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Simultaneous positron-emission tomography (PET)-magnetic resonance (MR) imaging is a hybrid technique in oncological hepatic imaging combining soft-tissue and functional contrast of dynamic contrast enhanced MR (DCE-MR) with metabolic information from PET. In this context, respiratory motion represents a major challenge by introducing blurring, artifacts and misregistration in the liver. In this work, we propose a free-breathing 3D non-rigid respiratory motion correction framework for simultaneously acquired DCE-MR and PET data, which makes use of higher spatial resolution MR data to derive motion information used directly during image reconstruction to minimize image blurring and motion artifacts. The main aim was to increase contrast of hepatic metastases to improve their detection and characterization. DCE-MR data were acquired at 3T through a golden radial phase encoding scheme, enabling derivation of motion fields. These were used in the motion compensated image reconstruction of DCE-MR time-series (48 time-points, 6 s temporal resolution, 1.5 mm isotropic spatial resolution) and 3D PET activity map, which was subsequently interpolated to the DCE-MR resolution. The extended Tofts model was fitted to DCE-MR data, obtaining functional parametric maps related to perfusion such as the endothelial permeability (). Fifty-seven hepatic metastases were identified and analyzed. Quantitative evaluations of motion correction in PET images demonstrated average percentage increases of 16% ± 5% (mean ± SD) in Contrast (C), 18% ± 6% in SUVmean and 14% ± 2% in SUVmax, while DCE-MR and scored contrast-to-noise-ratio increases of 64% ± 3% and 90% ± 6%, respectively. Motion-corrected data visually showed improved image contrast of hepatic metastases and effectively reduced blurring and motion artefacts. Scatter plots of SUVmean versus suggested that the proposed framework improved differentiation of measurements. The presented motion correction framework for simultaneously acquired PET-DCE-MR data provides accurately aligned images with increased contrast of hepatic lesions allowing for improved detection and characterization. [ABSTRACT FROM AUTHOR]

We have carried out a PET performance evaluation a silicon photo-multiplier (SiPM) based PET scanner designed for fully simultaneous pre-clinical PET/MR studies. The PET scanner has an inner diameter of 20 cm with an LYSO crystal size of 1.3 by 1.3 by 10 mm. The axial PET field of view (FOV) is 30.2 mm. The PET detector modules, which incorporate SiPMs, have been designed to be MR-compatible allowing them to be located directly within a Philips Achieva 3T MR scanner. The spatial resolution of the system measured using a point source in a non-active background, is just under 2.3 mm full width at half maximum (FWHM) in the transaxial direction when single slice rebinning (SSRB) and 2D filtered back-projection (FBP) is used for reconstruction, and 1.3 mm FWHM when resolution modeling is employed. The system sensitivity is 0.6% for a point source at the center of the FOV. The true coincidence count rate shows no sign of saturating at 30 MBq, at which point the randoms fraction is 8.2%, and the scatter fraction for a rat sized object is approximately 23%. Artifact-free images of phantoms have been obtained using FBP and iterative reconstructions. The performance is currently limited because only one of three axial ring positions is populated with detectors, and due to limitations of the first-generation detector readout ASIC used in the system. The performance of the system as described is sufficient for simultaneous PET-MR imaging of rat-sized animals and large organs within the mouse. This is demonstrated with dynamic PET and MR data acquired simultaneously from a mouse injected with a dual-labeled PET/MR probe. [ABSTRACT FROM PUBLISHER]

In hybrid PET/MR systems, attenuation maps can be derived from MR to correct for attenuation in PET. However, MR-based attenuation correction (AC) in abdominal applications remains challenging (i) because of poor signal from important tissue types in common MR sequences (e.g., cortical bone) and (ii) because of respiratory motion which results in misalignments between the derived attenuation maps and the PET emissions. Furthermore, respiratory motion also leads to motion-blurring artefacts in the final PET reconstructions. In this paper, we compute an MR-based 4D attenuation map including cortical bone by combining an Ultrashort Echo Time (UTE) acquisition with a subject-specific motion model derived from a second near real-time 3D MR image acquisition. This model allows us to create attenuation maps at any respiratory position which are used for AC in the reconstruction of different respiratory resolved PET images. The inverse of the model is used for motion compensation (MC) of these images. We demonstrate our approach on MR data from 5 healthy volunteers including 3 manually inserted artificial lesions. The impact of bone tissue and respiratory motion on AC is investigated in PET simulations (i) by misclassifying bone to soft tissue in the attenuation maps leading to errors of up to 26.0% in mean uptake for lesions close to bone, and (ii) by using a non-moving attenuation map leading to errors of up to 24.2%. The impact of respiratory motion on MC showed errors of up to 50.7% in areas of strong motion if MC was not performed. The results show that the effect of motion has to be considered both for attenuation correction and for motion-compensating PET emissions. This additive effect of motion is larger than the effect of a wrong AC. [ABSTRACT FROM PUBLISHER]