Evaluation of a direct 4D reconstruction method using GLLS for estimating parametric maps of micro-parameters

Estimation of non-linear micro-parameters is a computationally demanding process, since it involves the use of iterative non-linear fitting algorithms and it often results in very noisy parametric maps. Direct reconstruction algorithms can provide parametric maps with reduced variance, but usually the reconstruction is impractically time consuming with common non-linear fitting algorithms. In this work we employed a recently proposed direct parametric image reconstruction algorithm to estimate the parametric maps of all micro-parameters of a two-tissue compartment model, used to describe the kinetics of [¹⁸F]FDG. The algorithm decouples the tomographic and the kinetic modelling problems, allowing the use of previously developed post-reconstruction methods, such as the generalised linear least squares (GLLS) algorithm. Results on both clinical and simulated data show that the direct reconstruction method provides considerable quantitative and visual improvements for all micro-parameters compared to the conventional post-reconstruction fitting method. Additionally, due to the linearized nature of the GLLS algorithm, the fitting procedure does not considerably affect the overall reconstruction time.