Age- and sex-related effects on the neuroanatomy of healthy elderly
ABSTRACT Effects of age and sex, and their interaction on the structural brain anatomy of healthy elderly were assessed thanks to a cross-sectional study of a cohort of 662 subjects aged from 63 to 75 years. T1- and T2-weighted MRI scans were acquired in each subject and further processed using a voxel-based approach that was optimized for the identification of the cerebrospinal fluid (CSF) compartment. Analysis of covariance revealed a classical neuroanatomy sexual dimorphism, men exhibiting larger gray matter (GM), white matter (WM), and CSF compartment volumes, together with larger WM and CSF fractions, whereas women showed larger GM fraction. GM and WM were found to significantly decrease with age, while CSF volume significantly increased. Tissue probability map analysis showed that the highest rates of GM atrophy in this age range were localized in primary cortices, the angular and superior parietal gyri, the orbital part of the prefrontal cortex, and in the hippocampal region. There was no significant interaction between "Sex" and "Age" for any of the tissue volumes, as well as for any of the tissue probability maps. These findings indicate that brain atrophy during the seventh and eighth decades of life is ubiquitous and proceeds at a rate that is not modulated by "Sex".
Full-textDOI: · Available from: Fabrice Crivello, Aug 07, 2015
- SourceAvailable from: Quentin Duriez
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- "For the purpose of the present study, the hippocampus was considered as a region of specific interest (ROI) given that it is a highly recognized imaging marker of brain aging (Hof and Morrison, 2004). Similar to previous studies (Lemaître et al., 2005b; Crivello et al., 2010) left and right hippocampus volumes were automatically estimated by integrating the voxel intensities of the modulated GM partition images within hippocampus limits as defined by the AAL atlas (Tzourio-Mazoyer et al., 2002). Statistical analysis was performed on the total hippocampus volume (HIP), i.e., on sum of the left and right volumes. "
ABSTRACT: We investigated the cross-sectional and longitudinal effects of tobacco smoking on brain atrophy in a large cohort of healthy elderly participants (65–80 years). MRI was used for measuring whole brain (WB), gray matter (GM), white matter (WM), and hippocampus (HIP) volumes at study entry time (baseline, N = 1451), and the annualized rates of variation of these volumes using a 4-year follow-up MRI in a subpart of the cohort (N = 1111). Effects of smoking status (never, former, or current smoker) at study entry and of lifetime tobacco consumption on these brain phenotypes were studied using sex-stratified AN(C)OVAs, including other health parameters as covariates. At baseline, male current smokers had lower GM, while female current smokers had lower WM. In addition, female former smokers exhibited reduced baseline HIP, the reduction being correlated with lifetime tobacco consumption. Longitudinal analyses demonstrated that current smokers, whether men or women, had larger annualized rates of HIP atrophy, as compared to either non or former smokers, independent of their lifetime consumption of tobacco. There was no effect of smoking on the annualized rate of WM loss. In all cases, measured sizes of these tobacco-smoking effects were of the same order of magnitude than those of age, and larger than effect sizes of any other covariate. These results demonstrate that tobacco smoking is a major factor of brain aging, with sex- and tissue specific effects, notably on the HIP annualized rate of atrophy after the age of 65.Frontiers in Aging Neuroscience 11/2014; 6:299. DOI:10.3389/fnagi.2014.00299 · 2.84 Impact Factor
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- "MR images were segmented and stereotactically normalized to the Montreal Neurological Institute (MNI) space using a combined segmentation and registration approach  as implemented in the Statistical Parametric Mapping 8 (SPM8) software package (Wellcome Trust Centre for Neuroimaging, London, UK). Preexisting, freely available prior tissue probability maps for GM, white matter (WM), and cerebrospinal fluid (CSF) were used to assist segmentation and registration . The default setting of the unified segmentation engine was used as described in Arlt et al. . "
ABSTRACT: Hippocampal volume is a promising biomarker to enhance the accuracy of the diagnosis of dementia due to Alzheimer's disease (AD). However, whereas hippocampal volume is well studied in patient samples from clinical trials, its value in clinical routine patient care is still rather unclear. The aim of the present study, therefore, was to evaluate fully automated atlas-based hippocampal volumetry for detection of AD in the setting of a secondary care expert memory clinic for outpatients. One-hundred consecutive patients with memory complaints were clinically evaluated and categorized into three diagnostic groups: AD, intermediate AD, and non-AD. A software tool based on open source software (Statistical Parametric Mapping SPM8) was employed for fully automated tissue segmentation and stereotactical normalization of high-resolution three-dimensional T1-weighted magnetic resonance images. Predefined standard masks were used for computation of grey matter volume of the left and right hippocampus which then was scaled to the patient's total grey matter volume. The right hippocampal volume provided an area under the receiver operating characteristic curve of 84% for detection of AD patients in the whole sample. This indicates that fully automated MR-based hippocampal volumetry fulfills the requirements for a relevant core feasible biomarker for detection of AD in everyday patient care in a secondary care memory clinic for outpatients. The software used in the present study has been made freely available as an SPM8 toolbox. It is robust and fast so that it is easily integrated into routine workflow.Journal of Alzheimer's disease: JAD 09/2014; 44(1). DOI:10.3233/JAD-141446 · 4.15 Impact Factor
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- "A topographic histogram (i.e. damaged tissue overlap map) depicting the voxel-wise prevalence of infarct, peri-infarct damage, and white matter hypointensities combined (normalized to a custom older adult template (Lemaitre et al., 2005)) is shown in Fig. 2. FLAIR imaging is often utilized as the clinical standard for quantifying white matter pathology due to its ability to more conspicuously capture infarctions and white matter disease (Alexander et al., 1996). Because the equivalence of different MRI metrics for quantifying white matter pathology (e.g., FLAIR hyperintensities versus T1-weighted hypointensities) has not yet been established, white matter hyperintensities and periventricular hyperintensities were also quantified using Fazekas ratings (Fazekas et al., 1987, see Table 2) for a subset of 38 participants for which non-volumetric FLAIR images were available. "
ABSTRACT: Purpose: The purpose of this study was to delineate the relationship between several types of T1-weighted MRI pathology and motor rehabilitation potential following Constraint Induced Movement therapy (CI therapy) in chronic stroke. Methods: Stepwise regression was employed (n = 80) to identify predictors of motor recovery (prior to therapy) and of response to Constraint-Induced Movement therapy [measured via the Wolf Motor Function Test (WMFT) and Motor Activity Log (MAL)] from among the following: age, side of motor deficit, chronicity, gender, lesion volume, peri-infarct damage volume, white matter hypointensity volume, ventricular asymmetry, and lesion location. Results: Although extent of total stroke damage weakly correlated with poorer performance on the WMFT prior to therapy, this relationship was mediated by the location of the damage. No metric of tissue damage examined here was associated with real-world arm use at baseline (MAL at pre-treatment) or with CI therapy-induced improvement in either best motor performance upon request (WMFT) or spontaneous arm use for daily activities (MAL). Conclusions: In sum, the extent of brain tissue damage of any type examined here poorly predicted motor function and response to rehabilitation in chronic stroke.Restorative neurology and neuroscience 09/2014; DOI:10.3233/RNN-130366 · 4.18 Impact Factor