Optimizing positron emission tomography for accurate plant imaging using Monte Carlo simulations to correct positron range effects
Abstract Positron Emission Tomography (PET) is a valuable tool for plant imaging, but its accuracy can be compromised by positron range effects. This study improves PET accuracy using the GATE Monte Carlo simulation tool to estimate and correct these effects. The GATE model was validated for the Sie...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-95670-y |
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| Summary: | Abstract Positron Emission Tomography (PET) is a valuable tool for plant imaging, but its accuracy can be compromised by positron range effects. This study improves PET accuracy using the GATE Monte Carlo simulation tool to estimate and correct these effects. The GATE model was validated for the Siemens Biograph Vision system using the NEMA NU 2-2018 protocol, showing alignment with experimental data. Deviations were within 9% for sensitivity and 3% for peak Noise Equivalent Count Rate (NECR). Different isotopes (18F, 11C, 15O, and 30P) and plant phantom properties were analyzed for their impact on reconstructed images. A sixfold enhancement was observed for 15O and a threefold improvement for 11C when a magnetic field was applied to the plant phantom. Our findings suggest that integrating PET with magnetic resonance imaging can help address Positron range effects in plant imaging. This study provides valuable insights into PET imaging and offers refined methodologies for clinical and plant-centric research. Our research validates the use of GATE Monte Carlo simulation for Biograph Vision and advances our understanding of Positron range phenomena and potential mitigation strategies for precise PET Plant imaging. |
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| ISSN: | 2045-2322 |