Historically, positron emission tomography (PET) systems have been based on scintillation crystals coupled to photomultipliers tubes (PMTs). However, the limited quantum efficiency, bulkiness, and relatively high cost per unit surface area of PMTs, along with the growth of new applications for PET, offers opportunities for other photodetectors. Among these, small-animal scanners, hybrid PET/MRI systems, and incorporation of time-of-flight information are of particular interest and require low-cost, compact, fast, and magnetic field compatible photodetectors. With high quantum efficiency and compact structure, avalanche photodiodes (APDs) overcome several of the drawbacks of PMTs, but this is offset by degraded signal-to-noise and timing properties. Silicon photomultipliers (SiPMs) offer an alternative solution, combining many of the advantages of PMTs and APDs. They have high gain, excellent timing properties and are insensitive to magnetic fields. At the present time, SiPM technology is rapidly developing and therefore an investigation into optimal design and operating conditions is underway together with detailed characterization of SiPM-based PET detectors. Published data are extremely promising and show good energy and timing resolution, as well as the ability to decode small scintillator arrays. SiPMs clearly have the potential to be the photodetector of choice for some, or even perhaps most, PET systems.

Built on top of the Geant4 toolkit, GATE is collaboratively developed for more than 15 years to design Monte Carlo simulations of nuclear-based imaging systems. It is, in particular, used by researchers and industrials to design, optimize, understand and create innovative emission tomography systems. In this paper, we reviewed the recent developments that have been proposed to simulate modern detectors and provide a comprehensive report on imaging systems that have been simulated and evaluated in GATE. Additionally, some methodological developments that are not specific for imaging but that can improve detector modeling and provide computation time gains, such as Variance Reduction Techniques and Artificial Intelligence integration, are described and discussed.

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.

Positron emission tomography (PET) plays an increasingly important role in research and clinical applications, catalysed by remarkable technical advances and a growing appreciation of the need for reliable, sensitive biomarkers of human function in health and disease. Over the last 30 years, a large amount of the physics and engineering effort in PET has been motivated by the dominant clinical application during that period, oncology. This has led to important developments such as PET/CT, whole-body PET, 3D PET, accelerated statistical image reconstruction, and time-of-flight PET. Despite impressive improvements in image quality as a result of these advances, the emphasis on static, semi-quantitative ‘hot spot’ imaging for oncologic applications has meant that the capability of PET to quantify biologically relevant parameters based on tracer kinetics has not been fully exploited. More recent advances, such as PET/MR and total-body PET, have opened up the ability to address a vast range of new research questions, from which a future expansion of applications and radiotracers appears highly likely. Many of these new applications and tracers will, at least initially, require quantitative analyses that more fully exploit the exquisite sensitivity of PET and the tracer principle on which it is based. It is also expected that they will require more sophisticated quantitative analysis methods than those that are currently available. At the same time, artificial intelligence is revolutionizing data analysis and impacting the relationship between the statistical quality of the acquired data and the information we can extract from the data. In this roadmap, leaders of the key sub-disciplines of the field identify the challenges and opportunities to be addressed over the next ten years that will enable PET to realise its full quantitative potential, initially in research laboratories and, ultimately, in clinical practice.

In the development of positron emission tomography (PET) detectors, understanding and optimizing scintillator light collection is critical for achieving high performance, particularly when the design incorporates depth-of-interaction (DOI) encoding or time-of-flight information. Monte-Carlo simulations play an important role in guiding research in detector designs and popular software such as GATE now include models of light transport in scintillators. Although current simulation toolkits are able to provide accurate models of perfectly polished surfaces, they do not successfully predict light output for other surface finishes, for example those often used in DOI-encoding detectors. The lack of accuracy of those models mainly originates from a simplified description of rough surfaces as an ensemble of micro-facets determined by the distribution of their normal, typically a gaussian distribution. The user can specify the standard deviation of this distribution, but this parameter does not provide a full description of the surface reflectance properties. We propose a different approach based on 3D measurements of the surface using atomic force microscopy. Polished and rough (unpolished) crystals were scanned to compute the surface reflectance properties. The angular distributions of reflectance and reflected rays were computed and stored in look-up tables (LUTs). The LUTs account for the effect of incidence angle and were integrated in a light transport model. Crystals of different sizes were simulated with and without reflector. The simulated maximum light output and the light output as a function of DOI showed very good agreement with experimental characterization of the crystals, indicating that our approach provides an accurate model of polished and rough surfaces and could be used to predict light collection in scintillators. This model is based on a true 3D representation of the surface, makes no assumption about the surface and provides insight on the optical behaviour of rough crystals that can play a critical role in optimizing the design of PET detectors. This approach is also compatible with existing simulation toolkits and next steps include the implementation in GATE.

Accurately modeling the light transport in scintillation detectors is essential to design new detectors for nuclear medicine or high energy physics. Optical models implemented in software such as Geant4 and GATE suffer from important limitations that we addressed by implementing a new approach in which the crystal reflectance was computed from 3D surface measurements. The reflectance was saved in a look-up-table (LUT) then used in Monte Carlo simulation to determine the fate of optical photons. Our previous work using this approach demonstrated excellent agreement with experimental characterization of crystal light output in a limited configuration, i.e. when using no reflector. As scintillators are generally encapsulated in a reflector, it is essential to include the crystal-reflector interface in the LUT. Here we develop a new LUT computation and apply it to several reflector types. A second LUT that contains transmittance data is also saved to enable modeling of optical crosstalk. LUTs have been computed for rough and polished crystals coupled to a Lambertian (e.g. Teflon tape) or a specular reflector (e.g. ESR) using air or optical grease, and the light output was computed using a custom Monte Carlo code. 3 × 3 × 20 mm ³ lutetium oxyorthosilicate crystals were prepared using these combinations, and the light output was measured experimentally at different irradiation depths. For all reflector and surface finish combinations, the measured and simulated light output showed very good agreement. The behavior of optical photons at the interface crystal-reflector was studied using these simulations, and results highlighted the large difference in optical properties between rough and polished crystals, and Lambertian and specular reflectors. These simulations also showed how the travel path of individual scintillation photons was affected by the reflector and surface finish. The ultimate goal of this work is to implement this model in Geant4 and GATE, and provide a database of scintillators combined with a variety of reflectors.