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Brain magnetic resonance imaging (MRI) studies have demonstrated regional patterns of brain macrostructural atrophy and white matter microstructural alterations separately in the three major subtypes of frontotemporal lobar degeneration (FTLD), which includes behavioral variant frontotemporal dementia (bvFTD), semantic dementia (SD), and progressive nonfluent aphasia (PNFA). This study was to investigate to what extent the pattern of white matter microstructural alterations in FTLD subtypes mirrors the pattern of brain atrophy, and to compare the ability of various diffusion tensor imaging (DTI) indices in characterizing FTLD patients, as well as to determine whether DTI measures provide greater classification power for FTLD than measuring brain atrophy. Twenty-five patients with FTLD (13 with bvFTD, 6 with SD, and 6 with PNFA) and 19 healthy age-matched control subjects underwent both structural MRI and DTI scans. Measurements of regional brain atrophy were based on T1-weighted MRI data and voxel-based morphometry. Measurements of regional white matter degradation were based on voxelwise as well as regions-of-interest tests of DTI variations, expressed as fractional anisotropy, axial diffusivity, and radial diffusivity. Compared to controls, bvFTD, SD, and PNFA patients each exhibited characteristic regional patterns of brain atrophy and white matter damage. DTI overall provided significantly greater accuracy for FTLD classification than brain atrophy. Moreover, radial diffusivity was more sensitive in assessing white matter damage in FTLD than other DTI indices. The findings suggest that DTI in general and radial diffusivity in particular are more powerful measures for the classification of FTLD patients from controls than brain atrophy. [ABSTRACT FROM AUTHOR]

Amyloid-β accumulation in the brain is thought to be one of the earliest events in Alzheimer's disease, possibly leading to synaptic dysfunction, neurodegeneration and cognitive/functional decline. The earliest detectable changes seen with neuroimaging appear to be amyloid-β accumulation detected by (11)C-labelled Pittsburgh compound B positron emission tomography imaging. However, some individuals tolerate high brain amyloid-β loads without developing symptoms, while others progressively decline, suggesting that events in the brain downstream from amyloid-β deposition, such as regional brain atrophy rates, play an important role. The main purpose of this study was to understand the relationship between the regional distributions of increased amyloid-β and the regional distribution of increased brain atrophy rates in patients with mild cognitive impairment. To simultaneously capture the spatial distributions of amyloid-β and brain atrophy rates, we employed the statistical concept of parallel independent component analysis, an effective method for joint analysis of multimodal imaging data. Parallel independent component analysis identified significant relationships between two patterns of amyloid-β deposition and atrophy rates: (i) increased amyloid-β burden in the left precuneus/cuneus and medial-temporal regions was associated with increased brain atrophy rates in the left medial-temporal and parietal regions; and (ii) in contrast, increased amyloid-β burden in bilateral precuneus/cuneus and parietal regions was associated with increased brain atrophy rates in the right medial temporal regions. The spatial distribution of increased amyloid-β and the associated spatial distribution of increased brain atrophy rates embrace a characteristic pattern of brain structures known for a high vulnerability to Alzheimer's disease pathology, encouraging for the use of (11)C-labelled Pittsburgh compound B positron emission tomography measures as early indicators of Alzheimer's disease. These results may begin to shed light on the mechanisms by which amyloid-β deposition leads to neurodegeneration and cognitive decline and the development of a more specific Alzheimer's disease-specific imaging signature for diagnosis and use of this knowledge in the development of new anti-therapies for Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Alzheimer's disease and frontotemporal dementia (FTD) can be difficult to differentiate clinically because of overlapping symptoms. Distinguishing the two dementias based on volumetric measurements of brain atrophy with MRI has been only partially successful. Whether MRI measurements of cortical thinning improve the differentiation between Alzheimer's disease and FTD is unclear. In this study, we measured cortical thickness using a set of automated tools (Freesurfer) to reconstruct the brain's cortical surface from T1-weighted structural MRI data in 22 patients with Alzheimer's disease, 19 patients with FTD and 23 cognitively normal subjects. The goals were to detect the characteristic patterns of cortical thinning in these two types of dementia, to test the relationship between cortical thickness and cognitive impairment, to determine if measurement of cortical thickness is better than that of cortical volume for differentiating between these dementias and normal ageing and improving the classification of Alzheimer's disease and FTD based on neuropsychological scores alone. Compared to cognitively normal subjects, Alzheimer's disease patients had a thinner cortex primarily in bilateral, frontal, parietal, temporal and occipital lobes (P < 0.001), while FTD patients had a thinner cortex in bilateral, frontal and temporal regions and some thinning in inferior parietal regions and the posterior cingulate (P < 0.001). Compared to FTD patients, Alzheimer's disease patients had a thinner cortex (P < 0.001) in parts of bilateral parietal and precuneus regions. Cognitive impairment was negatively correlated with cortical thickness of frontal, parietal and temporal lobes in Alzheimer's disease, while similar correlations were not significant in FTD. Measurement of cortical thickness was similar to that of cortical volume in differentiating between normal ageing, Alzheimer's disease and FTD. Furthermore, cortical thickness measurements significantly improved the classification between Alzheimer's disease and FTD based on neuropsychological scores alone, including the Mini-Mental State Examination and a modified version of the Trail-Making Test. In conclusion, the characteristic patterns of cortical thinning in Alzheimer's disease and FTD suggest that cortical thickness may be a useful surrogate marker for these types of dementia. [ABSTRACT FROM AUTHOR]

Neurodegeneration refers to a large clinically and pathologically heterogeneous disease entity associated with slowly progressive neuronal loss in different anatomical and functional systems of the brain. Neurodegenerative diseases often affect cognition, e.g. Alzheimer's disease (AD), dementia with Lewy bodies and vascular dementia, or different aspects of the motor system, e.g., amyotrophic lateral sclerosis, Parkinson's disease and ataxic disorders. Owing to increasing knowledge about the mechanisms leading to neurodegeneration, the development of treatments able to modify the neurodegenerative process becomes possible for the first time. Currently, clinical outcome measures are used to assess the efficacy of such treatments. However, most clinical outcome measures have a low test-retest reliability and thus considerable measurement variance. Therefore, large patient populations and long observation times are needed to detect treatment effects. Furthermore, clinical outcome measures cannot distinguish between symptomatic and disease-modifying treatment effects. Therefore, alternative biomarkers including neuroimaging may take on a more important role in this process. Because MR scanners are widely available and allow for non-invasive detection and quantification of changes in brain structure and metabolism, there is increasing interest in the use of MRI/MRS to monitor objectively treatment effects in clinical trials of neurodegenerative diseases. Particularly volumetric MRI has been used to measure atrophy rates in treatment trials of AD because the relationship between atrophic changes and neuron loss is well established and correlates well with clinical measures. More research is needed to determine the value of other MR modalities, i.e. diffusion, perfusion and functional MRI and MR spectroscopy, for clinical trials with neuroprotective drugs. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Image reconstruction for magnetic resonance spectroscopic imaging (MRSI) requires specialized spatial and spectral data processing methods and benefits from the use of several sources of prior information that are not commonly available, including MRI-derived tissue segmentation, morphological analysis and spectral characteristics of the observed metabolites. In addition, incorporating information obtained from MRI data can enhance the display of low-resolution metabolite images and multiparametric and regional statistical analysis methods can improve detection of altered metabolite distributions. As a result, full MRSI processing and analysis can involve multiple processing steps and several different data types. In this paper, a processing environment is described that integrates and automates these data processing and analysis functions for imaging of proton metabolite distributions in the normal human brain. The capabilities include normalization of metabolite signal intensities and transformation into a common spatial reference frame, thereby allowing the formation of a database of MR-measured human metabolite values as a function of acquisition, spatial and subject parameters. This development is carried out under the MIDAS project (Metabolite Imaging and Data Analysis System), which provides an integrated set of MRI and MRSI processing functions. It is anticipated that further development and distribution of these capabilities will facilitate more widespread use of MRSI for diagnostic imaging, encourage the development of standardized MRSI acquisition, processing and analysis methods and enable improved mapping of metabolite distributions in the human brain. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Short echo time proton MR Spectroscopic Imaging (MRSI) suffers from low signal-to-noise ratio (SNR), limiting accuracy to estimate metabolite intensities. A method to coherently sum spectra in a region of interest of the human brain by appropriate peak alignment was developed to yield a mean spectrum with increased SNR. Furthermore, principal component (PC) spectra were calculated to estimate the variance of the mean spectrum. The mean or alternatively the first PC (PC1) spectrum from the same region can be used for quantitation of peak areas of metabolites in the human brain at increased SNR. Monte Carlo simulations showed that both mean and PC1 spectra were more accurate in estimating regional metabolite concentrations than solutions that regress individual spectra against the tissue compositions of MRSI voxels. Back-to-back MRSI studies on 10 healthy volunteers showed that mean spectra markedly improved reliability of brain metabolite measurements, most notably for myo-inositol, as compared to regression methods. Magn Reson Med, 2006. Published 2006 Wiley-Liss, Inc. [ABSTRACT FROM AUTHOR]

OBJECTIVES: After replication of previous findings we aimed to: 1) determine if previously reported 1 H MRSI differences between ALS patients and control subjects are limited to the motor cortex; and 2) determine the longitudinal metabolic changes corresponding to varying levels of diagnostic certainty. METHODS: Twenty-one patients with possible/suspected ALS, 24 patients with probable/definite ALS and 17 control subjects underwent multislice 1 H MRSI co-registered with tissue-segmented MRI to obtain concentrations of the brain metabolites N-acetylaspartate (NAA), creatine, and choline in the left and right motor cortex and in gray matter and white matter of non-motor regions in the brain. RESULTS: In the more affected hemisphere, reductions in the ratios, NAA/Cho and NAA/Cre+Cho were observed both within (12.6% and 9.5% respectively) and outside (9.2% and 7.3% respectively) the motor cortex in probable/definite ALS. However, these reductions were significantly greater within the motor cortex ( P <0.05 for NAA/Cho and P <0.005 for NAA/Cre+Cho). Longitudinal changes in NAA were observed at three months within the motor cortex of both possible/suspected ALS patients ( P <0.005) and at nine months outside the motor cortex of probable/definite patients ( P <0.005). However, there was no clear pattern of progressive change over time. CONCLUSIONS: NAA ratios are reduced in the motor cortex and outside the motor cortex in ALS, suggesting widespread neuronal injury. Longitudinal changes of NAA are not reliable, suggesting that NAA may not be a useful surrogate marker for treatment trials. [ABSTRACT FROM AUTHOR]

This article reviews recent studies of magnetic resonance imaging and magnetic resonance spectroscopy in dementia, including Alzheimer's disease, frontotemporal dementia, dementia with Lewy bodies, idiopathic Parkinson's disease, Huntington's disease, and vascular dementia. Magnetic resonance imaging and magnetic resonance spectroscopy can detect structural alteration and biochemical abnormalities in the brain of demented subjects and may help in the differential diagnosis and early detection of affected individuals, monitoring disease progression, and evaluation of therapeutic effect. [ABSTRACT FROM AUTHOR]

Chronic abuse of cocaine or alcohol is associated with structural, neuropathological and cognitive impairments that have been documented extensively. Little is known, however, about neurobiochemical changes in chronic substance abusers.We performed MRI and multi-slice brain proton magnetic resonance spectroscopic imaging (MRSI) to assess neuronal viability (via N-acetylaspartate (NAA)) and white matter metabolite status in 22 4-months-abstinent individuals dependent on crack cocaine only and on both crack cocaine and alcohol. Compared to 11 non-dependent controls we found (1) significantly lower NAA measures in the dorsolateral prefrontal cortex of the combined cocaine-dependent groups; (2) comparable spatial distribution and magnitude of these NAA effects for both cocaine-dependent groups; (3) higher choline-containing metabolites in frontal white matter of individuals dependent on both cocaine and alcohol; (4) absence of brain atrophy in both abstinent cocaine-dependent samples; and (5) partial recovery from prefrontal cortical NAA loss, primarily with abstinence from alcohol. The MRSI findings suggest preferential neuronal damage to the frontal cortex of both cocaine-dependent samples and gliosis in frontal white matter of individuals dependent on both alcohol and cocaine, conditions that persist for more than 4 months of abstinence. [ABSTRACT FROM AUTHOR]

In this study, we evaluated an MRI fingerprinting approach (MRvF) designed to provide high-resolution parametric maps of the microvascular architecture (i.e., blood volume fraction, vessel diameter) and function (blood oxygenation) simultaneously. The method was tested in rats (n = 115), divided in 3 models: brain tumors (9 L, C6, F98), permanent stroke, and a control group of healthy animals. We showed that fingerprinting can robustly distinguish between healthy and pathological brain tissues with different behaviors in tumor and stroke models. In particular, fingerprinting revealed that C6 and F98 glioma models have similar signatures while 9 L present a distinct evolution. We also showed that it is possible to improve the results of MRvF and obtain supplemental information by changing the numerical representation of the vascular network. Finally, good agreement was found between MRvF and conventional MR approaches in healthy tissues and in the C6, F98, and permanent stroke models. For the 9 L glioma model, fingerprinting showed blood oxygenation measurements that contradict results obtained with a quantitative BOLD approach. In conclusion, MR vascular fingerprinting seems to be an efficient technique to study microvascular properties in vivo. Multiple technical improvements are feasible and might improve diagnosis and management of brain diseases. [ABSTRACT FROM AUTHOR]

Abstract Background To test the hypothesis that white matter lesions (WML) are primarily associated with regional frontal cortical volumes, and to determine the mediating effects of these regional frontal cortices on the associations of WML with depressive symptoms and cognitive dysfunction. Methods Structural brains MRIs were performed on 161 participants: cognitively normal, cognitive impaired but not demented, and demented participants. Lobar WML volumes, regional frontal cortical volumes, depressive symptom severity, and cognitive abilities were measured. Multiple linear regression analyses were used to identify WML volume effects on frontal cortical volume. Structural equation modeling was used to determine the MRI-depression and the MRI-cognition path relationships. Results WML predicted frontal cortical volume, particularly in medial orbirtofrontal cortex, irrespective of age, gender, education, and group status. WML directly predicted depressive score, and this relationship was not mediated by regional frontal cortices. In contrast, the association between WML and cognitive function was indirect and mediated by regional frontal cortices. Conclusions These findings suggest that the neurobiological mechanisms underpinning depressive symptoms and cognitive dysfunction in older adults may differ.