Normalization Correction for Inter-Detector Scatter Enhanced Positron Emission Tomography

This technology is a correction calculation that uses inter-detector scatter (IDS) events collected by a Positron Emission Tomography (PET) scanner to improve PET image quality. This calculation increases the system’s sensitivity and can be used for preclinical and clinical applications, such as the detection of solid tumors.  

Researchers

Shivang Dave / Vicente Parot / Eduardo Lage / Joaquin Herraiz

Technology Areas: Computer Science: Bioinformatics / Sensing & Imaging: Imaging
Impact Areas: Healthy Living

  • normalization correction for multiple-detection enhanced emission tomography
    United States of America | Granted | 10,502,846

Technology

This technology is a strategy for normalization correction for IDS events that have been sorted by any method. The correction, determined during a calibration step, can then be applied to the coincidence data set for PET scans.In calibration, a radiation source is uniformly exposed to all detector pairs in a PET scanner. Double coincidences and IDS coincidences are acquired until enough measurements have been collected to achieve statistical significance in both data sets. IDS events are then sorted and represented, for example, in an LOR histogram. The number of IDS events sorted to a particular LOR is then divided by the average number of IDS events for all of the LORs in the scanner to calculate IDS normalization values for each LOR. In contrast to other normalization methods, which only generate normalization value for double coincidences, this method provides a second set of normalization values for IDS events. During the PET scan, sets of double coincidences and IDS coincidences are collected and stored as separate LOR histogram. The corresponding normalization (from calibration) will be applied independently to each data set. After correction, the data sets are added together to provide normalized information for accurate image reconstruction.  

Problem Addressed

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 is a specific correction for normalization of IDS events and provides the basis to calculate that correction for any event-sorting strategy and processing scheme to apply the correction to generate more accurate PET images.   

Advantages

  • Appropriately corrects and normalizes double coincidences and IDS coincidences generated by a PET scanner
  • Improves sensitivity of PET scans, which will improve diagnostics and reduce the amount of radioactive tracer required

Publications

"Simulation of Triple Coincidences in PET." Physics in Medicine & Biology 60, no. 1 (January 7, 2015): 117-136.

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