55 research outputs found

    Standard‐space atlas of the viscoelastic properties of the human brain

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    Standard anatomical atlases are common in neuroimaging because they facilitate data analyses and comparisons across subjects and studies. The purpose of this study was to develop a standardized human brain atlas based on the physical mechanical properties (i.e., tissue viscoelasticity) of brain tissue using magnetic resonance elastography (MRE). MRE is a phase contrast-based MRI method that quantifies tissue viscoelasticity noninvasively and in vivo thus providing a macroscopic representation of the microstructural constituents of soft biological tissue. The development of standardized brain MRE atlases are therefore beneficial for comparing neural tissue integrity across populations. Data from a large number of healthy, young adults from multiple studies collected using common MRE acquisition and analysis protocols were assembled (N = 134; 78F/ 56 M; 18–35 years). Nonlinear image registration methods were applied to normalize viscoelastic property maps (shear stiffness, μ, and damping ratio, ξ) to the MNI152 standard structural template within the spatial coordinates of the ICBM-152. We find that average MRE brain templates contain emerging and symmetrized anatomical detail. Leveraging the substantial amount of data assembled, we illustrate that subcortical gray matter structures, white matter tracts, and regions of the cerebral cortex exhibit differing mechanical characteristics. Moreover, we report sex differences in viscoelasticity for specific neuroanatomical structures, which has implications for understanding patterns of individual differences in health and disease. These atlases provide reference values for clinical investigations as well as novel biophysical signatures of neuroanatomy. The templates are made openly available (github.com/mechneurolab/mre134) to foster collaboration across research institutions and to support robust cross-center comparisons

    Influence of mild cognitive impairment and body mass index on white matter integrity assessed by diffusion tensor imaging

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    Mild cognitive impairment (MCI), a prodromal stage of Alzheimer's disease, is characterized by decreased memory and cognition, which are linked to degenerative changes in the brain. To assess whether white matter (WM) integrity is compromised in MCI, we collected diffusion-weighted images from 60 healthy older adults (OA) (69.16 ± 0.7) and 20 older adults with amnestic MCI (72.45 ± 1.9). WM integrity differences were examined using Tract-Based Spatial Statistics (TBSS). We hypothesized that those with MCI would have diminished WM integrity relative to OA. In a whole-brain comparison, those with MCI showed higher axial diffusivity in the splenium (SCC) and body of the corpus callosum (BCC), superior corona radiata (SCR), and the retrolenticular part of the internal capsule (RLIC) (p's < .05 TFCE-corrected). Additionally, significant between-group connectivity differences were observed using probabilistic tractography between the SCC, chosen from the TBSS results, and forceps major and minor (p-value's < .05). To further relate a physical health indicator to WM alterations, linear regression showed significant interactions between cognitive status and body mass index (BMI) on diffusivity outcome measures from probabilistic tractography (p-value-'s < .05). Additionally, we examined the association between relational memory, BMI, and WM integrity. WM integrity was positively associated with relational memory performance. These findings suggest that these regions may be more sensitive to early markers of neurodegenerative disease and health behaviors, suggesting that modifiable lifestyle factors may affect white matter integrity

    Mechanical properties of the in vivo adolescent human brain

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    Viscoelastic mechanical properties of the in vivo human brain, measured noninvasively with magnetic resonance elastography (MRE), have recently been shown to be affected by aging and neurological disease, as well as relate to performance on cognitive tasks in adults. The demonstrated sensitivity of brain mechanical properties to neural tissue integrity make them an attractive target for examining the developing brain; however, to date, MRE studies on children are lacking. In this work, we characterized global and regional brain stiffness and damping ratio in a sample of 40 adolescents aged 12–14 years, including the lobes of the cerebrum and subcortical gray matter structures. We also compared the properties of the adolescent brain to the healthy adult brain. Temporal and parietal cerebral lobes were softer in adolescents compared to adults. We found that of subcortical gray matter structures, the caudate and the putamen were significantly stiffer in adolescents, and that the hippocampus and amygdala were significantly less stiff than all other subcortical structures. This study provides the first detailed characterization of adolescent brain viscoelasticity and provides baseline data to be used in studying development and pathophysiology. Keywords: Magnetic resonance elastography, Brain, Stiffness, Viscoelasticity, Adolescent, Pediatri

    Rheological characterization and injection forces of concentrated protein formulations : an alternative predictive model for non-Newtonian solutions

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    Development of injection devices for subcutaneous drug administration requires a detailed understanding of user capability and forces occurring during the drug administration process. Injection forces of concentrated protein therapeutics are influenced by syringe properties (e.g., needle diameter) and injection speed, and are driven by solution properties such as rheology. In the present study, it is demonstrated that concentrated protein therapeutics may show significantly reduced injection forces because of shear-thinning (non-Newtonian) behavior. A mathematical model was thus established to predict/correlate injection forces of Newtonian and non-Newtonian solutions with viscosity data from plate/cone rheometry. The model was verified experimentally by glide-force measurements of reference and surrogate solutions. Application of the suggested model was demonstrated for injection force measurements of concentrated protein solutions to determine viscosity data at high shear rates (3x104-1.6x105s-1). By combining these data with viscosity data obtained by different viscosity methods (plate/cone and capillary rheometry), a viscosity-shear rate profile of the protein solution between 102 and 1.6x105s-1 was obtained, which was mathematically described by the Carreau model. Characterization of rheological properties allows to accurately predict injection forces for different syringe-needle combinations as well as injection rates, thus supporting the development of injection devices for combination products

    Spatiotemporal dynamics of low frequency BOLD fluctuations in rats and humans

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    Most studies involving spontaneous fluctuations in the BOLD signal extract connectivity patterns that show relationships between brain areas that are maintained over the length of the scanning session. In this study, however, we examine the spatiotemporal dynamics of the BOLD fluctuations to identify common patterns of propagation within a scan. A novel pattern finding algorithm was developed for detecting repeated spatiotemporal patterns in BOLD fMRI data. The algorithm was applied to high temporal resolution T2*-weighted multislice images obtained from rats and humans in the absence of any task or stimulation. In rats, the primary pattern consisted of waves of high signal intensity, propagating in a lateral to medial direction across the cortex, replicating our previous finding

    XuvTools: free, fast and reliable stitching of large 3D datasets.

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    Current biomedical research increasingly requires imaging large and thick 3D structures at high resolution. Prominent examples are the tracking of fine filaments over long distances in brain slices, or the localization of gene expression or cell migration in whole animals like Caenorhabditis elegans or zebrafish. To obtain both high resolution and a large field of view (FOV), a combination of multiple recordings ('tiles') is one of the options. Although hardware solutions exist for fast and reproducible acquisition of multiple 3D tiles, generic software solutions are missing to assemble ('stitch') these tiles quickly and accurately. In this paper, we present a framework that achieves fully automated recombination of tiles recorded at arbitrary positions in 3D space, as long as some small overlap between tiles is provided. A fully automated 3D correlation between all tiles is achieved such that no manual interaction or prior knowledge about tile positions is needed. We use (1) phase-only correlation in a multi-scale approach to estimate the coarse positions, (2) normalized cross-correlation of small patches extracted at salient points to obtain the precise matches, (3) find the globally optimal placement for all tiles by a singular value decomposition and (4) accomplish a nearly seamless stitching by a bleaching correction at the tile borders. If the dataset contains multiple channels, all channels are used to obtain the best matches between tiles. For speedup we employ a heuristic method to prune unneeded correlations, and compute all correlations via the fast Fourier transform (FFT), thereby achieving very good runtime performance. We demonstrate the successful application of the proposed framework to a wide range of different datasets from whole zebrafish embryos and C. elegans, mouse and rat brain slices and fine plant hairs (trichome). Further, we compare our stitching results to those of other commercially and freely available software solutions. The algorithms presented are being made available freely as an open source toolset 'XuvTools' at the corresponding author's website (http://lmb.informatik.uni-freiburg.de/people/ronneber), licensed under the GNU General Public License (GPL) v2. Binaries are provided for Linux and Microsoft Windows. The toolset is written in templated C++, such that it can operate on datasets with any bit-depth. Due to the consequent use of 64bit addressing, stacks of arbitrary size (i.e. larger than 4 GB) can be stitched. The runtime on a standard desktop computer is in the range of a few minutes. A user friendly interface for advanced manual interaction and visualization is also available

    Calculating distributed glacier mass balance for the Swiss Alps from regional climate model output: a methodical description and interpretation of the results

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    This study aims at giving a methodical description of the use of gridded output from a regional climate model (RCM) for the calculation of glacier mass balance distribution for the perimeter of the Swiss Alps. The mass balance model runs at daily steps and 100 m spatial resolution, while the regional model (REMO) RCM provides daily grids (∼18 km resolution) of dynamically downscaled reanalysis data. A combination of interpolation techniques and simple subgrid parameterizations is applied to bridge the gap in spatial resolution and to obtain daily input fields of air temperature, global radiation, and precipitation. Interpolation schemes are a key element and thus we test different interpolators. For validation, computed mass balances are compared to stake measurements and time series (1979–2003) of observed mass balance. The meteorological input fields are compared to measurements at weather stations. The applied inverse distance weighting introduces systematic biases due to spatial autocorrelation, whereas thin plate splines preserve the characteristics of the RCM output. While summer melt at point locations on several glaciers is well reproduced by the model, accumulation is mostly underestimated. These systematic shifts are correlated to biases of the meteorological input fields. Time series of mass balance obtained from the model run agree well with observed time series. We conclude that the gap in spatial resolution is not a major drawback, given that interpolators and parameterizations are selected upon detailed considerations. Biases in RCM precipitation are a major source for the observed underestimations in mass balance and have to be corrected prior to operational use of the presented approach
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