Simultaneous Multi-Isotope PET: A Computational Framework for Line of Response (LOR) Identification
PET imaging using non-pure positron emitters as radiotracers can be used to simultaneously image distributions of different molecules. We study the use of radionuclides that emit a high energy gamma in conjunction with positrons, producing triple coincidences. A given triple coincidence could be a t...
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Published in | 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) pp. 1 - 2 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
31.10.2020
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Subjects | |
Online Access | Get full text |
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Summary: | PET imaging using non-pure positron emitters as radiotracers can be used to simultaneously image distributions of different molecules. We study the use of radionuclides that emit a high energy gamma in conjunction with positrons, producing triple coincidences. A given triple coincidence could be a true coincidence corresponding to two annihilation photons and a high energy gamma emitted from the same source, or it could be a random triple coincidence arising from different sources. We develop an algorithm to identify true triple coincidences and the correct line of response (LOR) within these coincidences. We employ a probabilistic approach to the identification problem through synthesizing geometric, spatial, energy, and temporal information. These criteria are used to create a joint MLE representing the probability that a given set of particles is a true triple coincidence and contains a valid LOR. This approach allows for more accurate identification of true triple coincidences as opposed to only using a high energy threshold. For proof of concept image reconstruction, we use GATE Monte Carlo simulations. With a simple phantom composed of three spheres, we correctly identified 99% of true triple coincidences and 97% of true double coincidences for image reconstruction. Further correction factors should be implemented to obtain more accurate images. |
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ISSN: | 2577-0829 |
DOI: | 10.1109/NSS/MIC42677.2020.9507891 |