AW-OSEM parameter optimization for selected events related to the breath-hold CT position in respiratory-gated pet acquisitions

We present a novel CT-based method for minimizing the influence of respiratory motion in positron emission tomography (PET) images. The method relies on selection of events (i.e. detected coincidences) corresponding to the respiratory state in breath-hold X-ray computed tomography (CT) from respiratory-gated List Mode (LM) acquisitions. The low counting statistics in this method prompted an assessment of the tradeoff between the bias in standard imaging with motion and the increased variance associated with only using counts from a single phase of the respiratory cycle. The influence of AW-OSEM parameters (the number of iterations and the 3D Gaussian postfilter settings) was also optimized to suit the low counting statistics. Our results show that the parameter-optimized CT-based method reduces bias to 37.3%, compared with 70.7% for standard images with motion.