Euclidian distance-weighted smoothing for quantitative MRI: application to intervoxel anisotropy index mapping with DTI

During the computation of intervoxel anisotropy features, the inclusion of both eigenvalues and eigenvectors reduces the effect of noise, but spatial averaging blurs the resulting maps. We propose a new adaptive technique that uses data-dependent weights in the averaging process so that the influence of each neighbor in the local window is proportional to the similarity of characteristics of the neighbor considered to those of the reference central voxel. This likeness criterion is based on the multidimensional Euclidian distance using the entire available multispectral information contained in the diffusion-weighted images. This solution is controlled by a single parameter beta that results from a compromise between edge-preserving and noise-smoothing abilities. This Euclidian distance-weighted technique is a generic solution for filtering noise during parametric reconstruction. It was applied to map anisotropy using an intervoxel lattice index (LI) from experimental images of mouse brain in vivo and achieves noise reduction without distorting small anatomical structures. We also show how to employ in the discrimination scheme the images not used in the estimation of the considered feature.     

Detection of susceptibility effects using simultaneous T(2)* and magnetic field mapping

Tracking susceptibility effects is a convenient way to detect small inclusions in a bulk tissue matrix by MRI. We propose a quantitative assessment of these susceptibility effects by simultaneously mapping T(2)* and magnetic field from the time course of magnitude and phase using a multiple GE sequence at 4.7 T. A high-pass scheme is also introduced to highlight the mesoscopic magnetic field variations due to local susceptibility differences specifically in the magnetic field map. Applying this method to muscle tissue, we demonstrate that connective tissue generates detectable susceptibility effects through concomitant local magnetic field variation and T(2)* shortening.     

Water diffusion features as indicators of muscle structure ex vivo

The structures of two different bovine muscles, the Semitendinosus (ST) and the Triceps brachii (TB), were studied using quantitative maps obtained by diffusion tensor imaging at 4.7 T. The estimated features were: mean diffusivity, intra- and inter-voxel anisotropy and fiber tract orientation angles. Significant differences in anisotropy (fractional anisotropy and lattice index), spatial variations of anisotropy and fiber tract orientation were detected between ST and TB, and are discussed. Accumulation of free water, which diffuses more freely and isotropically than in the rest of the muscle, was detected and localized in ST. These results underline the usefulness of diffusion tensor measurements to characterize muscle structure and help understand the mechanisms of post mortem water exudation.     

Mapping of muscle deformation during heating: in situ dynamic MRI and nonlinear registration

We present developments in dynamic magnetic resonance imaging that allow internal structural muscle markers to be followed during heating. This monitoring is based on quantitative characterization of the experimental conditions and their temperature time course. A nonlinear image registration technique was optimized and applied to consecutively acquired images to measure the deformation fields in the muscle. A model coupling local deformation and temperature was obtained, which for the first time takes into account the variations of deformation and temperature in the sample. This modeling opens the way to a better understanding of the mechanisms responsible for mass loss and degradation of the textural properties of muscle during heating.     

Low-frequency complex magnetic susceptibility of magnetic composite microspheres in colloidal dispersion

A procedure is presented to determine the permanent magnetic dipole moment of composite microspheres containing magnetic nanoparticles with a blocked magnetic dipole moment. The composite particles are dispersed in a solvent, and the complex magnetic susceptibility is measured from 0.1 to 1000 Hz using a highly sensitive new setup. Composite particles with a permanent magnetic dipole moment are revealed by a characteristic frequency that corresponds to the Brownian rotation of the microspheres. From measured susceptibility spectra, we calculate the permanent magnetic dipole moment of recently developed cobalt ferrite-doped silica and latex microspheres.     

Ionic liquids based microwave-assisted extraction of lichen compounds with quantitative spectrophotodensitometry analysis

Ionic liquids based extraction method has been applied to the effective extraction of norstictic acid, a common depsidone isolated from Pertusaria pseudocorallina, a crustose lichen. Five 1-alkyl-3-methylimidazolium ionic liquids (ILs) differing in composition of alkyl chain and anion were investigated for extraction efficiency. The extraction amount of norstictic acid was determined after recovery on HPTLC with a spectrophotodensitometer. The proposed approaches (IL-MAE and IL-heat extraction (IL-HE)) have been evaluated in comparison with usual solvents such as tetrahydrofuran in heat-reflux extraction and microwave-assisted extraction (MAE). The results indicated that both the characteristics of the alkyl chain and anion influenced the extraction of polyphenolic compounds. The sulfate-based ILs [C(1)mim][MSO(4)] and [C(2)mim][ESO(4)] presented the best extraction efficiency of norstictic acid. The reduction of the extraction times between HE and MAE (2 h-5 min) and a non-negligible ratio of norstictic acid in total extract (28%) supports the suitability of the proposed method. This approach was successfully applied to obtain additional compounds from other crustose lichens (Pertusaria amara and Ochrolechia parella).     

Iterative algorithm for spatial and intensity normalization of MEMRI images. Application to tract-tracing of rat olfactory pathways

Manganese (Mn)-enhanced magnetic resonance imaging (MEMRI) is an emerging technique for visualizing neuronal pathways and mapping brain activity modulation in animal models. Spatial and intensity normalizations of MEMRI images acquired from different subjects are crucial steps as they can influence the results of groupwise analysis. However, no commonly accepted procedure has yet emerged. Here, a normalization method is proposed that performs both spatial and intensity normalizations in a single iterative process without the arbitrary choice of a reference image. Spatial and intensity normalizations benefit from this iterative process. On one hand, spatial normalization increases the accuracy of region of interest (ROI) positioning for intensity normalization. On the other hand, improving the intensity normalization of the different MEMRI images leads to a better-averaged target on which the images are spatially registered. After automatic fast brain segmentation and optimization of the normalization process, this algorithm revealed the presence of Mn up to the posterior entorhinal cortex in a tract-tracing experiment on rat olfactory pathways. Quantitative comparison of registration algorithms showed that a rigid model with anisotropic scaling is the best deformation model for intersubject registration of three-dimensional MEMRI images. Furthermore, intensity normalization errors may occur if the ROI chosen for intensity normalization intersects regions where Mn concentration differs between experimental groups. Our study suggests that cross-comparing Mn-injected animals against a Mn-free group may provide a control to avoid bias introduced by intensity normalization quality. It is essential to optimize spatial and intensity normalization as the detectability of local between-group variations in Mn concentration is directly tied to normalization quality.     

Directed synthesis of stable large polyoxomolybdate spheres

Polyoxometalates or POMs, a class of inorganic transition metal-oxide based clusters, have gained significant interest owing to their catalytic, magnetic, and material science applications. All such applications require high surface area POM based materials. However, chemically synthesized POMs are still at most in the range of a few nanometers, with their size and morphology being difficult to control. Hence, there is an immediate need to develop design principles that allow easy control of POM morphology and size on mesoscopic (50-500 nm) length scales. Here, we report a design strategy to meet this need. Our method reported here avoids a complex chemical labyrinth by using a prefabricated cationic 1,2-dioleol-3-trimethylammonium-propane (DOTAP) vesicle as a scaffold/structure directing agent and gluing simple anionic heptamolybdates by electrostatic interaction and hydrogen bonds to form large POM spheres. By this method, complexity in the resulting structure can be deliberately induced either via the scaffold or via the oxometalate. The high degree of control in the matter of the size and morphology of the resulting POM superstructures renders this method attractive from a synthetic standpoint.