Error propagation reduction in direct 4D image reconstruction using time-of-flight PET

Abstract

Direct 4D image reconstruction methods have been shown to generate parametric maps of improved precision and accuracy in dynamic PET. However due to the inability to construct a common single kinetic model for the entire FOV, the interleaving between tomographic and kinetic modelling steps causes errors in erroneously modelled regions to spatial propagate. Adaptive models have be used to mitigate the problem though are complex and difficult to optimize. In this work we demonstrate a new way to minimize errors, focusing on the tomographic step rather than the kinetic modelling and limiting the actual propagation of bias by incorporating time-offlight (TOF) within a direct 4D reconstruction framework. Using ever improving TOF resolutions (580ps, 440ps, 300ps and 160ps) we demonstrate that TOF direct 4D image reconstruction can substantially prevent error propagation from erroneous kinetic models. Errors appear to be constrained in the vicinity of erroneously modelled regions with bias reduction of up to 60% in well modelled regions compared to non-TOF direct 4D reconstruction. Combining such a TOF direct 4D image reconstruction with adaptive models, further improvements could possibly be achieved in the future.