Diffusion tensor imaging of white matter degeneration in Alzheimer’s disease and mild cognitive impairment

Neural Correlates of Cognitive Performance in Alzheimer's Disease- and Lewy Bodies-Related Cognitive Impairment

BACKGROUND

Clinicopathological studies have demonstrated that the neuropsychological profiles and outcomes are different between two dementia subtypes, namely Alzheimer's disease (AD) and Lewy bodies-related disease.

OBJECTIVE

We investigated the neural correlates of cognitive dysfunction in patients with AD-related cognitive impairment (ADCI) and those with Lewy bodies-related cognitive impairment (LBCI).

METHODS

We enrolled 216 ADCI patients, 183 LBCI patients, and 30 controls. Cortical thickness and diffusion tensor imaging analyses were performed to correlate gray matter and white matter (WM) abnormalities to cognitive composite scores for memory, visuospatial, and attention/executive domains in the ADCI spectrum (ADCI patients and controls) and the LBCI spectrum (LBCI patients and controls) separately.

RESULTS

Memory dysfunction correlated with cortical thinning and increased mean diffusivity in the AD-prone regions, particularly the medial temporal region, in ADCI. Meanwhile, it only correlated with increased mean diffusivity in the WM adjacent to the anteromedial temporal, insula, and basal frontal cortices in LBCI. Visuospatial dysfunction correlated with cortical thinning in posterior brain regions in ADCI, while it correlated with decreased fractional anisotropy in the corpus callosum and widespread WM regions in LBCI. Attention/executive dysfunction correlated with cortical thinning and WM abnormalities in widespread brain regions in both disease spectra; however, ADCI had more prominent correlation with cortical thickness and LBCI did with fractional anisotropy values.

CONCLUSIONS

Our study demonstrated that ADCI and LBCI have different neural correlates with respect to cognitive dysfunction. Cortical thinning had greater effects on cognitive dysfunction in the ADCI, while WM disruption did in the LBCI.

Acute cognitive impairment after traumatic brain injury predicts the occurrence of brain atrophy patterns similar to those observed in Alzheimer's disease

Traumatic brain injuries (TBIs) are often followed by persistent structural brain alterations and by cognitive sequalae, including memory deficits, reduced neural processing speed, impaired social function, and decision-making difficulties. Although mild TBI (mTBI) is a risk factor for Alzheimer's disease (AD), the extent to which these conditions share patterns of macroscale neurodegeneration has not been quantified. Comparing such patterns can not only reveal how the neurodegenerative trajectories of TBI and AD are similar, but may also identify brain atrophy features which can be leveraged to prognosticate AD risk after TBI. The primary aim of this study is to systematically map how TBI affects white matter (WM) and gray matter (GM) properties in AD-analogous patterns. Our findings identify substantial similarities in the regional macroscale neurodegeneration patterns associated with mTBI and AD. In cerebral GM, such similarities are most extensive in brain areas involved in memory and executive function, such as the temporal poles and orbitofrontal cortices, respectively. Our results indicate that the spatial pattern of cerebral WM degradation observed in AD is broadly similar to the pattern of diffuse axonal injury observed in TBI, which frequently affects WM structures like the fornix, corpus callosum, and corona radiata. Using machine learning, we find that the severity of AD-like brain changes observed during the chronic stage of mTBI can be accurately prognosticated based on acute assessments of post-traumatic mild cognitive impairment. These findings suggest that acute post-traumatic cognitive impairment predicts the magnitude of AD-like brain atrophy, which is itself associated with AD risk.

Late-life cynical hostility is associated with white matter alterations and the risk of Alzheimer's disease

BACKGROUND

Cynical hostility (CH), a specific dimension of hostility that consists of a mistrust of others, has been suggested as a high-risk trait for dementia. However, the influence of CH on the incidence of Alzheimer's disease (AD) remains poorly understood. This study investigated whether late-life CH is associated with AD risk and structural neuroimaging markers of AD.

METHODS

In community-dwelling older adults from the French ESPRIT cohort (n = 1388), incident dementia rate according to CH level was monitored during an 8-year follow-up and analyzed using Cox proportional hazards regression models. Brain magnetic resonance imaging volumes were measured at baseline (n = 508). Using automated segmentation procedures (Freesurfer 6.0), the authors assessed brain grey and white volumes on all magnetic resonance imaging scans. They also measured white matter hyperintensities volumes using semi-automated procedures. Mean volumes according to the level of CH were compared using ANOVA.

RESULTS

Eighty-four participants developed dementia (32 with AD). After controlling for potential confounders, high CH was predictive of AD (HR 2.74; 95% CI 1.10-6.85; p = 0.030) and all dementia types are taken together (HR 2.30; 95% CI 1.10-4.80; p = 0.027). High CH was associated with white matter alterations, particularly smaller anterior corpus callosum volume (p < 0.01) after False Discovery Rate correction, but not with grey matter volumes.

CONCLUSIONS

High CH in late life is associated with cerebral white matter alterations, designated as early markers of dementia, and higher AD risk. Identifying lifestyle and biological determinants related to CH could provide clues on AD physiopathology and avenues for prevention strategies.

Microstructural changes in the cingulate gyrus of patients with mild cognitive impairment induced by cerebral small vessel disease

Objective: The purpose of our study was to distinguish the changes in the microstructure of the cingulate cortex in patients with mild cognitive impairment (MCI) induced by cerebral small vessel disease (CSVD).Method: 80 patients were diagnosed with CSVD in this study, including 55 patients with MCI and 25 patients without MCI. Diffusion kurtosis imaging (DKI) and Montreal cognitive assessment (MoCA) were performed in all patients. The anterior cingulate gyrus, posterior cingulate gyrus and middle cingulate gyrus were selected as the regions of interest, and some parameters were recorded.Results: Compared with the non-MCI group, the MCI group mainly showed obviously higher mean diffusion (MD) and radial diffusion (RD) values (P = 0.022 and P = 0.029) but lower fractional anisotropy (FA), axial kurtosis (AK), mean kurtosis (MK) and radial kurtosis (RK) values (P = 0.047, P = 0.001, P < 0.01, and P = 0.001, respectively) in the right anterior cingulate gyrus. Meanwhile, in the right posterior cingulate gyrus, the MCI group also showed higher axial diffusion (AD) and MD (P = 0.027 and P = 0.030) and lower AK (P = 0.014). Additionally, negative correlations of AD, MD, and RD with MoCA scores and positive correlations of FA, AK, MK and RK with MoCA scores were observed in some regions of the cingulate gyrus.Conclusions: DKI is a good method to examine microstructural damage in the cingulate cortex, and some parameters of DKI may be used as imaging biomarkers to detect early MCI in patients with CSVD.

Alterations and Associations Between Magnetic Susceptibility of the Basal Ganglia and Diffusion Properties in Alzheimer's Disease

This study adopted diffusion tensor imaging to detect alterations in the diffusion parameters of the white matter fiber in Alzheimer's disease (AD) and used quantitative susceptibility mapping to detect changes in magnetic susceptibility. However, whether the changes of susceptibility values due to excessive iron in the basal ganglia have correlations with the alterations of the diffusion properties of the white matter in patients with AD are still unknown. We aim to investigate the correlations among magnetic susceptibility values of the basal ganglia, diffusion indexes of the white matter, and cognitive function in patients with AD. Thirty patients with AD and nineteen healthy controls (HCs) were recruited. Diffusion indexes of the whole brain were detected using tract-based spatial statistics. The caudate nucleus, putamen, and globus pallidus were selected as regions of interest, and their magnetic susceptibility values were measured. Compared with HCs, patients with AD showed that there were significantly increased axial diffusivity (AxD) in the internal capsule, superior corona radiata (SCR), and right anterior corona radiata (ACR); increased radial diffusivity (RD) in the right anterior limb of the internal capsule, ACR, and genu of the corpus callosum (GCC); and decreased fractional anisotropy (FA) in the right ACR and GCC. The alterations of RD values, FA values, and susceptibility values of the right caudate nucleus in patients with AD were correlated with cognitive scores. Besides, AxD values in the right internal capsule, ACR, and SCR were positively correlated with the magnetic susceptibility values of the right caudate nucleus in patients with AD. Our findings revealed that the magnetic susceptibility of the caudate nucleus may be an MRI-based biomarker of the cognitive dysfunction of AD and abnormal excessive iron distribution in the basal ganglia had adverse effects on the diffusion properties of the white matter.

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.

Small vessel disease more than Alzheimer's disease determines diffusion MRI alterations in memory clinic patients

INTRODUCTION

Microstructural alterations as assessed by diffusion tensor imaging (DTI) are key findings in both Alzheimer's disease (AD) and small vessel disease (SVD). We determined the contribution of each of these conditions to diffusion alterations.

METHODS

We studied six samples (N = 365 participants) covering the spectrum of AD and SVD, including genetically defined samples. We calculated diffusion measures from DTI and free water imaging. Simple linear, multivariable random forest, and voxel-based regressions were used to evaluate associations between AD biomarkers (amyloid beta, tau), SVD imaging markers, and diffusion measures.

RESULTS

SVD markers were strongly associated with diffusion measures and showed a higher contribution than AD biomarkers in multivariable analysis across all memory clinic samples. Voxel-wise analyses between tau and diffusion measures were not significant.

DISCUSSION

In memory clinic patients, the effect of SVD on diffusion alterations largely exceeds the effect of AD, supporting the value of diffusion measures as markers of SVD.

Morphological and microstructural brain changes in thyroid-associated ophthalmopathy: a combined voxel-based morphometry and diffusion tensor imaging study

PURPOSE

To explore the morphological and microstructural changes of grey and white matter in the patients of thyroid-associated ophthalmopathy (TAO).

METHODS

Twenty-five TAO patients and 25 well-matched healthy controls were recruited. Structural T1- and diffusion-weighted magnetic resonance imaging data were analyzed using voxel-based morphometry and voxel-based analysis of diffusion tensor imaging.

RESULTS

Compared with healthy controls, TAO group showed significantly decreased grey matter volume in the brain region of the right middle frontal gyrus. Meanwhile, TAO group showed significantly decreased fractional anisotropy (FA), but increased mean, axial and radial diffusivities in the brain regions of the right superior occipital gyrus, middle occipital gyrus and cuneus in TAO group. In addition, the FA value in significant brain regions showed a positive correlation with visual acuity (r = 0.456, P = 0.025) and a negative correlation with disease duration (r =  - 0.609, P = 0.003).

CONCLUSION

Significant morphological and microstructural abnormalities in areas corresponding to known functional deficits of vision and cognition could be found in TAO patients. These results extended our understanding of neural relationships with TAO.

Aberrant White Matter Microstructure as a Potential Diagnostic Marker in Alzheimer's Disease by Automated Fiber Quantification

Neuroimaging evidence has suggested white matter microstructure are heavily affected in Alzheimer's disease (AD). However, whether white matter dysfunction is localized at the specific regions of fiber tracts and whether they would be a potential biomarker for AD remain unclear. By automated fiber quantification (AFQ), we applied diffusion tensor images from 25 healthy controls (HC), 24 amnestic mild cognitive impairment (aMCI) patients and 18 AD patients to create tract profiles along 16 major white matter fibers. We compared diffusion metrics [Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (DA), and radial diffusivity (DR)] between groups. To assess the diagnostic value, we applied a random forest (RF) classifier, a type of machine learning method. In the global tract level, we found that aMCI and AD patients showed higher MD, DA, and DR values in some fiber tracts mostly in the left hemisphere compared to HC. In the point-wise level, widespread disruption were distributed on specific locations of different tracts. The point-wise MD measurements presented the best classification performance with respect to differentiating AD from HC. The two most important variables were localized in the prefrontal potion of left uncinate fasciculus and anterior thalamic radiation. In addition, the point-wise DA in the posterior component of the left cingulum cingulate displayed the most robust discriminative ability to identify AD from aMCI. Our findings provide evidence that white matter abnormalities based on the AFQ method could be as a diagnostic biomarker in AD.

Diffusion MRI detects early brain microstructure abnormalities in 2-month-old 3×Tg-AD mice

The 3×Tg-AD mouse is one of the most studied animal models of Alzheimer's disease (AD), and develops both amyloid beta deposits and neurofibrillary tangles in a temporal and spatial pattern that is similar to human AD pathology. Additionally, abnormal myelination patterns with changes in oligodendrocyte and myelin marker expression are reported to be an early pathological feature in this model. Only few diffusion MRI (dMRI) studies have investigated white matter abnormalities in 3×Tg-AD mice, with inconsistent results. Thus, the goal of this study was to investigate the sensitivity of dMRI to capture brain microstructural alterations in 2-month-old 3×Tg-AD mice. In the fimbria, the fractional anisotropy (FA), kurtosis fractional anisotropy (KFA), and radial kurtosis (K┴ ) were found to be significantly lower in 3×Tg-AD mice than in controls, while the mean diffusivity (MD) and radial diffusivity (D┴ ) were found to be elevated. In the fornix, K┴ was lower for 3×Tg-AD mice; in the dorsal hippocampus MD and D┴ were elevated, as were FA, MD, and D┴ in the ventral hippocampus. These results indicate, for the first time, dMRI changes associated with myelin abnormalities in young 3×Tg-AD mice, before they develop AD pathology. Morphological quantification of myelin basic protein immunoreactivity in the fimbria was significantly lower in the 3×Tg-AD mice compared with the age-matched controls. Our results demonstrate that dMRI is able to detect widespread, significant early brain morphological abnormalities in 2-month-old 3×Tg-AD mice.

Genome-wide interaction analysis of pathological hallmarks in Alzheimer's disease

Genome-wide association studies have identified many loci associated with Alzheimer's dementia. However, these variants only explain part of the heritability of Alzheimer's disease (AD). As genetic epistasis can be a major contributor to the "missing heritability" of AD, we conducted genome-wide epistasis screening for AD pathologies in 2 independent cohorts. First, we performed a genome-wide epistasis study of AD-related brain pathologies (N_max = 1318) in ROS/MAP. Candidate interactions were validated using cerebrospinal fluid biomarkers of AD in ADNI (N_max = 1128). Further functional analysis tested the association of candidate interactions with neuroimaging phenotypes. For tau and amyloid-β pathology, we identified 2803 and 464 candidate SNP-SNP interactions, respectively. Associations of candidate SNP-SNP interactions with brain volume and white matter changes from neuroimages provides additional insights into their molecular functions. Transcriptional analysis supported possible gene-gene interactions identified by statistical screening through their co-expression in the brain. In summary, we outlined an exhaustive epistasis analysis to identify novel genetic interactions with potential roles in AD pathologies. We further delved into the functional relevance of candidate interactions by association with neuroimaging phenotypes and analysis of co-expression between corresponding gene pairs.

The individualized prediction of cognitive test scores in mild cognitive impairment using structural and functional connectivity features

Neuropsychological assessments are essential in diagnosing age-related neurocognitive disorders. However, they are lengthy in duration and can be unreliable at times. To this end, we explored a modified connectome-based predictive modeling approach to estimating individualized scores from multiple cognitive domains using structural connectivity (SC) and functional connectivity (FC) features. Multi-shell HARDI and resting-state functional magnetic resonance imaging scans, and scores from 10 cognitive measures were acquired from 91 older adults with mild cognitive impairment. SC and FC matrices were derived from these scans and, in various combinations, entered into models along with demographic covariates to predict cognitive scores. Leave-one-out cross-validation was performed. Predictive accuracy was assessed via the correlation between predicted and observed scores (r_{predicted-observed}). Across all cognitive measures, significant r_{predicted-observed} (0.402 to 0.654) were observed from the best-predicting models. Six of these models consisted of multimodal features. For three cognitive measures, their best-predicting models' r_{predicted-observed} were similar to that of a model that included only demographic covariates- suggesting that SC and/or FC features did not contribute significantly on top of demographics. Cross-prediction models revealed that the best-predicting models were similarly accurate in predicting scores of related cognitive measures- suggesting their limited specificity in predicting cognitive scores. Generally, multimodal connectomes together with demographics, can be exploited as sensitive markers, though with limited specificity, to predict cognitive performance across a spectrum in multiple cognitive domains. In certain situations, it may not be worthwhile to acquire neuroimaging data, considering that demographics alone can be similarly accurate in predicting cognitive scores.

Early-Stage Identification and Pathological Development of Alzheimer's Disease Using Multimodal MRI

Alzheimer's disease (AD) is one of the most common progressive and irreversible neurodegenerative diseases. The study of the pathological mechanism of AD and early-stage diagnosis is essential and important. Subjective cognitive decline (SCD), the first at-risk stage of AD occurring prior to amnestic mild cognitive impairment (aMCI), is of great research value and has gained our interest. To investigate the entire pathological development of AD pathology efficiently, we proposed a machine learning classification method based on a multimodal support vector machine (SVM) to investigate the structural and functional connectivity patterns of the three stages of AD (SCD, aMCI, and AD). Our experiments achieved an accuracy of 98.58% in the AD group, 97.76% in the aMCI group, and 80.24% in the SCD group. Moreover, in our experiments, we identified the most discriminating brain regions, which were mainly located in the default mode network and subcortical structures (SCS). Notably, with the development of AD pathology, SCS regions have become increasingly important, and structural connectivity has shown more discriminative power than functional connectivity. The current study may shed new light on the pathological mechanism of AD and suggests that whole-brain connectivity may provide potential effective biomarkers for the early-stage diagnosis of AD.

Blood and cerebrospinal fluid neurofilament light differentially detect neurodegeneration in early Alzheimer's disease

Cerebrospinal fluid (CSF) neurofilament light (NfL) concentration has reproducibly been shown to reflect neurodegeneration in brain disorders, including Alzheimer's disease (AD). NfL concentration in blood correlates with the corresponding CSF levels, but few studies have directly compared the reliability of these 2 markers in sporadic AD. Herein, we measured plasma and CSF concentrations of NfL in 478 cognitively unimpaired (CU) subjects, 227 patients with mild cognitive impairment, and 113 patients with AD dementia. We found that the concentration of NfL in CSF, but not in plasma, was increased in response to Aβ pathology in CU subjects. Both CSF and plasma NfL concentrations were increased in patients with mild cognitive impairment and AD dementia. Furthermore, only NfL in CSF was associated with reduced white matter microstructure in CU subjects. Finally, in a transgenic mouse model of AD, CSF NfL increased before serum NfL in response to the development of Aβ pathology. In conclusion, NfL in CSF may be a more reliable biomarker of neurodegeneration than NfL in blood in preclinical sporadic AD.

Relationship between white matter glucose metabolism and fractional anisotropy in healthy and schizophrenia subjects

Decreased fractional anisotropy and increased glucose utilization in the white matter have been reported in schizophrenia. These findings may be indicative of an inverse relationship between these measures of white matter integrity and metabolism. We used ¹⁸F-fluorodeoxyglucose positron emission tomography and diffusion-tensor imaging in 19 healthy and 25 schizophrenia subjects to assess and compare coterritorial correlation patterns between glucose utilization and fractional anisotropy on a voxel-by-voxel basis and across a range of automatically placed representative white matter regions of interest. We found a pattern of predominantly negative correlations between white matter metabolism and fractional anisotropy in both healthy and schizophrenia subjects. The overall strength of the relationship was attenuated in subjects with schizophrenia, who displayed significantly fewer and weaker correlations in all regions assessed with the exception of the corpus callosum. This attenuation was most prominent in the left prefrontal white matter and this region also best predicted the diagnosis of schizophrenia. There exists an inverse relationship between the measures of white matter integrity and metabolism, which may therefore be physiologically linked. In subjects with schizophrenia, hypermetabolism in the white matter may be a function of lower white matter integrity, with lower efficiency and increased energetic cost of task-related computations.

Medial temporal lobe white matter pathway variability is associated with individual differences in episodic memory in cognitively normal older adults

Significant evidence demonstrates that aging is associated with variability in cognitive performance, even among individuals who are cognitively normal. In this study, we examined measures from magnetic resonance imaging and cerebrospinal fluid (CSF) to investigate which measures, alone or in combination, were associated with individual differences in episodic memory performance. Using hierarchical linear regressions, we compared the ability of diffusion tensor imaging (DTI) metrics, CSF measures of amyloid and tau, and gray matter volumes to explain variability in memory performance in a cohort of cognitively normal older adults. Measures of DTI microstructure were significantly associated with variance in memory performance, even after accounting for the contribution of the CSF and magnetic resonance imaging gray matter volume measures. Significant associations were found between DTI measures of the hippocampal cingulum and fornix with individual differences in memory. No such relationships were found between memory performance and CSF markers or gray matter volumes. These findings suggest that DTI metrics may be useful in identifying changes associated with aging or age-related diseases.

Radial diffusivity is the best global biomarker able to discriminate healthy elders, mild cognitive impairment, and Alzheimer's disease: A diagnostic study of DTI-derived data

INTRODUCTION

For the past two decades, diffusion tensor imaging (DTI)-derived metrics allowed the characterization of Alzheimer's disease (AzD). Previous studies reported only a few parameters (most commonly fractional anisotropy, mean diffusivity, and axial and radial diffusivities measured at selected regions). We aimed to assess the diagnostic performance of 11 DTI-derived tensor metrics by using a global approach.

MATERIALS AND METHODS

A prospective study performed in 34 subjects: 12 healthy elders, 11 mild cognitive impairment (MCI) patients, and 11 patients with AzD. Postprocessing of DTI magnetic resonance imaging allowed the calculation of 11 tensor metrics. Anisotropies included fractional (FA), and relative (RA). Diffusivities considered simple isotropic diffusion (p), simple anisotropic diffusion (q), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD). Tensors included the diffusion tensor total magnitude (L); and the linear (Cl), planar (Cp), and spherical tensors (Cs). We performed a multivariate discriminant analysis and diagnostic tests assessment.

RESULTS

RD was the only variable selected to assemble a predictive model: Wilks' λ = 0.581, χ2 (2) = 14.673, P = 0.001. The model's overall accuracy was 64.5%, with areas under the curve of 0.81, 0.73 and 0.66 to diagnose AzD, MCI, and healthy brains, respectively.

CONCLUSIONS

Global DTI-derived RD alone can discriminate between healthy elders, MCI, and AzD patients. Although this study proves evidence of a potential biomarker, it does not provide clinical guidance yet. Additional studies comparing DTI metrics might determine their usefulness to monitor disease progression, measure outcome in drug trials, and even perform the screening of pre-AzD subjects.

Correlation of microglial activation with white matter changes in dementia with Lewy bodies

Dementia with Lewy bodies (DLB) is characterized by alpha-synuclein protein deposition with variable degree of concurrent Alzheimer's pathology. Neuroinflammation is also increasingly recognized as a significant contributor to degeneration. We aimed to examine the relationship between microglial activation as measured with [¹¹C]-PK11195 brain PET, MR diffusion tensor imaging (DTI) and grey matter atrophy in DLB. Nineteen clinically probable DLB and 20 similarly aged controls underwent 3T structural MRI (T1-weighted) and diffusion-weighted imaging. Eighteen DLB subjects also underwent [¹¹C]-PK11195 PET imaging and 15 had [¹¹C]-Pittsburgh compound B amyloid PET, resulting in 9/15 being amyloid-positive. We used Computational Anatomy Toolbox (CAT12) for volume-based morphometry (VBM) and Tract-Based Spatial Statistics (TBSS) for DTI to assess group comparisons between DLB and controls and to identify associations of [¹¹C]-PK11195 binding with grey/white matter changes and cognitive score in DLB patients. VBM analyses showed that DLB had extensive reduction of grey matter volume in superior frontal, temporal, parietal and occipital cortices (family-wise error (FWE)-corrected p < 0.05). TBSS showed widespread changes in DLB for all DTI parameters (reduced fractional anisotropy, increased diffusivity), involving the corpus callosum, corona radiata and superior longitudinal fasciculus (FWE-corrected p < 0.05). Higher [¹¹C]-PK11195 binding in parietal cortices correlated with widespread lower mean and radial diffusivity in DLB patients (FWE-corrected p < 0.05). Furthermore, preserved cognition in DLB (higher Addenbrookes Cognitive Evaluation revised score) also correlated with higher [¹¹C]-PK11195 binding in frontal, temporal, and occipital lobes. However, microglial activation was not significantly associated with grey matter changes. Our study suggests that increased microglial activation is associated with a relative preservation of white matter and cognition in DLB, positioning neuroinflammation as a potential early marker of DLB etio-pathogenesis.

White matter and its relationship with cognition in subjective cognitive decline

INTRODUCTION

Subjective cognitive decline (SCD) is the earliest stage on the continuum toward Alzheimer's disease. This study examined (1) differences in white matter integrity between individuals with SCD and healthy control subjects and (2) how white matter integrity related to memory and executive function.

METHODS

Diffusion tensor imaging and neuropsychological assessment data were retrieved from the Alzheimer's Disease Neuroimaging Initiative database for 30 individuals with SCD and 44 control subjects.

RESULTS

Results revealed significantly lower white matter integrity in individuals with SCD relative to control subjects in widespread regions, including the bilateral corticospinal tracts, superior and inferior longitudinal fasciculi, fronto-occipital fasciculi, corpus callosum, forceps major and minor, hippocampi, anterior thalamic radiations, and the cerebellum. There was a widespread relationship between diffusion tensor imaging metrics and executive function in SCD, but not healthy control subjects, and no relationship with memory for either group.

DISCUSSION

Relatively lower white matter integrity in SCD may be a useful early biomarker for risk of future cognitive decline. Future research should better characterize the SCD group longitudinally and in individuals at risk for Alzheimer's disease.

White matter hypointensities and hyperintensities have equivalent correlations with age and CSF β-amyloid in the nondemented elderly

INTRODUCTION

T1- and T2-weighted sequences from MRI often provide useful complementary information about tissue properties. Leukoaraiosis results in signal abnormalities on T1-weighted images, which are automatically quantified by FreeSurfer, but this marker is poorly characterized and is rarely used. We evaluated associations between white matter hyperintensity (WM-hyper) volume from FLAIR and white matter hypointensity (WM-hypo) volume from T1-weighted images and compared their associations with age and cerebrospinal fluid (CSF) β-amyloid and tau.

METHODS

A total of 56 nondemented participants (68-94 years) were recruited and gave informed consent. All participants went through MR imaging on a GE 1.5T scanner and of these 47 underwent lumbar puncture for CSF analysis. WM-hypo was calculated using FreeSurfer analysis of T1 FSPGR 3D, and WM-hyper was calculated with the Lesion Segmentation Toolbox in the SPM software package using T2-FLAIR.

RESULTS

WM-hyper and WM-hypo were strongly correlated (r = .81; parameter estimate (p.e.): 1.53 ± 0.15; p < .0001). Age was significantly associated with both WM-hyper (r = .31, p.e. 0.078 ± 0.030, p = .013) and WM-hypo (r = .42, p.e. 0.055 ± 0.015, p < .001). CSF β-amyloid levels were predicted by WM-hyper (r = .33, p.e. -0.11 ± 0.044, p = .013) and WM-hypo (r = .42, p.e. -0.24 ± 0.073, p = .002). CSF tau levels were not correlated with either WM-hyper (p = .9) or WM-hypo (p = .99).

CONCLUSIONS

Strong correlations between WM-hyper and WM-hypo, and similar associations with age, abnormal β-amyloid, and tau suggest a general equivalence between these two imaging markers. Our work supports the equivalence of white matter hypointensity volumes derived from FreeSurfer for evaluating leukoaraiosis. This may have particular utility when T2-FLAIR is low in quality or absent, enabling analysis of older imaging data sets.

Narrative impairment, white matter damage and CSF biomarkers in the Alzheimer's disease spectrum

BACKGROUND

Narrative discourse (ND) refers to one's ability to verbally reproduce a sequence of temporally and logically-linked events. Impairments in ND may occur in subjects with Amnestic Mild Cognitive Impairment (aMCI) and Alzheimer's Disease (AD), but correlates across this function, neuroimaging and cerebrospinal fluid (CSF) AD biomarkers remain understudied.

OBJECTIVES

We sought to measure correlates among ND, Diffusion Tensor Imaging (DTI) indexes and AD CSF biomarkers in patients within the AD spectrum.

RESULTS

Groups differed in narrative production (NProd) and comprehension. aMCI and AD presented poorer inference abilities than controls. AD subjects were more impaired than controls and aMCI regarding WB (p<0.01). ROIs DTI assessment distinguished the three groups. Mean Diffusivity (MD) in the uncinate, bilateral parahippocampal cingulate and left inferior occipitofrontal fasciculi negatively correlated with NProd. Changes in specific tracts correlated with T-tau/Aβ1-42 ratio in CSF.

CONCLUSIONS

AD and aMCI patients presented more ND impairments than controls. Those findings were associated with changes in ventral language-associated and in the inferior parahippocampal pathways. The latest were correlated with biomarkers' levels in the CSF.

METHODS

AD (N=14), aMCI (N=31) and Control (N=39) groups were compared for whole brain (WB) and regions of interest (ROI) DTI parameters, ND and AD CSF biomarkers.

Premature white matter aging in patients with right mesial temporal lobe epilepsy: A machine learning approach based on diffusion MRI data

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A brain age prediction model was developed based on diffusion MRI data.

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Patients with right MTLE exhibited older brain age than those with left MTLE.

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Predicted age difference (PAD) was correlated with seizure frequency in right MTLE.

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Right uncinate fasciculus had highest contribution to the observed PAD in right MTLE.

Brain age prediction based on machine learning has been applied to various neurological diseases to discover its clinical values. By this innovative approach, it has been reported that the patients with refractory epilepsy had premature brain aging. Of refractory epilepsy, right and left subtypes of mesial temporal lobe epilepsy (MTLE) are the most common forms and exhibit distinct patterns in white matter alterations. So far, it is unclear whether these two subtypes of MTLE would have difference in white matter aging due to distinct white matter alterations. To address this issue, a machine learning based brain age model using diffusion MRI data was established to investigate biological age of white matter tracts. All diffusion MRI datasets were obtained from the same 3-Tesla MRI scanner. To build the brain age prediction model, diffusion MRI datasets of 300 healthy participants were processed to extract age-relevant diffusion indices from 76 major white matter tracts. The extracted diffusion indices underwent Gaussian process regression to build the prediction model for white matter brain age. The model was validated in an independent testing set (N = 40) to ensure no overfitting of the model. The model was then applied to patients with right and left MTLE and matched controls (right MTLE: N = 17, left MTLE: N = 18, controls: N = 37), and predicted age difference (PAD) was obtained by calculating the difference between each individual's predicted brain age and chronological age. The higher PAD score indicated older brain age. The results showed that right MTLE exhibited older predicted brain age than the other two groups (PAD of right MTLE = 10.9 years [p < 0.05 against left MTLE; p < 0.001 against control]; PAD of left MTLE = 2.2 years [p > 0.1 against control]; PAD of controls = 0.82 years). Patients with right and left MTLE showed strong correlations of the PAD scores with age of onset and duration of illness, but both groups showed opposite directions of correlations. In right MTLE, positive correlation of PAD with seizure frequency was found, and the right uncinate fasciculus was the most attributable tract to the increase in PAD. In conclusion, the present study found that patients with right MTLE exhibited premature white matter brain aging and their PAD scores were correlated with seizure frequency. Therefore, PAD is a potentially useful indicator of white matter impairment and disease severity in patients with right MTLE.

18F-AV1451 PET imaging and multimodal MRI changes in progressive supranuclear palsy

Objectives

Progressive supranuclear palsy (PSP) is characterized by deposition of straight filament tau aggregates in the grey matter (GM) of deep nuclei and cerebellum. We examined the relationship between tau pathology (assessed via ¹⁸F-AV1451 PET) and multimodal MRI imaging using GM volume, cortical thickness (CTh), and diffusion tensor imaging (DTI).

Methods

Twenty-three people with clinically probable PSP-Richardson’s syndrome (age 68.8 ± 5.8 years, 39% female) and 23 controls underwent structural 3 T brain MRI including DTI. Twenty-one patients also had ¹⁸F-AV1451 PET imaging. Voxelwise volume-based morphometry, surface-based morphometry, and DTI correlations were performed with ¹⁸F-AV1451 binding in typical PSP regions of interest (putamen, thalamus and dentate cerebellum). Clinical impairment was also assessed in relation to the different imaging modalities.

Results

PSP subjects showed GM volume loss in frontotemporal regions, basal ganglia, midbrain, and cerebellum (FDR-corrected p < 0.05), reduced CTh in the left entorhinal and fusiform gyrus (p < 0.001) as well as DTI changes in the corpus callosum, internal capsule, and superior longitudinal fasciculus (FWE-corrected p < 0.05). In PSP, higher ¹⁸F-AV1451 binding correlated with GM volume loss in frontal regions, DTI changes in motor tracts, and cortical thinning in parietooccipital areas. Cognitive impairment was related to decreased GM volume in frontotemporal regions, thalamus and pallidum, as well as DTI alteration in corpus callosum and cingulum.

Conclusion

This cross-sectional study demonstrates an association between in vivo proxy measures of tau pathology and grey and white matter degeneration in PSP. This adds to the present literature about the complex interplay between structural changes and protein deposition.

No relationship between fornix and cingulum degradation and within-network decreases in functional connectivity in prodromal Alzheimer's disease

INTRODUCTION

The earliest changes in the brain due to Alzheimer's disease are associated with the neural networks related to memory function. We investigated changes in functional and structural connectivity among regions that support memory function in prodromal Alzheimer's disease, i.e., during the mild cognitive impairment (MCI) stage.

METHODS

Twenty-three older healthy controls and 25 adults with MCI underwent multimodal MRI scanning. Limbic white matter tracts-the fornix, parahippocampal cingulum, retrosplenial cingulum, subgenual cingulum and uncinate fasciculus-were reconstructed in ExploreDTI using constrained spherical deconvolution-based tractography. Using a network-of-interest approach, resting-state functional connectivity time-series correlations among sub-parcellations of the default mode and limbic networks, the hippocampus and the thalamus were calculated in Conn.

ANALYSIS

Controlling for age, education, and gender between group linear regressions of five diffusion-weighted measures and of resting state connectivity measures were performed per hemisphere. FDR-corrections were performed within each class of measures. Correlations of within-network Fisher Z-transformed correlation coefficients and the mean diffusivity per tract were performed. Whole-brain graph theory measures of cluster coefficient and average path length were inspecting using the resting state data.

RESULTS & CONCLUSION

MCI-related changes in white matter structure were found in the fornix, left parahippocampal cingulum, left retrosplenial cingulum and left subgenual cingulum. Functional connectivity decreases were observed in the MCI group within the DMN-a sub-network, between the hippocampus and sub-areas -a and -c of the DMN, between DMN-c and DMN-a, and, in the right hemisphere only between DMN-c and both the thalamus and limbic-a. No relationships between white matter tract 'integrity' (mean diffusivity) and within sub-network functional connectivity were found. Graph theory revealed that changes in the MCI group was mostly restricted to diminished between-neighbour connections of the hippocampi and of nodes within DMN-a and DMN-b.

Synergism between fornix microstructure and beta amyloid accelerates memory decline in clinically normal older adults

The fornix is the primary efferent white matter tract of the hippocampus and is implicated in episodic memory. In this study, we investigated whether baseline measures of altered fornix microstructure and elevated beta amyloid (Aβ) burden influence prospective cognitive decline. A secondary goal examined whether Aβ burden is negatively associated with fornix microstructure. 253 clinically normal older adults underwent diffusion-weighted imaging and Pittsburgh Compound B positron emission tomography at baseline. We applied a novel streamline tractography protocol to reconstruct a fornix bundle in native space. Cognition was measured annually in domains of episodic memory, executive function, and processing speed (median follow-up = 4.0 ± 1.4 years). After controlling for covariates, linear mixed-effects models demonstrated an interaction of fornix microstructure with Aβ burden on episodic memory, such that combined lower fornix microstructure and higher Aβ burden was associated with accelerated decline. By contrast, associations with executive function and processing speed were not significant. There was no cross-sectional association between Aβ burden and fornix microstructure. In conclusion, altered fornix microstructure may accelerate memory decline in preclinical Alzheimer's disease.

Motor learning requires myelination to reduce asynchrony and spontaneity in neural activity

Myelination increases the conduction velocity in long‐range axons and is prerequisite for many brain functions. Impaired myelin regulation or impairment of myelin itself is frequently associated with deficits in learning and cognition in neurological and psychiatric disorders. However, it has not been revealed what perturbation of neural activity induced by myelin impairment causes learning deficits. Here, we measured neural activity in the motor cortex during motor learning in transgenic mice with a subtle impairment of their myelin. This deficit in myelin impaired motor learning, and was accompanied by a decrease in the amplitude of movement‐related activity and an increase in the frequency of spontaneous activity. Thalamocortical axons showed variability in axonal conduction with a large spread in the timing of postsynaptic cortical responses. Repetitive pairing of forelimb movements with optogenetic stimulation of thalamocortical axon terminals restored motor learning. Thus, myelin regulation helps to maintain the synchrony of cortical spike‐time arrivals through long‐range axons, facilitating the propagation of the information required for learning. Our results revealed the pathological neuronal circuit activity with impaired myelin and suggest the possibility that pairing of noninvasive brain stimulation with relevant behaviors may ameliorate cognitive and behavioral abnormalities in diseases with impaired myelination.

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

Introduction

Diffusion magnetic resonance imaging may allow for microscopic characterization of white matter degeneration in early stages of Alzheimer's disease.

Methods

Multishell Diffusion magnetic resonance imaging data were acquired from 100 participants (40 cognitively normal, 38 with subjective cognitive decline, and 22 with mild cognitive impairment [MCI]). White matter microscopic degeneration in 27 major tracts of interest was assessed using diffusion tensor imaging (DTI), neurite orientation dispersion and density imaging, and q-space imaging.

Results

Lower DTI fractional anisotropy and higher radial diffusivity were observed in the cingulum, thalamic radiation, and forceps major of participants with MCI. These tracts of interest also had the highest predictive power to discriminate groups. Diffusion metrics were associated with cognitive performance, particularly Rey Auditory Verbal Learning Test immediate recall, with the highest association observed in participants with MCI.

Discussion

While DTI was the most sensitive, neurite orientation dispersion and density imaging and q-space imaging complementarily characterized reduced axonal density accompanied with dispersed and less restricted white matter microstructures.

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Mild cognitive decline poses microstructural alterations in white matter tracts.

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The alterations include higher axonal dispersion and lower tissue restriction.

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Diffusion metrics are associated with cognitive outcomes in AD continuum.

Interactive effect of age and APOE-ε4 allele load on white matter myelin content in cognitively normal middle-aged subjects

The apolipoprotein E gene (APOE) ε4 allele has a strong and manifold impact on cognition and neuroimaging phenotypes in cognitively normal subjects, including alterations in the white matter (WM) microstructure. Such alterations have often been regarded as a reflection of potential thinning of the myelin sheath along axons, rather than pure axonal degeneration. Considering the main role of APOE in brain lipid transport, characterizing the impact of APOE on the myelin coating is therefore of crucial interest, especially in healthy APOE-ε4 homozygous individuals, who are exposed to a twelve-fold higher risk of developing Alzheimer's disease (AD), compared to the rest of the population. We examined T1w/T2w ratio maps in 515 cognitively healthy middle-aged participants from the ALFA study (ALzheimer and FAmilies) cohort, a single-site population-based study enriched for AD risk (68 APOE-ε4 homozygotes, 197 heterozygotes, and 250 non-carriers). Using tract-based spatial statistics, we assessed the impact of age and APOE genotype on this ratio taken as an indirect descriptor of myelin content. Healthy APOE-ε4 carriers display decreased T1w/T2w ratios in extensive regions in a dose-dependent manner. These differences were found to interact with age, suggesting faster changes in individuals with more ε4 alleles. These results obtained with T1w/T2w ratios, confirm the increased vulnerability of WM tracts in APOE-ε4 healthy carriers. Early alterations of myelin content could be the result of the impaired function of the ε4 isoform of the APOE protein in cholesterol transport. These findings help to clarify the possible interactions between the APOE-dependent non-pathological burden and age-related changes potentially at the source of the AD pathological cascade.

Associations between modifiable risk factors and white matter of the aging brain: insights from diffusion tensor imaging studies

There is increasing interest in factors that may modulate white matter (WM) breakdown and, consequentially, age-related cognitive and behavioral deficits. Recent diffusion tensor imaging studies have examined the relationship of such factors with WM microstructure. This review summarizes the evidence regarding the relationship between WM microstructure and recognized modifiable factors, including hearing loss, hypertension, diabetes, obesity, smoking, depressive symptoms, physical (in) activity, and social isolation, as well as sleep disturbances, diet, cognitive training, and meditation. Current cross-sectional evidence suggests a clear link between loss of WM integrity (lower fractional anisotropy and higher mean diffusivity) and hypertension, obesity, diabetes, and smoking; a relationship that seems to hold for hearing loss, social isolation, depressive symptoms, and sleep disturbances. Physical activity, cognitive training, diet, and meditation, on the other hand, may protect WM with aging. Preliminary evidence from cross-sectional studies of treated risk factors suggests that modification of factors could slow down negative effects on WM microstructure. Careful intervention studies are needed for this literature to contribute to public health initiatives going forward.

Microstructural White Matter Alterations in Mild Cognitive Impairment and Alzheimer's Disease : Study Based on Neurite Orientation Dispersion and Density Imaging (NODDI)

PURPOSE

To investigate microstructural alterations in white matter in mild cognitive impairment (MCI) and Alzheimer's disease (AD) using neurite orientation dispersion and density imaging (NODDI) and to assess the potential diagnostic performance of NODDI-derived parameters.

METHODS

In this study 14 MCI patients, 14 AD patients, and 14 healthy controls (HC) were recruited. The diffusion tensor imaging(DTI)-derived fractional anisotropy (FA) and NODDI-derived neurite density index (NDI), orientation dispersion index (ODI), and volume fraction of isotropic water molecules (Viso) were calculated from the diffusion data. The tract-based spatial statistics (TBSS) method was used for statistical analysis with one-way ANOVA. The correlations between the parameter values and mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA) scores were examined. A receiver operating characteristic (ROC) curve was conducted to assess the diagnostic performance of different parameters.

RESULTS

Compared with the HC group, the NDI and ODI values decreased significantly and the Viso values were significantly increased in the MCI and AD groups (p < 0.01, threshold-free cluster enhancement (TFCE)-corrected); however, there were no significant differences in FA values in the MCI group. The NDI, ODI, and Viso values of multiple fibers were significantly correlated with MMSE and MoCA scores. For the diagnosis of AD, the area under the ROC curve (AUC) for the NDI value of the splenium of corpus callosum was larger than the FA value (AUC = 0.885, 0.714, p = 0.042). The AUC of the Viso value of the right cerebral peduncle was larger than FA value (AUC = 0.934, 0.531, p = 0.004).

CONCLUSION

The NDI is more sensitive to white matter microstructural changes than FA and NODDI could be superior to DTI in the diagnosis of AD.

Elevated cerebrospinal fluid total tau in former professional athletes with multiple concussions

OBJECTIVE

To identify CSF biomarkers that are related to decreased white matter (WM) integrity and poor cognitive performance in former professional athletes with a history of multiple concussions.

METHODS

Concentrations of phosphorylated tau181, total tau (t-tau), and β-amyloid in the CSF were measured in 3 groups: 22 former professional athletes with multiple concussions (mean ± SD age 55.9 ± 12.2 years), 5 healthy controls (age 57.4 ± 5.2 years), and 12 participants (age 60.0 ± 6.6 years) diagnosed with Alzheimer disease (AD). All participants in the former athletes group underwent diffusion tensor imaging to determine WM tract integrity and completed neuropsychological testing. We divided the former athletes group into those with normal (<300 pg/mL) and high (>300 pg/mL) CSF t-tau.

RESULTS

CSF t-tau in the former athletes group was significantly higher than in the healthy control group (349.3 ± 182.6 vs 188.8 ± 39.9 pg/mL, p = 0.003) and significantly lower than in the patients with AD (349.3 ± 182.6 vs 857.0 ± 449.3 pg/mL, p = 0.007). Fractional anisotropy values across all the tracts were significantly lower in the high CSF t-tau group compared to the normal CSF t-tau group (p = 0.036). Participants in the high CSF t-tau group scored significantly lower on the Trail Making Test (TMT) Part B compared to the normal CSF t-tau group (t scores 45.6 ± 18.8 vs 62.3 ± 10.1, p = 0.017).

CONCLUSION

Our findings indicate that former athletes with multiple concussions are at increased risk of elevated levels of CSF t-tau and that high CSF t-tau is associated with reduced WM integrity and worse scores on the TMT Part B.

Perivascular space fluid contributes to diffusion tensor imaging changes in white matter

Diffusion tensor imaging (DTI) has been extensively used to map changes in brain tissue related to neurological disorders. Among the most widespread DTI findings are increased mean diffusivity and decreased fractional anisotropy of white matter tissue in neurodegenerative diseases. Here we utilize multi-shell diffusion imaging to separate diffusion signal of the brain parenchyma from non-parenchymal fluid within the white matter. We show that unincorporated anisotropic water in perivascular space (PVS) significantly, and systematically, biases DTI measures, casting new light on the biological validity of many previously reported findings. Despite the challenge this poses for interpreting these past findings, our results suggest that multi-shell diffusion MRI provides a new opportunity for incorporating the PVS contribution, ultimately strengthening the clinical and scientific value of diffusion MRI.

Nonparenchymal fluid is the source of increased mean diffusivity in preclinical Alzheimer's disease

Introduction

Although increased mean diffusivity of the white matter has been repeatedly linked to Alzheimer’s disease pathology, the underlying mechanism is not known.

Methods

Here, we used ADNI-3 multishell diffusion magnetic resonance imaging data to separate the diffusion signal of the parenchyma from less hindered fluid pools within the white matter such as perivascular space fluid and fluid-filled cavities.

Results

We found that the source of the pathological increase of the mean diffusivity is the increased nonparenchymal fluid, often found in lacunes and perivascular spaces. In this cohort, the cognitive decline was significantly associated with the fluid increase and not with the microstructural changes of the white matter parenchyma itself. The white matter fluid increase was dominantly observed in the sagittal stratum and anterior thalamic radiation.

Discussion

These findings are positive steps toward understanding the pathophysiology of white matter alteration and its role in the cognitive decline.

Diffusion MRI detects longitudinal white matter changes in the 3xTg-AD mouse model of Alzheimer's disease

The sensitivity of multiple diffusion MRI (dMRI) parameters to longitudinal changes in white matter microstructure was investigated for the 3xTg-AD transgenic mouse model of Alzheimer's disease, which manifests both amyloid beta plaques and neurofibrillary tangles. By employing a specific dMRI method known as diffusional kurtosis imaging, eight different diffusion parameters were quantified to characterize distinct aspects of water diffusion. Four female 3xTg-AD mice were imaged at five time points, ranging from 4.5 to 18 months of age, and the diffusion parameters were investigated in four white matter regions (fimbria, external capsule, internal capsule and corpus callosum). Significant changes were observed in several diffusion parameters, particularly in the fimbria and in the external capsule, with a statistically significant decrease in diffusivity and a statistically significant increase in kurtosis. Our preliminary results demonstrate that dMRI can detect microstructural changes in white matter for the 3xTg-AD mouse model due to aging and/or progression of pathology, depending strongly on the diffusion parameter and anatomical region.

Strength and Similarity Guided Group-level Brain Functional Network Construction for MCI Diagnosis

Sparse representation-based brain functional network modeling often results in large inter-subject variability in the network structure. This could reduce the statistical power in group comparison, or even deteriorate the generalization capability of the individualized diagnosis of brain diseases. Although group sparse representation (GSR) can alleviate such a limitation by increasing network similarity across subjects, it could, in turn, fail in providing satisfactory separability between the subjects from different groups (e.g., patients vs. controls). In this study, we propose to integrate individual functional connectivity (FC) information into the GSR-based network construction framework to achieve higher between-group separability while maintaining the merit of within-group consistency. Our method was based on an observation that the subjects from the same group have generally more similar FC patterns than those from different groups. To this end, we propose our new method, namely "strength and similarity guided GSR (SSGSR)", which exploits both BOLD signal temporal correlation-based "low-order" FC (LOFC) and inter-subject LOFC-profile similarity-based "high-order" FC (HOFC) as two priors to jointly guide the GSR-based network modeling. Extensive experimental comparisons are carried out, with the rs-fMRI data from mild cognitive impairment (MCI) subjects and healthy controls, between the proposed algorithm and other state-of-the-art brain network modeling approaches. Individualized MCI identification results show that our method could achieve a balance between the individually consistent brain functional network construction and the adequately maintained inter-group brain functional network distinctions, thus leading to a more accurate classification result. Our method also provides a promising and generalized solution for the future connectome-based individualized diagnosis of brain disease.

Association of Atrial Fibrillation With White Matter Disease

Background and Purpose- Evidence suggests that atrial fibrillation (AF) is associated with increased risk of cognitive decline and dementia, even in the absence of stroke. White matter disease (WMD) is a potential mechanism linking AF to cognitive impairment. In this study, we explored the association between prevalent AF and WMD. Methods- We performed a cross-sectional analysis of participants attending the ARIC-NCS (Atherosclerosis Risk in Communities-Neurocognitive Study) in 2011 to 2013 who underwent brain magnetic resonance imaging. AF was ascertained from study visit electrocardiograms or prior hospitalization codes. Extent of WMD was defined by measures of white matter (WM) microstructural integrity and WM hyperintensity volume. Multivariable linear regression models were used to assess the association between AF and WMD. Results- Among 1899 participants (mean age, 76 years; 28% black; 60% women), 133 (7%) had prevalent AF. After multivariable adjustment, differences between participants with and without AF were -0.001 (95% CI, -0.006 to 0.004) for global WM fractional anisotropy, 0.031×10-4 mm2/s (95% CI, -0.075 to 0.137) for global WM mean diffusivity, and 0.08 mm3 (95% CI, -0.14 to 0.30) for WM hyperintensity volume. Conclusions- The results suggest that there is no association between prevalent AF and WMD.

Quantification of white matter cellularity and damage in preclinical and early symptomatic Alzheimer's disease

Interest in understanding the roles of white matter (WM) inflammation and damage in the pathophysiology of Alzheimer disease (AD) has been growing significantly in recent years. However, in vivo magnetic resonance imaging (MRI) techniques for imaging inflammation are still lacking. An advanced diffusion-based MRI method, neuro-inflammation imaging (NII), has been developed to clinically image and quantify WM inflammation and damage in AD. Here, we employed NII measures in conjunction with cerebrospinal fluid (CSF) biomarker classification (for β-amyloid (Aβ) and neurodegeneration) to evaluate 200 participants in an ongoing study of memory and aging. Elevated NII-derived cellular diffusivity was observed in both preclinical and early symptomatic phases of AD, while disruption of WM integrity, as detected by decreased fractional anisotropy (FA) and increased radial diffusivity (RD), was only observed in the symptomatic phase of AD. This may suggest that WM inflammation occurs earlier than WM damage following abnormal Aβ accumulation in AD. The negative correlation between NII-derived cellular diffusivity and CSF Aβ42 level (a marker of amyloidosis) may indicate that WM inflammation is associated with increasing Aβ burden. NII-derived FA also negatively correlated with CSF t-tau level (a marker of neurodegeneration), suggesting that disruption of WM integrity is associated with increasing neurodegeneration. Our findings demonstrated the capability of NII to simultaneously image and quantify WM cellularity changes and damage in preclinical and early symptomatic AD. NII may serve as a clinically feasible imaging tool to study the individual and composite roles of WM inflammation and damage in AD.

Characterization of white matter changes along fibers by automated fiber quantification in the early stages of Alzheimer's disease

Brain white matter fiber bundles in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) have abnormalities not usually seen in unaffected subjects. Ideal algorithm of the localization-specific properties in white matter integrity might reveal the changes of tissue properties varying along each tract, while previous studies only detected the mean DTI parameters of each fiber. The aim of this study was to investigate whether these abnormalities of nerve fiber tracts are localized to specific regions of the tracts or spread throughout and to analyze which of the examined fiber tracts are involved in the early stages of Alzheimer's disease. In this study, we utilized VBA, TBSS as well as AFQ together to comprehensively investigate the white matter fiber impairment on 25 CE patients, 29 MCI patients and 34 normal control (NC) subjects. Two tract profiles, fractional anisotropy (FA) and mean diffusivity (MD), were extracted to evaluate the white matter integrity at 100 locations along each of 20 fiber tracts and then we validated the results with 27 CE patients, 21 MCI patients and 22 NC from the ADNI cohort. Also, we compare the AFQ with VBA and TBSS in our cohort. In comparison with NC, AD patients showed widespread FA reduction in 25% (5 /20) and MD increase in 65%(13/20) of the examined fiber tracts. The MCI patients showed a regional FA reduction in 5% (1/20) of the examined fiber tracts (right cingulum cingulate) and MD increase in 5%(1/20) of the examined fiber tracts (left arcuate fasciculus). Among these changed tracts, only the right cingulum cingulate showed widespread disruption of myelin or/and fiber axons in MCI and aggravated deterioration in AD, findings supported by FA/MD changes both by the mean and FA changes by point wise methods and TBSS. And the AFQ findings from ADNI cohort showed some similarity with our cohort, especially in the pointwise comparison of MD profiles between AD vs NC. Furthermore, the pattern of white matter abnormalities was different across neuronal fiber tracts; for example, the MCI and AD patients showed similar FA reduction in the middle part of the right cingulum cingulate, and the anterior part were not damaged. However, the left arcuate fasciculus showed MD elevation located at the temporal part of the fibers in the MCI patients and expanding to the temporal and middle part of the fibers in AD patients. So, the AFQ may be an alternative complementary method of VBA and TBSS, and may provide new insights into white matter degeneration in MCI and its association with AD.

Alterations of White Matter Integrity in Subcortical Ischemic Vascular Disease with and Without Cognitive Impairment: a TBSS Study

Patients with subcortical ischemic vascular disease (SIVD) may exhibit a high risk of cognitive impairment (CI) by disruption of white matter (WM) integrity. Diffusion tensor imaging (DTI) is recommended as a sensitive method to explore whole brain WM alterations at an asymptomatic stage of the disease, which might be correlated with underlying cognitive disorders. We aim to investigate alterations in WM microstructures and evaluate the relationships between the mean values of diffusion metrics (FA, MD, AD, and RD) and cognitive assessments in SIVD patients. Fifty SIVD patients with (SVCI, N = 25) and without (pre-SVCI, N = 25) cognitive impairments and normal controls (NC, N = 23) underwent DTI and neuropsychological examinations. DTI data were analyzed via TBSS to detect significant changes in WM tracts. Spearman correlation analysis was performed to evaluate relationships between the mean values of diffusion indices and the cognitive assessments. In general, extensive symmetrically altered areas that involved approximately the entire cerebral WM were noted in the pre-SVCI group but were less distinct than that noted in the SVCI group compared with NCs. The genu of corpus callosum exhibited the most damaged WM fiber. Throughout WM, FA was decreased, whereas MD, AD, and RD were increased. Some specific WM tracts in patient groups were significantly correlated with the severity of white matter hyperintensity (WMH), cognitive assessments about executive functions and processing speed. WM integrity has already been damaged at the pre-SVCI stage, which would be associate with future cognitive dysfunction. DTI could potentially establish early biomarkers to detect underlying mechanisms of SIVD.

Relationship Between DTI Metrics and Cognitive Function in Alzheimer's Disease

Introduction: Alzheimer's disease (AD) is a neurodegenerative disorder with a clinical presentation characterized by memory impairment and executive dysfunction. Our group previously demonstrated significant alterations in white matter microstructural metrics in AD compared to healthy older adults. We aimed to further investigate the relationship between white matter microstructure in AD and cognitive function, including memory and executive function. Methods: Diffusion tensor imaging (DTI) and neuropsychological data were downloaded from the AD Neuroimaging Initiative database for 49 individuals with AD and 48 matched healthy older adults. The relationship between whole-brain fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AxD), radial diffusivity (RD), and composite scores of memory and executive function was examined. We also considered voxel-wise relationships using Tract-Based Spatial Statistics. Results: As expected, individuals with AD had lower composite scores on tests of memory and executive function, as well as disrupted white matter integrity (low FA, high MD, AxD, and RD) relative to healthy older adults in widespread regions, including the hippocampus. When the AD and healthy older adult groups were combined, we found significant relationships between DTI metrics (FA/MD/AxD/RD) and memory scores across widespread regions of the brain, including the medial temporal regions. We also found significant relationships between DTI metrics (FA/MD/AxD/RD) and executive function in widespread regions, including the frontal areas in the combined group. However, when the groups were examined separately, no significant relationships were found between DTI metrics (FA/MD/AxD/RD) and memory performance for either group. Further, we did not find any significant relationships between DTI metrics (FA/MD/AxD/RD) and executive function in the AD group, but we did observe significant relationships between FA/RD, and executive function in healthy older adults. Conclusion: White matter integrity is disrupted in AD. In a mixed sample of AD and healthy elderly persons, associations between measures of white matter microstructure and memory and executive cognitive test performance were evident. However, no significant linear relationship between the degree of white matter disruption and level of cognitive functioning (memory and executive abilities) was found in those with AD. Future longitudinal studies of the relations between DTI metrics and cognitive function in AD are required to determine whether DTI has potential to measure progression of AD and/or treatment efficacy.

The Full Spectrum of Alzheimer's Disease Is Rooted in Metabolic Derangements That Drive Type 3 Diabetes

The standard practice in neuropathology is to diagnose Alzheimer's disease (AD) based on the distribution and abundance of neurofibrillary tangles and Aβ deposits. However, other significant abnormalities including neuroinflammation, gliosis, white matter degeneration, non-Aβ microvascular disease, and insulin-related metabolic dysfunction require further study to understand how they could be targeted to more effectively remediate AD. This review addresses non-Aβ and non-pTau AD-associated pathologies, highlighting their major features, roles in neurodegeneration, and etiopathic links to deficits in brain insulin and insulin-like growth factor signaling and cognitive impairment. The discussion delineates why AD with its most characteristic clinical and pathological phenotypic profiles should be regarded as a brain form of diabetes, i.e., type 3 diabetes, and entertains the hypothesis that type 3 diabetes is just one of the categories of insulin resistance diseases that can occur independently or overlap with one or more of the others, including type 2 diabetes, metabolic syndrome, and nonalcoholic fatty liver disease.

Relationships Between Diffusion Tensor Imaging and Cerebrospinal Fluid Metrics in Early Stages of the Alzheimer's Disease Continuum

Recently, the field of Alzheimer's disease (AD) research has adopted a new framework that places the progression of AD along a continuum consisting of a preclinical stage, followed by conversion to mild cognitive impairment, and ultimately dementia. Important neuropathological changes occur in the preclinical phase, necessitating the identification of metrics that can detect such early changes. While cerebrospinal fluid (CSF) measures of amyloid and tau are generally accepted as biomarkers of AD pathology, neuroimaging measures used to index white matter alterations throughout the brain remain less widely endorsed as candidate biomarkers. To explore the relationship between white matter alterations and AD pathology, we review the literature on multimodal studies that assessed both CSF markers and white matter indices, derived from diffusion tensor imaging (DTI) methods, across cohorts primarily in the early phases of AD. Our review indicates that abnormal CSF measures of Aβ42 and tau are associated with widespread alterations in white matter microstructure throughout the brain. Furthermore, white matter variability is related to individual differences in behavior and can aid in tracking longitudinal changes in cognition. Our review advocates for the utilization of DTI metrics in investigations of early AD and suggests that the combined use of DTI and CSF markers may better explain individual differences in cognition and disease progression. However, further research is needed to resolve certain mixed findings.

Patients with Mild Cognitive Impairment May be Stratified by Advanced Diffusion Metrics and Neurocognitive Testing

BACKGROUND AND PURPOSE

Mild cognitive impairment (MCI) is a prevalent disorder, with a subset of patients progressing to dementia each year. Although MCI may be subdivided into amnestic or vascular types as well as into single or multiple cognitive domain involvement, most prior studies using advanced diffusion imaging have not accounted for these categories. The purpose of the current study was to determine if the pattern of diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) metrics in patients with amnestic MCI (aMCI) correlate to specific cognitive domain impairments.

METHODS

Nineteen consecutive patients with aMCI referred for brain magnetic resonance imaging (MRI) were included. All subjects underwent neurocognitive testing. A z-score was calculated for each domain and a composite of all four domains. Brain MRI included standard structural imaging and diffusion imaging. Volumetric, DTI, and DKI metrics were calculated and statistical analysis was performed with adjustments for multiple measures and comparisons.

RESULTS

Statistically significant correlations between diffusion metrics and cognitive z-scores were detected: visuospatial-visuoconstructional z-scores only correlated with alterations in the corpus callosum splenium, executive functioning z-scores with the corpus callosum genu, memory testing z-scores with the left hippocampus, and composite z-scores with the anterior centrum semiovale.

CONCLUSION

Neuroimaging studies of patients with aMCI to date have assumed a population with homogeneous cognitive impairment. Our results demonstrate selective patterns of regional diffusion metric alterations correlate to specific cognitive domain impairments. Future studies should account for this heterogeneity, and this may also be useful for prognostication.

Subcortical nuclei in Alzheimer's disease: a volumetric and diffusion kurtosis imaging study

Background Previous studies revealed that subcortical nuclei were harmed in the process of Alzheimer's disease (AD). Purpose To investigate the volumetric and diffusion kurtosis imaging (DKI) parameter changes of subcortical nuclei in AD and their relationship with cognitive function. Materials and Methods A total of 17 mild AD patients, 15 moderate to severe AD patients, and 16 controls underwent neuropsychological tests and magnetic resonance imaging (MRI) scans. Volume, mean kurtosis (MK), mean diffusivity (MD), and fractional anisotropy (FA) were measured in hippocampus, thalamus, caudate, putamen, pallidum, and amygdala. MRI parameters were compared. Correlation analysis was performed between subcortical nuclei volume, DKI parameters, and MMSE score. Results Significant volume reduction was seen in the left hippocampus in mild AD, and the bilateral hippocampus, thalamus, putamen, left caudate, and right amygdala in moderate to severe AD ( P < 0.05). Increased MD values were observed in the left hippocampus, left amygdala, and right caudate in mild AD, and the bilateral hippocampus and right amygdala in moderate to severe AD ( P < 0.05). Decreased MK values were observed only in the bilateral hippocampus in moderate to severe AD ( P < 0.05). No group significances were found in FA value. MMSE score was positively correlated with the volume of the bilateral hippocampus, thalamus, and putamen, and MK value of the left hippocampus ( P < 0.05). A negative correlation was found with the MD value of the bilateral hippocampus and left amygdala ( P < 0.05). Conclusion Mild AD mainly has microscopic subcortical changes revealed by increased MD value, and moderate to severe AD mainly has macroscopic subcortical changes revealed by volume reduction. MK is more sensitive in severe AD than mild AD.

Microstructural brain changes track cognitive decline in mild cognitive impairment

Improved characterization of the microstructural brain changes occurring in the early stages of Alzheimer's disease may permit more timely disease detection. This study examined how longitudinal change in brain microstructure relates to cognitive decline in aging and prodromal Alzheimer's disease. At baseline and two-year follow-up, 29 healthy controls and 21 individuals with mild cognitive impairment or mild Alzheimer's disease underwent neuropsychological evaluation and restriction spectrum imaging (RSI). Microstructural change in the hippocampus, entorhinal cortex, and white matter tracts previously shown to be vulnerable to Alzheimer's disease, was compared between healthy controls and impaired participants. Partial correlations and stepwise linear regressions examined whether baseline RSI metrics predicted subsequent cognitive decline, or change in RSI metrics correlated with cognitive change. In medial temporal gray and white matter, restricted isotropic diffusion and crossing fibers were lower, and free water diffusion was higher, in impaired participants. Restricted isotropic diffusion in the hippocampus declined more rapidly for cognitively impaired participants. Baseline hippocampal restricted isotropic diffusion predicted cognitive decline, and change in hippocampal and entorhinal restricted isotropic diffusion correlated with cognitive decline. Within controls, changes in white matter restricted oriented diffusion and crossing fibers correlated with memory decline. In contrast, there were no correlations between rates of cortical atrophy and cognitive decline in the full sample or within controls. Changes in medial temporal lobe microarchitecture were associated with cognitive decline in prodromal Alzheimer's disease, and these changes were distinct from microstructural changes in normal cognitive aging. RSI metrics of brain microstructure may hold value for predicting cognitive decline in aging and for monitoring the course of Alzheimer's disease.

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Longitudinal diffusion MRI was conducted in individuals with MCI/AD and controls.

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Mean restricted diffusion in hippocampus declined more rapidly in MCI/AD.

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Baseline hippocampal restricted diffusion predicted cognitive decline.

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Change in medial temporal restricted diffusion correlated with cognitive decline.

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In healthy controls, white matter microstructure correlated with memory decline.