Validation of a computational chain from PET Monte Carlo simulations to reconstructed images

PET digitization chain for Monte Carlo simulation in GATE

Objective. We introduce a versatile methodology for the accurate modelling of PET imaging systems via Monte Carlo simulations, using the Geant4 application for tomographic emission (GATE) platform. Accurate Monte Carlo modelling involves the incorporation of a complete analytical signal processing chain, called the digitizer in GATE, to emulate the different count rates encountered in actual positron emission tomography (PET) systems.Approach. The proposed approach consists of two steps: (1) modelling the digitizer to replicate the detection chain of real systems, covering all available parameters, whether publicly accessible or supplied by manufacturers; (2) estimating the remaining parameters, i.e. background noise level, detection efficiency, and pile-up, using optimisation techniques based on experimental single and prompt event rates. We show that this two-step optimisation reproduces the other experimental count rates (true, scatter, and random), without the need for additional adjustments. This method has been applied and validated with experimental data derived from the NEMA count losses test for three state-of-the-art SiPM-based time-of-flight (TOF)-PET systems: Philips Vereos, Siemens Biograph Vision 600 and GE Discovery MI 4-ring.Main results. The results show good agreement between experiments and simulations for the three PET systems, with absolute relative discrepancies below 3%, 6%, 6%, 7% and 12% for prompt, random, true, scatter and noise equivalent count rates, respectively, within the 0-10 kBq·ml-1activity concentration range typically observed in whole-body18F scans.Significance. Overall, the proposed digitizer optimisation method was shown to be effective in reproducing count rates and NECR for three of the latest generation SiPM-based TOF-PET imaging systems. The proposed methodology could be applied to other PET scanners.

Validation of a discovery MI 4-ring model according to the NEMA NU 2-2018 standards: from Monte Carlo simulations to clinical-like reconstructions

BACKGROUND

We propose a comprehensive evaluation of a Discovery MI 4-ring (DMI) model, using a Monte Carlo simulator (GATE) and a clinical reconstruction software package (PET toolbox). The following performance characteristics were compared with actual measurements according to NEMA NU 2-2018 guidelines: system sensitivity, count losses and scatter fraction (SF), coincidence time resolution (CTR), spatial resolution (SR), and image quality (IQ). For SR and IQ tests, reconstruction of time-of-flight (TOF) simulated data was performed using the manufacturer's reconstruction software.

RESULTS

Simulated prompt, random, true, scatter and noise equivalent count rates closely matched the experimental rates with maximum relative differences of 1.6%, 5.3%, 7.8%, 6.6%, and 16.5%, respectively, in a clinical range of less than 10 kBq/mL. A 3.6% maximum relative difference was found between experimental and simulated sensitivities. The simulated spatial resolution was better than the experimental one. Simulated image quality metrics were relatively close to the experimental results.

CONCLUSIONS

The current model is able to reproduce the behaviour of the DMI count rates in the clinical range and generate clinical-like images with a reasonable match in terms of contrast and noise.

Monte Carlo investigation of PET [68Ga]Ga-DOTA-TOC activity-administration protocols for consistent image quality

One example of a PET exam that suffers from noise problems is [68Ga]Ga-DOTA-TOC, where patients are generally administered between 100 and 200 MBq [68Ga]Ga-DOTA-TOC, irrespective of size. However, a fixed activity can result in low signal-to-noise ratios (SNRs) in larger patients. This study aimed to evaluate the impact on image quality with respect to injected activity and patient habitus through Monte Carlo (MC) simulation. Eight anthropomorphic computer phantoms with body mass indices (BMIs) between 19 kg/m2 and 38 kg/m2 and tumours distributed in the liver were simulated using the MC software Gate v8.2 with an activity distribution defined according to [68Ga]Ga-DOTA-TOC standardised uptake values. Three activity-administration protocols were simulated: (i) with a fixed activity of 100 MBq, (ii) with the activity scaled by 2 MBq/kg, and (iii) with the activity scaled by a body size-dependent power-function based on the SNR obtained with (ii). BMI, weight, body surface area, and abdominal circumference were evaluated body size parameters. Images were reconstructed with the CASToR software and evaluated for background SNR and lesion contrast-to-noise ratio (CNR). Large SNR variabilities were obtained with protocols (i) and (ii), while (iii) generated good consistency. Several tumours failed to reach a CNR of 5 for large phantoms with protocol (i), but the CNR was generally improved by (ii) and (iii). An activity scaled by patient habitus generate better image quality consistency, which increases the likelihood that patients receive a similar standard of care.

The OpenGATE ecosystem for Monte Carlo simulation in medical physics

This paper reviews the ecosystem of GATE, an open-source Monte Carlo toolkit for medical physics. Based on the shoulders of Geant4, the principal modules (geometry, physics, scorers) are described with brief descriptions of some key concepts (Volume, Actors, Digitizer). The main source code repositories are detailed together with the automated compilation and tests processes (Continuous Integration). We then described how the OpenGATE collaboration managed the collaborative development of about one hundred developers during almost 20 years. The impact of GATE on medical physics and cancer research is then summarized, and examples of a few key applications are given. Finally, future development perspectives are indicated.