven healthy controls underwent structural magnetic resonance imaging, and assessment of financial abilitiesby means of the Numerical Activities of Daily Living Financial battery (NADL-F). As compared to healthy controls, MCI patients showed impaired performance in three out of the seven domains assessed by NADL-F: Item purchase, percentage, and financial concepts. The patients' performance in the NADL-F correlated with memory, language, visuo-spatial, and abstract reasoning composite scores. The analysis also revealed that volumetric differences in the limbic structures significantly correlated with financial abilities in MCI. Specifically, the patients' performance in the NADL-F was correlated with atrophy in the left medial and lateral amygdala and the right anterior thalamic radiation. These findings suggest that completing daily financial tasks involves sub-cortical regions in MCI and presumably also the motivational and emotional processes associated to them. Involvement of altered limbic structures in MCI patients suggests that impairment in financial abilities may be related to emotional and reflexive processing deficits.