Dataset Information

Voxel-based morphometry analyses of in vivo MRI in the aging mouse lemur primate.

ABSTRACT: Cerebral atrophy is one of the most widely brain alterations associated to aging. A clear relationship has been established between age-associated cognitive impairments and cerebral atrophy. The mouse lemur (Microcebus murinus) is a small primate used as a model of age-related neurodegenerative processes. It is the first non-human primate in which cerebral atrophy has been correlated with cognitive deficits. Previous studies of cerebral atrophy in this model were based on time consuming manual delineation or measurement of selected brain regions from magnetic resonance images (MRI). These measures could not be used to analyse regions that cannot be easily outlined such as the nucleus basalis of Meynert or the subiculum. In humans, morphometric assessment of structural changes with age is generally performed with automated procedures such as voxel-based morphometry (VBM). The objective of our work was to perform user-independent assessment of age-related morphological changes in the whole brain of large mouse lemur populations thanks to VBM. The study was based on the SPMMouse toolbox of SPM 8 and involved thirty mouse lemurs aged from 1.9 to 11.3 years. The automatic method revealed for the first time atrophy in regions where manual delineation is prohibitive (nucleus basalis of Meynert, subiculum, prepiriform cortex, Brodmann areas 13-16, hypothalamus, putamen, thalamus, corpus callosum). Some of these regions are described as particularly sensitive to age-associated alterations in humans. The method revealed also age-associated atrophy in cortical regions (cingulate, occipital, parietal), nucleus septalis, and the caudate. Manual measures performed in some of these regions were in good agreement with results from automatic measures. The templates generated in this study as well as the toolbox for SPM8 can be downloaded. These tools will be valuable for future evaluation of various treatments that are tested to modulate cerebral aging in lemurs.

SUBMITTER: Sawiak SJ

PROVIDER: S-EPMC4018531 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Voxel-based morphometry analyses of in vivo MRI in the aging mouse lemur primate.

Sawiak Stephen J SJ Picq Jean-Luc JL Dhenain Marc M

Frontiers in aging neuroscience 20140506

Cerebral atrophy is one of the most widely brain alterations associated to aging. A clear relationship has been established between age-associated cognitive impairments and cerebral atrophy. The mouse lemur (Microcebus murinus) is a small primate used as a model of age-related neurodegenerative processes. It is the first non-human primate in which cerebral atrophy has been correlated with cognitive deficits. Previous studies of cerebral atrophy in this model were based on time consuming manual d ...[more]

PMID: 24834052

Similar Datasets

Project description:Background and purposeVoxel-based morphometry is widely used for detecting gray matter abnormalities in epilepsy. However, its performance with changing parameters, smoothing and statistical threshold, is debatable. More important, the potential yield of combining multiple MR imaging contrasts (multispectral voxel-based morphometry) is still unclear. Our aim was to objectify smoothing and statistical cutoffs and systematically compare the performance of multispectral voxel-based morphometry with existing T1 voxel-based morphometry in patients with focal epilepsy and previously negative MRI.Materials and methods3D T1-, T2-, and T2-weighted FLAIR scans were acquired for 62 healthy volunteers and 13 patients with MR imaging negative for focal epilepsy on a Magnetom Skyra 3T scanner with an isotropic resolution of 0.9 mm3. We systematically optimized the main voxel-based morphometry parameters, smoothing level and statistical cutoff, with T1 voxel-based morphometry as a reference. As a next step, the performance of multispectral voxel-based morphometry models, T1+T2, T1+FLAIR, and T1+T2+FLAIR, was compared with that of T1 voxel-based morphometry using gray matter concentration and gray matter volume analysis.ResultsWe found the best performance of T1 at 12 mm and a T-threshold (statistical cutoff) of 3.7 for gray matter concentration analysis. When we incorporated these parameters, after expert visual interpretation of concordant and discordant findings, we identified T1+FLAIR as the best model with a concordant rate of 46.2% and a concordant rate/discordant rate of 1.20 compared with T1 with 30.8% and 0.67, respectively. Visual interpretation of voxel-based morphometry findings decreased concordant rates from 38.5%-46.2% to 15.4%-46.2% and discordant rates from 53.8%-84.6% to 30.8%-46.2% and increased specificity across models from 33.9%-40.3% to 46.8%-54.8%.ConclusionsMultispectral voxel-based morphometry, especially T1+FLAIR, can yield superior results over single-channel T1 in focal epilepsy patients with a negative conventional MR imaging.

Project description:Results from studies that have examined age-related changes in gray matter based on structural MRI scans have not always been consistent. Reasons for this variability likely include small or unevenly-distributed samples, different methods for tissue class segmentation and spatial normalization, and the use of different statistical models. Particularly relevant to the latter is the method of adjusting for global (total) gray matter when making inferences about regionally-specific changes. In the current study, we use voxel-based morphometry (VBM) to explore the impact of these methodological choices in assessing age-related changes in gray matter volume in a sample of 420 adults evenly distributed between the ages of 18-77 years. At a broad level, we replicate previous findings, showing age-related gray matter decline in nearly all parts of the brain, with particularly rapid decline in inferior regions of frontal cortex (e.g., insula and left inferior frontal gyrus) and the central sulcus. Segmentation was improved by increasing the number of tissue classes and using less age-biased templates, and registration was improved by using a diffeomorphic flow-based algorithm (DARTEL) rather than a "constrained warp" approach. Importantly, different approaches to adjusting for global effects--not adjusting, Local Covariation, Global Scaling, and Local Scaling--significantly affected regionally-specific estimates of age-related decline, as demonstrated by ranking age effects across anatomical ROIs. Split-half cross-validation showed that, on average, Local Covariation explained a greater proportion of age-related variance across these ROIs than did Global Scaling. Nonetheless, the appropriate choice for global adjustment depends on one's assumptions and specific research questions. More generally, these results emphasize the importance of being explicit about the assumptions underlying key methodological choices made in VBM analyses and the inferences that follow.

Project description:Recent technological progress enables MRI recordings at ultra-high fields of 7 T and above leading to brain images of higher resolution and increased signal-to-noise ratio. Despite these benefits, imaging at 7 T exhibits distinct challenges due to B1 field inhomogeneities, causing decreased image quality and problems in data analysis. Although several strategies have been proposed, a systematic investigation of bias-corrected 7 T data for voxel-based morphometry (VBM) is still missing and it is an ongoing matter of debate if VBM at 7 T can be carried out properly. Here, an optimized VBM study was conducted, evaluating the impact of field strength (3T vs. 7 T) and pulse sequence (MPRAGE vs. MP2RAGE) on gray matter volume (GMV) estimates. More specifically, twenty-two participants were measured under the conditions 3T MPRAGE, 7 T MPRAGE and 7 T MP2RAGE. Due to the fact that 7 T MPRAGE data exhibited strong intensity inhomogeneities, an alternative preprocessing pipeline was proposed and applied for that data. VBM analysis revealed higher GMV estimates for 7 T predominantly in superior cortical areas, caudate nucleus, cingulate cortex and the hippocampus. On the other hand, 3T yielded higher estimates especially in inferior cortical areas of the brain, cerebellum, thalamus and putamen compared to 7 T. Besides minor exceptions, these results were observed for 7 T MPRAGE as well for the 7 T MP2RAGE measurements. Results gained in the inferior parts of the brain should be taken with caution, as native GM segmentations displayed misclassifications in these regions for both 7 T sequences. This was supported by the test-retest measurements showing highest variability in these inferior regions of the brain for 7 T and also for the advanced MP2RAGE sequence. Hence, our data support the use of 7 T MRI for VBM analysis in cortical areas, but direct comparison between field strengths and sequences requires careful assessment. Similarly, analysis of the inferior cortical regions, cerebellum and subcortical regions still remains challenging at 7 T even if the advanced MP2RAGE sequence is used.

Dataset Information

Voxel-based morphometry analyses of in vivo MRI in the aging mouse lemur primate.

Publications

Voxel-based morphometry analyses of in vivo MRI in the aging mouse lemur primate.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets