q-Ball imaging is a high-angular-resolution diffusion imaging technique that has been proven very successful in resolving multiple intravoxel fiber orientations in MR images. The standard computation of the orientation distribution function (the probability of diffusion in a given direction) from q-ball data uses linear radial projection, neglecting the change in the volume element along each direction. This results in spherical distributions that are different from the true orientation distribution functions. For instance, they are neither normalized nor as sharp as expected and generally require postprocessing, such as artificial sharpening. In this paper, a new technique is proposed that, by considering the solid angle factor, uses the mathematically correct definition of the orientation distribution function and results in a dimensionless and normalized orientation distribution function expression. Our model is flexible enough so that orientation distribution functions can be estimated either from single q-shell datasets or by exploiting the greater information available from multiple q-shell acquisitions. We show that the latter can be achieved by using a more accurate multiexponential model for the diffusion signal. The improved performance of the proposed method is demonstrated on artificial examples and high-angular-resolution diffusion imaging data acquired on a 7-T magnet. Magn Reson Med 64: [554][555][556][557][558][559][560][561][562][563][564][565][566] 2010. V C 2010 WileyLiss, Inc.Key words: orientation distribution function; ODF; q-ball imaging; QBI; high angular resolution diffusion imaging; HARDI; constant solid angle; CSA Diffusion-weighted MRI provides valuable information about the fiber architecture of tissue by measuring the diffusion of water in three-dimensional (3D) space. The microscopic diffusion may be measured using the model-free diffusion spectrum imaging (1), which exploits the direct Fourier inversion of the diffusion signal. This technique is time intensive, as it measures the signal on a 3D (e.g., 11 Â 11 Â 11) Cartesian lattice. Thus, an alternative approach based on sampling only on one or multiple spherical shells in q-space has been proposed, referred to as high angular resolution diffusion imaging (HARDI) (2). The spherical shell, being a two-dimensional manifold, includes a number of measurement points that grows quadratically with the desired angular resolution, as opposed to cubically with the spatial resolution in the entire 3D lattice of q-space.While the 3D probability density function (PDF) of diffusion is helpful in studying the tissue microstructure, the orientation distribution function (ODF)-the marginal probability of diffusion in a given directionis the quantity of interest for mapping the orientation architecture of the tissue. q-Ball imaging (QBI) (3) is a widely used reconstruction scheme for HARDI, from which ODFs are approximated through a spherical tomographic inversion called the Funk-Radon transform (4). This technique's simplicity and its ability to ...

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The inability to visualize the initiation and progression of type-1 diabetes (T1D) noninvasively in humans is a major research and clinical stumbling block. We describe an advanced, exportable method for imaging the pancreatic inflammation underlying T1D, based on MRI of the clinically approved magnetic nanoparticle (MNP) ferumoxytol. The MNP-MRI approach, which reflects nanoparticle uptake by macrophages in the inflamed pancreatic lesion, has been validated extensively in mouse models of T1D and in a pilot human study. The methodological advances reported here were enabled by extensive optimization of image acquisition at 3T, as well as by the development of improved MRI registration and visualization technologies. A proof-of-principle study on patients recently diagnosed with T1D versus healthy controls yielded two major findings: First, there was a clear difference in whole-pancreas nanoparticle accumulation in patients and controls; second, the patients with T1D exhibited pronounced inter-and intrapancreatic heterogeneity in signal intensity. The ability to generate noninvasive, 3D, high-resolution maps of pancreatic inflammation in autoimmune diabetes should prove invaluable in assessing disease initiation and progression and as an indicator of response to emerging therapies.autoimmune diabetes | magnetic resonance imaging | nanoparticle | insulitis | pancreas

A global probabilistic fiber tracking approach based on the voting process provided by the Hough transform is introduced in this work. The proposed framework tests candidate 3D curves in the volume, assigning to each one a score computed from the diffusion images, and then selects the curves with the highest scores as the potential anatomical connections. The algorithm avoids local minima by performing an exhaustive search at the desired resolution. The technique is easily extended to multiple subjects, considering a single representative volume where the registered high-angular resolution diffusion images (HARDI) from all the subjects are non-linearly combined, thereby obtaining population-representative tracts. The tractography algorithm is run only once for the multiple subjects, and no tract alignment is necessary. We present experimental results on HARDI volumes, ranging from simulated and 1.5T physical phantoms to 7T and 4T human brain and 7T monkey brain datasets.

Polarization sensitive optical coherence tomography (PSOCT) with serial sectioning has enabled the investigation of 3D structures in mouse and human brain tissue samples. By using intrinsic optical properties of back-scattering and birefringence, PSOCT reliably images cytoarchitecture, myeloarchitecture and fiber orientations. In this study, we developed a fully automatic serial sectioning polarization sensitive optical coherence tomography (as-PSOCT) system to enable volumetric reconstruction of human brain samples with unprecedented sample size and resolution. The 3.5 μm in-plane resolution and 50 μm through-plane voxel size allow inspection of cortical layers that are a single-cell in width, as well as small crossing fibers. We show the abilities of as-PSOCT in quantifying layer thicknesses of the cerebellar cortex and creating microscopic tractography of intricate fiber networks in the subcortical nuclei and internal capsule regions, all based on volumetric reconstructions. as-PSOCT provides a viable tool for studying quantitative cytoarchitecture and myeloarchitecture and mapping connectivity with microscopic resolution in the human brain.