EM reconstruction of Dual Isotope PET with staggered injections and prompt gamma positron emitters

The aim of Dual Isotope Positron Emission Tomography (DIPET) is to create two independent images of two co-injected radiotracers. DIPET shortens the duration of the study, reduces patient discomfort and produces perfectly coregistered images. Its implementation is difficult because positron decay of any isotope creates only 511 keY photons. Recently, we have proposed a DIPET technique that uses a combination of radiotracer A which is a pure positron emitter (such as ¹⁸F or ¹¹C) and radiotracer B in which positron decay is followed by the emission of a high-energy (HE) prompt gamma (such as ³⁸K or ⁶⁰Cu). Events that are detected as triple coincidences of HE gammas with the corresponding two 511 keY photons identify the line-of-responses (LORs) that originate from isotope B (~10% of all events). These LORs are used to separate the two intertwined distributions, using a dedicated image reconstruction algorithm based on Expectation Maximization (EM). However, this approach is suboptimal as it combines high-statistics data (radiotracers A and B), with low-statistics (radiotracer B) to create separate images of radiotracers A and B. We hypothesize that from the performance of DIPET could be improved if an independent estimate of radiotracer A distribution is available by using staggered injections method. Here we investigate this hypothesis by developing and testing an EM-based algorithm for image reconstruction of such data. Our algorithm is general, i.e. can reconstruct staggered data, positron and HE gamma data or a combination of both. Reconstruction of DIPET data obtained from Monte-Carlo simulations shows that the combined method provides the best results in terms of separation of images corresponding to radiotracers A and B. Our EM algorithm provides not only good image separation for the combined method but also when only staggered injections or only prompt gamma data are used.