Issue |
E3S Web Conf.
Volume 601, 2025
The 3rd International Conference on Energy and Green Computing (ICEGC’2024)
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Article Number | 00089 | |
Number of page(s) | 10 | |
DOI | https://doi.org/10.1051/e3sconf/202560100089 | |
Published online | 16 January 2025 |
A Monte Carlo simulation study of the impact of increasing the axial field of view on PET scanner sensitivity with various scintillating crystals
1 Hassan First University of Settat, High Institute of Health Sciences, Laboratory of Health Sciences and Technologies, Settat, Morocco
2 Electrical and Computer Engineering, Texas A&M University at Qatar, Doha, 23874, Qatar
* Corresponding author: a.elouaridi@uhp.ac.ma
This study addresses sensitivity performance, a pivotal parameter of Positron Emission Tomography (PET) imaging, which measures the system’s ability to detect and precisely measure radiotracer signals. It primarily depends on the scintillation material and the system’s axial field of view (AFOV). Enhancing this performance can significantly increase overall system performance and clinical practice. This research evaluates the sensitivity of a simulated PET model based on different scintillation materials and extended AFOV values, following the NEMA NU 2-2018 protocol. A standard PET system model with an AFOV of 15.9 cm was developed using the GATE Monte Carlo simulation toolkit (v9.2), along with detailed modelling of the NEMA NU 2-2018 sensitivity phantom. Simulations examined six scintillation materials (BGO, GSO, LSO, LYSO, LuAP, and NaI) across AFOV sizes from 15.9 cm to 79.5 cm. Results showed a substantial increase in sensitivity with AFOV extension, following a quadratic relationship. BGO, LuAP, and LSO crystals demonstrated notable performance enhancements, while LYSO showed acceptable results. This study underscores the potential of AFOV extension and high-performance scintillation crystals to enhance sensitivity in PET scanners, thereby improving imaging quality and potentially advancing clinical practice.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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