We proposed and tested a novel geometry for PET system design analogous to pinhole SPECT called the virtual-pinhole PET (VP-PET) geometry to determine whether it could provide highresolution images. Methods: We analyzed the effects of photon acolinearity and detector sizes on system resolution and extended the empiric formula for reconstructed image resolution of conventional PET proposed earlier to predict the resolutions of VP-PET. To measure the system resolution of VP-PET, we recorded coincidence events as a 22 Na point source was stepped across the coincidence line of response between 2 detectors made from identical arrays of 12 · 12 lutetium oxyorthosilicate crystals (each measuring 1.51 · 1.51 · 10 mm 3 ) separated by 565 mm. To measure reconstructed image resolution, we built 4 VP-PET systems using 4 types of detectors (width, 1.51-6.4 mm) and imaged 4 point sources of 64 Cu (half-life 5 12.7 h to allow a long acquisition time). Tangential and radial resolutions were measured and averaged for each source and each system. We then imaged a polystyrene plastic phantom representing a 2.5-cm-thick cross-section of isolated breast volume. The phantom was filled with an aqueous solution of 64 Cu (713 kBq/mL) in which the following were imbedded: 4 spheric tumors ranging from 1.8 to 12.6 mm in inner diameter (ID), 6 micropipettes (0.7-or 1.1-mm ID filled with 64 Cu at 5·, 20·, or 50· background), and a 10.0-mm outer-diameter cold lesion. Results: The shape and measured full width at half maximum of the line spread functions agree well with the predicted values. Measured reconstructed image resolution (2.40-3.24 mm) was 66% of the predicted value for 3 of the 4 systems. In one case, the difference was 12.6%, possibly due to underestimation of the block effect from the low-resolution detector. In phantom experiments, all spheric tumors were detected. Small line sources were detected if the activity concentration is at least 20· background. Conclusion: We have developed and characterized a novel geometry for PET. A PET system following the VP-PET geometry provides high-resolution images for objects near the system's high-resolution detectors. This geometry may lead to the development of special-purpose PET systems or resolution-enhancing insert devices for conventional PET scanners. PET has evolved from a research tool for studying neurologic and cardiac functions of humans (1) to a clinical diagnostic tool for cancer patients (2), particularly since the introduction of PET/CT technology (3). With the introduction of high-resolution animal PET scanners in the mid1990s (4,5), PET became a driving force behind molecular imaging through in vivo imaging of small animals using positron-emitting radionuclide-labeled biomolecules (6).Resolution of PET is limited by the positron range of the radionuclide, acolinearity of the annihilation g-rays, and intrinsic spatial resolution of the detectors. For whole-body PET scanners with large diameters, the blurring of image resolution due to the acolinearity effect is approximatel...

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A full-ring PET insert device should be able to enhance the image resolution of existing small-animal PET scanners. Methods: The device consists of 18 high-resolution PET detectors in a cylindric enclosure. Each detector contains a cerium-doped lutetium oxyorthosilicate array (12 · 12 crystals, 0.72 · 1.51 · 3.75 mm each) coupled to a position-sensitive photomultiplier tube via an optical fiber bundle made of 8 · 16 square multiclad fibers. Signals from the insert detectors are connected to the scanner through the electronics of the disabled first ring of detectors, which permits coincidence detection between the 2 systems. Energy resolution of a detector was measured using a 68 Ge point source, and a calibrated 68 Ge point source stepped across the axial field of view (FOV) provided the sensitivity profile of the system. A 22 Na point source imaged at different offsets from the center characterized the in-plane resolution of the insert system. Imaging was then performed with a Derenzo phantom filled with 19.5 MBq of 18 F-fluoride and imaged for 2 h; a 24.3-g mouse injected with 129.5 MBq of 18 F-fluoride and imaged in 5 bed positions at 3.5 h after injection; and a 22.8-g mouse injected with 14.3 MBq of 18 F-FDG and imaged for 2 h with electrocardiogram gating. Results: The energy resolution of a typical detector module at 511 keV is 19.0% 6 3.1%. The peak sensitivity of the system is approximately 2.67%. The image resolution of the system ranges from 1.0-to 1.8-mm full width at half maximum near the center of the FOV, depending on the type of coincidence events used for image reconstruction. Derenzo phantom and mouse bone images showed significant improvement in transaxial image resolution using the insert device. Mouse heart images demonstrated the gated imaging capability of the device. Conclusion: We have built a prototype full-ring insert device for a small-animal PET scanner to provide higher-resolution PET images within a reduced imaging FOV. Development of additional correction techniques are needed to achieve quantitative imaging with such an insert. Hi gh-resolution PET scanners dedicated to small-animal imaging have been developed by several research groups since the 1990s (1-11). Combining high-resolution and quantitative imaging capability, small-animal PET has been a driving force behind the development of molecular imaging that brings together scientists from different disciplines to study biologic effects at the molecular level (12,13). Smallanimal PET has also been adopted by the pharmaceutical industry to study pharmacokinetics and pharmacodynamics to accelerate development of new drugs (14). The increasing demand for small-animal PET has led to commercialization of several small-animal PET technologies (15). Current technologic research and development is focused on further improvement of the resolution or sensitivity of small-animal PET systems (16).Most commercial small-animal PET scanners use inorganic scintillators for g-ray detection, a proven technology that provides good image resoluti...

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We found both interventions delivered similar improvements in the VAS and NDI scores in patients. Both techniques may be appropriately utilised when treating a patient with cervical brachialgia.

Abstract-Markov random fields (MRFs) have been widely used as prior models in various inverse problems such as tomographic reconstruction. While MRFs provide a simple and often effective way to model the spatial dependencies in images, they suffer from the fact that parameter estimation is difficult. In practice, this means that MRFs typically have very simple structure that cannot completely capture the subtle characteristics of complex images.In this paper, we present a novel Gaussian mixture Markov random field model (GM-MRF) that can be used as a very expressive prior model for inverse problems such as denoising and reconstruction. The GM-MRF forms a global image model by merging together individual Gaussian-mixture models (GMMs) for image patches. In addition, we present a novel analytical framework for computing MAP estimates using the GM-MRF prior model through the construction of surrogate functions that result in a sequence of quadratic optimizations. We also introduce a simple but effective method to adjust the GM-MRF so as to control the sharpness in low-and high-contrast regions of the reconstruction separately. We demonstrate the value of the model with experiments including image denoising and low-dose CT reconstruction.Index Terms-Markov random field (MRF), Gaussian mixture model (GMM), prior modeling, image model, patch-based method, model-based iterative reconstruction (MBIR).

A 25-year-old woman, who was 25 weeks pregnant, underwent insertion of a VP shunt for hydrocephalus, secondary to a bithalamic glioma. Two months later, she represented with symptoms of raised intracranial pressure and MR scan revealed increased ventricular size. On exploration of the shunt, manometry with saline confirmed blockage of the catheter distal to the valve. On re-opening the abdominal wound, the peritoneal catheter was found to be knotted, 2 cm from the end. This segment of the catheter was replaced, with resolution of symptoms, post-operatively. The present case illustrates that a knot in the peritoneal catheter is an extremely rare cause of shunt malfunction. Possible mechanisms underlying it are discussed.

Statistical image reconstruction algorithms in X-ray CT provide improved image quality for reduced dose levels but require substantial computation time. Iterative algorithms that converge in few iterations and that are amenable to massive parallelization are favorable in multiprocessor implementations. The separable quadratic surrogate (SQS) algorithm is desirable as it is simple and updates all voxels simultaneously. However, the standard SQS algorithm requires many iterations to converge. This paper proposes an extension of the SQS algorithm that leads to spatially non-uniform updates. The non-uniform (NU) SQS encourages larger step sizes for the voxels that are expected to change more between the current and the final image, accelerating convergence, while the derivation of NU-SQS guarantees monotonic descent. Ordered subsets (OS) algorithms can also accelerate SQS, provided suitable “subset balance” conditions hold. These conditions can fail in 3D helical cone-beam CT due to incomplete sampling outside the axial region-of-interest (ROI). This paper proposes a modified OS algorithm that is more stable outside the ROI in helical CT. We use CT scans to demonstrate that the proposed NU-OS-SQS algorithm handles the helical geometry better than the conventional OS methods and “converges” in less than half the time of ordinary OS-SQS.