A number of laboratories and companies are currently exploring the development of integrated imaging systems for magnetic resonance imaging (MRI) and positron emission tomography (PET). Scanners for both preclinical and human research applications are being pursued. In contrast to the widely distributed and now quite mature PET/computed tomography technology, most PET/MRI designs allow for simultaneous rather than sequential acquisition of PET and MRI data. While this offers the possibility of novel imaging strategies, it also creates considerable challenges for acquiring artifact-free images from both modalities. This paper discusses the motivation for developing combined PET/MRI technology, outlines the obstacles in realizing such an integrated instrument, and presents recent progress in the development of both the instrumentation and of novel imaging agents for combined PET/MRI studies. The performance of the first-generation PET/MRI systems is described. Finally, a range of possible biomedical applications for PET/MRI are outlined.

Within biological systems, water molecules undergo continuous stochastic Brownian motion. The diffusion rate can give clues to the structure of the underlying tissues. In some tissues, the rate is anisotropic. Diffusion-rate images can be calculated from diffusion-weighted MRI. A 2D diffusion tensor image (DTI) and an associated anatomical scalar field define seven values at each spatial location. We present two new methods for visually representing DTIs. The first method displays an array of ellipsoids, where the shape of each ellipsoid represents one tensor value. The ellipsoids are all normalized to approximately the same size so that they can be displayed simultaneously in context. The second method uses concepts from oil painting to represent the seven-valued data with multiple layers of varying brush strokes. Both methods successfully display most or all of the information in DTIs and provide exploratory methods for understanding them. The ellipsoid method has a simpler interpretation and explanation than the painting-motivated method; the painting-motivated method displays more of the information and is easier to read quantatively. We demonstrate the methods on images of the mouse spinal cord. The visualizations show significant differences between spinal cords from mice suffering from experimental allergic encephalomyelitis and spinal cords from wild-type mice. The differences are consistent with differences shown histologically and suggest that our new non-invasive imaging methodology and visualization of the results could have early diagnostic value for neurodegenerative diseases.

Here, the authors combine a pure phase-encoded magnetic resonance imaging (MRI) method with a new tissue-classification technique to make geometric models of a human tooth. They demonstrate the feasibility of three-dimensional imaging of solids using a conventional 11.7-T NMR spectrometer. In solid-state imaging, confounding line-broadening effects are typically eliminated using coherent averaging methods. Instead, the authors circumvent them by detecting the proton signal at a fixed phase-encode time following the radio-frequency excitation. By a judicious choice of the phase-encode time in the MRI protocol, the authors differentiate enamel and dentine sufficiently to successfully apply a new classification algorithm. This tissue-classification algorithm identifies the distribution of different material types, such as enamel and dentine, in volumetric data. In this algorithm, the authors treat a voxel as a volume, not as a single point, and assume that each voxel may contain more than one material. They use the distribution of MR image intensities within each voxel-sized volume to estimate the relative proportion of each material using a probabilistic approach. This combined approach, involving MRI and data classification, is directly applicable to bone imaging and hard-tissue contrast-based modeling of biological solids.

Resolution degradation due to gradient coil deformation and vibration in NMR microscopy is investigated using finite element analysis. From the analysis, deformations due to the Lorentz force can be as large as 1-10 mum depending on the gradient strength and coil frame material. Thus, these deformations can be one of the major resolution limiting factors in NMR microscopy. Coil vibration, which depends on the input current waveform and resolution degradation due to time-variant deformation and time-invariant deformation are investigated by numerical simulations.