Photopeak detection efficiency of thin LSO scintillators for positron emission tomography

Eric S. Harmon; Michael O. Thompson; C. Ross Schmidtlein; Andrzej Krol

doi:10.1117/12.2584837

15 February 2021 Photopeak detection efficiency of thin LSO scintillators for positron emission tomography

Eric S. Harmon, Michael O. Thompson, C. Ross Schmidtlein, Andrzej Krol

Proceedings Volume 11600, Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging; 116000B (2021) https://doi.org/10.1117/12.2584837
Event: SPIE Medical Imaging, 2021, Online Only

Abstract

There is a need to lower mass of scintillators in PET imagers. However, the tradeoff between scintillator thickness and axial field of view is not obvious, particularly if the total mass of the scintillator is a limitation. In this work, we developed fast analytical methods to assess performance of PET as a function of scintillator thickness. Calculation of the photopeak detection efficiency (PDE) is complicated by the fact that most incident 511 keV gamma rays first undergo Compton scattering in the scintillator resulting in a partial deposition of energy, as well as the production of a lower energy secondary gamma ray. The PDE is dependent on scintillator geometry and source position and must be recalculated when either changes. We compare Monte Carlo and our analytical lower and upper bound estimation of PDE for thin slab LSO scintillators as a function of its thickness assuming normal incidence. We show that that our analytical method achieves excellent agreement with the results obtained by time-consuming Monte Carlo approach. This is important because application of our fast method enables preliminary system optimization prior to time-consuming, complex Monte Carlo modeling.

Conference Presentation

Citation Download Citation

Eric S. Harmon, Michael O. Thompson, C. Ross Schmidtlein, and Andrzej Krol "Photopeak detection efficiency of thin LSO scintillators for positron emission tomography", Proc. SPIE 11600, Medical Imaging 2021: Biomedical Applications in Molecular, Structural, and Functional Imaging, 116000B (15 February 2021); https://doi.org/10.1117/12.2584837

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