One of the challenges in PET/MRI is the derivation of an attenuation map to correct the PET image for attenuation. Different methods have been suggested for deriving the attenuation map from an MR image. Because the low signal intensity of cortical bone on images acquired with conventional MRI sequences makes it difficult to detect this tissue type, these methods rely on some sort of anatomic precondition to predict the attenuation map, raising the question of whether these methods will be usable in the clinic when patients may exhibit anatomic abnormalities. Methods: We propose the use of the transverse relaxation rate, derived from images acquired with an ultrashort echo time sequence to classify the voxels into 1 of 3 tissue classes (bone, soft tissue, or air), without making any assumptions on patient anatomy. Each voxel is assigned a linear attenuation coefficient corresponding to its tissue class. A reference CT scan is used to determine the voxel-by-voxel accuracy of the proposed method. The overall accuracy of the MRI-based attenuation correction is evaluated using a method that takes into account the nonlocal effects of attenuation correction. Results: As a proof of concept, the head of a pig was used as a phantom for imaging. The new method yielded a correct tissue classification in 90% of the voxels. Five human brain PET/CT and MRI datasets were also processed, yielding slightly worse voxel-by-voxel performance, compared to a CT-derived attenuation map. The PET datasets were reconstructed using the segmented MRI attenuation map derived with the new method, and the resulting images were compared with segmented CT-based attenuation correction. An average error of around 5% was found in the brain. Conclusion: The feasibility of using the transverse relaxation rate map derived from ultrashort echo time MR images for the estimation of the attenuation map was shown on phantom and clinical brain data. The results indicate that the new method, compared with CTbased attenuation correction, yields clinically acceptable errors. The proposed method does not make any assumptions about patient anatomy and could therefore also be used in cases in which anatomic abnormalities are present. A new generation of medical imaging scanners, which will combine the high sensitivity of functional imaging by PET with the wide range of applications of MRI scanners, is currently being developed (1-4). Combined PET/MRI offers several advantages over PET/CT, of which the following relate to the particular strength of the MRI method. First, it is possible to acquire anatomic images with better soft-tissue contrast than CT. Second, the radiation dose to the patient is significantly smaller. Third, other applications such as spectroscopy or molecular imaging are also possible with MRI. A PET/MRI scanner will also be a useful research tool, for example, enabling researchers to validate molecular MRI protocols against PET, which can be considered the current gold standard in molecular imaging.One of the difficulties in the design of a m...

Quantitative PET imaging requires an attenuation map to correct for attenuation. In stand-alone PET or PET/CT, the attenuation map is usually derived from a transmission scan or CT image, respectively. In PET/MR, these methods will most likely not be used. Therefore, attenuation correction has long been regarded as one of the major challenges in the development of PET/MR. In the past few years, much progress has been made in this field. In this review, the challenges faced in attenuation correction for PET/MR are discussed. Different methods have been proposed to overcome these challenges. An overview of the MR-based (template-based and voxel-based), transmission-based and emission-based methods and the results that have been obtained is provided. Although several methods show promising results, no single method fulfils all of the requirements for the ideal attenuation correction method for PET/MR. Therefore, more work is still necessary in this field. To allow implementation in routine clinical practice, extensive evaluation of the proposed methods is necessary to demonstrate robustness and automation.

When using a segmented attenuation map, at least five different tissue types should be considered: cortical bone, spongeous bone, soft tissue, lung, and air. Furthermore, the interpatient variability of lung attenuation coefficients should be taken into account. Limited misclassification from bone to soft tissue and from lung to air is acceptable, as these do not lead to relevant errors.

A new preclinical PET system based on dSiPMs, called DigiPET, is presented. The system is based on thin monolithic scintillation crystals and exhibits superior spatial resolution at low-cost compared to systems based on pixelated crystals. Current dedicated small-rodent PET scanners have a spatial resolution in the order of 1 mm. Most of them have a large footprint, requiring considerable laboratory space. For rodent brain imaging, a PET scanner with sub-millimeter resolution is desired. To achieve this, crystals with a pixel pitch down to 0.5 mm have been used. However, fine pixels are difficult to produce and will render systems expensive. In this work, we present the first results with a high-resolution preclinical PET scanner based on thin monolithic scintillators and a large solid angle. The design is dedicated to rat-brain imaging and therefore has a very compact geometry. Four detectors were placed in a square arrangement with a distance of 34.5 mm between two opposing detector modules, defining a field of view (FOV) of 32 × 32 × 32 mm(3). Each detector consists of a thin monolithic LYSO crystal of 32 × 32 × 2 mm(3) optically coupled to a digital silicon photomultiplier (dSiPM). Event positioning within each detector was obtained using the maximum likelihood estimation (MLE) method. To evaluate the system performance, we measured the energy resolution, coincidence resolving time (CRT), sensitivity and spatial resolution. The image quality was evaluated by acquiring a hot-rod phantom filled with (18)F-FDG and a rat head one hour after an (18)F-FDG injection. The MLE yielded an average intrinsic spatial resolution on the detector of 0.54 mm FWHM. We obtained a CRT of 680 ps and an energy resolution of 18% FWHM at 511 keV. The sensitivity and spatial resolution obtained at the center of the FOV were 6.0 cps kBq(-1) and 0.7 mm, respectively. In the reconstructed images of the hot-rod phantom, hot rods down to 0.7 mm can be discriminated. In conclusion, a compact PET scanner was built using dSiPM technology and thin monolithic LYSO crystals. Excellent spatial resolution and acceptable sensitivity were demonstrated. Promising results were also obtained in a hot-rod phantom and in rat-brain imaging.