Maximum likelihood estimation yields accurate line-of-response assignment for positron + prompt gamma ray events in...

For accurate disease characterization using positron emission tomography (PET), it is desirable to image multiple radiotracers in a single scan. Conventional PET methods cannot do this due to the indistinguishable annihilation photons produced by different radiotracers. One approach is to label one radiotracer with a positron+prompt-gamma (β+-γ) isotope producing triple coincidences, and another with a pure positron-emitting (β+) isotope producing double coincidences. However,β+-γemitters present challenges in correctly identifying the two annihilation photons, or equivalently, assigning the correct line-of-response (LOR) to triple-photon coincidence events. Here, we propose a maximum likelihood estimation (MLE) framework leveraging spatial, timing, and energy information to determine the most probable LOR. Simulation studies validated the method: simulations showed over 96% and 94% accuracy for LOR assignment ofβ+-γemitters22Na and124I point sources, respectively. Furthermore, simulated phantom imaging of22Na or124I distributions alongside aβ+emitter demonstrated that MLE LOR assignment achieved comparable image quality-measured by contrast recovery coefficient and cross-talk ratio-to benchmark methods, where the prompt gamma was identified using an energy threshold (⩾650keV) for22Na and as the highest-energy photon for124I.