TOF-PET image reconstruction with multiple timing kernels applied on
Cherenkov radiation in BGO
Abstract
Today Time-Of-Flight in PET scanners assumes a unique, well-defined
timing resolution for all coincidence events.
However, recent BGO-Cherenkov detectors, combining prompt Cherenkov
emission and the typical BGO scintillation signal, are capable of
sorting events into multiple mixture timing kernels and therefore
increase the available information for the image reconstruction. The
number of Cherenkov photons detected per event impacts directly the
signal rise time, which can therefore be used to improve the timing
resolution.
In this work, we present a simulation toolkit that outputs data with
multiple timing resolutions and image reconstruction that incorporates
this information.
A full cylindrical BGO-Cherenkov PET model was compared, in terms of
contrast recovery and contrast-to-noise ratio, against non-TOF and an
LYSO model with time resolution of 213 ps.
Two reconstruction approaches for the mixture kernels were tested;
mixture Gaussian and decomposed simple Gaussian models. The decomposed
model used the exact mixture component applied in the simulation.
Images reconstructed using mixture kernels provided similar mean value
and less noise as compared to the decomposed simple Gaussian kernels.
Although, the later converged faster.
Related to the standard LYSO model, the BGO-Cherenkov provided similar
contrast, although, in most cases, with more iterations.
However, due to the higher sensitivity, the contrast-to-noise ratio was
26.4% better for the BGO model.