Morphological and chemical studies of pathological human and mice brain at the subcellular level: correlation between light, electron, and nanosims microscopies

Neurodegenerative diseases induce morphological and chemical alterations in well-characterized regions of the brain. Understanding their pathological processes requires the use of methods that assess both morphological and chemical alterations in the tissues. In the past, microprobe approaches such as scanning electron microscopy combined with an X-ray spectrometer, Proton induced X-ray emission, secondary ion mass spectrometry (SIMS), and laser microprobe mass analysis have been used for the study of pathological human brain with limited success. At the present, new SIMS instruments have been developed, such as the NanoSIMS-50 ion microprobe, that allow the simultaneous identification of five elements with high sensitivity, at subcellular spatial resolution (about 50-100 nm with the Cs(+) source and about 150-200 nm with O(-) source). Working in scanning mode, 2D distribution of five elements (elemental maps) can be obtained, thus providing their exact colocalization. The analysis can be performed on semithin or ultrathin embedded sections. The possibility of using transmission electron microscopy and SIMS on the same ultrathin sections allows the correlation between structural and analytical observations at subcellular and ultrastructural level to be established. Our observations on pathological brain areas allow us to establish that the NanoSIMS-50 ion microprobe is a highly useful instrument for the imaging of the morphological and chemical alterations that take place in these brain areas. In the human brain our results put forward the subcellular distribution of iron-ferritin-hemosiderin in the hippocampus of Alzheimer disease patients. In the thalamus of transgenic mice, our results have shown the presence of Ca-Fe mineralized amyloid deposits.     

Experimental characterization of helical coils as hyperthermiaapplicators

A series of helical-coil hyperthermia applicators have been designed for treating human limbs. Several experiments to determine their operating characteristics were conducted using muscle-equivalent, cylindrical, and lower-body-shaped phantoms. It was found that this kind of applicator has to be operated at resonances which are both sharp and load-dependent. This can have significant clinical implications, since changes in the position of the patient and/or the tissue dielectric properties with temperature can produce a severe mismatch. Moreover, even though the patterns of energy deposition were found to be relative transversely uniform and axially belt-shaped within the cylindrical phantoms, they were strongly dependent on the shape of the phantom and of the coil for the more realistic human-shaped phantom. Intense local heating was observed whenever the winding of the helical coil was within a few millimeters of the surface of the human-shaped phantom. The tests with the human-shaped phantom showed that there can be significant energy deposition outside of the region intended for treatment     

A fast wavelet-based reconstruction method for magnetic resonance imaging

In this work, we exploit the fact that wavelets can represent magnetic resonance images well, with relatively few coefficients. We use this property to improve magnetic resonance imaging (MRI) reconstructions from undersampled data with arbitrary k-space trajectories. Reconstruction is posed as an optimization problem that could be solved with the iterative shrinkage/thresholding algorithm (ISTA) which, unfortunately, converges slowly. To make the approach more practical, we propose a variant that combines recent improvements in convex optimization and that can be tuned to a given specific k-space trajectory. We present a mathematical analysis that explains the performance of the algorithms. Using simulated and in vivo data, we show that our nonlinear method is fast, as it accelerates ISTA by almost two orders of magnitude. We also show that it remains competitive with TV regularization in terms of image quality.     

Realistic analytical phantoms for parallel magnetic resonance imaging

The quantitative validation of reconstruction algorithms requires reliable data. Rasterized simulations are popular but they are tainted by an aliasing component that impacts the assessment of the performance of reconstruction. We introduce analytical simulation tools that are suited to parallel magnetic resonance imaging and allow one to build realistic phantoms. The proposed phantoms are composed of ellipses and regions with piecewise-polynomial boundaries, including spline contours, Bézier contours, and polygons. In addition, they take the channel sensitivity into account, for which we investigate two possible models. Our analytical formulations provide well-defined data in both the spatial and k-space domains. Our main contribution is the closed-form determination of the Fourier transforms that are involved. Experiments validate the proposed implementation. In a typical parallel magnetic resonance imaging reconstruction experiment, we quantify the bias in the overly optimistic results obtained with rasterized simulations-the inverse-crime situation. We provide a package that implements the different simulations and provide tools to guide the design of realistic phantoms.