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Blood-Brain Barrier opening (BBBO) with Focus Ultrasound (FUS) seems to give significant results in clearing amyloid plaques and restoring memory in Alzheimer's disease (AD-Tg) transgenic mice models. So far, only few teams have produced results [Burgess, 2014 — Leinenga, 2015] which motivates more investigations. To do so we set up two protocols: one on wild type (WT) mice and one AD-Tg mice.

Brain tumors therapy is limited by the Blood-Tumor Barrier (BTB) and Blood-Brain Barrier (BBB), still intact in the infiltrative areas. Low intensity Focused Ultrasound (FUS) in conjunction with microbubbles is the only method allowing the local disruption of the BTB/BBB [Hynynen et al. 2001, Zhao et al. 2015]. Proper study of the influence of acoustic scanning parameters (duty cycle, number of focal spots) on the amount of delivered nanoparticles is not available so far. Here, we compared two acoustic strategies to enhance the molecular concentration within brain tumors. The efficacy of the two methods is evaluated on the basis of absolute concentrations of delivered MR-contrast agents (CA) and on their rates of uptake/clearance by the tumors.

Low intensity Focused Ultrasound (FUS) combined with microbubbles open locally and not invasively the Blood-Brain Barrier (BBB) allowing passage of nanoparticles into the brain [Hynynen et al. 2001]. However, since the quantity of particles that can be delivered with this technique depends on tissue properties, on particle properties as well as on acoustic parameters, so far a model fully predicting the result of a FUS induced BBB opening experiment is missing. Here, we introduce a mathematical model depicting both the vascular permeability as a function of time and the diffusion process occurring in brain tissue. This model takes into account acoustic pressure, particle size, blood pharmacokinetics and diffusion rates.

Parallel MRI is a fast imaging technique that allows reconstruction of full Field-of-View (FoV) images based on under-sampled k-space data acquired using multiple receiver coils with complementary sensitivity profiles. It enables the acquisition of highly resolved images either in space or in time, which is of particular interest in applications like functional neuroimaging. These improvements are counterbalanced by a degraded SNR and the presence of artifacts that depend on the reconstruction algorithm. To improve the performance of the widely used SENSE algorithm, 2D regularization in the wavelet domain has recently been efficiently investigated [1]. In this paper, we extend this work to 3D-wavelet decompositions in order to manipulate all slices together. We illustrate the gain induced by such extension in terms of statistical impact on functional MRI (fMRI) data analysis using a fast-event related protocol. Our results show that our 3D reconstruction algorithm outperforms its 2D counterpart and the SENSE algorithm in several statistical respects at the group-level: peak localization, local maxima, cluster extent, robustness to high acceleration factors.

In order to deal with inhomogeneous groups of subjects in fMRI studies, we investigate several robust statistics to perform random-effect analysis on the mean population effect (sign statistic, Wilcoxon's signed rank statistic and empirical t statistic). The tests' significance levels are calibrated using the same sign permutation framework, allowing for exact specificity control under a mild symmetry assumption about the subjects' distribution. The benefit of the robust approach is illustrated on a speech listening experiment involving three month-old infants.

Positron volume images have been produced by the new large-area positron camera PETRRA directly from list-mode data acquisition then reconstruction using backprojection then filter methods (BPF). These images have been corrected for scatter and attenuation using backprojection space methods. Two methods have been developed to provide scatter distributions. The first method uses a spatially-invariant scatter response function derived from measured point spread functions in a water-filled phantom. The second uses the scatter distributions measured at various points in the same phantom to allow for the spatial variance of the scatter. The correction methods have been tested using a uniformly-filled radioactive elliptical phantom (major and minor axes of 29.5 cm and 19.6 cm). Preliminary results show that both methods can improve the quantitative nature of the reconstructed images but that the use of spatially variant scatter distribution is superior. The methods could be applied to any large-area, rotating positron camera system which acquires data in list mode.