Direct parametric estimation of blood flow in abdominal PET/CT within an EM reconstruction framework

Parametric estimation of perfusion using [¹⁵O]-H₂O is an important biomarker for assessing treatment response in oncology clinical trials involving anti-vascular and anti-angiogenic agents. Traditionally the set of dynamic images are reconstructed independently, followed by post-reconstruction kinetic modelling. This methodology results in sub-optimal and often noisy end point parameters if voxel-by-voxel kinetic modelling is used. In [¹⁵O]-H₂O scans, the extremely short temporal frames and the rapid decay of the tracer results in further signal-to-noise ratio (SNR) reduction. Direct 4-D reconstruction methods have the potential to reduce noise and improve parameter estimates by combining image reconstruction and kinetic modelling in a unified process. In this work we implement a direct parametric reconstruction using an EM framework and apply it on a real [¹⁵O]-H₂O PET/CT dataset to derive parametric images of perfusion (f), clearance rate (k₂) and fractional blood volume (V_a). Results show substantial variance reduction both in perfusion and k₂ images compared to the post-reconstruction kinetic analysis, especially in areas of increased perfusion. This results in increased tumour-to-background contrast and improved delineation of organ boundaries. Although further analysis in needed, direct reconstruction methods have the potential to be applied in a wide variety of oncology PET/CT studies with the improvements highly depended on the tracer and the system under study.