A validated Geant4 model of a whole-body PET scanner with four-layer DOI detectors

Abstract

The simulation model emulates the behaviour of the unique depth of interaction 26 sensing capability of the scanner without needing to directly simulate optical photon 27 transport in the scintillator and photodetector modules. The model was validated by 28 evaluating and comparing performance metrics from the NEMA NU 2-2012 protocol 29 on both the simulated and physical scanner, including spatial resolution, sensitivity, 30 scatter fraction, noise equivalent count rates and image quality. The results show 31 that the average sensitivities of the scanner in the field-of-view were 5.9 cps/kBq and 6.0 cps/kBq for experiment and simulation, respectively. The average spatial resolutions measured for point sources placed at several radial offsets were 5.2±0.7 mm 34 and 5.0±0.8 mm FWHM for experiment and simulation, respectively. The peak NECR 35 was 22.9 kcps at 7.4 kBq/mL for the experiment, while the NECR obtained via 36 simulation was 23.3 kcps at the same activity. The scatter fractions were 44% and 37 41.3% for the experiment and simulation, respectively. Contrast recovery estimates performed in different regions of a simulated image quality phantom matched the 39 experimental results with an average error of -8.7% and +3.4% for hot and cold 40 lesions, respectively. The results demonstrate that the developed Geant4 model reliably 41 reproduces the key NEMA NU 2-2012 performance metrics evaluated on the prototype 42 PET scanner. A simplified version of the model is included as an advanced example 43 in Geant4 version 10.5. 44 1. Introduction 45 Positron emission tomography (PET) is a non-invasive nuclear medicine technique that 46 is used for the clinical diagnosis of cancer and the study of a range of diseases and 47 biochemical processes in living organisms. The quality of reconstructed PET images 48 is limited by the amount of activity in the object, the duration of the scan, and 49 the performance of the PET scanner -which, in turn, depends on its constituent 50 components, such as the type and size of scintillator material used, the detection efficiency, geometrical arrangement of the detectors and the readout electronics. In 52 addition, the choice of parameters for data acquisition (such as acquisition time, energy 53 window, and coincidence timing window) and reconstruction (choice of algorithm, 54 number of subsets, number of iterations etc.) also affect the quality of the reconstructed 55 image. Experimental optimisation of these parameters is very expensive in terms of time, 56 materials and labour.57 Monte Carlo simulation provides a versatile and low-cost alternative to 58 experimental optimisation of imaging parameters. High-fidelity simulations of existing 59 physical scanners, validated for correctness against experimental measurements, enable 60 the development of new image reconstruction algorithms, segmentation methods and 61 optimised imaging protocols for quantitative evaluation of radiotracer uptake metrics.

Design and simulation of a semiconductor detector-based Compton imaging system with efficiency analysis

“…Single-photon emission computed tomography (SPECT) and the Compton imaging system are two well-known examples of single-photon imaging of radioactive nuclei that decay by emitting a gamma-ray [1,2]. Another method, positron emission tomography (PET), uses positron-emitting radioisotopes as radioactive material [3].…”

Design and simulation of a semiconductor detector-based Compton imaging system with efficiency analysis

“…Single-photon emission computed tomography (SPECT) and Compton imaging systems are two well-known examples of single-photon imaging of radioactive nuclei that decay by emitting gamma rays [1,2]. Positron emission tomography (PET) uses positron-emitting radioisotopes as radioactive materials [3].…”

X-ray-Fluorescence Imaging for In Vivo Detection of Gold-Nanoparticle-Labeled Immune Cells: A GEANT4 Based Feasibility Study

“…Due to the high cost and very limited access to synchrotrons, numerical feasibility studies for XFI in human-sized objects are needed to optimize the design of practical experiments. For medical purposes, different Monte Carlo-based tools are available, for example PENELOPE, MCNP, and PENFAST are used for dosimetry in radiotherapy, or GATE/GEANT4 and FLUKA are used for medical physics in general [19][20][21]. For the research of radiotherapy with high energy photons, PENH or FLUKA can be used [19,22].…”

“…We decided for the commonly used GEANT4 toolkit because it offers high flexibility and supports the modeling of complex geometries [23,24]. Numerous studies evaluated the accuracy of GEANT4 simulations in comparison to practical measurements and other Monte Carlo codes established in medical physics, agreeing that it is suitable for medical research [21,23,25,26]. The practical experience of our team with measurements of reference targets and dosimetry meets the results of these studies, such that the simulation error of Geant4 lies within reasonable limits, e.g., below 6 to 10% [21,23,25].…”

“…Numerous studies evaluated the accuracy of GEANT4 simulations in comparison to practical measurements and other Monte Carlo codes established in medical physics, agreeing that it is suitable for medical research [21,23,25,26]. The practical experience of our team with measurements of reference targets and dosimetry meets the results of these studies, such that the simulation error of Geant4 lies within reasonable limits, e.g., below 6 to 10% [21,23,25]. Furthermore, several GEANT4 simulation studies showed that the sensitivity of XFI in human-sized objects increased in the past decade [13,14,27].…”