Regionally-specific diffusion tensor imaging in mild cognitive impairment and Alzheimer's disease

False Recognition in Behavioral Variant Frontotemporal Dementia and Alzheimer's Disease-Disinhibition or Amnesia?

Episodic memory recall processes in Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) can be similarly impaired, whereas recognition performance is more variable. A potential reason for this variability could be false-positive errors made on recognition trials and whether these errors are due to amnesia per se or a general over-endorsement of recognition items regardless of memory. The current study addressed this issue by analysing recognition performance on the Rey Auditory Verbal Learning Test (RAVLT) in 39 bvFTD, 77 AD and 61 control participants from two centers (India, Australia), as well as disinhibition assessed using the Hayling test. Whereas both AD and bvFTD patients were comparably impaired on delayed recall, bvFTD patients showed intact recognition performance in terms of the number of correct hits. However, both patient groups endorsed significantly more false-positives than controls, and bvFTD and AD patients scored equally poorly on a sensitivity index (correct hits-false-positives). Furthermore, measures of disinhibition were significantly associated with false positives in both groups, with a stronger relationship with false-positives in bvFTD. Voxel-based morphometry analyses revealed similar neural correlates of false positive endorsement across bvFTD and AD, with both patient groups showing involvement of prefrontal and Papez circuitry regions, such as medial temporal and thalamic regions, and a DTI analysis detected an emerging but non-significant trend between false positives and decreased fornix integrity in bvFTD only. These findings suggest that false-positive errors on recognition tests relate to similar mechanisms in bvFTD and AD, reflecting deficits in episodic memory processes and disinhibition. These findings highlight that current memory tests are not sufficient to accurately distinguish between bvFTD and AD patients.

Removing inter-subject technical variability in magnetic resonance imaging studies

Magnetic resonance imaging (MRI) intensities are acquired in arbitrary units, making scans non-comparable across sites and between subjects. Intensity normalization is a first step for the improvement of comparability of the images across subjects. However, we show that unwanted inter-scan variability associated with imaging site, scanner effect, and other technical artifacts is still present after standard intensity normalization in large multi-site neuroimaging studies. We propose RAVEL (Removal of Artificial Voxel Effect by Linear regression), a tool to remove residual technical variability after intensity normalization. As proposed by SVA and RUV [Leek and Storey, 2007, 2008, Gagnon-Bartsch and Speed, 2012], two batch effect correction tools largely used in genomics, we decompose the voxel intensities of images registered to a template into a biological component and an unwanted variation component. The unwanted variation component is estimated from a control region obtained from the cerebrospinal fluid (CSF), where intensities are known to be unassociated with disease status and other clinical covariates. We perform a singular value decomposition (SVD) of the control voxels to estimate factors of unwanted variation. We then estimate the unwanted factors using linear regression for every voxel of the brain and take the residuals as the RAVEL-corrected intensities. We assess the performance of RAVEL using T1-weighted (T1-w) images from more than 900 subjects with Alzheimer's disease (AD) and mild cognitive impairment (MCI), as well as healthy controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We compare RAVEL to two intensity-normalization-only methods: histogram matching and White Stripe. We show that RAVEL performs best at improving the replicability of the brain regions that are empirically found to be most associated with AD, and that these regions are significantly more present in structures impacted by AD (hippocampus, amygdala, parahippocampal gyrus, enthorinal area, and fornix stria terminals). In addition, we show that the RAVEL-corrected intensities have the best performance in distinguishing between MCI subjects and healthy subjects using the mean hippocampal intensity (AUC=67%), a marked improvement compared to results from intensity normalization alone (AUC=63% and 59% for histogram matching and White Stripe, respectively). RAVEL is promising for many other imaging modalities.

Neuroimaging basis in the conversion of aMCI patients with APOE-ε4 to AD: study protocol of a prospective diagnostic trial

BACKGROUND

The ε4 allele of the Apolipoprotein E gene (APOE-ε4) is a potent genetic risk factor for sporadic Alzheimer's disease (AD). Amnestic mild cognitive impairment (aMCI) is an intermediate state between normal cognitive aging and dementia, which is easy to convert to AD dementia. It is an urgent problem in the field of cognitive neuroscience to reveal the conversion of aMCI-ε4 to AD. Based on our preliminary work, we will study the neuroimaging features in the special group of aMCI-ε4 with multi-modality magnetic resonance imaging (structural MRI, resting state-fMRI and diffusion tensor imaging) longitudinally.

METHODS/DESIGN

In this study, 200 right-handed subjects who are diagnosed as aMCI with APOE-ε4 will be recruited at the memory clinic of the Neurology Department, XuanWu Hospital, Capital Medical University, Beijing, China. All subjects will undergo the neuroimaging and neuropsychological evaluation at a 1 year-interval for 3 years. The primary outcome measures are 1) Microstructural alterations revealed with multimodal MRI scans including structure MRI (sMRI), resting state functional MRI (rs-fMRI), diffusion tensor imaging (DTI); 2) neuropsychological evaluation, including the World Health Organization-University of California-LosAngeles Auditory Verbal Learning Test (WHO-UCLA AVLT), Addenbrook's cognitive examination-revised (ACE-R), mini-mental state examination (MMSE), Montreal Cognitive Assessment (MoCA), Clinical Dementia Rating scale (CDR).

DISCUSSION

This study is to find out the neuroimaging biomarker and the changing laws of the marker during the progress of aMCI-ε4 to AD, and the final purpose is to provide scientific evidence for new prevention, diagnosis and treatment of AD.

TRIAL REGISTRATION

This study has been registered to ClinicalTrials.gov (NCT02225964, https://www.clinicaltrials.gov/ ) in August 24, 2014.

Effects of donepezil on brain morphometric and metabolic changes in patients with Alzheimer's disease: A DARTEL-based VBM and (1)H-MRS

A few studies have performed on the brain morphometric changes over the whole brain structure following donepezil treatment in patients with Alzheimer's disease (AD). We evaluated the gray matter (GM) and white matter (WM) volume alterations and cellular metabolic changes in patients with AD before and after donepezil treatment, and further to reveal the correlations of the scores of various neuropsychological scales with the volumetric and metabolic changes. Twenty-one subjects comprising of 11 patients with AD and 10 age-matched healthy controls participated in this study. All of the patients participated in the follow-up study 24weeks following donepezil treatment. In this study, a combination of voxel-based morphometry (VBM) and proton magnetic resonance spectroscopy ((1)H-MRS) was used to assess the brain morphometric and metabolic alterations in AD. In the GM volumetric analysis, both of the untreated and treated patients with donepezil showed significantly reduced volumes in the hippocampus (Hip), parahippocampal gyrus (PHG), precuneus (PCu) and middle frontal gyrus compared with healthy controls. However, donepezil-treated patients showed significantly increased volumes in the Hip, PCu, fusiform gyrus and caudate nucleus compared to untreated patients. In the WM volumetric analysis, untreated and treated patients showed significant volume reductions in the posterior limb of internal capsule (PLIC), cerebral peduncle of the midbrain and PHG compared to healthy controls. However, there was no significant WM morphological change after donepezil treatment in patients with AD. In MRS study, untreated patients with AD showed decreased N-acetylaspartate/creatine (NAA/Cr) and increased myo-inositol (mI)/Cr compared to healthy controls, while treated patients showed only decreased NAA/Cr in the same comparison. However, the treated patients showed simultaneously increased NAA/Cr and decreased mI/Cr and choline (Cho)/Cr ratios compared to untreated patients. This study shows the regional GM and WM volume changes in combination with metabolic changes following donepezil treatment in AD. These findings would be helpful to aid our understanding of the neuroanatomical mechanisms associated with effects of donepezil on the cognitive function in AD.

Imaging the accumulation and suppression of tau pathology using multiparametric MRI

Mouse models of Alzheimer's disease have served as valuable tools for investigating pathogenic mechanisms relating to neurodegeneration, including tau-mediated and neurofibrillary tangle pathology-a major hallmark of the disease. In this work, we have used multiparametric magnetic resonance imaging (MRI) in a longitudinal study of neurodegeneration in the rTg4510 mouse model of tauopathy, a subset of which were treated with doxycycline at different time points to suppress the tau transgene. Using this paradigm, we investigated the sensitivity of multiparametric MRI to both the accumulation and suppression of pathologic tau. Tau-related atrophy was discernible from 5.5 months within the cortex and hippocampus. We observed markedly less atrophy in the treated rTg4510 mice, which was enhanced after doxycycline intervention from 3.5 months. We also observed differences in amide proton transfer, cerebral blood flow, and diffusion tensor imaging parameters in the rTg4510 mice, which were significantly less altered after doxycycline treatment. We propose that these non-invasive MRI techniques offer insight into pathologic mechanisms underpinning Alzheimer's disease that may be important when evaluating emerging therapeutics targeting one of more of these processes.

β-amyloid, hippocampal atrophy and their relation to longitudinal brain change in cognitively normal individuals

Recent literature has examined baseline hippocampal volume and extent of brain amyloidosis to test potential synergistic effects on worsening cognition and extent of brain atrophy. Use of hippocampal volume in prior studies was based on the notion that limbic circuit degeneration is an early manifestation of the Alzheimer's Disease (AD) pathophysiology. To clarify these interactions early in the AD process, we tested the effects of amyloid and baseline normalized hippocampal volume on longitudinal brain atrophy rates in a group of cognitively normal individuals. Results showed that the combination of elevated β-amyloid and baseline hippocampal atrophy is associated with increased rates specific to the limbic circuit and splenium. Importantly, this atrophy pattern emerged from a voxelwise analysis, corroborated by regression models over region of interests in native space. The results are broadly consistent with previous studies of the effects of amyloid and baseline hippocampal atrophy in normals, while pointing to accelerated atrophy of AD-vulnerable regions detectable at the preclinical stage.

Insight from uncertainty: bootstrap-derived diffusion metrics differentially predict memory function among older adults

Diffusion tensor imaging suffers from an intrinsic low signal-to-noise ratio. Bootstrap algorithms have been introduced to provide a non-parametric method to estimate the uncertainty of the measured diffusion parameters. To quantify the variability of the principal diffusion direction, bootstrap-derived metrics such as the cone of uncertainty have been proposed. However, bootstrap-derived metrics are not independent of the underlying diffusion profile. A higher mean diffusivity causes a smaller signal-to-noise ratio and, thus, increases the measurement uncertainty. Moreover, the goodness of the tensor model, which relies strongly on the complexity of the underlying diffusion profile, influences bootstrap-derived metrics as well. The presented simulations clearly depict the cone of uncertainty as a function of the underlying diffusion profile. Since the relationship of the cone of uncertainty and common diffusion parameters, such as the mean diffusivity and the fractional anisotropy, is not linear, the cone of uncertainty has a different sensitivity. In vivo analysis of the fornix reveals the cone of uncertainty to be a predictor of memory function among older adults. No significant correlation occurs with the common diffusion parameters. The present work not only demonstrates the cone of uncertainty as a function of the actual diffusion profile, but also discloses the cone of uncertainty as a sensitive predictor of memory function. Future studies should incorporate bootstrap-derived metrics to provide more comprehensive analysis.

Genetic and degenerative disorders primarily causing dementia

Neuroimaging comprises a powerful set of instruments to diagnose the different causes of dementia, clarify their neurobiology, and monitor their treatment. Magnetic resonance imaging (MRI) depicts volume changes with neurodegeneration and inflammation, as well as abnormalities in functional and structural connectivity. MRI arterial spin labeling allows for the quantification of regional cerebral blood flow, characteristically altered in Alzheimer's disease, diffuse Lewy-body disease, and the frontotemporal dementias. Positron emission tomography allows for the determination of regional metabolism, with similar abnormalities as flow, and for the measurement of β-amyloid and abnormal tau deposition in the brain, as well as regional inflammation. These instruments allow for the quantification in vivo of most of the pathologic features observed in disorders causing dementia. Importantly, they allow for the longitudinal study of these abnormalities, having revealed, for instance, that the deposition of β-amyloid in the brain can antecede by decades the onset of dementia. Thus, a therapeutic window has been opened and the efficacy of immunotherapies directed at removing β-amyloid from the brain of asymptomatic individuals is currently being tested. Tau and inflammation imaging, still in their infancy, combined with genomics, should provide powerful insights into these disorders and facilitate their treatment.

Multimodality Imaging Approach in Alzheimer disease. Part I: Structural MRI, Functional MRI, Diffusion Tensor Imaging and Magnetization Transfer Imaging

The authors make a complete review of the potential clinical applications of traditional and novel magnetic resonance imaging (MRI) techniques in the evaluation of patients with Alzheimer's disease, including structural MRI, functional MRI, diffusion tension imaging and magnetization transfer imaging.

Investigation of resolution effects using a specialized diffusion tensor phantom

PURPOSE

The clinical potential of the diffusion imaging-based analysis of fine brain structures such as fornix or cingulum is high due to the central role of these structures in psychiatric diseases. However, the quantification of diffusion parameters in fine structures is especially prone to partial volume effects (PVEs).

METHODS

In this study, a phantom for the investigation of PVEs and their influence on diffusion parameters in fine structures of different diameter is presented. The phantom is produced by winding wet polyester fibers onto a spindle. The resulting fiber strands have well defined square cross-sections of 1-25 mm(2) and provide a homogeneous and high fractional anisotropy (FA ≈ 0.9).

RESULTS

Several PVEs are demonstrated and analyzed. It is shown that inferred results such as the fiber geometry and diffusion parameters strongly depend on the relative position of the structure of interest to the voxel-grid. Several implications of PVEs on post-processing methods such as Tract-based Spatial Statistics and fiber tractography are demonstrated.

CONCLUSION

These results show that the handling of PVEs in common post-processing tasks can be problematic, and that the presented phantom provides a valuable tool for the improvement and evaluation of these effects.

Atlas-based diffusion tensor imaging correlates of executive function

Impairment in executive function (EF) is commonly found in Alzheimer's disease (AD) and mild cognitive impairment (MCI). Atlas-based diffusion tensor imaging (DTI) methods may be useful in relating regional integrity to EF measures in MCI and AD. Sixty-six participants (25 normal controls, 22 MCI, and 19 AD) received DTI scans and clinical evaluation. DTI scans were applied to a pre-segmented atlas and fractional anisotropy (FA) and mean diffusivity (MD) were calculated. ANOVA was used to assess group differences in frontal, parietal, and cerebellar regions. For regions differing between groups (p < 0.01), linear regression examined the relationship between EF scores and regional FA and MD. Anisotropy and diffusivity in frontal and parietal lobe white matter structures were associated with EF scores in MCI and only frontal lobe structures in AD. EF was more strongly associated with FA than MD. The relationship between EF and anisotropy and diffusivity was strongest in MCI. These results suggest that regional white matter integrity is compromised in MCI and AD and that FA may be a better correlate of EF than MD.

Short-term white matter alterations in Alzheimer's disease characterized by diffusion tensor imaging

PURPOSE

To investigate whether there are any white matter changes in a 6-month follow-up of mild-moderate Alzheimer's patients using diffusion tensor imaging (DTI).

MATERIALS AND METHODS

We recruited 18 mild-moderate Alzheimer's disease patients and they underwent magnetic resonance imaging (MRI) at recruitment and at 6-month follow-up. Diffusion MRI images were processed using DTI-ToolKit to create a population-based tensor template. This template was integrated with a voxel-wise and atlas-based analysis in FSL to determine the magnitude and location of change in diffusion metrics over the 6-month follow-up period.

RESULTS

There were significant widespread changes in diffusion metrics across the entire white matter skeleton (P < 0.001), 95% confidence interval (CI) difference in fractional anisotropy: -0.007 (-0.011, -0.002), mean diffusivity: 0.040 (0.023, 0.058), axial diffusivity: 0.015 (0.008, 0.022), radial diffusivity: 0.012 (0.006, 0.019), as well as regions of interest in the splenium and superior longitudinal fasciculus.

CONCLUSION

Our findings show that diffusion metrics are altered in a 6-month follow-up period of mild-moderate Alzheimer's patients, supporting the potential of DTI metrics to act as sensitive biomarkers for disease progression even over a relatively short time interval, and the potential utility to be applied to clinical trials of putative disease-modifying therapies.

White matter integrity in dementia with Lewy bodies: a voxel-based analysis of diffusion tensor imaging

Many patients with dementia with Lewy bodies (DLB) have overlapping Alzheimer's disease (AD)-related pathology, which may contribute to white matter (WM) diffusivity alterations on diffusion tensor imaging (DTI). Consecutive patients with DLB (n = 30), age- and sex-matched AD patients (n = 30), and cognitively normal controls (n = 60) were recruited. All subjects underwent DTI, 18F 2-fluoro-deoxy-d-glucose, and (11)C Pittsburgh compound B positron emission tomography scans. DLB patients had reduced fractional anisotropy (FA) in the parietooccipital WM but not elsewhere compared with cognitively normal controls, and elevated FA in parahippocampal WM compared with AD patients, which persisted after controlling for β-amyloid load in DLB. The pattern of WM FA alterations on DTI was consistent with the more diffuse posterior parietal and occipital glucose hypometabolism of 2-fluoro-deoxy-d-glucose positron emission tomography in the cortex. DLB is characterized by a loss of parietooccipital WM integrity, independent of concomitant AD-related β-amyloid load. Cortical glucose hypometabolism accompanies WM FA alterations with a concordant pattern of gray and WM involvement in the parietooccipital lobes in DLB.

Detecting statistically significant differences in quantitative MRI experiments, applied to diffusion tensor imaging

In this work we present a framework for reliably detecting significant differences in quantitative magnetic resonance imaging and evaluate it with diffusion tensor imaging (DTI) experiments. As part of this framework we propose a new spatially regularized maximum likelihood estimator that simultaneously estimates the quantitative parameters and the spatially-smoothly-varying noise level from the acquisitions. The noise level estimation method does not require repeated acquisitions. We show that the amount of regularization in this method can be set a priori to achieve a desired coefficient of variation of the estimated noise level. The noise level estimate allows the construction of a Cramér-Rao-lower-bound based test statistic that reliably assesses the significance of differences between voxels within a scan or across different scans. We show that the regularized noise level estimate improves upon existing methods and results in a substantially increased precision of the uncertainty estimates of the DTI parameters. It enables correct specification of the null distribution of the test statistic and with it the test statistic obtains the highest sensitivity and specificity. The source code of the estimation framework, test statistic and experiment scripts are made available to the community.

Diffusion-MRI in neurodegenerative disorders

The ability to image the whole brain through ever more subtle and specific methods/contrasts has come to play a key role in understanding the basis of brain abnormalities in several diseases. In magnetic resonance imaging (MRI), "diffusion" (i.e. the random, thermally-induced displacements of water molecules over time) represents an extraordinarily sensitive contrast mechanism, and the exquisite structural detail it affords has proven useful in a vast number of clinical as well as research applications. Since diffusion-MRI is a truly quantitative imaging technique, the indices it provides can serve as potential imaging biomarkers which could allow early detection of pathological alterations as well as tracking and possibly predicting subtle changes in follow-up examinations and clinical trials. Accordingly, diffusion-MRI has proven useful in obtaining information to better understand the microstructural changes and neurophysiological mechanisms underlying various neurodegenerative disorders. In this review article, we summarize and explore the main applications, findings, perspectives as well as challenges and future research of diffusion-MRI in various neurodegenerative disorders including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Huntington's disease and degenerative ataxias.

Fornix White Matter is Correlated with Resting-State Functional Connectivity of the Thalamus and Hippocampus in Healthy Aging but Not in Mild Cognitive Impairment - A Preliminary Study

In this study, we wished to examine the relationship between the structural connectivity of the fornix, a white matter (WM) tract in the limbic system, which is affected in amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease, and the resting-state functional connectivity (FC) of two key related subcortical structures, the thalamus, and hippocampus. Twenty-two older healthy controls (HC) and 18 older adults with aMCI underwent multi-modal MRI scanning. The fornix was reconstructed using constrained-spherical deconvolution-based tractography. The FC between the thalamus and hippocampus was calculated using a region-of-interest approach from which the mean time series were exacted and correlated. Diffusion tensor imaging measures of the WM microstructure of the fornix were correlated against the Fisher Z correlation values from the FC analysis. There was no difference between the groups in the fornix WM measures, nor in the resting-state FC of the thalamus and hippocampus. We did however find that the relationship between functional and structural connectivity differed significantly between the groups. In the HCs, there was a significant positive association between linear diffusion (CL) in the fornix and the FC of the thalamus and hippocampus, however, there was no relationship between these measures in the aMCI group. These preliminary findings suggest that in aMCI, the relationship between the functional and structural connectivity of regions of the limbic system may be significantly altered compared to healthy ageing. The combined use of diffusion weighted imaging and functional MRI may advance our understanding of neural network changes in aMCI, and elucidate subtle changes in the relationship between structural and functional brain networks.

Quantitative measurement to evaluate morphological changes of the corpus callosum in patients with subcortical ischemic vascular dementia

BACKGROUND

Subcortical ischemic vascular dementia (SIVD) is a subtype of dementia associated with abnormalities in the subcortical white matter regions. Recent imaging techniques can be used to detect such abnormalities in vivo.

PURPOSE

To examine morphological changes of the corpus callosum in patients with SIVD by using magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI).

MATERIAL AND METHODS

MRI was performed to explore changes of cerebral white matter, especially corpus callosum. Brain matter diffusivity was examined with DTI by measuring the fractional anisotropy (FA). Results of 30 patients diagnosed with SIVD and 30 healthy subjects were analyzed and compared.

RESULTS

The thicknesses of the genu, the anterior third, middle, and posterior third of the body, and the splenium of the corpus callosum were smaller in SIVD patients compared to healthy controls (0.54 ± 0.08 vs. 0.68 ± 0.09 cm, P = 0.0011; 0.27 ± 0.06 vs. 0.38 ± 0.07 cm, P = 0.002; 0.28 ± 0.05 vs. 0.38 ± 0.08 cm, P = 0.009; 0.18 ± 0.04 vs. 0.26 ± 0.06 cm, P = 0.013; 0.54 ± 0.07 vs. 0.72 ± 0.09 cm, P = 0.003, respectively). The FA values of the genu and splenium of the corpus callosum in patients with SIVD were decreased compared to healthy controls (0.664 ± 0.042 vs. 0.778 ± 0.041, P < 0.001; 0.691 ± 0.038 vs. 0.786 ± 0.039, P = 0.001, respectively).

CONCLUSION

Patients with SIVD exhibit corpus callosum atrophy and morphological changes, and these characteristics may be useful for diagnosis.

Principles and management of neuropsychiatric symptoms in Alzheimer's dementia

Neuropsychiatric symptoms of Alzheimer's disease (NPS-AD) are highly prevalent and lead to poor medical and functional outcomes. In spite of the burdensome nature of NPS-AD, we are continuing to refine the nosology and only beginning to understand the underlying pathophysiology. Cluster analyses have frequently identified three to five subsyndromes of NPS-AD: behavioral dysfunction (for example, agitation/aggressiveness), psychosis (for example, delusions and hallucinations), and mood disturbance (for example, depression or apathy). Recent neurobiological studies have used new neuroimaging techniques to elucidate behaviorally relevant circuits and networks associated with these subsyndromes. Several fronto-subcortical circuits, cortico-cortical networks, and neurotransmitter systems have been proposed as regions and mechanisms underlying NPS-AD. Common to most of these subsyndromes is the broad overlap of regions associated with the salience network (anterior cingulate and insula), mood regulation (amygdala), and motivated behavior (frontal cortex). Treatment strategies for dysregulated mood syndromes (depression and apathy) have primarily targeted serotonergic mechanisms with antidepressants or dopaminergic mechanisms with psychostimulants. Psychotic symptoms have largely been targeted with anti-psychotic medications despite controversial risk/benefit tradeoffs. Management of behavioral dyscontrol, including agitation and aggression in AD, has encompassed a wide range of psychoactive medications as well as non-pharmacological approaches. Developing rational therapeutic approaches for NPS-AD will require a firmer understanding of the underlying etiology in order to improve nosology as well as provide the empirical evidence necessary to overcome regulatory and funding challenges to further study these debilitating symptoms.

White matter disruption at the prodromal stage of Alzheimer's disease: relationships with hippocampal atrophy and episodic memory performance

White matter tract alterations have been consistently described in Alzheimer's disease (AD). In particular, limbic fronto-temporal connections, which are critical to episodic memory function, may degenerate early in the course of the disease. However the relation between white matter tract degeneration, hippocampal atrophy and episodic memory impairment at the earliest stages of AD is still unclear. In this magnetic resonance imaging study, white matter integrity and hippocampal volumes were evaluated in patients with amnestic mild cognitive impairment due to AD (Albert et al., 2011) (n = 22) and healthy controls (n = 15). Performance in various episodic memory tasks was also evaluated in each participant. Relative to controls, patients showed a significant reduction of white matter fractional anisotropy (FA) and increase of radial diffusivity (RD) in the bilateral uncinate fasciculus, parahippocampal cingulum and fornix. Within the patient group, significant intra-hemispheric correlations were notably found between hippocampal grey matter volume and FA in the uncinate fasciculus, suggesting a relationship between atrophy and disconnection of the hippocampus. Moreover, episodic recognition scores were related with uncinate fasciculus FA across patients. These results indicate that fronto-hippocampal connectivity is reduced from the earliest pre-demential stages of AD. Disruption of fronto-hippocampal connections may occur progressively, in parallel with hippocampal atrophy, and may specifically contribute to early initial impairment in episodic memory.

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Limbic fronto-temporal connections (cingulum, uncinate fasciculus and fornix) are altered from the prodromal stage of AD.

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In prodromal AD patients, intra-hemispheric correlations were found between uncinate fasciculus FA and hippocampal atrophy.

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In prodromal AD patients, uncinate fasciculus FA was correlated with scores on episodic recognition.

The fornix in mild cognitive impairment and Alzheimer's disease

The fornix is an integral white matter bundle located in the medial diencephalon and is part of the limbic structures. It serves a vital role in memory functions and as such has become the subject of recent research emphasis in Alzheimer's disease (AD) and mild cognitive impairment (MCI). As the characteristic pathological processes of AD progress, structural and functional changes to the medial temporal lobes and other regions become evident years before clinical symptoms are present. Though gray matter atrophy has been the most studied, degradation of white matter structures especially the fornix may precede these and has become detectable with use of diffusion tensor imaging (DTI) and other complimentary imaging techniques. Recent research utilizing DTI measurement of the fornix has shown good discriminability of diagnostic groups, particularly early and preclinical, as well as predictive power for incident MCI and AD. Stimulating and modulating fornix function by the way of DBS has been an exciting new area as pharmacological therapeutics has been slow to develop.

Fornix as an imaging marker for episodic memory deficits in healthy aging and in various neurological disorders

The fornix is a part of the limbic system and constitutes the major efferent and afferent white matter tracts from the hippocampi. The underdevelopment of or injuries to the fornix are strongly associated with memory deficits. Its role in memory impairments was suggested long ago with cases of surgical forniceal transections. However, recent advances in brain imaging techniques, such as diffusion tensor imaging, have revealed that macrostructural and microstructural abnormalities of the fornix correlated highly with declarative and episodic memory performance. This structure appears to provide a robust and early imaging predictor for memory deficits not only in neurodegenerative and neuroinflammatory diseases, such as Alzheimer's disease and multiple sclerosis, but also in schizophrenia and psychiatric disorders, and during neurodevelopment and “typical” aging. The objective of the manuscript is to present a systematic review regarding published brain imaging research on the fornix, including the development of its tracts, its role in various neurological diseases, and its relationship to neurocognitive performance in human studies.

Longitudinal diffusion tensor imaging in frontotemporal dementia

OBJECTIVE

Novel biomarkers for monitoring progression in neurodegenerative conditions are needed. Measurement of microstructural changes in white matter (WM) using diffusion tensor imaging (DTI) may be a useful outcome measure. Here we report trajectories of WM change using serial DTI in a cohort with behavioral variant frontotemporal dementia (bvFTD).

METHODS

Twenty-three patients with bvFTD (12 having genetic mutations), and 18 age-matched control participants were assessed using DTI and neuropsychological batteries at baseline and ~1.3 years later. Baseline and follow-up DTI scans were registered using a groupwise approach. Annualized rates of change for DTI metrics, neuropsychological measures, and whole brain volume were calculated. DTI metric performances were compared, and sample sizes for potential clinical trials were calculated.

RESULTS

In the bvFTD group as a whole, rates of change in fractional anisotropy (FA) and mean diffusivity (MD) within the right paracallosal cingulum were greatest (FA: -6.8%/yr, p < 0.001; MD: 2.9%/yr, p = 0.01). MAPT carriers had the greatest change within left uncinate fasciculus (FA: -7.9%/yr, p < 0.001; MD: 10.9%/yr, p < 0.001); sporadic bvFTD and C9ORF72 carriers had the greatest change within right paracallosal cingulum (sporadic bvFTD, FA: -6.7%/yr, p < 0.001; MD: 3.8%/yr, p = 0.001; C9ORF72, FA: -6.8%/yr, p = 0.004). Sample size estimates using FA change were substantially lower than neuropsychological or whole brain measures of change.

INTERPRETATION

Serial DTI scans may be useful for measuring disease progression in bvFTD, with particular trajectories of WM damage emerging. Sample size calculations suggest that longitudinal DTI may be a useful biomarker in future clinical trials.

Alzheimer's disease and the fornix

Alzheimer’s disease (AD) is the most common form of neurodegenerative dementia. Researchers have long been focused on the cortical pathology of AD, since the most important pathologic features are the senile plaques found in the cortex, and the neurofibrillary tangles and neuronal loss that begin in the entorhinal cortex and the hippocampus. In addition to these gray matter (GM) structures, histopathological studies indicate that the white matter (WM) is also a good target for both the early diagnosis of AD and for monitoring disease progression. The fornix is a WM bundle that constitutes a core element of the limbic circuits, and is one of the most important anatomical structures related to memory. Functional and anatomical features of the fornix have naturally captured researchers’ attention as possible diagnostic and prognostic markers of AD. Indeed, neurodegeneration of the fornix has been histologically observed in AD, and growing evidence indicates that the alterations seen in the fornix are potentially a good marker to predict future conversion from mild cognitive impairment (MCI) to AD, and even from cognitively normal individuals to AD. The degree of alteration is correlated with the degree of memory impairment, indicating the potential for the use of the fornix as a functional marker. Moreover, there have been attempts to stimulate the fornix using deep brain stimulation (DBS) to augment cognitive function in AD, and ongoing research has suggested positive effects of DBS on brain glucose metabolism in AD patients. On the other hand, disease specificity for fornix degeneration, methodologies to evaluate fornix degeneration, and the clinical significance of the fornix DBS, especially for the long-term impact on the quality of life, are mostly unknown and need to be elucidated.

Diffusion tensor imaging in Alzheimer's disease and affective disorders

The functional organization of the brain in segregated neuronal networks has become a leading paradigm in the study of brain diseases. Diffusion tensor imaging (DTI) allows testing the validity and clinical utility of this paradigm on the structural connectivity level. DTI in Alzheimer's disease (AD) suggests a selective impairment of intracortical projecting fiber tracts underlying the functional disorganization of neuronal networks supporting memory and other cognitive functions. These findings have already been tested for their utility as clinical markers of AD in large multicenter studies. Affective disorders, including major depressive disorder (MDD) and bipolar disorder (BP), show a high comorbidity with AD in geriatric populations and may even have a pathogenetic overlap with AD. DTI studies in MDD and BP are still limited to small-scale monocenter studies, revealing subtle abnormalities in cortico-subcortial networks associated with affect regulation and reward/aversion control. The clinical utility of these findings remains to be further explored. The present paper presents the methodological background of diffusion imaging, including DTI and diffusion spectrum imaging, and discusses key findings in AD and affective disorders. The results of our review strongly point toward the necessity of large-scale multicenter multimodal transnosological networks to study the structural and functional basis of neuronal disconnection underlying different neuropsychiatric diseases.

Tools for multiple granularity analysis of brain MRI data for individualized image analysis

Voxel-based analysis is widely used for quantitative analysis of brain MRI. While this type of analysis provides the highest granularity level of spatial information (i.e., each voxel), the sheer number of voxels and noisy information from each voxel often lead to low sensitivity for detection of abnormalities. To ameliorate this issue, granularity reduction is commonly performed by applying isotropic spatial filtering. This study proposes a systematic reduction of the spatial information using ontology-based hierarchical structural relationships. The 254 brain structures were first defined in multiple (n=29) geriatric atlases. The multiple atlases were then applied to T1-weighted MR images of each subject's data for automated brain parcellation and five levels of ontological relationships were established, which further reduced the spatial dimension to as few as 11 structures. At each ontology level, the amount of atrophy was evaluated, providing a unique view of low-granularity analysis. This reduction of spatial information allowed us to investigate the anatomical features of each patient, demonstrated in an Alzheimer's disease group.

Age-related decline in white matter integrity in a mouse model of tauopathy: an in vivo diffusion tensor magnetic resonance imaging study

Elevated expression of human hyperphosphorylated tau is associated with neuronal loss and white matter (WM) pathology in Alzheimer's disease (AD) and related neurodegenerative disorders. Using in vivo diffusion tensor magnetic resonance imaging (DT-MRI) at 11.1 Tesla we measured age-related alterations in WM diffusion anisotropy indices in a mouse model of human tauopathy (rTg4510) and nontransgenic (nonTg) control mice at the age of 2.5, 4.5, and 8 months. Similar to previous DT-MRI studies in AD subjects, 8-month-old rTg4510 mice showed lower fractional anisotropy (FA) values in WM structures than nonTg. The low WM FA in rTg4510 mice was observed in the genu and splenium of the corpus callosum, anterior commissure, fimbria, and internal capsule and was associated with a higher radial diffusivity than nonTg. Interestingly, rTg4510 mice showed lower estimates for the mode of anisotropy than controls at 2.5 months suggesting that changes in this diffusivity metric are detectable at an early stage preceding severe tauopathy. Immunogold electron microscopy partly supports our diffusion tensor imaging findings. At the age of 4 months, rTg4510 mice show axonal tau inclusions and unmyelinated processes. At later ages (12 months and 14 months) we observed inclusions in myelin sheath, axons, and unmyelinated processes, and a "disorganized" pattern of myelinated fiber arrangement with enlarged inter-axonal spaces in rTg4510 but not in nonTg mice. Our data support a role for the progression of tau pathology in reduced WM integrity measured by DT-MRI. Further in vivo DT-MRI studies in the rTg4510 mouse should help better discern the detailed mechanisms of reduced FA and anisotropy mode, and the specific role of tau during neurodegeneration.

Early Brain Loss in Circuits Affected by Alzheimer's Disease is Predicted by Fornix Microstructure but may be Independent of Gray Matter

In a cohort of community-recruited elderly subjects with normal cognition at initial evaluation, we found that baseline fornix white matter (WM) microstructure was significantly correlated with early volumetric longitudinal tissue change across a region of interest (called fornix significant ROI, fSROI), which overlaps circuits known to be selectively vulnerable to Alzheimer’s dementia pathology. Other WM and gray matter regions had much weaker or non-existent associations with longitudinal tissue change. Tissue loss in fSROI was in turn a significant factor in a survival model of cognitive decline, as was baseline fornix microstructure. These findings suggest that WM deterioration in the fornix and tissue loss in fSROI may be the early beginnings of posterior limbic circuit and default mode network degeneration. We also found that gray matter baseline volumes in the entorhinal cortex and hippocampus predicted cognitive decline in survival models. But since GM regions did not also significantly predict brain-tissue loss, our results may imply a view in which early, prodromal deterioration appears as two quasi independent processes in white and gray matter regions of the limbic circuit crucial to memory.

White matter microstructure in late middle-age: Effects of apolipoprotein E4 and parental family history of Alzheimer's disease

INTRODUCTION

Little is still known about the effects of risk factors for Alzheimer's disease (AD) on white matter microstructure in cognitively healthy adults. The purpose of this cross-sectional study was to assess the effect of two well-known risk factors for AD, parental family history and APOE4 genotype.

METHODS

This study included 343 participants from the Wisconsin Registry for Alzheimer's Prevention, who underwent diffusion tensor imaging (DTI). A region of interest analysis was performed on fractional anisotropy maps, in addition to mean, radial, and axial diffusivity maps, aligned to a common template space using a diffeomorphic, tensor-based registration method. The analysis focused on brain regions known to be affected in AD including the corpus callosum, superior longitudinal fasciculus, fornix, cingulum, and uncinate fasciculus. Analyses assessed the impact of APOE4, parental family history of AD, age, and sex on white matter microstructure in late middle-aged participants (aged 47-76 years).

RESULTS

Both APOE4 and parental family history were associated with microstructural white matter differences. Participants with parental family history of AD had higher FA in the genu of the corpus callosum and the superior longitudinal fasciculus. We observed an interaction between family history and APOE4, where participants who were family history positive but APOE4 negative had lower axial diffusivity in the uncinate fasciculus, and participants who were both family history positive and APOE4 positive had higher axial diffusivity in this region. We also observed an interaction between APOE4 and age, whereby older participants (=65 years of age) who were APOE4 carriers, had higher MD in the superior longitudinal fasciculus and in the portion of the cingulum bundle running adjacent to the cingulate cortex, compared to non-carriers. Older participants who were APOE4 carriers also showed higher radial diffusivity in the genu compared to non-carriers. Across all participants, age had an effect on FA, MD, and axial and radial diffusivities. Sex differences were observed in FA and radial diffusivity.

CONCLUSION

APOE4 genotype, parental family history of AD, age, and sex are all associated with microstructural white matter differences in late middle-aged adults. In participants at risk for AD, alterations in diffusion characteristics-both expected and unexpected-may represent cellular changes occurring at the earliest disease stages, but further work is needed. Higher mean, radial, and axial diffusivities were observed in participants who are more likely to be experiencing later stage preclinical pathology, including participants who were both older and carried APOE4, or who were positive for both APOE4 and parental family history of AD.

Impaired cortical oscillatory coupling in mild cognitive impairment: anatomical substrate and ApoE4 effects

Our current knowledge about the anatomical substrate of impaired resting-state cortical oscillatory coupling in mild cognitive impairment is still rudimentary. Here, we show that both resting-state oscillatory coupling and its anatomical correlates clearly distinguish healthy older (HO) adults from individuals with amnestic mild cognitive impairment (aMCI). aMCI showed failures in neural-phase coupling of resting-state electroencephalographic alpha activity mostly evident between fronto-temporal and parietal regions. As oligomers of amyloid-beta (Aβ) are linked to synaptic dysfunction in Alzheimer's disease (AD), we further investigated whether plasma concentrations of these oligomers (Aβ40 and Aβ42) accounted for impaired patterns of oscillatory coupling in aMCI. Results revealed that decreased plasma Aβ42 was associated with augmented coupling of parieto-temporal regions in HO subjects, but no relationship was found in aMCI. Oscillatory coupling of frontal regions was also significantly reduced in aMCI carriers of the ε4 allele of the Apolipoprotein E (ApoE) compared to ε4 noncarriers, although neither neuroanatomical nor plasma Aβ changes accounted for this difference. However, the abnormal pattern of oscillatory coupling in aMCI was negatively related to volume of the angular gyrus, and positively related to volume of the precuneus and the splenium of the corpus callosum. Previous evidence suggests that all these regions are neuropathological targets of AD. The current study takes that scenario one step further, suggesting that this anatomical damage could be responsible for disrupted cortical oscillatory coupling in aMCI. Together, these data shed light on how the MCI status modifies anatomo-functional relationships underlying coordination of large-scale cortical systems in the resting-state.

Advances in longitudinal studies of amnestic mild cognitive impairment and Alzheimer's disease based on multi-modal MRI techniques

Amnestic mild cognitive impairment (aMCI) is a prodromal stage of Alzheimer's disease (AD), and 75%-80% of aMCI patients finally develop AD. So, early identification of patients with aMCI or AD is of great significance for prevention and intervention. According to cross-sectional studies, it is known that the hippocampus, posterior cingulate cortex, and corpus callosum are key areas in studies based on structural MRI (sMRI), functional MRI (fMRI), and diffusion tensor imaging (DTI) respectively. Recently, longitudinal studies using each MRI modality have demonstrated that the neuroimaging abnormalities generally involve the posterior brain regions at the very beginning and then gradually affect the anterior areas during the progression of aMCI to AD. However, it is not known whether follow-up studies based on multi-modal neuroimaging techniques (e.g., sMRI, fMRI, and DTI) can help build effective MRI models that can be directly applied to the screening and diagnosis of aMCI and AD. Thus, in the future, large-scale multi-center follow-up studies are urgently needed, not only to build an MRI diagnostic model that can be used on a single person, but also to evaluate the variability and stability of the model in the general population. In this review, we present longitudinal studies using each MRI modality separately, and then discuss the future directions in this field.

Associations between white matter microstructure and amyloid burden in preclinical Alzheimer's disease: A multimodal imaging investigation

Some cognitively healthy individuals develop brain amyloid accumulation, suggestive of incipient Alzheimer's disease (AD), but the effect of amyloid on other potentially informative imaging modalities, such as Diffusion Tensor Imaging (DTI), in characterizing brain changes in preclinical AD requires further exploration. In this study, a sample (N = 139, mean age 60.6, range 46 to 71) from the Wisconsin Registry for Alzheimer's Prevention (WRAP), a cohort enriched for AD risk factors, was recruited for a multimodal imaging investigation that included DTI and [C-11]Pittsburgh Compound B (PiB) positron emission tomography (PET). Participants were grouped as amyloid positive (Aβ+), amyloid indeterminate (Aβi), or amyloid negative (Aβ-) based on the amount and pattern of amyloid deposition. Regional voxel-wise analyses of four DTI metrics, fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (Da), and radial diffusivity (Dr), were performed based on amyloid grouping. Three regions of interest (ROIs), the cingulum adjacent to the corpus callosum, hippocampal cingulum, and lateral fornix, were selected based on their involvement in the early stages of AD. Voxel-wise analysis revealed higher FA among Aβ+ compared to Aβ- in all three ROIs and in Aβi compared to Aβ- in the cingulum adjacent to the corpus callosum. Follow-up exploratory whole-brain analyses were consistent with the ROI findings, revealing multiple regions where higher FA was associated with greater amyloid. Lower fronto-lateral gray matter MD was associated with higher amyloid burden. Further investigation showed a negative correlation between MD and PiB signal, suggesting that Aβ accumulation impairs diffusion. Interestingly, these findings in a largely presymptomatic sample are in contradistinction to relationships reported in the literature in symptomatic disease stages of Mild Cognitive Impairment and AD, which usually show higher MD and lower FA. Together with analyses showing that cognitive function in these participants is not associated with any of the four DTI metrics, the present results suggest an early relationship between PiB and DTI, which may be a meaningful indicator of the initiating or compensatory mechanisms of AD prior to cognitive decline.

Ex vivo T2 relaxation: associations with age-related neuropathology and cognition

The transverse relaxation time constant, T(2), is sensitive to brain tissue's free water content and the presence of paramagnetic materials such as iron. In this study, ex vivo magnetic resonance imaging was used to investigate alterations in T(2) related to Alzheimer's disease (AD) pathology and other types of neuropathology common in old age, as well as the relationship between T(2) alterations and cognition. Cerebral hemispheres were obtained from 371 deceased older adults. Using fast spin-echo imaging with multiple echo times, T(2) maps were produced and warped to a study-specific template. Hemispheres underwent neuropathologic examination for identification of AD pathology and other common age-related neuropathologies. Voxelwise linear regression was carried out to detect regions of pathology-related T(2) alterations and, in separate analyses, regions in which T(2) alterations were linked to antemortem cognitive performance. AD pathology was associated with T(2) prolongation in white matter of all lobes and T(2) shortening in the basal ganglia and insula. Gross infarcts were associated with T(2) prolongation in white matter of all lobes, and in the thalamus and basal ganglia. Hippocampal sclerosis was associated with T(2) prolongation in the hippocampus and white matter of the temporal lobe. After controlling for neuropathology, T(2) prolongation in the frontal lobe white matter was associated with lower performance in the episodic, semantic, and working memory domains. In addition, voxelwise analysis of in vivo and ex vivo T(2) values indicated a positive relationship between the two, though further investigation is necessary to accurately translate findings of the present study to the in vivo case.

CSF contamination contributes to apparent microstructural alterations in mild cognitive impairment

Diffusion MRI is used widely to probe microstructural alterations in neurological and psychiatric disease. However, ageing and neurodegeneration are also associated with atrophy, which leads to artefacts through partial volume effects due to cerebrospinal-fluid contamination (CSFC). The aim of this study was to explore the influence of CSFC on apparent microstructural changes in mild cognitive impairment (MCI) at several spatial levels: individually reconstructed tracts; at the level of a whole white matter skeleton (tract-based spatial statistics); and histograms derived from all white matter. 25 individuals with MCI and 20 matched controls underwent diffusion MRI. We corrected for CSFC using a post-acquisition voxel-by-voxel approach of free-water elimination. Tracts varied in their susceptibility to CSFC. The apparent pattern of tract involvement in disease shifted when correction was applied. Both spurious group differences, driven by CSFC, and masking of true differences were observed. Tract-based spatial statistics were found to be robust across much of the skeleton but with some localised CSFC effects. Diffusivity measures were affected disproportionately in MCI, and group differences in fornix microstructure were exaggerated. Group differences in white matter histogram measures were also partly driven by CSFC. For diffusivity measures, up to two thirds of observed group differences were due to CSFC. Our results demonstrate that CSFC has an impact on quantitative differences between MCI and controls. Furthermore, it affects the apparent spatial pattern of white matter involvement. Free-water elimination provides a step towards disentangling intrinsic and volumetric alterations in individuals prone to atrophy.

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We examine the effect of CSFC on perceived microstructural alterations in MCI.

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We correct for CSFC with free-water elimination and assess at three spatial levels.

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The pattern of individual tract involvement is shifted due to CSFC.

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TBSS is robust to CSFC in much of the skeleton.

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Group differences in white matter diffusion histograms are partly driven by CSFC.

Different patterns of white matter disruption among amnestic mild cognitive impairment subtypes: relationship with neuropsychological performance

Amnestic mild cognitive impairment (aMCI) is recognized as the prodromal phase of Alzheimer's disease (AD). Evidence showed that patients with multiple-domain (MD) aMCI were at higher risk of converting to dementia and exhibited more severe gray matter atrophy than single-domain (SD) aMCI. The investigation of the microstructural abnormalities of white matter (WM) among different subtypes of aMCI and their relations with cognitive performances can help to understand the variations among aMCI subtypes and to construct potential imaging based biomarkers to monitor the progression of aMCI. Diffusion-weighted MRI data were acquired from 40 patients with aMCI (aMCI-SD: n = 19; aMCI-MD: n = 21) and 37 healthy controls (HC). Voxel-wise and atlas-based analyses of whole-brain WM were performed among three groups. The correlations between the altered diffusion metrics of the WM tracts and the neuropsychological scores in each subtype of aMCI were assessed. The aMCI-MD patients showed disrupted integrity in multiple WM tracts across the whole-brain when compared with HCs or with aMCI-SD. In contrast, only few WM regions with diffusion changes were found in aMCI-SD as compared to HCs and with less significance. For neuropsychological correlations, only aMCI-MD patients exhibited significant associations between disrupted WM connectivity (in the body of the corpus callosum and the right anterior internal capsules) and cognitive impairments (MMSE and Digit Symb-Coding scores), whereas no such correlations were found in aMCI-SD. These findings indicate that the degeneration extensively exists in WM tracts in aMCI-MD that precedes the development of AD, whereas underlying WM pathology in aMCI-SD is imperceptible. The results are consistent with the view that aMCI is not a uniform disease entity and presents heterogeneity in the clinical progression.

Cingulum correlates of cognitive functions in patients with mild cognitive impairment and early Alzheimer's disease: a diffusion spectrum imaging study

Diffusion spectrum imaging (DSI) of MRI can detect neural fiber tract changes. We investigated integrity of cingulum bundle (CB) in patients with mild cognitive impairment (MCI) and early Alzheimer's disease (EAD) using DSI tractography and explored its relationship with cognitive functions. We recruited 8 patients with MCI, 9 with EAD and 15 healthy controls (HC). All subjects received a battery of neuropsychological tests to access their executive, memory and language functions. We used a 3.0-tesla MRI scanner to obtain T1- and T2-weighted images for anatomy and used a pulsed gradient twice-refocused spin-echo diffusion echo-planar imaging sequence to acquire DSI. Patients with EAD performed significantly poorer than the HC on most tests in executive and memory functions. Significantly smaller general fractional anisotropy (GFA) values were found in the posterior and inferior segments of left CB and of the anterior segment of right CB of the EAD compared with those of the HC. Spearman's correlation on the patient groups showed that GFA values of the posterior segment of the left CB were significantly negatively associated with the time used to complete Color Trails Test Part II and positively correlated with performance of the logical memory and visual reproduction. GFA values of inferior segment of bilateral CB were positively associated with the performance of visual recognition. DSI tractography demonstrates significant preferential degeneration of the CB on the left side in patients with EAD. The location-specific degeneration is associated with corresponding declines in both executive and memory functions.

Full diffusion characterization implicates regionally disparate neuropathology in mild cognitive impairment

Diffusion tensor imaging (DTI) is used to detect tissue pathology. In Alzheimer's disease (AD) research, DTI has been used to elucidate differences in disease stages and to track progression over time and clinical severity. Many of these studies have identified the fornix as particularly vulnerable in the early stages of pathology associated with memory decline in prodromal AD. Emerging research suggests principal tensor components, axial (DA) and radial (DR) diffusivity, are more sensitive to underlying tissue pathology than are mean diffusivity (MD) and fractional anisotropy (FA). Given the established regionally specific tissue decline in MCI, we examined components of the full diffusion tensor (MD, FA, DR, and DA) for sensitivity to regional pathology associated with specific memory deficits in 18 individuals with MCI. We investigated multiple regions of interest, including fornix, temporal stem, and control regions for association with severity of impairment on multiple memory measures, including a type of neuropsychological task shown to be particularly sensitive to early memory decline in MCI. Better paired associate learning was selectively associated with lower DA (β = -0.663, p = 0.003), but not with DR, MD, or FA of the temporal stems. Conversely, better paired associate learning was associated with lower DR (β = -0.523, p = 0.026), higher FA (β = 0.498, p = 0.036), and lower MD (β = -0.513, p = 0.030), but not DA in the fornix. No association was found for control regions, or for control cognitive measures. These findings suggest disparate pathology of temporal stems and fornix white matter in association with early memory impairment in MCI. Further, they highlight the methodological importance of evaluating the full tensor, rather than only summative metrics in research using DTI.

Associations between white matter microstructure and cognitive performance in old and very old age

Increasing age is associated with deficits in a wide range of cognitive domains as well as with structural brain changes. Recent studies using diffusion tensor imaging (DTI) have shown that microstructural integrity of white matter is associated with cognitive performance in elderly persons, especially on tests that rely on perceptual speed. We used structural equation modeling to investigate associations between white matter microstructure and cognitive functions in a population-based sample of elderly persons (age ≥ 60 years), free of dementia, stroke, and neurological disorders (n = 253). Participants underwent a magnetic resonance imaging scan, from which mean fractional anisotropy (FA) and mean diffusivity (MD) of seven white matter tracts were quantified. Cognitive functioning was analyzed according to performance in five task domains (perceptual speed, episodic memory, semantic memory, letter fluency, and category fluency). After controlling for age, FA and MD were exclusively related to perceptual speed. When further stratifying the sample into two age groups, the associations were reliable in the old-old (≥78 years) only. This relationship between white matter microstructure and perceptual speed remained significant after excluding persons in a preclinical dementia phase. The observed pattern of results suggests that microstructural white matter integrity may be especially important to perceptual speed among very old adults.

Use of diffusion tensor imaging for evaluating changes in the microstructural integrity of white matter over 3 years in patients with amnesic-type mild cognitive impairment converting to Alzheimer's disease

BACKGROUND AND PURPOSE

Patients with amnestic mild cognitive impairment (aMCI) are at risk of developing Alzheimer's disease (AD). It is therefore important to identify biomarkers of conversion to AD. This study examined whether the integrity of white matter can predict this conversion.

METHODS

Magnetic resonance imaging (MRI), diffusion tensor imaging (DTI) and neuropsychological features of aMCI subjects (n = 41) were compared with normal controls (n = 20) for 12-36 months.

RESULTS

Compared to controls, 22 aMCI subjects had lower fractional anisotropy (FA) values in the cingulate fasciculus (CF) at baseline, and 19 of those converted to AD during follow-up. Only two of the other 19 aMCI patients converted to AD. Compared to baseline, AD converters showed lower FA values in the anterior frontal lobe, temporal lobe, hippocampus, inferior fronto-occipital fascicles, corpus callosum genu and CF, and higher apparent diffusion coefficient values in the temporal lobe and hippocampus.

CONCLUSIONS

Those aMCI subjects with lower than normal FA values in the CF were more likely to convert to AD. The connectivity of the hippocampus and cingulate bundles may be affected in the early stage of AD. Impairment of white matter and fiber bundles was more severe at the AD stage than the aMCI stage.

White matter abnormalities associated with Alzheimer's disease and mild cognitive impairment: a critical review of MRI studies

In this article, the authors aim to present a critical review of recent MRI studies addressing white matter (WM) abnormalities in Alzheimer's disease (AD) and mild cognitive impairment (MCI), by searching PubMed and reviewing MRI studies evaluating subjects with AD or MCI using WM volumetric methods, diffusion tensor imaging and assessment of WM hyperintensities. Studies have found that, compared with healthy controls, AD and MCI samples display WM volumetric reductions and diffusion tensor imaging findings suggestive of reduced WM integrity. These changes affect complex networks relevant to episodic memory and other cognitive processes, including fiber connections that directly link medial temporal structures and the corpus callosum. Abnormalities in cortico-cortical and cortico-subcortical WM interconnections are associated with an increased risk of progression from MCI to dementia. It can be concluded that WM abnormalities are detectable in early stages of AD and MCI. Degeneration of WM networks causes disconnection among neural cells and the degree of such changes is related to cognitive decline.

Cerebral small vessel disease affects white matter microstructure in mild cognitive impairment

Microstructural white matter deterioration is a frequent finding in mild cognitive impairment (MCI), potentially underlying default mode network (DMN) dysfunctioning. Thus far, microstructural damage in MCI has been attributed to Alzheimer's disease pathophysiology. A cerebrovascular role, in particular the role of cerebral small vessel disease (CSVD), received less interest. Here, we used diffusion tensor imaging (DTI) to examine the role of CSVD in microstructural deterioration within the normal appearing white matter (NAWM) in MCI. MCI patients were subdivided into those with (n = 20) and without (n = 31) macrostructural CSVD evidence on MRI. Using TBSS we performed microstructural integrity comparisons within the whole brain NAWM. Secondly, we segmented white matter tracts interconnecting DMN brain regions by means of automated tractography segmentation. We used NAWM DTI measures from these tracts as dependent variables in a stepwise-linear regression analysis, with structural and demographical predictors. Our results indicated microstructural deterioration within the anterior corpus callosum, internal and external capsule and periventricular white matter in MCI patients with CSVD, while in MCI patients without CSVD, deterioration was restricted to the right perforant path, a tract along the hippocampus. Within the full cohort of MCI patients, microstructure within the NAWM of the DMN fiber tracts was affected by the presence of CSVD. Within the cingulum along the hippocampal cortex we found a relationship between microstructural integrity and ipsilateral hippocampal volume and the extent of white matter hyperintensity. In conclusion, we found evidence of CSVD-related microstructural damage in fiber tracts subserving the DMN in MCI.

Characterization of a normal control group: are they healthy?

We examined the health of a control group (18-81years) in our aging study, which is similar to control groups used in other neuroimaging studies. The current study was motivated by our previous results showing that one third of the elder control group had moderate to severe white matter hyperintensities and/or cortical volume loss which correlated with poor performance on memory tasks. Therefore, we predicted that cardiovascular risk factors (e.g., hypertension, high cholesterol) within the control group would account for significant variance on working memory task performance. Fifty-five participants completed 4 verbal and spatial working memory tasks, neuropsychological exams, diffusion tensor imaging (DTI), and blood tests to assess vascular risk. In addition to using a repeated measures ANOVA design, a cluster analysis was applied to the vascular risk measures as a data reduction step to characterize relationships between conjoint risk factors. The cluster groupings were used to predict working memory performance. The results show that higher levels of systolic blood pressure were associated with: 1) poor spatial working memory accuracy; and 2) lower fractional anisotropy (FA) values in multiple brain regions. In contrast, higher levels of total cholesterol corresponded with increased accuracy in verbal working memory. An association between lower FA values and higher cholesterol levels were identified in different brain regions from those associated with systolic blood pressure. The conjoint risk analysis revealed that Risk Cluster Group 3 (the group with the greatest number of risk factors) displayed: 1) the poorest performance on the spatial working memory tasks; 2) the longest reaction times across both spatial and verbal memory tasks; and 3) the lowest FA values across widespread brain regions. Our results confirm that a considerable range of vascular risk factors are present in a typical control group, even in younger individuals, which have robust effects on brain anatomy and function. These results present a new challenge to neuroimaging studies both for defining a cohort from which to characterize 'normative' brain circuitry and for establishing a control group to compare with other clinical populations.

Evaluation of group-specific, whole-brain atlas generation using Volume-based Template Estimation (VTE): application to normal and Alzheimer's populations

MRI-based human brain atlases, which serve as a common coordinate system for image analysis, play an increasingly important role in our understanding of brain anatomy, image registration, and segmentation. Study-specific brain atlases are often obtained from one of the subjects in a study or by averaging the images of all participants after linear or non-linear registration. The latter approach has the advantage of providing an unbiased anatomical representation of the study population. But, the image contrast is influenced by both inherent MR contrasts and residual anatomical variability after the registration; in addition, the topology of the brain structures cannot reliably be preserved. In this study, we demonstrated a population-based template-creation approach, which is based on Bayesian template estimation on a diffeomorphic random orbit model. This approach attempts to define a population-representative template without the cross-subject intensity averaging; thus, the topology of the brain structures is preserved. It has been tested for segmented brain structures, such as the hippocampus, but its validity on whole-brain MR images has not been examined. This paper validates and evaluates this atlas generation approach, i.e., Volume-based Template Estimation (VTE). Using datasets from normal subjects and Alzheimer's patients, quantitative measurements of sub-cortical structural volumes, metric distance, displacement vector, and Jacobian were examined to validate the group-averaged shape features of the VTE. In addition to the volume-based quantitative analysis, the preserved brain topology of the VTE allows surface-based analysis within the same atlas framework. This property was demonstrated by analyzing the registration accuracy of the pre- and post-central gyri. The proposed method achieved registration accuracy within 1mm for these population-preserved cortical structures in an elderly population.

Longitudinal, region-specific course of diffusion tensor imaging measures in mild cognitive impairment and Alzheimer's disease

BACKGROUND

Diffusion tensor imaging (DTI) is a promising method for identifying significant cross-sectional differences of white-matter tracts in normal controls (NC) and those with mild cognitive impairment (MCI) or Alzheimer's disease (AD). There have not been many studies establishing its longitudinal utility.

METHODS

Seventy-five participants (25 NC, 25 amnestic MCI, and 25 AD) had 3-Tesla MRI scans and clinical evaluations at baseline and 3, 6, and 12 months. Fractional anisotropy (FA) and mean diffusivity (MD) were analyzed at each time-point and longitudinally in eight a priori-selected areas taken from four regions of interest (ROIs).

RESULTS

Cross-sectionally, MD values were higher, and FA values lower in the fornix and splenium of the AD group compared with either MCI or NC (P < .01). Within-group change was more evident in MD than in FA over 12 months: MD increased in the inferior, anterior cingulum, and fornix in both the MCI and AD groups (P < .01).

CONCLUSIONS

There were stable, cross-sectional, region-specific differences between the NC and AD groups in both FA and MD at each time-point over 12 months. Longitudinally, MD was a better indicator of change than FA. Significant increases of fornix MD in the MCI group suggest this is an early indicator of progression.

Gross feature recognition of Anatomical Images based on Atlas grid (GAIA): Incorporating the local discrepancy between an atlas and a target image to capture the features of anatomic brain MRI

We aimed to develop a new method to convert T1-weighted brain MRIs to feature vectors, which could be used for content-based image retrieval (CBIR). To overcome the wide range of anatomical variability in clinical cases and the inconsistency of imaging protocols, we introduced the Gross feature recognition of Anatomical Images based on Atlas grid (GAIA), in which the local intensity alteration, caused by pathological (e.g., ischemia) or physiological (development and aging) intensity changes, as well as by atlas–image misregistration, is used to capture the anatomical features of target images.

As a proof-of-concept, the GAIA was applied for pattern recognition of the neuroanatomical features of multiple stages of Alzheimer's disease, Huntington's disease, spinocerebellar ataxia type 6, and four subtypes of primary progressive aphasia. For each of these diseases, feature vectors based on a training dataset were applied to a test dataset to evaluate the accuracy of pattern recognition. The feature vectors extracted from the training dataset agreed well with the known pathological hallmarks of the selected neurodegenerative diseases. Overall, discriminant scores of the test images accurately categorized these test images to the correct disease categories. Images without typical disease-related anatomical features were misclassified. The proposed method is a promising method for image feature extraction based on disease-related anatomical features, which should enable users to submit a patient image and search past clinical cases with similar anatomical phenotypes.

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A novel method to convert anatomical brain MRIs to feature vectors is introduced.

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Degree of local atlas–image disagreement is used to capture the anatomical features.

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The method was applied for pattern recognition of various neurodegenerative diseases.

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The feature vectors agreed well with the known pathological hallmarks of diseases.

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The method accurately categorized test images to the correct disease categories.

Effectiveness of regional DTI measures in distinguishing Alzheimer's disease, MCI, and normal aging

The Alzheimer's Disease Neuroimaging Initiative (ADNI) recently added diffusion tensor imaging (DTI), among several other new imaging modalities, in an effort to identify sensitive biomarkers of Alzheimer's disease (AD). While anatomical MRI is the main structural neuroimaging method used in most AD studies and clinical trials, DTI is sensitive to microscopic white matter (WM) changes not detectable with standard MRI, offering additional markers of neurodegeneration. Prior DTI studies of AD report lower fractional anisotropy (FA), and increased mean, axial, and radial diffusivity (MD, AxD, RD) throughout WM. Here we assessed which DTI measures may best identify differences among AD, mild cognitive impairment (MCI), and cognitively healthy elderly control (NC) groups, in region of interest (ROI) and voxel-based analyses of 155 ADNI participants (mean age: 73.5 ± 7.4; 90 M/65 F; 44 NC, 88 MCI, 23 AD). Both VBA and ROI analyses revealed widespread group differences in FA and all diffusivity measures. DTI maps were strongly correlated with widely-used clinical ratings (MMSE, CDR-sob, and ADAS-cog). When effect sizes were ranked, FA analyses were least sensitive for picking up group differences. Diffusivity measures could detect more subtle MCI differences, where FA could not. ROIs showing strongest group differentiation (lowest p-values) included tracts that pass through the temporal lobe, and posterior brain regions. The left hippocampal component of the cingulum showed consistently high effect sizes for distinguishing groups, across all diffusivity and anisotropy measures, and in correlations with cognitive scores.