Compton Camera Image Reconstruction with A-Priori Information from a Beam Tagging Hodoscope

Compton cameras (CC) have been proposed for range monitoring in proton therapy. The goal is to detected the prompt-gamma (PG) radiation which emerges from the patient, and estimate the underlying activation distribution by using tomographic reconstruction algorithms. The reconstructed CC images are often affected by high levels of statistical noise and other artefacts. With the aim of improving the reconstructed images, here we study various approaches able to exploit a-priori information from a beam-tagging hodoscope. The latter provides an estimation about the beam spread and its direction, so that this information can be used before or during the reconstruction in different ways, e.g. to restrict the volume-of-response assigned to each event, or to design a novel penalty function for regularized image reconstruction. We have implemented several approaches using Monte Carlo simulated data. In particular, our penalized reconstruction led to a significant improvement of the image quality. The estimated distal edge was well resolved for all tested scenarios.