Abstract
It is important to predict and understand how scanner design characteristics will affect image quality relevant to clinical tasks when developing a new system. It is a complex task to understand the interplay among multiple system parameters such as time-of-flight (TOF) resolution, sensitivity, intrinsic spatial resolution, and depth-of-interaction (DOI) resolution. This can be achieved by Monte Carlo (MC) simulation. Here we perform MC simulation using SimSET to simulate brain-dedicated positron emission tomography (PET) scanners with varying system parameters such as DOI resolution, intrinsic spatial resolution and TOF resolution. We report preliminary results from simulating various phantoms. The results show that DOI information greatly improves image resolution particularly in the peripheral regions, reducing parallax errors even without point spread function modeling, that smaller detector elements improve image resolution, and that TOF information lowers image noise. The MC simulation analysis provides useful results for optimizing detector geometry and hardware for high resolution neuro-PET scanner design.
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