Sensitivity booster for DOI-PET by utilizing Compton scattering events between detector blocks

In a conventional PET scanner, coincidence events are measured with the limited energy window for detection of photoelectric events in order to reject Compton scatter events that occur in a patient, but Compton scatter events caused in detector crystals are also rejected. Scatter events within the patient cause scatter coincidences, but inter crystal scattering (ICS) events have useful information for determining an activity distribution. Some researchers have reported the feasibility of PET scanners based on a Compton camera for tracing ICS into the detector. However, these detectors require expensive semiconductor detectors for high-energy resolution. In the Anger-type block detector, single photons interacting with multiple detectors can be obtained for each interacting position and complete information can be gotten just as for photoelectric events in the single detector. ICS events in the single detector have been used to get coincidence, but single photons interacting with multiple detectors have not been used to get coincidence actively. In this work, we developed a new method to improve sensitivity using Compton kinetics in a DOI-PET scanner. The proposed method promises to improve the sensitivity using coincidence events of single photons interacting with multiple detectors, which are identified as the first interaction (FI). FI estimation accuracy can be improved to determine FI validity from the correlation between Compton scattering angles calculated on energy and coincidence LOR. We simulated animal PET scanner consisting of 42 detectors. Each detector block consisted of three types of scintillator crystals (LSO, GSO, GAGG). After the simulation, coincidence events are added as information for several DOI resolutions. From the simulation results, we concluded the proposed method promises to improve the sensitivity considerably as effective Z of the scintillator is low. Also, we showed that FI estimate accuracy is improved, as DOI resolution is high.