  Single-bed whole-body positron emission tomography based on resistive plate
chamber detectors (RPC-PET) has been proposed for human studies, as a
complementary resource to scintillator-based PET scanners. The purpose of this
work is mainly about providing a reconstruction solution to such whole-body
single-bed data collection on an event-by-event basis. We demonstrate a fully
three-dimensional time-of-flight (TOF)-based reconstruction algorithm that is
capable of processing the highly inclined lines of response acquired from a
system with a very large axial field of view, such as those used in RPC-PET.
Such algorithm must be sufficiently fast that it will not compromise the
clinical workflow of an RPC-PET system. We present simulation results from a
voxelized version of the anthropomorphic NCAT phantom, with oncological lesions
introduced into critical regions within the human body. The list-mode data was
reconstructed with a TOF-weighted maximum-likelihood expectation maximization
(MLEM). To accelerate the reconstruction time of the algorithm, a
multi-threaded approach supported by graphical processing units (GPUs) was
developed. Additionally, a TOF-assisted data division method is suggested that
allows the data from nine body regions to be reconstructed independently and
much more rapidly. The application of a TOF-based scatter rejection method
reduces the overall body scatter from 57.1% to 32.9%. The results also show
that a 300-ps FWHM RPC-PET scanner allows for the production of a reconstructed
image in 3.5 minutes following a 7-minute acquisition upon the injection of 2
mCi of activity (146 M coincidence events). We present for the first time a
full realistic reconstruction of a whole body, long axial coverage, RPC-PET
scanner. We demonstrate clinically relevant reconstruction times comparable (or
lower) to the patient acquisition times on both multi-threaded CPU and GPU.
