High-resolution positronium lifetime tomography by the method of moments.

Abstract

Objective.Positronium lifetime tomography (PLT) is an emerging modality that aims to reconstruct 3D images of positronium lifetime in humans and animalsin vivo. The lifetime of ortho-positronium can be influenced by the microstructure and the concentration of bio-active molecules in tissue, providing valuable information for better understanding disease progression and treatment response. However, efficient high-resolution lifetime image reconstruction methods are currently lacking. Existing methods are either computationally intensive or have poor spatial resolution. This paper presents a fast, high-resolution lifetime image reconstruction method for PLT.Approach. The proposed method, called SIMPLE-Moment (Statistical IMage reconstruction of Positron annihilation LifetimE by Moment weighting), first reconstructs a set of moment images and then estimates the ortho-positronium lifetime image using the method of moments. The implementation of SIMPLE-Moment requires minimal modification to the conventional ordered subset expectation maximization algorithm.Main results.With reasonable assumptions, the proposed method can reconstruct an ortho-positronium lifetime image with a computational cost equivalent to three standard positron emission tomography (PET) image reconstructions. A Monte Carlo simulation study based on an existing time-of-flight PET scanner demonstrates that the ortho-positronium lifetime image reconstructed by SIMPLE-Moment is accurate and comparable to results obtained using the more computationally intensive Statistical Positronium Lifetime Image reconstruction via time-Thresholding (SPLIT) method.Significance. The proposed SIMPLE-Moment method provides an efficient approach to high-resolution reconstruction of ortho-positronium lifetime images. By reducing computational costs while enhancing spatial resolution, this method has the potential to make PLT more accessible and practical for clinical and research applications.