Abstract: A high-resolution silicon detector probe, in coincidence with a conventional PET scanner, is expected to provide images of higher quality than those achievable using the scanner alone. Spatial resolution should improve due to the finer pixelization of the probe detector, while increased sensitivity in the probe vicinity is expected to decrease noise. A PET-probe prototype is being developed utilizing this principle. The system includes a probe consisting of ten layers of silicon detectors, each a 80 x 52 array of 1 x 1 x 1 mm(3) pixels, to be operated in coincidence with a modern clinical PET scanner. Detailed simulation studies of this system have been performed to assess the effect of the additional probe information on the quality of the reconstructed images. A grid of point sources was simulated to study the contribution of the probe to the system resolution at different locations over the field of view (FOV). A resolution phantom was used to demonstrate the effect on image resolution for two probe positions. A homogeneous source distribution with hot and cold regions was used to demonstrate that the localized improvement in resolution does not come at the expense of the overall quality of the image. Since the improvement is constrained to an area close to the probe, breast imaging is proposed as a potential application for the novel geometry. In this sense, a simplified breast phantom, adjacent to heart and torso compartments, was simulated and the effect of the probe on lesion detectability, through measurements of the local contrast recovery coefficient-to-noise ratio (CNR), was observed. The list-mode ML-EM algorithm was used for image reconstruction in all cases. As expected, the point spread function of the PET-probe system was found to be non-isotropic and vary with position, offering improvement in specific regions. Increase in resolution, of factors of up to 2, was observed in the region close to the probe. Images of the resolution phantom showed visible improvement in resolution when including the probe in the simulations. The image quality study demonstrated that contrast and spill-over ratio in other areas of the FOV were not sacrificed for this enhancement. The CNR study performed on the breast phantom indicates increased lesion detectability provided by the probe.

Abstract: A method to improve light collection efficiency of gamma-ray imaging detectors by using retroreflector arrays has been tested, simulations of the behaviour of the scintillation light illuminating the retroreflector surface have been made. Measurements including retroreflector arrays in the setup have also been taken. For the measurements, positron emission tomography (PET) detectors with continuous scintillation crystals have been used. Each detector module consists of a continuous LSO-scintillator of dimensions 49x49x10 mm(3) and a H8500 position-sensitive photo-multiplier (PSPMT) from Hamamatsu. By using a continuous scintillation crystal, the scintillation light distribution has not been destroyed and the energy, the centroids along the x- and y-direction and the depth of interaction (DOI) can be estimated. Simulations have also been run taking into account the use of continuous scintillation crystals. Due to the geometry of the continuous scintillation crystals in comparison with pixelated crystals, a good light collection efficiency is necessary to correctly reconstruct the impact point of the gamma-ray. The aim of this study is to investigate whether micro-machine retro-reflectors improve light yield without misestimation of the impact point. The results shows an improvement on the energy and centroid resolutions without worsening the depth of interaction resolution. Therefore it can be concluded that using retroreflector arrays at the entrance side of the scintillation crystal improves light collection efficiency without worsening the impact point estimation.

Abstract: A neural network for software compensation was developed for the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL). The neural network uses spatial and temporal event information from the AHCAL and energy information, which is expected to improve sensitivity to shower development and the neutron fraction of the hadron shower. The neural network method produced a depth-dependent energy weighting and a time-dependent threshold for enhancing energy deposits consistent with the timescale of evaporation neutrons. Additionally, it was observed to learn an energy-weighting indicative of longitudinal leakage correction. In addition, the method produced a linear detector response and outperformed a published control method regarding resolution for every particle energy studied.