Attenuation correction is an essential requirement for quantification of positron emission tomography (PET) data. In PET/CT acquisition systems, attenuation maps are derived from computed tomography (CT) images. However, in hybrid PET/MR scanners, magnetic resonance imaging (MRI) images do not directly provide a patient-specific attenuation map. The aim of the proposed work is to improve attenuation correction for PET/MR scanners by generating synthetic CTs and attenuation maps. The synthetic images are generated through a multi-atlas information propagation scheme, locally matching the MRI-derived patient's morphology to a database of MRI/CT pairs, using a local image similarity measure. Results show significant improvements in CT synthesis and PET reconstruction accuracy when compared to a segmentation method using an ultrashort-echo-time MRI sequence and to a simplified atlas-based method.

Accurate quantification in PET and SPECT requires correction for a number of physical factors, such as photon attenuation, Compton scattering and random coincidences (in PET). Another factor affecting quantification is the limited spatial resolution. While considerable effort has gone into development of routine correction techniques for the former factors, less attention has been paid to the latter. Spatial resolution-related effects, referred to as 'partial volume effects' (PVEs), depend not only on the characteristics of the imaging system but also on the object and activity distribution. Spatial and/or temporal variations in PVE can often be confounding factors. Partial volume correction (PVC) could in theory be achieved by some kind of inverse filtering technique, reversing the effect of the system PSF. However, these methods are limited, and usually lead to noise-amplification or image artefacts. Some form of regularization is therefore needed, and this can be achieved using information from co-registered anatomical images, such as CT or MRI. The purpose of this paper is to enhance understanding of PVEs and to review possible approaches for PVC. We also present a review of clinical applications of PVC within the fields of neurology, cardiology and oncology, including specific examples.

Care should be taken when applying PVC to amyloid PET images. Assumptions made in existing PVC strategies can induce biases that could lead to erroneous inferences about uptake in certain regions. The proposed RBV PVC technique accounts for within-compartment variability, with the potential to reduce errors of this kind.

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All of the proposed novel methods have an average global performance within likely acceptable limits (±5% of CT-based reference), and the main difference among the methods was found in the robustness, outlier analysis, and clinical feasibility. Overall, the best performing methods were MR-ACBOSTON, MR-ACMAXPROB, MR-ACRESOLUTE and MR-ACUCL, ordered alphabetically. These methods all minimized the number of outliers, standard deviation, and average global and local error. The methods MR-ACMUNICH and MR-ACCAR-RiDR were both within acceptable quantitative limits, so these methods should be considered if processing time is a factor. The method MR-ACSEGBONE also demonstrates promising results, and performs well within the likely acceptable quantitative limits. For clinical routine scans where processing time can be a key factor, this vendor-provided solution currently outperforms most methods. With the performance of the methods presented here, it may be concluded that the challenge of improving the accuracy of MR-AC in adult brains with normal anatomy has been solved to a quantitatively acceptable degree, which is smaller than the quantification reproducibility in PET imaging.

Recent advances in technology have enabled the combination of positron emission tomography (PET) with magnetic resonance imaging (MRI). These PET-MRI scanners simultaneously acquire functional PET and anatomical or functional MRI data. As function and anatomy are not independent of one another the images to be reconstructed are likely to have shared structures. We aim to exploit this inherent structural similarity by reconstructing from both modalities in a joint reconstruction framework. The structural similarity between two modalities can be modelled in two different ways: edges are more likely to be at similar positions and/or to have similar orientations. We analyse the diffusion process generated by minimizing priors that encapsulate these different models. It turns out that the class of parallel level set priors always corresponds to anisotropic diffusion which is sometimes forward and sometimes backward diffusion. We perform numerical experiments where we jointly reconstruct from blurred Radon data with Poisson noise (PET) and under-sampled Fourier data with Gaussian noise (MRI). Our results show that both modalities benefit from each other in areas of shared edge information. The joint reconstructions have less artefacts and sharper edges compared to separate reconstructions and the ℓ 2 -error can be reduced in all of the considered cases of under-sampling.

This study described and validated a new solid-state singlephoton g-camera and compared it with a conventional-SPECT Anger camera. The compact new camera uses a unique method for localizing g-photon information with a bank of 9 solid-state detector columns with tungsten collimators that rotate independently. Methods: Several phantom studies were performed comparing the new technology with conventional-SPECT technology. These included measurements of line sources and single-and dual-radionuclide studies of a torso phantom. Simulations were also performed using a cardiothoracic phantom. Furthermore, 18 patients were scanned with both the new camera and a conventional-SPECT camera. Results: The new camera had a count sensitivity that was 10 times higher than that of the conventional camera and a compensated spatial resolution that was moderately better. Dual-radionuclide studies using a phantom show the further potential of the new camera for a 2-tracer simultaneous acquisition. Two-minute clinical studies with the new camera and 11-min studies with the conventional camera qualitatively showed good-to-excellent image quality and improved myocardial edge definition for the new camera. Conclusion: These initial performance characteristics of a new solid-state single-photon g-camera offer great promise for clinical dynamic SPECT protocols, with important implications for applications in nuclear cardiology and molecular imaging. Nucl ear medicine has evolved as a clinical and research discipline for the noninvasive assessment of physiologic and molecular function in normal and diseased tissues. Principally performed with nanomolar quantities of administered radiopharmaceuticals and an external scintillation camera, nuclear medicine imaging uses 2 types of modalities: singlephoton imaging (including planar imaging and SPECT) and PET, with the former comprising nearly three fourths of all clinical procedures. With SPECT, myocardial perfusion studies predominate; these studies were performed in approximately 7,000,000 patients in the United States in 2004 and provided images of relative myocardial perfusion at rest and under stress. By assessing the extent of ischemic and infarcted myocardium, SPECT provides noninvasive information that has become central in clinical decision making, determining the need for invasive cardiac catheterization and myocardial revascularization in many patients (1,2).SPECT is typically performed using an Anger scintillation camera, named after its inventor, Hal Anger (3). Most myocardial SPECT is performed with 2 scintillation cameras oriented at 90°and mounted on a gantry that rotates around the patient. Typically, each scintillation camera is equipped with parallel-hole high-resolution collimators. Since collimation is necessary to acquire the projection views, only 0.02% of the photons emitted from the heart are collected. As a result, acquisition times of 10-20 min are required for myocardial SPECT studies. Although new detector technologies using solid-state materials have been explored (...

Detection of scattered gamma quanta degrades image contrast and quantitative accuracy of single-photon emission computed tomography (SPECT) imaging. This paper reviews methods to characterize and model scatter in SPECT and correct for its image degrading effects, both for clinical and small animal SPECT. Traditionally scatter correction methods were limited in accuracy, noise properties and/or generality and were not very widely applied. For small animal SPECT, these approximate methods of correction are often sufficient since the fraction of detected scattered photons is small. This contrasts with patient imaging where better accuracy can lead to significant improvement of image quality. As a result, over the last two decades, several new and improved scatter correction methods have been developed, although often at the cost of increased complexity and computation time. In concert with (i) the increasing number of energy windows on modern SPECT systems and (ii) excellent attenuation maps provided in SPECT/CT, some of these methods give new opportunities to remove degrading effects of scatter in both standard and complex situations and therefore are a gateway to highly quantitative single- and multi-tracer molecular imaging with improved noise properties. Widespread implementation of such scatter correction methods, however, still requires significant effort.