Extension of the GATE Monte-Carlo simulation package to model bioluminescence and fluorescence imaging

Quantitative Assessment on Optical Properties as a Basis for Bioluminescence Imaging: An Experimental and Numerical Approach to the Transport of Optical Photons in Phantom Materials

Bioluminescence imaging (BLI) is a widely used technique in preclinical scientific research, particularly in the development of mRNA-based medications and non-invasive tumor diagnostics. It has become an essential tool in current science. However, the current state of bioluminescence imaging is primarily qualitative, making it challenging to obtain quantitative measurements and to draw accurate conclusions. This fact is caused by the unique properties of optical photons and tissue interactions. In this paper, we propose an experimental setup and Geant4-simulations to gain a better understanding of the optical properties and processes involved in bioluminescence imaging. Our goal is to advance the field towards more quantitative measurements. We will discuss the details of our experimental setup, the data we collected, the outcomes of the Geant4-simulations, and additional information on the underlying physical processes.

Investigation of TG-43 Dosimetric Parameters for 192Ir Brachytherapy Source Using GATE Monte Carlo Code

Purpose

According to the revised Task Group number 43 recommendations, a brachytherapy source must be validated against a similar or identical source before its clinical application. The purpose of this investigation is to verify the dosimetric data of the high dose rate (HDR) BEBIG 192Ir source (Ir2.A85-2).

Materials and Methods

The HDR 192Ir encapsulated seed was simulated and its main dosimetric data were calculated using Geant4 Application for Tomographic Emission (GATE) simulation code. Cubic cells were used for the calculation of dose rate constant and radial dose function while for anisotropy function ring cells were used. DoseActors were simulated and attached to the respective cells to obtain the required data.

Results

The dose rate constant was obtained as 1.098 ± 0.003 cGy.h - 1.U - 1, differing by 1.0% from the reference value reported by Granero et al. Similarly, the calculated values for radial dose and anisotropy functions presented good agreement with the results obtained by Granero et al.

Conclusion

The results of this study suggest that the GATE Monte Carlo code is a valid toolkit for benchmarking brachytherapy sources and can be used for brachytherapy simulation-based studies and verification of brachytherapy treatment planning systems.

Monte-Carlo techniques for radiotherapy applications I: introduction and overview of the different Monte-Carlo codes

Introduction:

The dose calculation plays a crucial role in many aspects of contemporary clinical radiotherapy treatment planning process. It therefore goes without saying that the accuracy of the dose calculation is of very high importance. The gold standard for absorbed dose calculation is the Monte-Carlo algorithm.

Methods:

This first of two papers gives an overview of the main openly available and supported codes that have been widely used for radiotherapy simulations.

Results:

The paper aims to provide an overview of Monte-Carlo in the field of radiotherapy and point the reader in the right direction of work that could help them get started or develop their existing understanding and use of Monte-Carlo algorithms in their practice.

Conclusions:

It also serves as a useful companion to a curated collection of papers on Monte-Carlo that have been published in this journal.

Gold Nanoparticles-Mediated Photothermal Therapy of Pancreas Using GATE: A New Simulation Platform

This work presents the first investigation of gold nanorods (GNRs)-based photothermal therapy of the pancreas tumor using the Monte Carlo-based code implemented with Geant4 Application for Emission Tomography (GATE). The model of a human pancreas was obtained by segmenting an abdominal computed tomography (CT) scan, and its physical and chemical properties, were obtained from experimental and theoretical data. In GATE, GNRs-mediated hyperthermal therapy, simple heat diffusion as well as interstitial laser ablation were then modeled in the pancreas tumor by defining the optical parameters of this tissue when it is loaded with GNRs. Two different experimental setups on ex vivo pancreas tissue and GNRs-embedded water were devised to benchmark the developed Monte Carlo-based model for the hyperthermia in the pancreas alone and with GNRs, respectively. The influence of GNRs on heat distribution and temperature increase within the pancreas tumor was compared for two different power values (1.2 W and 2.1 W) when the tumor was exposed to 808 nm laser irradiation and with two different laser applicator diameters. Benchmark tests demonstrated the possibility of the accurate simulating of NPs-assisted thermal therapy and reproducing the experimental data with GATE software. Then, the output of the simulated GNR-mediated hyperthermia emphasized the importance of the precise evaluation of all of the parameters for optimizing the preplanning of cancer thermal therapy. Simulation results on temperature distribution in the pancreas tumor showed that the temperature enhancement caused by raising the power was increased with time in both the tumor with and without GNRs, but it was higher for the GNR-load tumor compared to tumor alone.

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.

Development of a digital zebrafish phantom and its application to dedicated small-fish PET

Objective. We are developing a small-fish positron emission tomography (PET) scanner dedicated to small aquatic animals relevant for biomedical and biological research, e.g. zebrafish. We plan to use Monte Carlo simulations to optimize its configuration and the required water-filled imaging chambers. Our objectives were: (1) to create a digital 3D zebrafish phantom using conventional micro-CT, (2) include the phantom into a simulated PET environment based on the framework GATE, and (3) investigate the effects of the water environment on the reconstructed images. Approach. To create the phantom, we performed ex vivo measurements of zebrafish specimen using a tabletop micro-CT and compared three methods to fixate the specimen. From segmented micro-CT images we created digital emission and transmission phantoms which were incorporated in GATE via tessellated volumes. Two chamber sizes were considered. For reference, a simulation with the zebrafish in air was implemented. The simulated data were reconstructed using CASToR. For attenuation correction, we used the exact attenuation information or a uniform distribution (only water). Several realizations of each scenario were performed; the reconstructed images were quantitatively evaluated. Main results. Fixation in formalin led to the best soft-tissue contrast at the cost of some specimen deformation. After attenuation correction, no significant differences were found between the reconstructed images. The PET images reflected well the higher uptake simulated in the brain and heart, despite their small size and surrounding background activity; the swim bladder (no activity) was clearly identified. The simplified attenuation map, consisting only of water, slightly worsened the images. Significance. A conventional micro-CT can provide sufficient image quality to generate numerical phantoms of small fish without contrast media. Such phantoms are useful to evaluate in-silico small aquatic animal imaging concepts and develop imaging protocols. Our results support the feasibility of zebrafish PET with an aqueous environment.

A deep learning and Monte Carlo based framework for bioluminescence imaging center of mass-guided glioblastoma targeting

Objective. Bioluminescence imaging (BLI) is a valuable tool for non-invasive monitoring of glioblastoma multiforme (GBM) tumor-bearing small animals without incurring x-ray radiation burden. However, the use of this imaging modality is limited due to photon scattering and lack of spatial information. Attempts at reconstructing bioluminescence tomography (BLT) using mathematical models of light propagation show limited progress. Approach. This paper employed a different approach by using a deep convolutional neural network (CNN) to predict the tumor’s center of mass (CoM). Transfer-learning with a sizeable artificial database is employed to facilitate the training process for, the much smaller, target database including Monte Carlo (MC) simulations of real orthotopic glioblastoma models. Predicted CoM was then used to estimate a BLI-based planning target volume (bPTV), by using the CoM as the center of a sphere, encompassing the tumor. The volume of the encompassing target sphere was estimated based on the total number of photons reaching the skin surface. Main results. Results show sub-millimeter accuracy for CoM prediction with a median error of 0.59 mm. The proposed method also provides promising performance for BLI-based tumor targeting with on average 94% of the tumor inside the bPTV while keeping the average healthy tissue coverage below 10%. Significance. This work introduced a framework for developing and using a CNN for targeted radiation studies for GBM based on BLI. The framework will enable biologists to use BLI as their main image-guidance tool to target GBM tumors in rat models, avoiding delivery of high x-ray imaging dose to the animals.

Frequency-dependent optimal weighting approach for megavoltage multilayer imagers

Multi-layer imaging (MLI) devices improve the detective quantum efficiency (DQE) while maintaining the spatial resolution of conventional mega-voltage (MV) x-ray detectors for applications in radiotherapy. To date, only MLIs with identical detector layers have been explored. However, it may be possible to instead use different scintillation materials in each layer to improve the final image quality. To this end, we developed and validated a method for optimally combining the individual images from each layer of MLI devices that are built with heterogeneous layers. Two configurations were modeled within the GATE Monte Carlo package by stacking different layers of a terbium doped gadolinium oxysulfide Gd2O2S:Tb (GOS) phosphor and a LKH-5 glass scintillator. Detector response was characterized in terms of the modulation transfer function (MTF), normalized noise power spectrum (NNPS) and DQE. Spatial frequency-dependent weighting factors were then analytically derived for each layer such that the total DQE of the summed combination image would be maximized across all spatial modes. The final image is obtained as the weighted sum of the sub-images from each layer. Optimal weighting factors that maximize the DQE were found to be the quotient of MTF and NNPS of each layer in the heterogeneous MLI detector. Results validated the improvement of the DQE across the entire frequency domain. For the LKH-5 slab configuration, DQE(0) increases between 2%-3% (absolute), while the corresponding improvement for the LKH-5 pixelated configuration was 7%. The performance of the weighting method was quantitatively evaluated with respect to spatial resolution, contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of simulated planar images of phantoms at 2.5 and 6 MV. The line pair phantom acquisition exhibited a twofold increase in CNR and SNR, however MTF was degraded at spatial frequencies greater than 0.2 lp mm^-1. For the Las Vegas phantom, the weighting improved the CNR by around 30% depending on the contrast region while the SNR values are higher by a factor of 2.5. These results indicate that the imaging performance of MLI systems can be enhanced using the proposed frequency-dependent weighting scheme. The CNR and SNR of the weighted combined image are improved across all spatial scales independent of the detector combination or photon beam energy.

Laser-induced optothermal response of gold nanoparticles: From a physical viewpoint to cancer treatment application

Gold nanoparticles (GNPs)-based photothermal therapy (PTT) is a promising minimally invasive thermal therapy for the treatment of focal malignancies. Although GNPs-based PTT has been known for over two decades and GNPs possess unique properties as therapeutic agents, the delivery of a safe and effective therapy is still an open question. This review aims at providing relevant and recent information on the usage of GNPs in combination with the laser to treat cancers, pointing out the practical aspects that bear on the therapy outcome. Emphasis is given to the assessment of the GNPs' properties and the physical mechanisms underlying the laser-induced heat generation in GNPs-loaded tissues. The main techniques available for temperature measurement and the current theoretical simulation approaches predicting the therapeutic outcome are reviewed. Topical challenges in delivering safe thermal dosage are also presented with the aim to discuss the state-of-the-art and the future perspective in the field of GNPs-mediated PTT.

Detecting Differences of Fluorescent Markers Distribution in Single Cell Microscopy: Textural or Pointillist Feature Space?

We consider the detection of change in spatial distribution of fluorescent markers inside cells imaged by single cell microscopy. Such problems are important in bioimaging since the density of these markers can reflect the healthy or pathological state of cells, the spatial organization of DNA, or cell cycle stage. With the new super-resolved microscopes and associated microfluidic devices, bio-markers can be detected in single cells individually or collectively as a texture depending on the quality of the microscope impulse response. In this work, we propose, via numerical simulations, to address detection of changes in spatial density or in spatial clustering with an individual (pointillist) or collective (textural) approach by comparing their performances according to the size of the impulse response of the microscope. Pointillist approaches show good performances for small impulse response sizes only, while all textural approaches are found to overcome pointillist approaches with small as well as with large impulse response sizes. These results are validated with real fluorescence microscopy images with conventional resolution. This, a priori non-intuitive result in the perspective of the quest of super-resolution, demonstrates that, for difference detection tasks in single cell microscopy, super-resolved microscopes may not be mandatory and that lower cost, sub-resolved, microscopes can be sufficient.

Development of an embedded multimodality imaging platform for onco-pharmacology using a smart anticancer prodrug as an example

Increasingly, in vivo imaging holds a strategic position in bio-pharmaceutical innovation. We will present the implementation of an integrated multimodal imaging setup enabling the assessment of multiple, complementary parameters. The system allows the fusion of information provided by: Near infrared fluorescent biomarkers, bioluminescence (for tumor proliferation status), Photoacoustic and Ultrasound imaging. We will study representative applications to the development of a smart prodrug, delivering a highly cytotoxic chemotherapeutic agent to cancer tumors. The results realized the ability of this embedded, multimodality imaging platform to firstly detect bioluminescent and fluorescent signals, and secondly, record ultrasound and photoacoustic data from the same animal. This study demonstrated that the prodrug was effective in three different models of hypoxia in human cancers compared to the parental cytotoxic agent and the vehicle groups. Monitoring by photoacoustic imaging during the treatments revealed that the prodrug exhibits an intrinsic capability to prevent the progression of tumor hypoxia. It is essential for onco-pharmacology studies to precisely document the hypoxic status of tumors both before and during the time course of treatments. This approach opens new perspectives for exploitation of preclinical mouse models of cancer, especially when considering associations between hypoxia, neoangiogenesis and antitumor activity.

Extending the Hybrid Surgical Guidance Concept With Freehand Fluorescence Tomography

Within image-guided surgery, 'hybrid' guidance technologies have been used to integrate the complementary features of radioactive guidance and fluorescence guidance. Here, we explore how the generation of a novel freehand fluorescence (fhFluo) imaging approach complements freehand SPECT (fhSPECT) in a hybrid setup. Near-infrared optical tracking was used to register the position and the orientation of a hybrid opto-nuclear detection probe while recording its readings. Dedicated look-up table models were used for 3D reconstruction. In phantom and excised tissue settings (i.e., flat-surface human skin explants), fhSPECT and fhFluo were investigated for image resolution and in-tissue signal penetration. Finally, the combined potential of these freehand technologies was evaluated on prostate and lymph node specimens of prostate cancer patients receiving prostatectomy and sentinel lymph node dissection (tracers: indocyanine green (ICG) +^99m Tc-nanocolloid or ICG-^99mTc-nanocolloid). After hardware and software integration, the hybrid setup created 3D nuclear and fluorescence tomography scans. The imaging resolution of fhFluo (1 mm) was superior to that of fhSPECT (6 mm). Fluorescence modalities were confined to a maximum depth of 0.5 cm, while nuclear modalities were usable at all evaluated depths (<2 cm). Both fhSPECT and fhFluo enabled augmented- and virtual-reality navigation toward segmented image hotspots, including relative hotspot quantification with an accuracy of 3.9% and 4.1%. Imaging in surgical specimens confirmed these trends (fhSPECT: in-depth detectability, low resolution, and fhFluo: superior resolution, superficial detectability). Overall, when radioactive and fluorescent tracer signatures are used, fhFluo has complementary value to fhSPECT. Combined the freehand technologies render a unique hybrid imaging and navigation modality.

Optical and thermal simulations for the design of optodes for minimally invasive optogenetics stimulation or photomodulation of deep and large cortical areas in non-human primate brain

The use of optogenetics or photobiomodulation in non-human primate (NHP) requires the ability to noninvasively stimulate large and deep cortical brain tissues volumes. In this context, the optical and geometrical parameters of optodes are critical. Methods and general guidelines to optimize these parameters have to be defined.

OBJECTIVE

We propose the design of an optode for safe and efficient optical stimulation of a large volume of NHP cortex, down to 3-5 mm depths without inserting fibers into the cortex.

APPROACH

Monte Carlo simulations of optical and thermal transport have been carried out using the Geant4 application for tomographic emission (GATE) platform. Parameters such as the fiber diameter, numerical aperture, number of fibers and their geometrical arrangement have been studied. Optimal hardware parameters are proposed to obtain homogeneous fluence above the fluence threshold for opsin activation without detrimental thermal effects.

MAIN RESULTS

The simulations show that a large fiber diameter and a large numerical aperture are preferable since they allow limiting power concentration and hence the resulting thermal increases at the brain surface. To obtain a volume of 200-500 mm³ of brain tissues receiving a fluence above the opsin activation threshold for optogenetics or below a phototocixity threshold for photobiomodulation, a 4 fibers configuration is proposed. The optimal distance between the fibers was found to be 4 mm. A practical implementation of the optode has been performed and the corresponding fluence and thermal maps have been simulated.

SIGNIFICANCE

The present study defines a method to optimize the design of optode and the choice of stimulation parameters for optogenetics and more generally light delivery to deep and large volumes of tissues in NHP brain with a controlled irradiance dosimetry. The general guidelines are the use of silica fibers with a large numerical aperture and a large diameter. The combination of several fibers is required if large volumes need to be stimulated while avoiding thermal effects.

Lens implementation on the GATE Monte Carlo toolkit for optical imaging simulation

Optical imaging techniques are widely used for in vivo preclinical studies, and it is well known that the Geant4 Application for Emission Tomography (GATE) can be employed for the Monte Carlo (MC) modeling of light transport inside heterogeneous tissues. However, the GATE MC toolkit is limited in that it does not yet include optical lens implementation, even though this is required for a more realistic optical imaging simulation. We describe our implementation of a biconvex lens into the GATE MC toolkit to improve both the sensitivity and spatial resolution for optical imaging simulation. The lens implemented into the GATE was validated against the ZEMAX optical simulation using an US air force 1951 resolution target. The ray diagrams and the charge-coupled device images of the GATE optical simulation agreed with the ZEMAX optical simulation results. In conclusion, the use of a lens on the GATE optical simulation could improve the image quality of bioluminescence and fluorescence significantly as compared with pinhole optics.

A novel multilayer MV imager computational model for component optimization

PURPOSE

A novel Megavoltage (MV) multilayer imager (MLI) design featuring higher detective quantum efficiency and lower noise than current conventional MV imagers in clinical use has been recently reported. Optimization of the MLI design for multiple applications including tumor tracking, MV-CBCT and portal dosimetry requires a computational model that will provide insight into the physics processes that affect the overall and individual components' performance. The purpose of the current work was to develop and validate a comprehensive computational model that can be used for MLI optimization.

METHODS

The MLI model was built using the Geant4 Application for Tomographic Emission (GATE) application. The model includes x-ray and charged-particle interactions as well as the optical transfer within the phosphor. A first prototype MLI device featuring a stack of four detection layers was used for model validation. Each layer of the prototype contains a copper buildup plate, a phosphor screen and photodiode array. The model was validated against measured data of Modulation Transfer Function (MTF), Noise-Power Spectrum (NPS), and Detective Quantum Efficiency (DQE). MTF was computed using a slanted slit with 2.3^° angle and 0.1 mm width. NPS was obtained using the autocorrelation function technique. DQE was calculated from MTF and NPS data. The comparison metrics between simulated and measured data were the Pearson's correlation coefficient (r) and the normalized root-mean-square error (NRMSE).

RESULTS

Good agreement between measured and simulated MTF and NPS values was observed. Pearson's correlation coefficient for the combined signal from all layers of the MLI was equal to 0.9991 for MTF and 0.9992 for NPS; NRMSE was 0.0121 for MTF and 0.0194 for NPS. Similarly, the DQE correlation coefficient for the combined signal was 0.9888 and the NRMSE was 0.0686.

CONCLUSIONS

A comprehensive model of the novel MLI design was developed using the GATE toolkit and validated against measured MTF, NPS, and DQE data acquired with a prototype device featuring four layers. This model will be used for further optimization of the imager components and configuration for clinical radiotherapy applications.

An integrated model of scintillator-reflector properties for advanced simulations of optical transport

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 mm³ 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.

Simulation of nanoparticle-mediated near-infrared thermal therapy using GATE

Application of nanotechnology for biomedicine in cancer therapy allows for direct delivery of anticancer agents to tumors. An example of such therapies is the nanoparticle-mediated near-infrared hyperthermia treatment. In order to investigate the influence of nanoparticle properties on the spatial distribution of heat in the tumor and healthy tissues, accurate simulations are required. The Geant4 Application for Emission Tomography (GATE) open-source simulation platform, based on the Geant4 toolkit, is widely used by the research community involved in molecular imaging, radiotherapy and optical imaging. We present an extension of GATE that can model nanoparticle-mediated hyperthermal therapy as well as simple heat diffusion in biological tissues. This new feature of GATE combined with optical imaging allows for the simulation of a theranostic scenario in which the patient is injected with theranostic nanosystems that can simultaneously deliver therapeutic (i.e. hyperthermia therapy) and imaging agents (i.e. fluorescence imaging).

Optical absorption characteristics in the assessment of powder phosphor-based x-ray detectors: from nano- to micro-scale

X-ray phosphor-based detectors have enormously improved the quality of medical imaging examinations through the optimization of optical diffusion. In recent years, with the development of science and technology in the field of materials, improved powder phosphors require structural and optical properties that contribute to better optical signal propagation. The purpose of this paper was to provide a quantitative and qualitative understanding of the optical absorption characteristics in the assessment of powder phosphor-based detectors (from nano- scale up to micro-scale). Variations on the optical absorption parameters (i.e. the light extinction coefficient [Formula: see text] and the percentage probability of light absorption p%) were evaluated based on Mie calculations examining a wide range of light wavelengths, particle refractive indices and sizes. To model and assess the effects of the aforementioned parameters on optical diffusion, Monte Carlo simulation techniques were employed considering: (i) phosphors of different layer thickness, 100 μm (thin layer) and 300 μm (thick layer), respectively, (ii) light extinction coefficient values, 1, 3 and 6 μm(-1), and (iii) percentage probability of light absorption p% in the range 10(-4)-10(-2). Results showed that the [Formula: see text] coefficient is high for phosphor grains in the submicron scale and for low light wavelengths. At higher wavelengths (above 650 nm), optical quanta follow approximately similar depths until interaction for grain diameter 500 nm and 1 μm. Regarding the variability of the refractive index, high variations of the [Formula: see text] coefficient occurred above 1.6. Furthermore, results derived from Monte Carlo modeling showed that high spatial resolution phosphors can be accomplished by increasing the [Formula: see text] parameter. More specifically, the FWHM was found to decrease (i.e. higher resolution): (i) 4.8% at 100 μm and (ii) 9.5%, at 300 μm layer thickness. This study attempted to examine the role of the optical absorption parameters on optical diffusion studies. A significant outcome of the present investigation was that the improvement of phosphor spatial resolution without decreasing the light collection efficiency too much can be better achieved by increasing the parameter [Formula: see text] rather than the parameter p%.