Small-animal PET systems are now striving for sub-millimetre resolution. Current systems based upon PSPMTs and finely pixellated scintillators can be pushed to higher resolution, but at the expense of other performance parameters and a rapidly escalating cost. Moreover, depth of interaction (DOI) information is usually difficult to assess in such systems, even though this information is highly desirable to reduce the parallax error, which is often the dominant error for such high-resolution systems. In this study we propose a high-resolution detector head for a small-animal PET imaging system with intrinsic DOI information. Instead of a pixellated scintillator, our design is based upon the classic Anger camera principle, i.e. the head is constructed of modular layers each consisting of a continuous slab of scintillator, viewed by a new type of compact silicon photodetector. The photodetector is the recently developed silicon photomultiplier (SiPM) that as well as being very compact has many other attractive properties: high gain at low bias voltage, excellent single-photoelectron resolution and fast timing. A detector head of about 4 x 4 cm2 in area is proposed, constructed from three modular layers of the type described above. We perform a simulation study, using the Monte Carlo simulation package Geant4. The simulation results are used to optimize the geometry of the detector head and characterize its performance. Additionally, hit estimation algorithms are studied to determine the interaction position of annihilation photons correctly over the whole detector surface. The resulting detector has a nearly uniform efficiency for 511 keV photons of approximately 70% and an intrinsic spatial resolution of less than approximately 0.4 mm full width at half maximum (fwhm).

Iterative image reconstruction algorithms for positron emission tomography (PET) require a sophisticated system matrix (model) of the scanner. Our aim is to set up such a model offline for the YAP-(S)PET II small animal imaging tomograph in order to use it subsequently with standard ML-EM (maximum-likelihood expectation maximization) and OSEM (ordered subset expectation maximization) for fully three-dimensional image reconstruction. In general, the system model can be obtained analytically, via measurements or via Monte Carlo simulations. In this paper, we present the multi-ray method, which can be considered as a hybrid method to set up the system model offline. It incorporates accurate analytical (geometric) considerations as well as crystal depth and crystal scatter effects. At the same time, it has the potential to model seamlessly other physical aspects such as the positron range. The proposed method is based on multiple rays which are traced from/to the detector crystals through the image volume. Such a ray-tracing approach itself is not new; however, we derive a novel mathematical formulation of the approach and investigate the positioning of the integration (ray-end) points. First, we study single system matrix entries and show that the positioning and weighting of the ray-end points according to Gaussian integration give better results compared to equally spaced integration points (trapezoidal integration), especially if only a small number of integration points (rays) are used. Additionally, we show that, for a given variance of the single matrix entries, the number of rays (events) required to calculate the whole matrix is a factor of 20 larger when using a pure Monte-Carlo-based method. Finally, we analyse the quality of the model by reconstructing phantom data from the YAP-(S)PET II scanner.

In this paper we present a new method for the determination of geometrical misalignments in cone-beam CT scanners, from the analysis of the projection data of a generic object. No a priori knowledge of the object shape and positioning is required. We show that a cost function, which depends on the misalignment parameters, can be defined using the projection data and that such a cost function has a local minimum in correspondence to the actual parameters of the system. Hence, the calibration of the scanner can be carried out by minimizing the cost function using standard optimization techniques. The method is developed for a particular class of 3D object functions, for which the redundancy of the fan beam sinogram in the transaxial midplane can be extended to cone-beam projection data, even at wide cone angles. The method has an approximated validity for objects which do not belong to that class; in that case, a suitable subset of the projection data can be selected in order to compute the cost function. We show by numerical simulations that our method is capable to determine with high accuracy the most critical misalignment parameters of the scanner, i.e., the transversal shift and the skew of the detector. Additionally, the detector slant can be determined. Other parameters such as the detector tilt, the longitudinal shift and the error in the source-detector distance cannot be determined with our method, as the proposed cost function has a very weak dependence on them. However, due to the negligible influence of these latter parameters in the reconstructed image quality, they can be kept fixed at estimated values in both calibration and reconstruction processes without compromising the final result. A trade-off between computational cost and calibration accuracy must be considered when choosing the data subset used for the computation of the cost function. Results on real data of a mouse femur as obtained with a small animal micro-CT are shown as well, proving the capability of the proposed calibration method. In principle, the method can be adapted to other cone-beam imaging modalities (e.g., single photon emission computed tomography).