Effectiveness of diffusion tensor imaging in differentiating early-stage subcortical ischemic vascular disease, Alzheimer's disease and normal ageing

Joint diffusional kurtosis magnetic resonance imaging analysis of white matter and the thalamus to identify subcortical ischemic vascular disease

Identifying subcortical ischemic vascular disease (SIVD) in older adults is important but challenging. Growing evidence suggests that diffusional kurtosis imaging (DKI) can detect SIVD-relevant microstructural pathology, and a systematic assessment of the discriminant power of DKI metrics in various brain tissue microstructures is urgently needed. Therefore, the current study aimed to explore the value of DKI and diffusion tensor imaging (DTI) metrics in detecting early-stage SIVD by combining multiple diffusion metrics, analysis strategies, and clinical-radiological constraints. This prospective study compared DKI with diffusivity and macroscopic imaging evaluations across the aging spectrum including SIVD, Alzheimer's disease (AD), and cognitively normal (NC) groups. Using a white matter atlas and segregated thalamus analysis with considerations of the pre-identified macroscopic pathology, the most effective diffusion metrics were selected and then examined using multiple clinical-radiological constraints in a two-group or three-group paradigm. A total of 122 participants (mean age, 74.6 ± 7.38 years, 72 women) including 42 with SIVD, 50 with AD, and 30 NC were evaluated. Fractional anisotropy, mean kurtosis, and radial kurtosis were critical metrics in detecting early-stage SIVD. The optimal selection of diffusion metrics showed 84.4-100% correct classification of the results in a three-group paradigm, with an area under the curve of .909-.987 in a two-group paradigm related to SIVD detection (all P < .001). We therefore concluded that greatly resilient to the effect of pre-identified macroscopic pathology, the combination of DKI/DTI metrics showed preferable performance in identifying early-stage SIVD among adults across the aging spectrum.

Regional Vulnerability of the Corpus Callosum in the Context of Cardiovascular Risk

Many factors outside of cardiovascular health can impact the structure of white matter. Identification of reliable and clinically meaningful biomarkers of the neural effects of systemic and cardiovascular health are needed to refine etiologic predictions. We examined whether the corpus callosum demonstrates regional vulnerability to systemic cardiovascular risk factors. Three hundred and ninety-four older adults without dementia completed brain MRI, neurobehavioral evaluations, and blood draws. A subset (n = 126, n = 128) of individuals had blood plasma analyzed for inflammatory markers of interest (IL-6 and TNF-alpha). Considering diffusion tensor imaging (DTI) is a particularly reliable measure of white matter integrity, we utilized DTI to examine fractional anisotropy (FA) of anterior and posterior regions of the corpus callosum. Using multiple linear regression models, we simultaneously examined FA of the genu and the splenium to compare their associations with systemic and cardiovascular risk factors. Lower FA of the genu but not splenium was associated with greater systemic and cardiovascular risk, including higher systolic blood pressure (β = -0.17, p = .020), hemoglobin A1C (β = -0.21, p = .016) and IL-6 (β = -0.34, p = .005). FA of the genu was uniquely associated with cognitive processing speed (β = 0.20, p = .0015) and executive functioning (β = 0.15, p = .012), but not memory performances (β = 0.05, p = .357). Our results demonstrated differential vulnerability of the corpus callosum, such that frontal regions showed stronger, independent associations with biomarkers of systemic and cardiovascular health in comparison to posterior regions. Posterior white matter integrity may not reflect cardiovascular health. Clinically, these findings support the utility of examining the anterior corpus callosum as an indicator of cerebrovascular health.

The clinical profile of cerebral small vessel disease: Toward an evidence-based identification of cognitive markers

There is no consensus on which test is more suited to outline the cognitive deficits of cerebral small vessel disease (cSVD) patients. We explored the ability of eight cognitive tests, selected in a previous systematic review as the most commonly used in this population, to differentiate among cSVD patients, controls, and other dementing conditions performing a meta-analysis of 86 studies. We found that cSVD patients performed worse than healthy controls in all tests while data on the comparison to neurodegenerative diseases were limited. We outlined a lack of data on these tests' accuracy on the diagnosis. Cognitive tests measuring processing speed were those mostly associated with neuroimaging cSVD markers. There is currently incomplete evidence that a single test could differentiate cSVD patients with cognitive decline from other dementing diseases. We make preliminary proposals on possible strategies to gain information about the clinical definition of cSVD that currently remains a neuroimaging-based one.

Frequency-dependent white-matter functional network changes associated with cognitive deficits in subcortical vascular cognitive impairment

Vascular cognitive impairment (VCI) refers to all forms of cognitive decline associated with cerebrovascular diseases, in which white matter (WM) is highly vulnerable. Although previous studies have shown that blood oxygen level-dependent (BOLD) signals inside WM can effectively reflect neural activities, whether WM BOLD signal alterations are present and their roles underlying cognitive impairment in VCI remain largely unknown. In this study, 36 subcortical VCI (SVCI) patients and 36 healthy controls were enrolled to evaluate WM dysfunction. Specifically, fourteen distinct WM networks were identified from resting-state functional MRI using K-means clustering analysis. Subsequently, between-network functional connectivity (FC) and within-network BOLD signal amplitude of WM networks were calculated in three frequency bands (band A: 0.01-0.15 Hz, band B: 0.08-0.15 Hz, and band C: 0.01-0.08 Hz). Patients with SVCI manifested decreased FC mainly in bilateral parietal WM regions, forceps major, superior and inferior longitudinal fasciculi. These connections extensively linked with distinct WM networks and with gray-matter networks such as frontoparietal control, dorsal and ventral attention networks, which exhibited frequency-specific alterations in SVCI. Additionally, extensive amplitude reductions were found in SVCI, showing frequency-dependent properties in parietal, anterior corona radiate, pre/post central, superior and inferior longitudinal fasciculus networks. Furthermore, these decreased FC and amplitudes showed significant positive correlations with cognitive performances in SVCI, and high diagnostic performances for SVCI especially combining all bands. Our study indicated that VCI-related cognitive deficits were characterized by frequency-dependent WM functional abnormalities, which offered novel applicable neuromarkers for VCI.

Association between Changes in White Matter Microstructure and Cognitive Impairment in White Matter Lesions

This study investigated the characteristics of cognitive impairment in patients with white matter lesions (WMLs) caused by cerebral small vessel disease and the corresponding changes in WM microstructures. Diffusion tensor imaging (DTI) data of 50 patients with WMLs and 37 healthy controls were collected. Patients were divided into vascular cognitive impairment non-dementia and vascular dementia groups. Tract-based spatial statistics showed that patients with WMLs had significantly lower fractional anisotropy (FA) and higher mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) values throughout the WM areas but predominately in the forceps minor, forceps major (FMA), bilateral corticospinal tract, inferior fronto-occipital fasciculus, superior longitudinal fasciculus, inferior longitudinal fasciculus (ILF), and anterior thalamic radiation, compared to the control group. These fiber bundles were selected as regions of interest. There were significant differences in the FA, MD, AD, and RD values (p < 0.05) between groups. The DTI metrics of all fiber bundles significantly correlated with the Montreal Cognitive Assessment (p < 0.05), with the exception of the AD values of the FMA and ILF. Patients with WMLs showed changes in diffusion parameters in the main WM fiber bundles. Quantifiable changes in WM microstructure are the main pathological basis of cognitive impairment, and may serve as a biomarker of WMLs.

Prospective Memory and Default Mode Network Functional Connectivity in Normal and Pathological Aging

BACKGROUND

Prospective memory (PM), the ability to execute a previously formed intention given the proper circumstance, has been proven to be vulnerable to Alzheimer's disease. Previous studies have indicated the involvement of the frontoparietal networks; however, it is proposed that PM may also be associated with other neural substrates that support stimulus-dependent spontaneous cognition.

OBJECTIVE

The present study aimed to examine the hypothesis that PM deficit in Alzheimer's disease is related to altered functional connectivity (FC) within the default mode network (DMN).

METHODS

Thirty-four patients with very mild or mild dementia (17 with Alzheimer's disease and 17 with subcortical ischemic vascular disease) and 22 cognitively-normal participants aged above 60 received a computerized PM task and resting-state functional magnetic resonance imaging study. Seed-based functional connectivity analysis was performed at group level within the DMN.

RESULTS

We found that the dementia groups showed worse PM performance and altered FC within the DMN as compared to the normal aging individuals. The FC between the medial prefrontal cortices and precuneus/posterior cingulate cortex was significantly correlated with PM in normal aging, while the FC between the right precuneus and bilateral inferior parietal lobules was correlated with PM in patients with Alzheimer's disease.

CONCLUSION

These findings support a potential role for the DMN in PM, and corroborate that PM deficit in Alzheimer's disease was associated with altered FC within the posterior hubs of the DMN, with spatial patterning different from normal aging.

Dissociable Functional Brain Networks Associated With Apathy in Subcortical Ischemic Vascular Disease and Alzheimer’s Disease

Few studies have investigated differences in functional connectivity (FC) between patients with subcortical ischemic vascular disease (SIVD) and Alzheimer’s disease (AD), especially in relation to apathy. Therefore, the aim of this study was to compare apathy-related FC changes among patients with SIVD, AD, and cognitively normal subjects. The SIVD group had the highest level of apathy as measured using the Apathy Evaluation Scale-clinician version (AES). Dementia staging, volume of white matter hyperintensities (WMH), and the Beck Depression Inventory were the most significant clinical predictors for apathy. Group-wise comparisons revealed that the SIVD patients had the worst level of “Initiation” by factor analysis of the AES. FCs from four resting state networks (RSNs) were compared, and the connectograms at the level of intra- and inter-RSNs revealed dissociable FC changes, shared FC in the dorsal attention network, and distinct FC in the salient network across SIVD and AD. Neuronal correlates for “Initiation” deficits that underlie apathy were explored through a regional-specific approach, which showed that the right inferior frontal gyrus, left middle frontal gyrus, and left anterior insula were the critical hubs. These findings broaden the disconnection theory by considering the effect of FC interactions across multiple RSNs on apathy formation.

Stage-Dependent Cerebral Blood Flow and Leukoaraiosis Couplings in Subcortical Ischemic Vascular Disease and Alzheimer's Disease

Background:

Alzheimer’s disease (AD) and subcortical ischemic vascular disease (SIVD) have both been associated with white matter hyperintensities (WMHs) and altered cerebral blood flow (CBF) although the etiology of AD is still unclear.

Objective:

To test the hypothesis that CBF and WMHs have differential effects on cognition and that the relationship between CBF and WMHs changes with the subtypes and stages of dementia.

Methods:

Forty-two patients with SIVD, 50 patients with clinically-diagnosed AD, and 30 cognitively-normal subjects were included. Based on the Clinical Dementia Rating (CDR), the patients were dichotomized into early-stage (CDR = 0.5) and late-stage (CDR = 1 or 2) groups. CBF and WMH metrics were derived from magnetic resonance imaging and correlated with cognition.

Results:

Hierarchical linear regression revealed that CBF metrics had distinct contribution to global cognition, memory, and attention, whereas WMH metrics had distinct contribution to executive function (all p < 0.05). In SIVD, the WMHs in frontotemporal areas correlated with the CBF in bilateral thalami at the early stage; the correlation then became between the WMHs in basal ganglia and the CBF in frontotemporal areas at the late stage. A similar corticosubcortical coupling was observed in AD but involved fewer areas.

Conclusion:

A stage-dependent coupling between CBF and WMHs was identified in AD and SIVD, where the extent of cortical WMHs correlated with subcortical CBF for CDR = 0.5, whereas the extent of subcortical WMHs correlated with cortical CBF for CDR = 1–2.

Neuroimaging and biomarker evidence of neurodegeneration in asthma

BACKGROUND

Epidemiologic studies have shown that Alzheimer's disease (AD) and related dementias (ADRD) are seen more frequently with asthma, especially with greater asthma severity or exacerbation frequency.

OBJECTIVE

To examine the changes in brain structure that may underlie this phenomenon, we examined diffusion-weighted magnetic resonance imaging (dMRI) and blood-based biomarkers of AD (phosphorylated tau 181, p-Tau181), neurodegeneration (neurofilament light chain, NfL), and glial activation (glial fibrillary acidic protein, GFAP).

METHODS

dMRI data were obtained in 111 individuals with asthma, ranging in disease severity from mild to severe, and 135 healthy controls. Regression analyses were used to test the relationships between asthma severity and neuroimaging measures, as well as AD pathology, neurodegeneration, and glial activation, indexed by plasma p-Tau181, NfL, and GFAP, respectively. Additional relationships were tested with cognitive function.

RESULTS

Asthma participants had widespread and large-magnitude differences in several dMRI metrics, which were indicative of neuroinflammation and neurodegeneration, and which were robustly associated with GFAP and, to a lesser extent, NfL. The AD biomarker p-Tau181 was only minimally associated with neuroimaging outcomes. Further, asthma severity was associated with deleterious changes in neuroimaging outcomes, which in turn were associated with slower processing speed, a test of cognitive performance.

CONCLUSIONS

Asthma, particularly when severe, is associated with characteristics of neuroinflammation and neurodegeneration, and may be a potential risk factor for neural injury and cognitive dysfunction. There is a need to determine how asthma may affect brain health and whether treatment directed toward characteristics of asthma associated with these risks can mitigate these effects.

Determining the OPTIMAL DTI analysis method for application in cerebral small vessel disease

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We were not able to identify a single optimal diffusion-weighted imaging analysis strategy across all 6 cohorts.

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Diffusion tensor imaging measures at baseline predicted dementia conversion in cerebral small vessel disease and mild cognitive impairment.

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Diffusion tensor imaging measures at baseline may be sensitive to differentiate between later vascular dementia vs Alzheimer’s disease dementia.

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Diffusion tensor imaging measures significantly changed over time in cohorts with cerebral small vessel disease and cohorts with mild cognitive impairment. Change in diffusion tensor imaging measures were only consistently associated with dementia conversion in severe SVD.

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The diffusion tensor imaging measures PSMD and DSEG required the lowest minimum sample sizes for a hypothetical clinical trial in patients with sporadic cerebral small vessel disease and mild cognitive impairment.

Background

DTI is sensitive to white matter (WM) microstructural damage and has been suggested as a surrogate marker for phase 2 clinical trials in cerebral small vessel disease (SVD). The study’s objective is to establish the best way to analyse the diffusion-weighted imaging data in SVD for this purpose. The ideal method would be sensitive to change and predict dementia conversion, but also straightforward to implement and ideally automated. As part of the OPTIMAL collaboration, we evaluated five different DTI analysis strategies across six different cohorts with differing SVD severity.

Methods

Those 5 strategies were: (1) conventional mean diffusivity WM histogram measure (MD median), (2) a principal component-derived measure based on conventional WM histogram measures (PC1), (3) peak width skeletonized mean diffusivity (PSMD), (4) diffusion tensor image segmentation θ (DSEG θ) and (5) a WM measure of global network efficiency (Geff). The association between each measure and cognitive function was tested using a linear regression model adjusted by clinical markers. Changes in the imaging measures over time were determined. In three cohort studies, repeated imaging data together with data on incident dementia were available. The association between the baseline measure, change measure and incident dementia conversion was examined using Cox proportional-hazard regression or logistic regression models. Sample size estimates for a hypothetical clinical trial were furthermore computed for each DTI analysis strategy.

Results

There was a consistent cross-sectional association between the imaging measures and impaired cognitive function across all cohorts. All baseline measures predicted dementia conversion in severe SVD. In mild SVD, PC1, PSMD and Geff predicted dementia conversion. In MCI, all markers except Geff predicted dementia conversion. Baseline DTI was significantly different in patients converting to vascular dementia than to Alzheimer’ s disease. Significant change in all measures was associated with dementia conversion in severe but not in mild SVD. The automatic and semi-automatic measures PSMD and DSEG θ required the lowest minimum sample sizes for a hypothetical clinical trial in single-centre sporadic SVD cohorts.

Conclusion

DTI parameters obtained from all analysis methods predicted dementia, and there was no clear winner amongst the different analysis strategies. The fully automated analysis provided by PSMD offers advantages particularly for large datasets.

Prospective Memory and Regional Functional Connectivity in Subcortical Ischemic Vascular Disease

Objectives: Patients with subcortical ischemic vascular disease (SIVD) often have prominent frontal dysfunction. However, it remains unclear how SIVD affects prospective memory (PM), which strongly relies on the frontoparietal network. The present study aimed to investigate PM performance in patients with early stage SIVD as compared to those with Alzheimer's disease (AD) and to older adults with normal cognition, and to explore the neural correlates of PM deficits. Method: Patients with very-mild to mild dementia due to SIVD or AD and normal controls (NC) aged above 60 years were recruited. Seventy-three participants (20 SIVD, 22 AD, and 31 NC) underwent structural magnetic resonance imaging (MRI), cognitive screening tests, and a computerized PM test. Sixty-five of these participants (19 SIVD, 20 AD, and 26 NC) also received resting-state functional MRI. Results: The group with SIVD had significantly fewer PM hits than the control group on both time-based and non-focal event-based PM tasks. Among patients in the very early stage, only those with SIVD but not AD performed significantly worse than the controls. Correlational analyses showed that non-focal event-based PM in SIVD was positively correlated with regional homogeneity in bilateral superior and middle frontal gyri, while time-based PM was not significantly associated with regional homogeneity in any of the regions of interest within the dorsal frontoparietal regions. Conclusions: The findings of this study highlight the vulnerability of non-focal event-based PM to the disruption of regional functional connectivity in bilateral superior and middle frontal gyri in patients with SIVD.

The Associations Between White Matter Disruptions and Cognitive Decline at the Early Stage of Subcortical Vascular Cognitive Impairment: A Case-Control Study

Objective

Emerging evidence suggests that white matter (WM) disruption is associated with the incidence of subcortical vascular cognitive impairment (SVCI). However, our knowledge regarding this relationship in the early stage of SVCI is limited. We aimed to investigate the associations between WM disruptions and cognitive declines at the early stage of SVCI.

Method

We performed a case–control study, involving 22 cases and 19 controls. The cases were patients at the early stage of SVCI, which was defined as subcortical ischemic vascular disease with normal global cognitive measures (pre-SVCI). The controls were healthy people matched by age, sex, and education years. We assessed the differences in a battery of neuropsychological tests between the two groups, investigated the diffusion changes in 40 WM tracts among the participants via an atlas-based segmentation strategy, and compared the differences between the cases and controls by multiple linear regression analysis. We then evaluated the relationships between diffusion indices and cognitive assessment scores by Pearson’s correlation.

Results

The pre-SVCI group exhibited significant differences in the Montreal cognitive assessment (MoCA), Rey–Osterrieth Complex Figure (R-O)-copy, and Trail Making Test (TMT)-B test compared with the controls. Compared with the controls, some long associative and projective bundles, such as the right anterior corona radiata (ACR), the right inferior fronto-occipital fasciculus (IFOF), and the left external capsule (EC), were extensively damaged in cases after Bonferroni correction (p < 0.05/40). Damages to specific fibers, such as the right ACR, IFOF, and posterior thalamic radiation (PTR), exhibited significant correlations with declines in MoCA, R-O delay, and the Mini-Mental State Examination (MMSE), respectively, after Bonferroni correction (p < 0.05/14).

Conclusion

Long WM tracts, especially those in the right hemisphere, were extensively damaged in the pre-SVCI patients and correlated with declines in executive functions and spatial processing. Patients of pre-SVCI are likely at an ultra-early stage of SVCI, and there is a very high risk of this condition becoming SVCI.

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.

White matter hyperintensities in patients with Parkinson's disease: A systematic review and meta-analysis

INTRODUCTION

Mechanisms driving neurodegeneration in Parkinson's disease (PD) are unclear and neurovascular dysfunction may be a contributing factor. White matter hyperintensities (WMH) are commonly found on brain MRI in patients with PD. It is controversial if they are more prevalent or more severe in PD compared with controls. This systematic review aims to answer this question.

METHODS

A systematic search of electronic databases was conducted for studies of WMH in patients with PD. A qualitative synthesis was done for studies reporting WMH prevalence or WMH scores on a visual rating scale (VRS). In studies reporting total WMH volume, the difference between patients with PD and controls was pooled using random effects meta-analysis.

RESULTS

Among 3860 subjects from 24 studies, 2360 were cases and 1500 controls. Fifteen studies reported WMH scores and four studies reported the prevalence of WMH. On VRS, five studies reported no difference in WMH scores, three found higher WMH scores in PD compared to controls, three reported increased WMH scores either in periventricular or deep white matter, and four reported higher scores only in PD with dementia. In studies reporting WMH volume, there was no difference between patients with PD and controls (pooled standardized mean difference = 0.1, 95%CI: -0.1-0.4, I² = 81%).

CONCLUSION

WMH are not more prevalent or severe in patients with PD than in age-matched controls. PD dementia may have more severe WMH compared to controls and PD with normal cognition. Prospective studies using standardized methods of WMH assessment are needed.

Validity and Reliability of the New Chinese Version of the Frontal Assessment Battery-Phonemic

BACKGROUND

Alzheimer's disease dementia (ADD) is an important health problem in the world.

OBJECTIVE

The present study investigated the validity and reliability of a new version of the Frontal Assessment Battery (FAB) named the FAB-phonemic (FAB-P).

METHODS

A total of 76 patients with ADD, 107 patients with amnestic mild cognitive impairment (aMCI), 37 patients with non-amnestic MCI (naMCI), and 123 healthy controls were included in this study. All participants were evaluated with the FAB-P and the cognitive assessments according to a standard procedure.

RESULTS

The global FAB-P scores in patients with ADD were lower than those of patients with aMCI, patients with naMCI, and healthy controls (p < 0.001). Patients with aMCI performed worse than healthy controls (p < 0.001). The interrater reliability, test-retest reliability, and Cronbach's alpha coefficient for the FAB-P were 0.997, 0.819, and 0.736, respectively. The test could distinguish the patients with mild ADD, aMCI, and naMCI from healthy controls with classification accuracy of 89.4%, 70.9%, and 61.6%, respectively. It could also discriminate between the patients with ADD and aMCI, between those with ADD and naMCI, and between those with aMCI and naMCI with classification accuracy of 73.8%, 83.9%, and 58.0%, respectively. The regression analysis revealed that the Montreal Cognitive Assessment and the Stroop Color Word Test Part C had the greatest contribution to FAB-P score variance.

CONCLUSION

The FAB-P is a valid and reliable tool for evaluating frontal lobe function and can effectively discriminate ADD, aMCI, and naMCI.

Discriminating subcortical ischemic vascular disease and Alzheimer's disease by diffusion kurtosis imaging in segregated thalamic regions

Differentiating between subcortical ischemic vascular disease (SIVD), Alzheimer's disease (AD), and normal cognition (NC) remains a challenge, and reliable neuroimaging biomarkers are needed. The current study, therefore, investigated the discriminative ability of diffusion kurtosis imaging (DKI) metrics in segregated thalamic regions and compare with diffusion tensor imaging (DTI) metrics. Twenty‐three SIVD patients, 30 AD patients, and 24 NC participants underwent brain magnetic resonance imaging. The DKI metrics including mean kurtosis (MK), axial kurtosis (K_axial) and radial kurtosis (K_radial) and the DTI metrics including diffusivity and fractional anisotropy (FA) were measured within the whole thalamus and segregated thalamic subregions. Strategic correlations by group, thalamo‐frontal connectivity, and canonical discriminant analysis (CDA) were used to demonstrate the discriminative ability of DKI for SIVD, AD, and NC. Whole and segregated thalamus analysis suggested that DKI metrics are less affected by white matter hyperintensities compared to DTI metrics. Segregated thalamic analysis showed that MK and K_radial were notably different between SIVD and AD/NC. The correlation analysis between K_axial and MK showed a nonsignificant relationship in SIVD group, a trend of negative relationship in AD group, and a significant positive relationship in NC group. A wider spatial distribution of thalamo‐frontal connectivity differences across groups was shown by MK compared to FA. CDA showed a discriminant power of 97.4% correct classification using all DKI metrics. Our findings support that DKI metrics could be more sensitive than DTI metrics to reflect microstructural changes within the gray matter, hence providing complementary information for currently outlined pathogenesis of SIVD and AD.

Using Fractional Anisotropy Imaging to Detect Mild Cognitive Impairment and Alzheimer's Disease among Mexican Americans and Non-Hispanic Whites: A HABLE Study

INTRODUCTION

Alzheimer's disease (AD) is the most frequently occurring neurodegenerative disease; however, little work has been conducted examining biomarkers of AD among Mexican Americans. Here, we examined diffusion tensor MRI marker profiles for detecting mild cognitive impairment (MCI) and dementia in a multi-ethnic cohort.

METHODS

3T MRI measures of fractional anisotropy (FA) were examined among 1,636 participants of the ongoing community-based Health &amp; Aging Brain among Latino Elders (HABLE) community-based study (Mexican American n = 851; non-Hispanic white n = 785).

RESULTS

The FA profile was highly accurate in detecting both MCI (area under the receiver operating characteristic curve [AUC] = 0.99) and dementia (AUC = 0.98). However, the FA profile varied significantly not only between diagnostic groups but also between Mexican Americans and non-Hispanic whites.

CONCLUSION

Findings suggest that diffusion tensor imaging markers may have a role in the neurodiagnostic process for detecting MCI and dementia among diverse populations.

Reduced fractional anisotropy of the genu of the corpus callosum as a cerebrovascular disease marker and predictor of longitudinal cognition in MCI

Our goal was to evaluate the utility of diffusion tensor imaging (DTI) for predicting future cognitive decline in mild cognitive impairment (MCI) in conjunction with Alzheimer's disease (AD) biomarkers (amyloid positron emission tomography and AD signature neurodegeneration) in 132 MCI individuals ≥60 year old with structural magnetic resonance imaging, DTI, amyloid positron emission tomography, and at least one clinical follow-up. We used mixed-effect models to evaluate the prognostic ability of fractional anisotropy of the genu of the corpus callosum (FA-Genu), as a cerebrovascular disease marker, for predicting cognitive decline along with AD biomarkers. We contrasted the value of white matter hyperintensities, a traditional cerebrovascular disease marker as well as FA in the hippocampal cingulum bundle with the FA-Genu models. FA-Genu significantly predicted cognitive decline even after accounting for AD biomarkers. WMH was not associated with cognitive decline in the model with both WMH and FA-Genu. DTI specifically FA-Genu provides unique complementary information to AD biomarkers and has significant utility for prediction of cognitive decline in MCI.

Greater Social Engagement and Greater Gray Matter Microstructural Integrity in Brain Regions Relevant to Dementia

OBJECTIVE

Social engagement (SE) may protect against cognitive decline in older adults. We estimate associations of SE with gray matter (GM) microstructure in regions of interest (ROI) relevant to social cognition, among community-dwelling older adults.

METHOD

Cross-sectional analysis of 293 Health ABC study participants who underwent 3 Tesla magnetic resonance imaging with diffusion tensor and free from cognitive impairment was conducted. Linear regression models tested associations between SE index (marital status, not living alone, social activities, work, and volunteering) and mean diffusivity (MD) of GM ROIs, adjusted for age, race, gender, and education. Hearing and activities of daily living (ADL) difficulties were tested as confounders. Effect modification by gender was tested with interaction terms and stratification by gender.

RESULTS

Higher SE was significantly related to lower MD (greater GM microstructural integrity) (shown as standardized estimate [p-value]) in left middle frontal gyrus-orbital part: -.168 (.005), left caudate nucleus: -.141 (.02), left temporal pole-middle temporal gyrus: -.136 (.03), right middle frontal gyrus: -.160 (.006), right superior frontal gyrus-orbital part: -.187 (.002), and right middle frontal gyrus-orbital part: -.124 (.04), when adjusted for demographic attributes. Associations were robust to adjustments for hearing or ADL difficulty. There was significant effect modification by gender for some ROIs, with associations only for females.

DISCUSSION

SE is related to greater microstructural integrity of specific GM regions relevant to social cognition, that have described roles in dementia. SE may therefore be a useful preventive mechanism against loss of GM integrity in older adults.

Attention and Functional Connectivity Among Patients With Early-Stage Subcortical Ischemic Vascular Disease and Alzheimer's Disease

The current study compared attention profiles and functional connectivity of frontal regions in patients with early-stage subcortical ischemic vascular disease (SIVD) and Alzheimer's disease (AD). Twenty patients with SIVD, 32 patients with AD, and 23 subjects with normal cognition (NC) received cognition and resting-state functional MRI (rs-fMRI) evaluations. The Cognitive Abilities Screening Instrument (CASI) was used to assess global cognition, and simple attention, processing speed, divided attention, and vigilance/sustained attention were evaluated using the Digit Span Forward, Trail Making Test, Symbol Digit Modality Test, and Conners Continuous Performance Test, respectively. Voxel-based regional homogeneity (ReHo) derived from rs-fMRI data was analyzed to identify significant clusters, which were further correlated with attention profiles. Although the patients with SIVD and AD had comparable global cognitive ability, those with SIVD exhibited worse divided attention and vigilance/sustained attention than those with AD. Compared with the NC group, the patients with SIVD exhibited decreased ReHo within the right middle frontal gyrus (MFG) and left anterior cingulate gyrus (ACG), whereas the patients with AD exhibited increased ReHo within the right orbital part of frontal regions. Correlations between these three clusters with attention exhibited distinct patterns according to the dementia subtype, as did attention indices with significance in predicting global cognition. In summary, our study suggested that worse attention performance was associated with functional disconnection within the frontal regions among patients with SIVD than in those with AD. Frontal functional disconnection may underlie the pathogenesis responsible for defective divided attention, vigilance/sustained attention, and notable within-group variations identified in SIVD.

Microstructural Correlates and Laterality Effect of Prospective Memory in Non-Demented Adults with Memory Complaints

BACKGROUND

An increasing number of studies suggest the importance of prospective memory (ProM) due to its functional relevance and sensitivity to neuropathology. However, its relevant neural substrates have not been sufficiently explored.

OBJECTIVES

The present study aimed to investigate the relationship between structural connectivity and both objective and subjective ProM measures in a group of non-demented people with subjective memory complaints, and to examine the potential of ProM measures to detect the difference between subjective cognitive decline (SCD) and mild cognitive impairment (MCI) in the pre-dementia stage.

METHOD

Thirty-sevennon-dementedparticipants aged above 50 years were recruited from an outpatient Neurology Clinic; 13 of them fulfilled the criteria of MCI and 24 of SCD. All subjects received comprehensive neuropsychological tests, including the adapted version of the Cambridge Prospective Memory Test, as well as the Taiwan version of the Prospective and Retrospective Memory Questionnaire. The diffusion tensor imaging technique with tract-based spatial statistics was applied to measure cerebral microstructural changes.

RESULTS

Time-based ProM performance was significantly correlated with microstructural integrity of the right superior longitudinal fasciculus, while the event-based one was associated with that of the left superior longitudinal fasciculus and the genu of the corpus callosum among all participants and in the SCD group. After controlling for age, the correlation remained significant between event-based ProM performance and the left superior longitudinal fasciculus among all participants and in the MCI group, as well as between event-based ProM performance and the genu among all participants. Although self-reported ProM failures in real life was associated with fiber disruption of the left superior longitudinal fasciculus among all participants and within the MCI group, an inverse relationship was also observed with that of the corpus callosum in the SCD group even after controlling for age. As compared to the SCD group, people with MCI performed significantly worse on time-based ProM tasks and reported more ProM failures in daily life.

CONCLUSIONS

ProM was related to the integrity of interhemispheric commissural fibers and association fibers that connect the frontal lobe with posterior regions, with a task-specific laterality effect. Time-based ProM tasks and self-reported ProM questionnaire may be sensitive to early pathological cognitive deterioration, while the concomitant aging process and individual awareness level may respectively confound the results of evaluation.

Altered functional connectivity in patients with subcortical ischemic vascular disease: A resting-state fMRI study

Patients with subcortical ischemic vascular disease (SIVD) may hold a high risk of cognitive impairment (CI) by affecting the functional connectivity (FC) of resting-state networks (RSNs). Current studies have mainly focused on the patients with CI but have ignored the prodromal stage when people suffered subcortical vascular damage, but without CI. Independent component analysis (ICA) of rs-fMRI could detect altered FC in RSNs at the early stage of the disease. 81 SIVD patients with CI (SVCI = 29) and without CI (pre-SVCI = 25), and 27 normal controls (NCs) were scanned with rs-fMRI, analyzed by ICA and assessed by neuropsychological examinations. We found significantly altered FC within the RSNs of sensorimotor network (SMN), posterior default mode networks (pDMN), right frontoparietal network (rFPN) and language network (LN) (P < 0.05, AlphaSim corrected). The pre-SVCI group showed significantly increased FC in brain regions of the multiple RSNs when compared with the other two groups. The mean values extracted from the right inferior frontal gyrus (IFG.R) and the left posterior cingulate gyrus (PCG.L) were significantly correlated with clock drawing test (CDT). The right precentral/postcentral gyrus (PreCG.R/PoCG.R) and the right supramarginal gyrus (SMG.R) were positively correlated with Stroop-1 Test. We concluded the FC in RSNs had already been changed at the early stage of the disease as the maladaptive response or compensatory reallocation of the cognitive resources. The ICA of rs-fMRI can be applied as a potential approach to identify the underlying mechanisms of SIVD.

Review of diffusion MRI studies in chronic white matter diseases

Diffusion MRI studies characterizing the changes in white matter (WM) due to vascular cognitive impairment, which includes all forms of small vessel disease are reviewed. We reviewed the usefulness of diffusion methods in discriminating the affected WM regions and its relation to cognitive impairment. These studies were categorized based on the diffusion MRI techniques used. The most common method was the diffusion tensor imaging, whereas other methods included diffusion weighted imaging, diffusion kurtosis imaging, intravoxel incoherent motion, and studies based on diffusion tractography. The diffusion measures showed correlation with cognitive scores and disease progression, with mean diffusivity being the most robust parameter. Future studies should focus on incorporating multi-compartment and higher order diffusion models, which can handle the presence of multiple and crossing fibers inside a voxel.

Development of a cerebrovascular magnetic resonance imaging biomarker for cognitive aging

OBJECTIVE

Recent availability of amyloid and tau positron emission tomography (PET) has provided us with a unique opportunity to measure the association of systemic vascular health with brain health after accounting for the impact of Alzheimer disease (AD) pathologies. We wanted to quantify early cerebrovascular health-related magnetic resonance imaging brain measures (structure, perfusion, microstructural integrity) and evaluate their utility as a biomarker for cerebrovascular health.

METHODS

We used 2 independent samples (discovery, n = 390; validation, n = 1,035) of individuals, aged ≥ 60 years, along the cognitive continuum with imaging from the population-based sample of Mayo Clinic Study of Aging. We ascertained vascular health by summing up recently existing cardiovascular and metabolic conditions (CMC) from health care records (hypertension, hyperlipidemia, cardiac arrhythmias, coronary artery disease, congestive heart failure, diabetes mellitus, and stroke). Using multiple regression models, we quantified associations between CMC and brain health after accounting for age, sex, education/occupation, and AD burden (from amyloid and tau PET).

RESULTS

Systemic vascular health was associated with medial temporal lobe thinning, widespread cerebral hypoperfusion, and loss of microstructural integrity in several white matter tracts including the corpus callosum and fornix. Further investigations suggested that microstructural integrity of the genu of the corpus callosum was suitable for assessing prodromal cerebrovascular health, had similar distributions in the discovery and independent validation datasets, and predicted cognitive performance above and beyond amyloid deposition.

INTERPRETATION

Systemic vascular health has significant impact on brain structure and function. Quantifying prodromal cerebrovascular health-related brain measures that are independent of AD pathology-related changes has great utility for cognitive aging. Ann Neurol 2018;84:713-724.

Visual Attention Performances and Related Cerebral Microstructural Integrity Among Subjects With Subjective Cognitive Decline and Mild Cognitive Impairment

Objective: To compare visual attention performances and diffusion tensor imaging (DTI) between subjects with subjective cognitive decline (SCD) and mild cognitive impairment (MCI), and to discover neuronal substrates related to visual attention performances. Methods: Thirty-nine subjects with SCD and 15 with MCI, diagnosed following neuropsychological tests and conventional brain magnetic resonance imaging, were recruited. All subjects were further examined by the Conners Continuous Performance Test 3 (CPT3) and DTI including fractional anisotropy (FA) and mean diffusivity (MD), in which group comparisons and stepwise linear regression were made. Results: Subjects with MCI had a worse performance in all retrieval indices of verbal/nonverbal memory tests than those with SCD in the context of comparable general cognition and demographic status. In the CPT3, subjects with MCI had a significant longer hit reaction time (HRT) by univariate but not multivariate comparisons. Further analysis suggested that a longer HRT across all interstimuli intervals and at the point of fourth to sixth blocks were noted among MCI subjects. In DTI evaluations, FA value within the left forceps major was the only hotspot with significant between-group differences after the Bonferroni correction of FA and MD values. On the basis that HRT had significant inverse correlations with FA value within the genu of the corpus callosum and left forceps minor, regression analysis was conducted, showing HRT was best predicted by the FA value within the left forceps minor. Area under receiver operative characteristic curve was 0.70; the optimum cut-off for HRT was 515.8 ms, with a sensitivity of 85% but specificity of 47%. Conclusions: Our report suggested that impaired sustained attention and vigilance to be an early cognitive marker in differentiating MCI from SCD, where MCI subjects had a longer HRT across all interstimuli intervals and more profoundly in later blocks. FA measures appeared to be more sensitive DTI parameters than MD values in detecting microstructural changes between SCD and MCI. The role of the anterior interhemispheric fibers in sustained attention implementation during visual signal detection task was highlighted.

Sleep Disorders Associated With Alzheimer's Disease: A Perspective

Sleep disturbances, as well as sleep-wake rhythm disturbances, are typical symptoms of Alzheimer's disease (AD) that may precede the other clinical signs of this neurodegenerative disease. Here, we describe clinical features of sleep disorders in AD and the relation between sleep disorders and both cognitive impairment and poor prognosis of the disease. There are difficulties of the diagnosis of sleep disorders based on sleep questionnaires, polysomnography or actigraphy in the AD patients. Typical disturbances of the neurophysiological sleep architecture in the course of the AD include deep sleep and paradoxical sleep deprivation. Among sleep disorders occurring in patients with AD, the most frequent disorders are sleep breathing disorders and restless legs syndrome. Sleep disorders may influence circadian fluctuations of the concentrations of amyloid-β in the interstitial brain fluid and in the cerebrovascular fluid related to the glymphatic brain system and production of the amyloid-β. There is accumulating evidence suggesting that disordered sleep contributes to cognitive decline and the development of AD pathology. In this mini-review, we highlight and discuss the association between sleep disorders and AD.

Data-Driven Differential Diagnosis of Dementia Using Multiclass Disease State Index Classifier

Clinical decision support systems (CDSSs) hold potential for the differential diagnosis of neurodegenerative diseases. We developed a novel CDSS, the PredictND tool, designed for differential diagnosis of different types of dementia. It combines information obtained from multiple diagnostic tests such as neuropsychological tests, MRI and cerebrospinal fluid samples. Here we evaluated how the classifier used in it performs in differentiating between controls with subjective cognitive decline, dementia due to Alzheimer's disease, vascular dementia, frontotemporal lobar degeneration and dementia with Lewy bodies. We used the multiclass Disease State Index classifier, which is the classifier used by the PredictND tool, to differentiate between controls and patients with the four different types of dementia. The multiclass Disease State Index classifier is an extension of a previously developed two-class Disease State Index classifier. As the two-class Disease State Index classifier, the multiclass Disease State Index classifier also offers a visualization of its decision making process, which makes it especially suitable for medical decision support where interpretability of the results is highly important. A subset of the Amsterdam Dementia cohort, consisting of 504 patients (age 65 ± 8 years, 44% females) with data from neuropsychological tests, cerebrospinal fluid samples and both automatic and visual MRI quantifications, was used for the evaluation. The Disease State Index classifier was highly accurate in separating the five classes from each other (balanced accuracy 82.3%). Accuracy was highest for vascular dementia and lowest for dementia with Lewy bodies. For the 50% of patients for which the classifier was most confident on the classification the balanced accuracy was 93.6%. Data-driven CDSSs can be of aid in differential diagnosis in clinical practice. The decision support system tested in this study was highly accurate in separating the different dementias and controls from each other. In addition to the predicted class, it also provides a confidence measure for the classification.

Specific Patterns of White Matter Alterations Help Distinguishing Alzheimer's and Vascular Dementia

Alzheimer disease (AD) and vascular dementia (VaD) together represent the majority of dementia cases. Since their neuropsychological profiles often overlap and white matter lesions are observed in elderly subjects including AD, differentiating between VaD and AD can be difficult. Characterization of these different forms of dementia would benefit by identification of quantitative imaging biomarkers specifically sensitive to AD or VaD. Parameters of microstructural abnormalities derived from diffusion tensor imaging (DTI) have been reported to be helpful in differentiating between dementias, but only few studies have used them to compare AD and VaD with a voxelwise approach. Therefore, in this study a whole brain statistical analysis was performed on DTI data of 93 subjects (31 AD, 27 VaD, and 35 healthy controls—HC) to identify specific white matter patterns of alteration in patients affected by VaD and AD with respect to HC. Parahippocampal tracts were found to be mainly affected in AD, while VaD showed more spread white matter damages associated with thalamic radiations involvement. The genu of the corpus callosum was predominantly affected in VaD, while the splenium was predominantly affected in AD revealing the existence of specific patterns of alteration useful in distinguishing between VaD and AD. Therefore, DTI parameters of these regions could be informative to understand the pathogenesis and support the etiological diagnosis of dementia. Further studies on larger cohorts of subjects, characterized for brain amyloidosis, will allow to confirm and to integrate the present findings and, furthermore, to elucidate the mechanisms of mixed dementia. These steps will be essential to translate these advances to clinical practice.