Diffusion-weighted and magnetization transfer imaging of the corpus callosum in Alzheimer's disease

Abnormal white matter changes in Alzheimer's disease based on diffusion tensor imaging: A systematic review

Alzheimer's disease (AD) is a degenerative neurological disease in elderly individuals. Subjective cognitive decline (SCD), mild cognitive impairment (MCI) and further development to dementia (d-AD) are considered to be major stages of the progressive pathological development of AD. Diffusion tensor imaging (DTI), one of the most important modalities of MRI, can describe the microstructure of white matter through its tensor model. It is widely used in understanding the central nervous system mechanism and finding appropriate potential biomarkers for the early stages of AD. Based on the multilevel analysis methods of DTI (voxelwise, fiberwise and networkwise), we summarized that AD patients mainly showed extensive microstructural damage, structural disconnection and topological abnormalities in the corpus callosum, fornix, and medial temporal lobe, including the hippocampus and cingulum. The diffusion features and structural connectomics of specific regions can provide information for the early assisted recognition of AD. The classification accuracy of SCD and normal controls can reach 92.68% at present. And due to the further changes of brain structure and function, the classification accuracy of MCI, d-AD and normal controls can reach more than 97%. Finally, we summarized the limitations of current DTI-based AD research and propose possible future research directions.

Saturation Transfer MRI for Detection of Metabolic and Microstructural Impairments Underlying Neurodegeneration in Alzheimer's Disease

Alzheimer's disease (AD) is one of the most common causes of dementia and difficult to study as the pool of subjects is highly heterogeneous. Saturation transfer (ST) magnetic resonance imaging (MRI) methods are quantitative modalities with potential for non-invasive identification and tracking of various aspects of AD pathology. In this review we cover ST-MRI studies in both humans and animal models of AD over the past 20 years. A number of magnetization transfer (MT) studies have shown promising results in human brain. Increased computing power enables more quantitative MT studies, while access to higher magnetic fields improves the specificity of chemical exchange saturation transfer (CEST) techniques. While much work remains to be done, results so far are very encouraging. MT is sensitive to patterns of AD-related pathological changes, improving differential diagnosis, and CEST is sensitive to particular pathological processes which could greatly assist in the development and monitoring of therapeutic treatments of this currently incurable disease.

Altered Connection and Diagnosis Utility of White Matter in Alzheimer's Disease: A Multi-site Automated Fiber Quantification Study

Alzheimer's disease (AD) is a typical neurodegenerative disease that is associated with cognitive decline, memory loss, and functional disconnection. Diffusion tensor imaging (DTI) has been widely used to investigate the integrity and degeneration of white matter in AD. In this study, with one of the world's largest DTI biobanks (865 individuals), we aim to explore the diagnosis utility and stability of tractbased features (extracted by automated fiber quantification (AFQ) pipeline) in AD. First, we studied the clinical association of tract-based features by detecting AD-associated alterations of diffusion properties along fiber bundles. Then, a binary classification experiment between AD and normal controls was performed using tract-based diffusion properties as features and support vector machine (SVM) as a classifier with an independent site cross-validation strategy. The average accuracy of 77.90% (the highest was 88.89%) showed that white matter properties as biomarkers had a relatively stable role in the clinical diagnosis of AD.Clinical Relevance- White matter characteristics are valid and robust biomarkers of AD, which have high accuracy and generalizability in the AD diagnosis in a large multi-site dataset.

Vascular health and diffusion properties of normal appearing white matter in midlife

In this study, we perform a region of interest diffusion tensor imaging and advanced diffusion complexity analysis of normal appearing white matter to determine the impact of vascular health on these diffusivity metrics in midlife adults. 77 participants (26 black, 35 female) at year 30 visit in the Coronary Artery Risk Development in Young Adults longitudinal study were scanned with an advanced diffusion-weighted imaging and fluid-attenuated inversion recovery protocol. Fractional anisotropy and non-linear diffusion complexity measures were estimated. Cumulative measures across 30 years (9 study visits) of systolic blood pressure, body mass index, glucose, smoking and cholesterol were calculated as the area under the curve from baseline up to year 30 examination. Partial correlation analyses assessed the association between cumulative vascular health measures and normal appearing white matter diffusion metrics in these participants. Midlife normal appearing white matter diffusion properties were significantly associated (P < 0.05) with cumulative exposure to vascular risk factors from young adulthood over the 30-year time period. Higher cumulative systolic blood pressure exposure was associated with increased complexity and decreased fractional anisotropy. Higher cumulative body mass index exposure was associated with decreased fractional anisotropy. Additionally, in the normal appearing white matter of black participants (P < 0.05), who exhibited a higher cumulative vascular risk exposure, fractional anisotropy was lower and complexity was higher in comparison to normal appearing white matter in white participants. Higher burden of vascular risk factor exposure from young adulthood to midlife is associated with changes in the diffusion properties of normal appearing white matter in midlife. These changes which may reflect axonal disruption, increased inflammation and/or increased glial proliferation, were primarily observed in both anterior and posterior normal appearing white matter regions of the corpus callosum. These results suggest that microstructural changes in normal appearing white matter are sensitive to vascular health during young adulthood and are possibly therapeutic targets in interventions focused on preserving white matter health across life.

The Impact of Hearing Loss on Clinical Dementia and Preclinical Cognitive Impairment in Later Life

BACKGROUND

Dementia and cognitive impairment were significantly associated with hearing loss. The impact of hearing loss on dementia and cognitive impairment is understudied, particularly for different effect on cognitive impairment according to types of hearing loss.

OBJECTIVE

The present study was conducted to elucidate the association between clinically diagnosed dementia and hearing loss with consideration of the type of hearing loss among an elderly population, and to explore the effects of different types of hearing loss on preclinical cognitive impairment.

METHODS

Data (n = 59,675) from the Korean National Health Insurance Service-Health Screening were used to calculate odds ratios (OR) for cognitive impairment according to type of hearing loss (conductive, sensorineural, mixed, and noise-induced hearing losses, and presbycusis). Cognitive impairment was assessed using the Korean Dementia Screening Questionnaire-Prescreening (KDSQ-P).

RESULTS

Cognitive impairment was significantly associated with conductive (OR: 1.45, 95% confidence interval (CI): 1.20-1.77), sensorineural (OR: 1.23, CI: 1.12-1.36), and noise-induced hearing loss (OR: 1.32, CI: 1.12-1.56), and presbycusis (OR: 1.53, CI: 1.25-1.87). Among participants scoring positive on the KDSQ-P (score≥4), the KDSQ-P score was significantly elevated in the mixed and noise-induced hearing loss groups.

CONCLUSION

This study revealed a significant correlation between different types of hearing loss and cognitive impairment. Noise-induced hearing loss is especially important because it occurs earlier than other types of hearing loss and has large effects on cognitive impairment.

Diagnosis of Alzheimer's Disease Using Brain Network

Recent studies suggest the brain functional connectivity impairment is the early event occurred in case of Alzheimer’s disease (AD) as well as mild cognitive impairment (MCI). We model the brain as a graph based network to study these impairment. In this paper, we present a new diagnosis approach using graph theory based features from functional magnetic resonance (fMR) images to discriminate AD, MCI, and healthy control (HC) subjects using different classification techniques. These techniques include linear support vector machine (LSVM), and regularized extreme learning machine (RELM). We used pairwise Pearson’s correlation-based functional connectivity to construct the brain network. We compare the classification performance of brain network using Alzheimer’s disease neuroimaging initiative (ADNI) datasets. Node2vec graph embedding approach is employed to convert graph features to feature vectors. Experimental results show that the SVM with LASSO feature selection method generates better classification accuracy compared to other classification technique.

Enhanced White Matter Integrity in Corpus Callosum of Long-Term Brahmakumaris Rajayoga Meditators

Meditation has a versatile nature to affect cognitive functioning of human brain. Recent researches demonstrated its effects on white matter (WM) properties of human brain. In this research, we aim to investigate WM microstructure of corpus callosum (CC) in long-term meditators (LTMs) of rajayoga meditation using diffusion tensor imaging. For this cross-sectional analysis, 22 LTMs and 17 control participants of age ranging from 30 to 50 years were recruited. Results show high fractional anisotropy values with low mean diffusivity in whole as well as different segments of CC in the LTM group. Also the experience of meditation was correlated with WM properties of CC tracts. Findings may suggest rajayoga meditation to bring potential changes in microstructure of CC segments. Further studies are suggested in clinical population to check its validity and efficacy against disorders involving agenesis of WM.

Microstructural white matter alterations in preclinical Alzheimer's disease detected using free water elimination diffusion tensor imaging

Brain changes associated with Alzheimer's disease (AD) begin decades before disease diagnosis. While β-amyloid plaques and neurofibrillary tangles are defining features of AD, neuronal loss and synaptic pathology are closely related to the cognitive dysfunction. Brain imaging methods that are tuned to assess degeneration of myelinated nerve fibers in the brain (collectively called white matter) include diffusion tensor imaging (DTI) and related techniques, and are expected to shed light on disease-related loss of structural connectivity. Participants (N = 70, ages 47-76 years) from the Wisconsin Registry for Alzheimer's Prevention study underwent DTI and hybrid diffusion imaging to determine a free-water elimination (FWE-DTI) model. The study assessed the extent to which preclinical AD pathology affects brain white matter. Preclinical AD pathology was determined using cerebrospinal fluid (CSF) biomarkers. The sample was enriched for AD risk (APOE ε4 and parental history of AD). AD pathology assessed by CSF analyses was significantly associated with altered microstructure on both DTI and FWE-DTI. Affected regions included frontal, parietal, and especially temporal white matter. The f-value derived from the FWE-DTI model appeared to be the most sensitive to the relationship between the CSF AD biomarkers and microstructural alterations in white matter. These findings suggest that white matter degeneration is an early pathological feature of AD that may have utility both for early disease detection and as outcome measures for clinical trials. More complex models of microstructural diffusion properties including FWE-DTI may provide increased sensitivity to early brain changes associated with AD over standard DTI.

3D tract-specific local and global analysis of white matter integrity in Alzheimer's disease

Alzheimer's disease (AD) is a chronic neurodegenerative disease characterized by progressive decline in memory and other aspects of cognitive function. Diffusion‐weighted imaging (DWI) offers a non‐invasive approach to delineate the effects of AD on white matter (WM) integrity. Previous studies calculated either some summary statistics over regions of interest (ROI analysis) or some statistics along mean skeleton lines (Tract Based Spatial Statistic [TBSS]), so they cannot quantify subtle local WM alterations along major tracts. Here, a comprehensive WM analysis framework to map disease effects on 3D tracts both locally and globally, based on a study of 200 subjects: 49 healthy elderly normal controls, 110 with mild cognitive impairment, and 41 AD patients has been presented. 18 major WM tracts were extracted with our automated clustering algorithm—autoMATE (automated Multi‐Atlas Tract Extraction); we then extracted multiple DWI‐derived parameters of WM integrity along the WM tracts across all subjects. A novel statistical functional analysis method—FADTTS (Functional Analysis for Diffusion Tensor Tract Statistics) was applied to quantify degenerative patterns along WM tracts across different stages of AD. Gradually increasing WM alterations were found in all tracts in successive stages of AD. Among all 18 WM tracts, the fornix was most adversely affected. Among all the parameters, mean diffusivity (MD) was the most sensitive to WM alterations in AD. This study provides a systematic workflow to examine WM integrity across automatically computed 3D tracts in AD and may be useful in studying other neurological and psychiatric disorders. Hum Brain Mapp 38:1191–1207, 2017. © 2016 Wiley Periodicals, Inc.

On the early diagnosis of Alzheimer's Disease from multimodal signals: A survey

INTRODUCTION

The number of Alzheimer's Disease (AD) patients is increasing with increased life expectancy and 115.4 million people are expected to be affected in 2050. Unfortunately, AD is commonly diagnosed too late, when irreversible damages have been caused in the patient.

OBJECTIVE

An automatic, continuous and unobtrusive early AD detection method would be required to improve patients' life quality and avoid big healthcare costs. Thus, the objective of this survey is to review the multimodal signals that could be used in the development of such a system, emphasizing on the accuracy that they have shown up to date for AD detection. Some useful tools and specific issues towards this goal will also have to be reviewed.

METHODS

An extensive literature review was performed following a specific search strategy, inclusion criteria, data extraction and quality assessment in the Inspec, Compendex and PubMed databases.

RESULTS

This work reviews the extensive list of psychological, physiological, behavioural and cognitive measurements that could be used for AD detection. The most promising measurements seem to be magnetic resonance imaging (MRI) for AD vs control (CTL) discrimination with an 98.95% accuracy, while electroencephalogram (EEG) shows the best results for mild cognitive impairment (MCI) vs CTL (97.88%) and MCI vs AD distinction (94.05%). Available physiological and behavioural AD datasets are listed, as well as medical imaging analysis steps and neuroimaging processing toolboxes. Some issues such as "label noise" and multi-site data are discussed.

CONCLUSIONS

The development of an unobtrusive and transparent AD detection system should be based on a multimodal system in order to take full advantage of all kinds of symptoms, detect even the smallest changes and combine them, so as to detect AD as early as possible. Such a multimodal system might probably be based on physiological monitoring of MRI or EEG, as well as behavioural measurements like the ones proposed along the article. The mentioned AD datasets and image processing toolboxes are available for their use towards this goal. Issues like "label noise" and multi-site neuroimaging incompatibilities may also have to be overcome, but methods for this purpose are already available.

Mild Cognitive Impairment is Associated With White Matter Integrity Changes in Late-Myelinating Regions Within the Corpus Callosum

Degenerative brain changes in Alzheimer's disease may occur in reverse order of normal brain development based on the retrogenesis model. This study tested whether evidence of reverse myelination was observed in mild cognitive impairment (MCI) using a data-driven analytic approach based on life span developmental data. Whole-brain high-resolution diffusion tensor imaging scans were obtained for 31 patients with MCI and 79 demographically matched healthy older adults. Comparisons across corpus callosum (CC) regions of interest (ROIs) showed decreased fractional anisotropy (FA) in the body but not in the genu or splenium; early-, middle-, and late-myelinating ROIs restricted to the CC revealed decreased FA in late- but not early- or middle-myelinating ROIs. Voxelwise group differences revealed areas of lower FA in MCI, but whole-brain differences were equally distributed across early-, middle-, and late-myelinating regions. Overall, results within the CC support the retrogenesis model, although caution is needed when generalizing these results beyond the CC.

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.

Corpus callosum atrophy associated with the degree of cognitive decline in patients with Alzheimer's dementia or mild cognitive impairment: a meta-analysis of the region of interest structural imaging studies

Individual structural neuroimaging studies of the corpus callosum (CC) in Alzheimer's disease (AD) and mild cognitive impairment (MCI) with the region of interest (ROI) analysis have yielded inconsistent findings. The aim of this study was to conduct a meta-analysis of structural imaging studies using ROI technique to measure the CC midsagittal area changes in patients with AD or MCI. Databases of PubMed, the Cochrane Library, the ISI Web of Science, and Science Direct from inception to June 2014 were searched with key words "corpus callosum" or "callosal", plus "Alzheimer's disease" or "mild cognitive impairment". Twenty-three studies with 603 patients with AD, 146 with MCI, and 638 healthy controls were included in this meta-analysis. Effect size was used to measure the difference between patients with AD or MCI and healthy controls. Significant callosal atrophy was found in MCI patients with an effect size of -0.36 (95% CI, -0.57 to -0.14; P = 0.001). The degree of the CC atrophy in mild AD was less severe than that in moderate AD with a mean effect size -0.69 (95% CI, -0.89 to -0.49) versus -0.92 (95% CI, -1.16 to -0.69), respectively. Comparing with healthy controls, patients with MCI had atrophy in the anterior portion of the CC (i.e., rostrum and genu). In contrast, patients with AD had atrophy in both anterior and posterior portions (i.e., splenium). These results suggest that callosal atrophy may be related to the degree of cognitive decline in patients with MCI and AD, and it may be used as a biomarker for patients with cognitive deficit even before meeting the criteria for AD.

Brain imaging of mild cognitive impairment and Alzheimer's disease

The rapidly increasing prevalence of cognitive impairment and Alzheimer's disease has the potential to create a major worldwide healthcare crisis. Structural MRI studies in patients with Alzheimer's disease and mild cognitive impairment are currently attracting considerable interest. It is extremely important to study early structural and metabolic changes, such as those in the hippocampus, entorhinal cortex, and gray matter structures in the medial temporal lobe, to allow the early detection of mild cognitive impairment and Alzheimer's disease. The microstructural integrity of white matter can be studied with diffusion tensor imaging. Increased mean diffusivity and decreased fractional anisotropy are found in subjects with white matter damage. Functional imaging studies with positron emission tomography tracer compounds enable detection of amyloid plaques in the living brain in patients with Alzheimer's disease. In this review, we will focus on key findings from brain imaging studies in mild cognitive impairment and Alzheimer's disease, including structural brain changes studied with MRI and white matter changes seen with diffusion tensor imaging, and other specific imaging methodologies will also be discussed.

Diffusion tensor MRI of chemotherapy-induced cognitive impairment in non-CNS cancer patients: a review

Patients with non-central nervous system cancers often experience subtle cognitive deficits after treatment with cytotoxic agents. Therapy-induced structural changes to the brain could be one of the possible causes underlying these reported cognitive deficits. In this review, we evaluate the use of diffusion tensor imaging (DTI) for assessing possible therapy-induced changes in the microstructure of the cerebral white matter (WM) and provide a critical overview of the published DTI research on therapy-induced cognitive impairment. Both cross-sectional and longitudinal DTI studies have demonstrated abnormal microstructural properties in WM regions involved in cognition. These findings correlated with cognitive performance, suggesting that there is a link between reduced "WM integrity" and chemotherapy-induced impaired cognition. In this paper, we will also introduce the basics of diffusion tensor imaging and how it can be applied to evaluate effects of therapy on structural changes in cerebral WM. The review concludes with considerations and discussion regarding DTI data interpretation and possible future directions for investigating therapy-induced WM changes in cancer patients. This review article is part of a Special Issue entitled: Neuroimaging Studies of Cancer and Cancer Treatment.

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.

Magnetization transfer contrast imaging reveals amyloid pathology in Alzheimer's disease transgenic mice

The presence of amyloid plaques in the brain is one of the pathological hallmarks of Alzheimer's disease, which might already be present in the early stage of the disease. Therefore it is important to track amyloid plaques as early as possible. In this paper, we report magnetization transfer contrast magnetic resonance imaging (MTC MRI) as a novel approach to detect amyloid plaques in vivo. Two mice models, APP/PS1 and BRI, developing amyloid pathology were investigated with MTC MRI, T2 relaxation measurements and immunohistochemistry (IHC). MT-ratios of several brain regions were compared to T2-values and correlated with quantitative IHC, revealing amyloid load and gliosis in different brain regions. APP/PS1 mice develop large compact plaques, resembling late stage Alzheimer's disease, while rather small and diffuse plaques are deposited in BRI mice, reflecting early stage of Alzheimer's disease. We found significantly higher MT-ratio's in the brain of APP/PS1 mice as compared to their controls and similar trends in BRI mice. A region based MT-ratio and IHC analysis and correlations between MT-ratios and quantitative IHC indicate amyloid plaques as the main substrate for altered MT-ratios in transgenic animals. We additionally demonstrated the improved sensitivity of MTC MRI to amyloid pathology as compared to traditional T2 relaxation measurements. Our results suggest that MTC MRI reveals extensive, and potentially even early amyloid pathology. Further unraveling the MT-effect of each pathological feature during each stage of AD might indicate MTC MRI as a useful diagnostic technique.

Diffusion tensor metrics as biomarkers in Alzheimer's disease

Background

Although diffusion tensor imaging has been a major research focus for Alzheimer’s disease in recent years, it remains unclear whether it has sufficient stability to have biomarker potential. To date, frequently inconsistent results have been reported, though lack of standardisation in acquisition and analysis make such discrepancies difficult to interpret. There is also, at present, little knowledge of how the biometric properties of diffusion tensor imaging might evolve in the course of Alzheimer’s disease.

Methods

The biomarker question was addressed in this study by adopting a standardised protocol both for the whole brain (tract-based spatial statistics), and for a region of interest: the midline corpus callosum. In order to study the evolution of tensor changes, cross-sectional data from very mild (N = 21) and mild (N = 22) Alzheimer’s disease patients were examined as well as a longitudinal cohort (N = 16) that had been rescanned at 12 months.

Findings and Significance

The results revealed that increased axial and mean diffusivity are the first abnormalities to occur and that the first region to develop such significant differences was mesial parietal/splenial white matter; these metrics, however, remained relatively static with advancing disease indicating they are suitable as ‘state-specific’ markers. In contrast, increased radial diffusivity, and therefore decreased fractional anisotropy–though less detectable early–became increasingly abnormal with disease progression, and, in the splenium of the corpus callosum, correlated significantly with dementia severity; these metrics therefore appear ‘stage-specific’ and would be ideal for monitoring disease progression. In addition, the cross-sectional and longitudinal analyses showed that the progressive abnormalities in radial diffusivity and fractional anisotropy always occurred in areas that had first shown an increase in axial and mean diffusivity. Given that the former two metrics correlate with dementia severity, but the latter two did not, it would appear that increased axial diffusivity represents an upstream event that precedes neuronal loss.

What does the corpus callosum tell us about brain changes in the elderly?

The corpus callosum is the largest hemispheric interconnection bundle in the human brain. Its anterior-posterior fiber caliber gradient can help in understanding the pathophysiological mechanisms underlying white matter changes both in old age and dementia. Here, the Leukoaraiosis and Disability (LADIS) study, a longitudinal cohort study, which shows an association between corpus callosum atrophy and cognitive and motor decline in the elderly, provides the possibility to consider the use of multimodal macro-microstructural imaging of corpus callosum as a marker of structural brain changes of physiological and pathological aging.

CSF T-Tau/Aβ42 predicts white matter microstructure in healthy adults at risk for Alzheimer's disease

Cerebrospinal fluid (CSF) biomarkers T-Tau and Aβ(42) are linked with Alzheimer's disease (AD), yet little is known about the relationship between CSF biomarkers and structural brain alteration in healthy adults. In this study we examined the extent to which AD biomarkers measured in CSF predict brain microstructure indexed by diffusion tensor imaging (DTI) and volume indexed by T1-weighted imaging. Forty-three middle-aged adults with parental family history of AD received baseline lumbar puncture and MRI approximately 3.5 years later. Voxel-wise image analysis methods were used to test whether baseline CSF Aβ(42), total tau (T-Tau), phosphorylated tau (P-Tau) and neurofilament light protein predicted brain microstructure as indexed by DTI and gray matter volume indexed by T1-weighted imaging. T-Tau and T-Tau/Aβ(42) were widely correlated with indices of brain microstructure (mean, axial, and radial diffusivity), notably in white matter regions adjacent to gray matter structures affected in the earliest stages of AD. None of the CSF biomarkers were related to gray matter volume. Elevated P-Tau and P-Tau/Aβ(42) levels were associated with lower recognition performance on the Rey Auditory Verbal Learning Test. Overall, the results suggest that CSF biomarkers are related to brain microstructure in healthy adults with elevated risk of developing AD. Furthermore, the results clearly suggest that early pathological changes in AD can be detected with DTI and occur not only in cortex, but also in white matter.

Unveiling molecular events in the brain by noninvasive imaging

Neuroimaging allows researchers and clinicians to noninvasively assess structure and function of the brain. With the advances of imaging modalities such as magnetic resonance, nuclear, and optical imaging; the design of target-specific probes; and/or the introduction of reporter gene assays, these technologies are now capable of visualizing cellular and molecular processes in vivo. Undoubtedly, the system biological character of molecular neuroimaging, which allows for the study of molecular events in the intact organism, will enhance our understanding of physiology and pathophysiology of the brain and improve our ability to diagnose and treat diseases more specifically. Technical/scientific challenges to be faced are the development of highly sensitive imaging modalities, the design of specific imaging probe molecules capable of penetrating the CNS and reporting on endogenous cellular and molecular processes, and the development of tools for extracting quantitative, biologically relevant information from imaging data. Today, molecular neuroimaging is still an experimental approach with limited clinical impact; this is expected to change within the next decade. This article provides an overview of molecular neuroimaging approaches with a focus on rodent studies documenting the exploratory state of the field. Concepts are illustrated by discussing applications related to the pathophysiology of Alzheimer's disease.

A meta-analysis of voxel-based morphometry studies of white matter volume alterations in Alzheimer's disease

BACKGROUND

Structural neuroimaging studies of white matter volume (WMV) in Alzheimer's disease (AD) with voxel-based morphometry (VBM) have yielded variable findings.

METHODS

A systematic review of VBM studies of WMV of patients with AD and healthy control (HC) subjects indexed in PubMed, ISI Web of Science, and EMBASE from 1990 to June 2011 was conducted. Coordinates were extracted from clusters with significant difference in WMV between patients with AD and HC subjects. Meta-analysis was performed using Effect Size Signed Differential Mapping (ES-SDM).

RESULTS

Eight studies were enrolled, which included 227 patients with AD and 215 HC subjects. WMV reduction at 69 coordinates in AD and no WMV increase were found in the current meta-analysis. Significant reductions were observed in the left parahippocampal gyrus extending to the temporal white matter, the right temporal white matter extending to the parahippocampal gyrus and the posterior corpus callosum. The findings remain largely unchanged in the jackknife sensitivity analyses.

CONCLUSIONS

White matter atrophy was clearly identified in AD, mainly in bilateral structures close to memory formations such as the hippocampus, amygdala, and entorhinal cortex.

Correlating magnetic resonance findings with neuropathology and clinical signs in dogs and cats

The histologic characteristics that are the basis for diagnosis of central nervous system conditions cannot be visualized directly using magnetic resonance (MR) methods, but clinical diagnosis may be based on the frequency and pattern of MR imaging signs, which represent predominantly the gross morphologic features of lesions. Additional quantitative MR measures of myelination, cell swelling, gliosis, and neuronal loss may also be used for more specific characterization of lesions. These measures include magnetization transfer ratio, apparent diffusion coefficient, and the concentrations or ratios of metabolites identified by spectroscopy. Confidence that an MR abnormality is responsible for the clinical signs depends primarily on the degree of correspondence between the site of the lesion and the neuroanatomical localization.

[Mild cognitive impairment: diagnostic value of different MR techniques]

In view of an increasingly aging population the prevalence of dementia is also expected to increase rapidly. As well as clinical, neuropsychological and laboratory procedures magnetic resonance imaging (MRI) plays an important role in the early diagnosis of dementia which is important in the precursor stage of mild cognitive impairment (MCI). On the one hand this stage is associated with an increased risk of dementia and on the other hand an early treatment in this stage could attenuate development of the disease. In addition to morphological changes different functional MRI techniques can help in the early diagnosis of dementia and the precursor stages. Moreover, it is important to detect those MCI patients who are at particularly risk for developing dementia. In the differentiation of converters to non-converters initial studies suggest that particularly voxel-based morphometry, MR spectroscopy and diffusion tensor imaging can provide important additional information.

Regional variation, hemispheric asymmetries and gender differences in pericortical white matter

Brain white matter tissue composition can be quantified using Diffusion Tensor Imaging (DTI) and Magnetization Transfer Imaging (MTI). Fractional Anisotropy (FA), derived from DTI, indexes the integrity, density and organization of axons. Magnetization Transfer Ratio (MTR), derived from MTI, indexes to the presence of cell membranes and myelin. The combined use of FA and MTR provides a more complete picture of white matter structure than either imaging modality in isolation. Here we describe the regional distribution of FA and MTR measurements of pericortical white matter in 56 young, healthy right-handed subjects. Significant regional and lobar differences are seen for both measures along with a significant gender difference in FA. Highly consistent hemispheric asymmetries in FA and MTR were observed, suggesting that the greater fiber coherence and increased myelination of fibers in left hemisphere perisylvian regions may provide a structural basis for left-hemisphere language dominance.

White matter integrity and cortical metabolic associations in aging and dementia

BACKGROUND

Studies show that white matter hyperintensities, regardless of location, primarily affect frontal lobe metabolism and function. This report investigated how regional white matter integrity (measured as fractional anisotropy [FA]) relates to brain metabolism, to unravel the complex relationship between white matter changes and brain metabolism.

OBJECTIVE

To elucidate the relationship between white matter integrity and gray matter metabolism using diffusion tensor imaging and fluorodeoxyglucose-positron emission tomography in a cohort of 16 subjects ranging from normal to demented (age, >55 years).

METHODS

Mean FA values from white matter regions underlying the medial prefrontal, inferior-lateral prefrontal, parietal association, and posterior temporal areas and the corpus callosum were regressed with glucose metabolism (by positron emission tomography), using statistical parametric mapping (P < 0.005; voxel cluster, >100). Regional cerebral glucose metabolism was the primary outcome measure. According to our hypothesis, those hypometabolic cortical regions affected by Alzheimer's disease would correlate with a lower FA of associated tracks.

RESULTS

Our data show inter-regional positive correlations between FA and gray matter metabolism for the prefrontal cortex, temporal, and parietal regions. Our results suggest that left prefrontal FA is associated with left temporal and parietal metabolism. Further, left posterior temporal FA correlated with left prefrontal metabolism. Finally, bilateral parietal FA correlated with bilateral temporal metabolism.

CONCLUSIONS

These regions are associated with cognitive processes affected in Alzheimer's disease and cerebrovascular disease, suggesting a link with white matter degeneration and gray matter hypometabolism. Therefore, cortical function and white matter degeneration are related in aging and dementia.

Diffusion tensor imaging in Alzheimer's disease and mild cognitive impairment

Structural magnetic resonance imaging (MRI) studies of Alzheimer’s disease and mild cognitive impairment (MCI) have focused on the hippocampus and entorhinal cortex; gray matter structures in the medial temporal lobe. Few studies have investigated the integrity of white matter in patients with AD or MCI. Diffusion tensor imaging (DTI) is a MRI technique that allows for the interrogation of the microstructural integrity of white matter. Based on increases in translational diffusion (mean diffusivity: MD) and decreases directional diffusion (fractional anisotropy: FA) damage to white matter can be assessed. Studies have identified regions of increased MD and decreased FA in patients with AD and MCI in all lobes of the brain, as well as medial temporal lobe structures including the hippocampus, entorhinal cortex and parahippocampal white matter. The pattern of white matter integrity disruption tends to follow an anterior to posterior gradient with greater damage noted in posterior regions in AD and MCI. Recent studies have exploited inter-voxel directional similarities to develop models of white matter pathways, and have used these models to assess the integrity of inter-cerebral connections. Particular focus has been applied to the parahippocampal white matter (including the perforant path) and the posterior cingulum. Although many studies have found DTI indicators of impaired white matter in AD and MCI, other studies have failed to detect any differences in MD or FA between the groups, demonstrating the need for large replicative studies. DTI is an evolving technique and advances in its application ought to provide new insights into AD and MCI.

Diffusion tensor imaging for Alzheimer's disease: A review of concepts and potential clinical applicability

In view of the urgent need to identify an early and specific biomarker for Alzheimer's disease (AD), a PubMed database search was performed using the terms "Alzheimer disease" and "Diffusion Magnetic Resonance Imaging" to enable review of Diffusion tensor imaging (DTI) concepts and its potential clinical role in AD evaluation. Detailed analysis of selected abstracts showed that the main DTI measures, fractional anisotropy and apparent diffusion coefficient, indicators of fiber tract integrity, provide a direct assessment of WM fibers and may be used as a new biomarker for AD. These findings were found to correlate with cognitive assessments, rates of AD progression and were also able to differentiate among groups including mild cognitive impairment, AD, and other dementias. Despite several consistent DTI findings in AD patients, there is still a lack of knowledge and studies on the DTI field. DTI is not yet ready for clinical use, and requires extensive further research in order to achieve this goal.

Callosal atrophy in mild cognitive impairment and Alzheimer's disease: different effects in different stages

Alzheimer's Disease (AD) is a neurodegenerative disorder that mainly affects grey matter (GM). Nevertheless, a number of investigations have documented white matter (WM) pathology associated with AD. The corpus callosum (CC) is the largest WM fiber bundle in the human brain. It has been shown to be susceptible to atrophy in AD mainly as a correlate of Wallerian degeneration of commissural nerve fibers of the neocortex. The aim of this study was to investigate which callosal regions are affected and whether callosal degeneration is associated with the stage of the disease. For this purpose, we analyzed high-resolution MRI data of patients with amnesic mild cognitive impairment (MCI) (n=20), mild AD (n=20), severe AD (n=10), and of healthy controls (n=20). Callosal morphology was investigated applying two different structural techniques: mesh-based geometrical modeling methods and whole-brain voxel-based analyses. Our findings indicate significant reductions in severe AD patients compared to healthy controls in anterior (genu and anterior body) and posterior (splenium) sections. In contrast, differences between healthy controls and mild AD patients or amnesic MCI patients were less pronounced and did not survive corrections for multiple comparisons. When correlating anterior and posterior WM density of the CC with GM density of the cortex in the severe AD group, we detected significant positive relationships between posterior sections of the CC and the cortex. We conclude that callosal atrophy is present predominantly in the latest stage of AD, where two mechanisms might contribute to WM alterations in severe AD: the Wallerian degeneration in posterior subregions and the myelin breakdown process in anterior subregions.

Diffusion tensor changes in patients with amnesic mild cognitive impairment and various dementias

White matter damage and its contribution to clinical manifestations in patients with dementia have been increasingly recognized. To explore white matter changes in different types of dementia, we examined brain water diffusivity with diffusion tensor imaging (DTI). We measured fractional anisotropy and mean diffusivity of multiple white matter regions in patients with amnesic mild cognitive impairment (MCI, n=10), Alzheimer's disease (AD, n=30), subcortical ischemic vascular dementia (SIVD, n=18), frontotemporal dementia (FTD, n=7), and control subjects (n=20). We performed pairwise comparisons in each region of interest between patients and controls. MCI patients showed diffusion tensor change (DTC) in the left anterior periventricular (PV) area, possibly in the right posterior PV area, and the genu of the corpus callosum. AD patients showed DTC in the corpus callosum, and in frontal and parieto-occipital subcortical and anterior PV areas. In SIVD patients, DTC occurred in the genu of the corpus callosum, and in bilateral frontal subcortical and PV areas. FTD patients differed from controls in showing DTC in the temporal and frontal subcortical areas, the genu of the corpus callosum and PV areas. The degree of DTC correlated with the clinical severity of dementia as assessed by the clinical dementia rating (CDR). Mean diffusivity was diffusely and positively associated with the CDR scores. Fractional anisotropy of the PV areas was negatively associated with the CDR scores, suggesting a critical role of the lateral cholinergic pathways.

Regional white matter integrity differentiates between vascular dementia and Alzheimer disease

BACKGROUND AND PURPOSE

Considerable clinical and radiological overlap between vascular dementia (VaD) and Alzheimer disease (AD) often makes the diagnosis difficult. Diffusion-tensor imaging studies showed that fractional anisotropy (FA) could be a useful marker for white matter changes. This study aimed to identify regional FA changes to identify a biomarker that could be used to differentiate VaD from AD.

METHODS

T1-weighted and diffusion-tensor imaging scans were obtained in 13 VaD patients, 16 AD patients, and 22 healthy elderly controls. We used tract-based spatial statistics to study regional changes in fractional anisotropy in AD, VaD, and elderly controls. We then used probabilistic tractography to parcel the corpus callosum in 7 regions according to its connectivity with major cerebral cortices using diffusion-tensor imaging data set. We compared the volume and mean FA in each set of transcallosal fibers between groups using ANOVA and then applied a discriminant analysis based on FA and T2-weighted imaging measures.

RESULTS

FA reduction in forceps minor was the most significant area of difference between AD and VaD. Segmentation of the corpus callosum using tractography and comparison of FA changes of each segment confirmed the FA changes in transcallosal prefrontal tracts of patients with VaD when compared to AD. The best discriminant model was the combination of transcallosal prefrontal FA and Fazekas score with 87.5% accuracy, 100% specificity, and 93% sensitivity (P<0.0001).

CONCLUSIONS

Integrating mean FA in the forceps minor to the Fazekas score provides a useful quantitative marker for differentiating AD from VaD.

Diffusion tensor imaging investigations in Alzheimer's disease: the resurgence of white matter compromise in the cortical dysfunction of the aging brain

Diffusion tensor imaging (DTI) is a sophisticated MRI-based neuroimaging technique that enables in vivo quantification of differences in molecular diffusion at the cellular level. Owing to the highly directional architecture of white matter (WM), DTI is providing important clues of the structure and geometric organization of this neural compartment. Since DTI can detect changes even in the case of radiologically "normal" appearing WM, researchers are using the technique for the study of WM integrity at the initial stages of the most common neurodegenerative disorders. Along with a well characterized cortical pathology (neuritic plaques and intracellular neurofibrillary tangles), WM changes have been also demonstrated in Alzheimer's disease (AD). However, these changes had been for years found nonliable in the onset and progress of AD, basically due to lack of incriminatory evidence. The use of novel tools such as DTI has enabled the anatomical distribution of WM microstructural damage in the prodromal stages of AD to be gauged and determined, granting a long-delayed protagonic role to WM in the natural history of this highly prevalent neurodegenerative condition.

Decrease in glucose metabolism in frontal cortex associated with deterioration of microstructure of corpus callosum measured by diffusion tensor imaging in healthy elderly

The neural functions of signaling are carried out by the interconnection of neurons via neuronal fibers. Diffusion tensor imaging has recently become an established technique that enables the in vivo visualization of white matter (WM) fibers. Studies of normal aging have suggested the disruption of WM fiber microstructures with anterior-posterior gradient. Because neuronal activity is tightly coupled with glucose metabolism, neuronal death or a decrease in synaptic activity with aging may cause a decrease in glucose metabolism in the brain. We examined whether the disruption of callosal fiber microstructures in the healthy elderly is accompanied by changes in regional glucose metabolism (rMGlu) in the brain. Fifteen healthy volunteers in their seventies participated. Fractional anisotropies (FAs) of the genu and splenium of the corpus callosum (CC) were measured for each subject, and their correlations with rMGlu were analyzed using SPM2 software. We found a statistically significant positive correlation of rMGlu in the bilateral frontal cortices with the FA of the genu of the CC, whereas there was no correlation of the FA of the splenium of the CC and rMGlu. By voxel-based morphometry, we found no decrease in gray matter concentration associated with FA. The results indicate that neuronal activity in the frontal cortices may decrease with the disruption of the microstructures of the CC without corresponding gray matter atrophy.

Cerebral infarction associated with moyamoya disease: histogram-based quantitative analysis of diffusion tensor imaging -- a preliminary study

Moyamoya disease (MMD) is a rare disorder of unknown etiology in which terminal portions of the internal carotid arteries become steno-occlusive, with fine collateral "moyamoya vessels" formed secondarily, resulting in serial ischemic strokes throughout its clinical course. Whole-brain histogram (WBH) of diffusion tensor imaging (WBH-DTI) is an analytical tool whose feasibility has been ascertained in various pathologies. To elucidate whether WBH-DTI could detect any difference between ischemic MMD and normal controls, we examined 27 consecutive MMD patients without hemorrhage and 48 normal controls in this prospective study using a 3.0-T magnetic resonance scanner. WBHs of fractional anisotropy (FA) (WBH-FA) and mean diffusivity (MD) (WBH-MD) were compared among three groups: Group 1, MMD patients with infarct (n=15); Group 2, MMD patients without infarct (n=12); and Group 3, normal controls (n=48). Group 1 showed significantly higher peak height and significantly lower mean value on WBH-FA, as well as significantly lower peak height and significantly higher mean value on WBH-MD, compared with Groups 2 and 3. No significant difference was seen in parameters at either WBH-FA or WBH-MD between Groups 2 and 3. These results might reflect the pathological severity of each group, and WBH-DTI could feasibly detect differences between ischemic MMD with infarction and MMD without infarction and normal controls.

[Imaging of the Alzheimer's disease: MRI and functional imaging]

The MRI is often the initial exploration proposed to a patient presenting a confusion of memory. This examination has for purpose first to eliminate surgical differential diagnoses, such as a chronic hydrocephalus of the adult. It can then help in the differential diagnosis between the various insane syndromes, like Alzheimer's disease.

MMSE scores correlate with local ventricular enlargement in the spectrum from cognitively normal to Alzheimer disease

In this work, we aimed at correlating focal atrophy in periventricular structures with cognitive function, in the spectrum from healthy subjects to severe Alzheimer disease: 28 subjects with normal cognition and 84 patients presenting various degrees of cognitive impairment were included in the study. The cognitive level of each subject was assessed with the Mini-Mental State Examination (MMSE). Atrophy in periventricular structures was inferred by modeling and analyzing local shape variations of brain ventricles: for a given subject, we distinguished between the severity of atrophy, estimated as local enlargement (in mm) of the ventricular surface relative to an average normal subject, and the extent of atrophy, defined as the percentage of the ventricular surface (global or per anatomical region) significantly different from an average control. Linear regression across subjects was performed to evaluate the correlation between atrophy and MMSE score. The severity of atrophy showed good correlation with MMSE score in the left thalamus, the left temporal horn, the left corona radiata, and the right caudate nuclei. The extent of atrophy showed no significant correlations. In conclusion, the MMSE scores correlate with localized depth of atrophy in well-defined periventricular structures.

Lobar distribution of changes in gray matter and white matter in memory clinic patients: detected using magnetization transfer imaging

BACKGROUND AND PURPOSE

Previous studies have shown involvement of both gray matter (GM) and white matter (WM) in mild cognitive impairment (MCI) and Alzheimer disease (AD). In this study, we assessed the lobar distribution of the GM and WM pathology over the brain and the association of lobar distribution with global cognitive decline.

MATERIALS AND METHODS

Fifty-five patients with AD, 19 patients with MCI, and 43 subjects with normal cognitive function participated in this study. GM and WM were segmented on dual fast spin-echo and fluid-attenuated inversion recovery MR images. A custom template representing anatomic areas was applied. Magnetization transfer imaging (MTI) peak height and mean magnetization transfer ratio (MTR) provided measures for structural brain damage.

RESULTS

Both mean MTR and MTI peak height showed that patients with AD had more structural brain damage in the GM of all lobes compared with controls. Patients with MCI had lower GM peak height compared with controls for the temporal and frontal lobe. WM peak height was lower for all lobes investigated for patients with both AD and MCI. WM mean MTR was lower in the frontal, parietal, and temporal lobes for patients with AD compared with controls. Age and both temporal GM peak height and mean MTR were the only parameters that predicted cognition.

CONCLUSION

This study shows that in addition to more focal GM MTI changes in the temporal and frontal lobes, widespread WM changes are present in the earliest stages of AD. This might point to an important role for WM pathology in the earliest stage of AD.

Magnetic resonance imaging of myelin

The ability to measure myelin in vivo has great consequences for furthering our knowledge of normal development, as well as for understanding a wide range of neurological disorders. The following review summarizes the current state of myelin imaging using MR. We consider five MR techniques that have been used to study myelin: 1) conventional MR, 2) MR spectroscopy, 3) diffusion, 4) magnetization transfer, and 5) T2 relaxation. Fundamental studies involving peripheral nerve and MR/histology comparisons have aided in the interpretation and validation of MR data. We highlight a number of important findings related to myelin development, damage, and repair, and we conclude with a critical summary of the current techniques available and their potential to image myelin in vivo.

Diffusion tensor MRI to investigate dementias: a brief review

Diffusion tensor magnetic resonance imaging (DT-MRI) is a powerful quantitative technique with the ability to detect in vivo microscopic characteristics and abnormalities of brain tissue. It has been successfully applied to a number of neurological conditions, such as stroke, multiple sclerosis and brain tumors, providing information otherwise inaccessible on the pathological substrates. DT-MRI has also been used to study patients with cognitive decline, mainly those with Alzheimer's disease. Several image-analysis approaches have been employed, including region of interest, histogram, voxel-based analyses and DT-MRI-based tractography. Specific patterns of spatial distribution of tissue damage and correlations with neuropsychological measures have been reported. This review focuses on the use of DT-MRI to investigate dementias. The main clinical results and the different methods of image analysis will be overviewed and discussed.

White matter damage in Alzheimer disease and mild cognitive impairment: assessment with diffusion-tensor MR imaging and parallel imaging techniques

PURPOSE

To prospectively determine regional differences in fiber tract integrity between elderly patients with Alzheimer disease (AD), those with mild cognitive impairment (MCI), and healthy elderly subjects by using diffusion-tensor imaging with parallel imaging techniques and a new eight-element receiving coil.

MATERIALS AND METHODS

Institutional review board approval and informed consent were obtained. Fifteen patients with AD (seven men, eight women; mean age; 68.8 years), 16 patients with MCI (nine men, seven women; mean age, 68.9 years) and 19 healthy control subjects (eight men, 11 women; mean age, 63.9 years) underwent diffusion-tensor imaging performed with a 1.5-T magnetic resonance system. An echo-planar imaging diffusion sequence was used with an integrated parallel acquisition technique (PAT) and an eight-element head coil. The mean apparent diffusion coefficient (ADC), fractional anisotropy (FA), and relative anisotropy (RA) values of several white matter (WM) regions were determined. The Kruskal-Wallis test was used initially to test for overall equality of median values in each data group. Single posttest comparisons were performed with the Mann-Whitney U test, with an overall statistical significance level of .05.

RESULTS

FA and RA values were significantly (P < .05) decreased, whereas ADC values in the splenium of the corpus callosum were higher in patients with AD than in patients with MCI. Evidence of higher ADC values in the WM of the temporal lobe was observed in patients with AD compared with the ADC values in patients with MCI and in control subjects. ADC values in the parietal WM were significantly (P < .05) elevated in patients with MCI compared with those in control subjects. The images obtained with integrated PAT showed fewer susceptibility artifacts and were less distorted than images acquired without parallel imaging techniques.

CONCLUSION

Reduced FA and RA values in patients with AD suggest that diffusion-tensor imaging of the brain can be used to confirm clinical manifestation of AD but is less applicable in the detection of MCI.

Quantitative MR imaging in Alzheimer disease

Alzheimer disease (AD) is the most common type of dementia. It currently affects approximately 4 million people in the United States. AD is a progressive neurodegenerative disorder characterized by the gradual deposition of neuritic plaques and neurofibrillary tangles in the brain, which is thought to occur decades before the onset of clinical symptoms. Identification of people at risk before the clinical appearance of dementia has become a priority due to the potential benefits of therapeutic intervention. Although atrophy of medial temporal lobe structures has been shown to correlate with progression of AD, a growing number of recent reports have indicated that such atrophy may not be specific to AD. To improve diagnostic specificity, new quantitative magnetic resonance (MR) imaging methods are being developed that exploit known pathogenic mechanisms exclusive to AD. This article reviews the MR techniques that are currently available for the diagnostic assessment of AD.

Mild Cognitive Impairment: Apparent Diffusion Coefficient in Regional Gray Matter and White Matter Structures

PURPOSE

To prospectively evaluate regional alterations in the apparent diffusion coefficient (ADC) of cortical gray and white matter and subcortical structures that are known to be involved in mild cognitive impairment (MCI).

MATERIALS AND METHODS

Magnetic resonance (MR) imaging was performed in 13 patients with MCI (nine men, four women; mean age, 74 years +/- 6 [standard deviation]) and 13 healthy elderly control subjects (seven men, six women; mean age, 75 years +/- 4). This study was approved by the institutional review board and was HIPAA compliant. Each subject gave informed consent. ADC was measured from manually drawn regions of interest (ROIs) of the hippocampus, parahippocampal gyrus, amygdala, corpus callosum, and anterior and posterior cingulate gyrus and from automatically defined frontal, parietal, occipital, and temporal lobes by using template masking. ROIs were outlined on anatomic images then mapped onto ADC maps by using coregistration transformation matrix. A skeleton-based region competition segmentation algorithm was used for segmentation of gray and white matter. The group difference in ADC values was assessed with independent-sample t tests. Pearson correlation analysis was used to examine the correlation of ADC values with age and memory test scores.

RESULTS

Higher ADCs were found in hippocampus, temporal lobe gray matter, and corpus callosum of patients with MCI compared with that of control subjects (P < .05). By pooling all subjects together, an elevated hippocampal ADC was significantly correlated with worse memory performance scores in 5-minute and 30-minute delayed word-list recall tasks (P < .05).

CONCLUSION

ADCs from gray and white matter of different brain regions can be analyzed by applying an automated template-masking method in conjunction with a skeleton-based region competition segmentation algorithm.

Shape differences of the brain ventricles in Alzheimer's disease

The brain ventricles are surrounded by gray and white matter structures that are often affected in dementia in general and Alzheimer's disease (AD) in particular. Any change of volume or shape occurring in these structures must affect the volume and shape of the ventricles. It is well known that ventricular volume is significantly higher in AD patients compared to age-matched healthy subjects. However, the large overlap between the two volume distributions makes the measurement unsuitable as a biomarker of the disease. The purpose of this work was to assess whether local shape differences of the ventricles can be detected when comparing AD patients and controls. In this work, we captured the ventricle's shape and shape variations of 29 AD subjects and 25 age-matched controls, using a fully automatic shape modeling technique. By applying permutation tests on every single node of a mesh representation of the shapes, we identified local areas with significant differences. About 22% of an average surface of the ventricles presented significant difference (P < 0.05) ( approximately 14% of the left against approximately 7% of the right side). We found out that in patients with Alzheimer disease, not only the lateral horns were significantly affected, but also the areas adjacent to the anterior corpus callosum, the splenium of the corpus callosum, the amygdala, the thalamus, the tale of the caudate nuclei (especially the left one), and the head of the left caudate nucleus.