Modelling the transport of optical photons in scintillation detectors for diagnostic and radiotherapy imaging

Roncali, Emilie; Mosleh-Shirazi, Mohammad Amin; Badano, Aldo

doi:10.1088/1361-6560/aa8b31

Cited by 28 publications

(16 citation statements)

References 135 publications

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“…The PTS describes this quantity and is a complex function depending on the depth of interaction, hence, if the crystal is irradiated head-on or on the side etc. Several groups have worked on simulating the light transport in scintillators, either via Monte-Carlo simulations or by analytical considerations (Gundacker et al 2013, Cates et al 2015, Roncali et al 2017.…”

Section: Sensing Scintillation Light With Sipmsmentioning

confidence: 99%

The silicon photomultiplier: fundamentals and applications of a modern solid-state photon detector

2020

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The silicon photomultiplier (SiPM) is an established device of choice for a variety of applications, e.g. in time of flight positron emission tomography (TOF-PET), lifetime fluorescence spectroscopy, distance measurements in LIDAR applications, astrophysics, quantum-cryptography and related applications as well as in high energy physics (HEP).To fully utilize the exceptional performances of the SiPM, in particular its sensitivity down to single photon detection, the dynamic range and its intrinsically fast timing properties, a qualitative description and understanding of the main SiPM parameters and properties is necessary. These analyses consider the structure and the electrical model of a single photon avalanche diode (SPAD) and the integration in an array of SPADs, i.e. the SiPM. The discussion will include the front-end readout and the comparison between analog-SiPMs, where the array of SPADs is connected in parallel, and the digital SiPM, where each SPAD is read out and digitized by its own electronic channel.For several applications a further complete phenomenological view on SiPMs is necessary, defining several SiPM intrinsic parameters, i.e. gain fluctuation, afterpulsing, excess noise, dark count rate, prompt and delayed optical crosstalk, single photon time resolution (SPTR), photon detection effieciency (PDE) etc. These qualities of SiPMs influence directly and indirectly the time and energy resolution, for example in PET and HEP. This complete overview of all parameters allows one to draw solid conclusions on how best performances can be achieved for the various needs of the different applications.

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Section: Sensing Scintillation Light With Sipmsmentioning

confidence: 99%

The silicon photomultiplier: fundamentals and applications of a modern solid-state photon detector

2020

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“…There are many publications on how these factors affect energy resolution, but these only address h ot and, therefore, cannot be extrapolated straightforwardly to timing performance. Understanding how the crystal geometry, surface treatment, and reflectors affect the CRT requires time-resolved simulations (Yang et al 2013, Ter Weele et al 2015c, Roncali et al 2017 and experiments (Gundacker et al 2014, Berg et al 2015, Ter Weele et al 2015b, Nemallapudi et al 2016b.…”

Section: Optimization Of Optical Transfermentioning

confidence: 99%

Physics and technology of time-of-flight PET detectors

Schaart

2021

Phys. Med. Biol.

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The imaging performance of clinical positron emission tomography (PET) systems has evolved impressively during the last ∼15 years. A main driver of these improvements has been the introduction of time-of-flight (TOF) detectors with high spatial resolution and detection efficiency, initially based on photomultiplier tubes, later silicon photomultipliers. This review aims to offer insight into the challenges encountered, solutions developed, and lessons learned during this period. Detectors based on fast, bright, inorganic scintillators form the scope of this work, as these are used in essentially all clinical TOF-PET systems today. The improvement of the coincidence resolving time (CRT) requires the optimization of the entire detection chain and a sound understanding of the physics involved facilitates this effort greatly. Therefore, the theory of scintillation detector timing is reviewed first. Once the fundamentals have been set forth, the principal detector components are discussed: the scintillator and the photosensor. The parameters that influence the CRT are examined and the history, state-of-the-art, and ongoing developments are reviewed. Finally, the interplay between these components and the optimization of the overall detector design are considered. Based on the knowledge gained to date, it appears feasible to improve the CRT from the values of 200-400 ps achieved by current state-of-the-art TOF-PET systems to about 100 ps or less, even though this may require the implementation of advanced methods such as time resolution recovery. At the same time, it appears unlikely that a system-level CRT in the order of ∼10 ps can be reached with conventional scintillation detectors. Such a CRT could eliminate the need for conventional tomographic image reconstruction and a search for new approaches to timestamp annihilation photons with ultra-high precision is therefore warranted. While the focus of this review is on timing performance, it attempts to approach the topic from a clinically driven perspective, i.e. bearing in mind that the ultimate goal is to optimize the value of PET in research and (personalized) medicine. Selected abbreviations and symbols BSR Backside readout C d Diode capacitance CFD Constant-fraction discriminator CRLB Cramér-Rao lower bound CRT Coincidence resolving time C q Parallel capacitance of quench resistor DCR Dark count rate DOI Depth of interaction dSiPM Digital silicon photomultiplier DSR Dual-sided readout

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“…Optical Monte Carlo simulations are extensively used to understand, optimize, and design crystal-based gamma detectors in nuclear medicine and high-energy physics (Staelens et al 2003, Roncali et al 2017a, Ghabrial et al 2018. In such detectors, a detailed description of the light transport in the crystal and the light collection by the photodetector are needed to optimize their energy, spatial, and timing performance (Bauer et al 2009, Ariño-Estrada et al 2020, He et al 2022.…”

Section: Introductionmentioning

confidence: 99%

A generative adversarial network to speed up optical Monte Carlo simulations

Trigila

Srikanth

Roncali

2023

Mach. Learn.: Sci. Technol.

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Detailed simulation of optical photon transport and detection in radiation detectors is often used for crystal-based gamma detector optimization. However, the time and memory burden associated with the track-wise approach to particle transport and detection in commonly used Monte Carlo codes makes optical simulation prohibitive at a system level, where hundreds to thousands of scintillators must be modeled. Consequently, current large system simulations do not include detailed detector models to analyze the potential performance gain with new radiation detector technologies. Generative Adversarial Networks are explored as a tool to speed up the optical simulation of crystal-based detectors. These networks learn training datasets made of high-dimensional data distributions. Once trained, the resulting model can produce distributions belonging to the training data probability distribution. In this work, we present the proof of concept of using a Generative Adversarial Network to enable high-fidelity optical simulations of nuclear medicine systems, mitigating their computational complexity. The architecture of the first network version and high-fidelity training dataset is discussed. The latter is generated through accurate optical simulation with GATE/Geant4, and contains the position, direction, and energy distributions of the optical photons emitted by 511 keV gamma rays in bismuth germanate and detected on the photodetector face. We compare the GAN and simulation-generated distributions in terms of similarity using the Jensen-Shannon distance. Excellent agreement was found with similarity values higher than 93.5% for all distributions. Moreover, the GAN speeded the optical photon distribution generation by up to 2 orders of magnitude. These very promising results have the potential to drastically change the use of nuclear imaging system optical simulations by enabling high-fidelity system-level simulations in reasonable computation times. The ultimate is to integrate the GAN within GATE/Geant4 since numerous applications (large detectors, bright scintillators, Cerenkov-based timing positron emission tomography) can benefit from these improvements.

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Modelling the transport of optical photons in scintillation detectors for diagnostic and radiotherapy imaging

Cited by 28 publications

References 135 publications

The silicon photomultiplier: fundamentals and applications of a modern solid-state photon detector

The silicon photomultiplier: fundamentals and applications of a modern solid-state photon detector

Physics and technology of time-of-flight PET detectors

A generative adversarial network to speed up optical Monte Carlo simulations

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