Positron Emission Tomography (PET) scans are frequently used in the early detection of solid tumors, as well as for evaluating heart disease and multiple neurological disorders. In PET, the patient is administered a radioactive tracer that accumulates in metabolically active tissues, such as tumors. The radioactive tracer emits photons which are detected by the scanner. Specifically, PET scanners are optimized to detect double coincidences, which occur when two photons emitted from the same annihilation event encounter opposite block detectors within a specific coincidence time window. Double coincidences provide valid, meaningful information.
Scattered coincidences are also detected by the PET scanner and produce distorted information that decreases the sensitivity of PET scanners. Scatter coincidences occur when at least one of the emitted photons undergoes scattering and loses a fraction of its total energy before its detection, and the event is then detected by a pair of detectors that are non-collinear with the originating annihilation. Current methods for correcting inter-detector scatter (IDS) coincidence data involve sorting a given IDS coincidence event to the appropriate line-of-response (LOR) by determining the most likely order of detection of an IDS coincidence from the initial annihilation event. The sorted IDS coincidence data set and double coincidence data set are then merged and normalized solely based on information from the double-coincidence data set. However, this approach produces artifacts in resulting PET images, thereby reducing the sensitivity of the scanner in preclinical and clinical applications.
Increasing the sensitivity of PET systems could reduce scan time and reduce the amount of radioactive compound injected to the patient to obtain similar quality images. This invention corrects and normalizes IDS information to generate more accurate PET images.