Publicly available framework for simulating and experimentally validating clinical PET systems

Teaghan B. O'Briain*, Carlos Uribe, Ioannis Sechopoulos, Christian Michel, Magdalena Bazalova-Carter

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Background: Monte Carlo (MC) simulations are a powerful tool to model medical imaging systems. However, before simulations can be considered as the ground truth, they have to be validated with experiments. Purpose: To provide a pipeline that models a clinical PET/CT system using MC simulations after extensively validating the results against experimental measurements. Methods: A clinical four-ring PET imaging system was modelled using GATE (v. 9.0). To validate the simulations, PET images were acquired of a cylindrical phantom, point source, and image quality phantom with the modelled system and the simulations of the experimental procedures. For the purpose of validating the quantification capabilities and image quality provided by the simulation pipeline, the simulations were compared against the measurements in terms of their count rates and sensitivity as well as their image uniformity, resolution, recovery coefficients, coefficients of variation, contrast, and background variability. Results: When compared to the measured data, the number of true detections in the MC simulations was within 5%. The scatter fraction was found to be (30.0 ± 2.2)% and (28.8 ± 1.7)% in the measured and simulated scans, respectively. Analyzing the measured and simulated sinograms, the sensitivities were found to be 8.2 cps/kBq and 7.8 cps/kBq, respectively. The fraction of random coincidences were 19% in the measured data and 25% in the simulation. When calculating the image uniformity within the axial slices, the measured image exhibited a uniformity of (0.015 ± 0.005), while the simulated image had a uniformity of (0.029 ± 0.011). In the axial direction, the uniformity was measured to be (0.024 ± 0.006) and (0.040 ± 0.015) for the measured and simulated data, respectively. Comparing the image resolution, an average percentage difference of 2.9% was found between the measurements and simulations. The recovery coefficients calculated in both the measured and simulated images were found to be within the EARL ranges, except for that of the simulation of the smallest sphere. The coefficients of variation for the measured and simulated images were found to be 12% and 13%, respectively. Lastly, the background variability was consistent between the measurements and simulations, while the average percentage difference in the sphere contrasts was found to be 8.8%. Conclusion: The clinical PET/CT system was modeled and validated to provide a simulation pipeline for the community. The pipeline and the validation procedures have been made available ( This article is protected by copyright. All rights reserved.

Original languageEnglish
Pages (from-to)1549-1559
JournalMedical physics
Issue number3
Early online date10 Oct 2022
Publication statusPublished - Mar 2023


  • Monte Carlo
  • PET imaging
  • phantoms


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