Monte Carlo model of a prototype flat-panel detector for multi-energy applications in radiotherapy.

BACKGROUND: The incorporation of multi-energy capabilities into radiotherapy flat-panel detectors offers advantages including enhanced soft tissue visualization by reduction of signal from overlapping anatomy such as bone in 2D image projections; creation of virtual monoenergetic images for 3D contrast enhancement, metal artefact reduction and direct acquisition of relative electron density. A novel dual-layer on-board imager offering dual energy processing capabilities is being designed. As opposed to other dual-energy implementation techniques which require separate acquisition with two different x-ray spectra, the dual-layer detector design enables simultaneous acquisition of high and low energy images with a single exposure. A computational framework is required to optimize the design parameters and evaluate detector performance for specific clinical applications. PURPOSE: In this study, we report on the development of a Monte Carlo (MC) model of the imager including model validation. METHODS: The stack-up of the dual-layer imager (DLI) was implemented in GEANT4 Application for Tomographic Emission (GATE). The DLI model has an active area of 43×43 cm2 , with top and bottom Cesium Iodide (CsI) scintillators of 600 and 800 µm thickness, respectively. Measurement of spatial resolution and imaging of dedicated multi-material dual-energy (DE) phantoms were used to validate the model. The modulation transfer function (MTF) of the detector was calculated for a 120 kVp x-ray spectrum using a 0.5 mm thick tantalum edge rotated by 2.5o . For imaging validation, the DE phantom was imaged using a 140 kVp x-ray spectrum. For both validation simulations, corresponding measurements were done using an initial prototype of the imager. Agreement between simulations and measurement was assessed using normalized root mean square error (NRMSE) and 1D profile difference for the MTF and phantom images respectively. Further comparison between measurement and simulation was made using virtual monoenergetic images (VMIs) generated from basis material images derived using precomputed look-up tables. RESULTS: The MTF of the bottom layer of the dual-layer model shows values decreasing more quickly with spatial frequency, compared to the top layer, due to the thicker bottom scintillator thickness and scatter from the top layer. A comparison with measurement shows NRMSE of 0.013 and 0.015 as well as identical MTF50 of 0.8 mm1 and 1.0 mm1 for the top and bottom layer respectively. For the DE imaging of the DE-phantom, although a maximum deviation of 3.3% is observed for the 10 mm aluminum and Teflon inserts at the top layer, the agreement for all other inserts is less than 2.2% of the measured value at both layers. Material decomposition of simulated scatter-free DE images gives an average accuracy in PMMA and aluminum composition of 4.9% and 10.3% for 11-30 mm PMMA and 1-10 mm aluminum objects respectively. A comparison of decomposed values using scatter containing measured and simulated DE images shows good agreement within statistical uncertainty. CONCLUSION: Validation using both MTF and phantom imaging shows good agreement between simulation and measurements. With the present configuration of the digital prototype, the model can generate material decomposed images and virtual monoenergetic images.

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.

GPU-accelerated Monte Carlo simulation of MV-CBCT.

Monte Carlo simulation (MCS) is one of the most accurate computation methods for dose calculation and image formation in radiation therapy. However, the high computational complexity and long execution time of MCS limits its broad use. In this paper, we present a novel strategy to accelerate MCS using a graphic processing unit (GPU), and we demonstrate the application in mega-voltage (MV) cone-beam computed tomography (CBCT) simulation. A new framework that generates a series of MV projections from a single simulation run is designed specifically for MV-CBCT acquisition. A Geant4-based GPU code for photon simulation is incorporated into the framework for the simulation of photon transport through a phantom volume. The FastEPID method, which accelerates the simulation of MV images, is modified and integrated into the framework. The proposed GPU-based simulation strategy was tested for its accuracy and efficiency in a Catphan 604 phantom and an anthropomorphic pelvis phantom with beam energies at 2.5 MV, 6 MV, and 6 MV FFF. In all cases, the proposed GPU-based simulation demonstrated great simulation accuracy and excellent agreement with measurement and CPU-based simulation in terms of reconstructed image qualities. The MV-CBCT simulation was accelerated by factors of roughly 900-2300 using an NVIDIA Tesla V100 GPU card against a 2.5 GHz AMD Opteron™ Processor 6380.

A rapid, accurate image simulation strategy for mega-voltage cone-beam computed tomography.

Intensive computation time is required to simulate images of electronic portal imaging device (EPID) using Monte Carlo (MC) technique, limiting the development of applications associated with EPID, such as mega-voltage cone-beam computed tomography (MV-CBCT). In this study, a fast, accurate simulation strategy for MV-CBCT utilizing the FastEPID technique has been developed and validated. During FastEPID simulation, photon detection was determined by pre-calculated photon energy deposition efficiency (η) and particle transport within the EPID was replaced with a pre-calculated optical photon spread function. This method is capable of reducing the time required for EPID image simulation by a factor of 90-140, without compromising image quality. MV-CBCT images reconstructed from the FastEPID simulated projections have been validated against measurement in terms of mean Hounsfield unit (HU), noise, and cupping artifact. These images were obtained with both a Catphan 604 phantom and an anthropomorphic pelvis phantom, under treatment beam energies of 2.5 MV, 6 MV, and 6 MV flattening filter free. The agreement between measurement and simulation was excellent in all cases. This novel strategy was capable of reducing the run time of a full scan simulation of MV-CBCT performed on a CPU cluster to a matter of hours, rather than weeks or months required by a conventional approach. Multiple applications associated with MV-CBCT (e.g. imager design optimization) are anticipated to gain from the implementation of this novel simulation strategy.

Low Z target switching to increase tumor endothelial cell dose enhancement during gold nanoparticle-aided radiation therapy.

PURPOSE: Previous studies have introduced gold nanoparticles as vascular-disrupting agents during radiation therapy. Crucial to this concept is the low energy photon content of the therapy radiation beam. The authors introduce a new mode of delivery including a linear accelerator target that can toggle between low Z and high Z targets during beam delivery. In this study, the authors examine the potential increase in tumor blood vessel endothelial cell radiation dose enhancement with the low Z target. METHODS: The authors use Monte Carlo methods to simulate delivery of three different clinical photon beams: (1) a 6 MV standard (Cu/W) beam, (2) a 6 MV flattening filter free (Cu/W), and (3) a 6 MV (carbon) beam. The photon energy spectra for each scenario are generated for depths in tissue-equivalent material: 2, 10, and 20 cm. The endothelial dose enhancement for each target and depth is calculated using a previously published analytic method. RESULTS: It is found that the carbon target increases the proportion of low energy (<150 keV) photons at 10 cm depth to 28% from 8% for the 6 MV standard (Cu/W) beam. This nearly quadrupling of the low energy photon content incident on a gold nanoparticle results in 7.7 times the endothelial dose enhancement as a 6 MV standard (Cu/W) beam at this depth. Increased surface dose from the low Z target can be mitigated by well-spaced beam arrangements. CONCLUSIONS: By using the fast-switching target, one can modulate the photon beam during delivery, producing a customized photon energy spectrum for each specific situation.

4D cone beam CT-based dose assessment for SBRT lung cancer treatment.

The purpose of this research is to develop a 4DCBCT-based dose assessment method for calculating actual delivered dose for patients with significant respiratory motion or anatomical changes during the course of SBRT. To address the limitation of 4DCT-based dose assessment, we propose to calculate the delivered dose using time-varying ('fluoroscopic') 3D patient images generated from a 4DCBCT-based motion model. The method includes four steps: (1) before each treatment, 4DCBCT data is acquired with the patient in treatment position, based on which a patient-specific motion model is created using a principal components analysis algorithm. (2) During treatment, 2D time-varying kV projection images are continuously acquired, from which time-varying 'fluoroscopic' 3D images of the patient are reconstructed using the motion model. (3) Lateral truncation artifacts are corrected using planning 4DCT images. (4) The 3D dose distribution is computed for each timepoint in the set of 3D fluoroscopic images, from which the total effective 3D delivered dose is calculated by accumulating deformed dose distributions. This approach is validated using six modified XCAT phantoms with lung tumors and different respiratory motions derived from patient data. The estimated doses are compared to that calculated using ground-truth XCAT phantoms. For each XCAT phantom, the calculated delivered tumor dose values generally follow the same trend as that of the ground truth and at most timepoints the difference is less than 5%. For the overall delivered dose, the normalized error of calculated 3D dose distribution is generally less than 3% and the tumor D95 error is less than 1.5%. XCAT phantom studies indicate the potential of the proposed method to accurately estimate 3D tumor dose distributions for SBRT lung treatment based on 4DCBCT imaging and motion modeling. Further research is necessary to investigate its performance for clinical patient data.

3D delivered dose assessment using a 4DCT-based motion model.

PURPOSE: The purpose of this work is to develop a clinically feasible method of calculating actual delivered dose distributions for patients who have significant respiratory motion during the course of stereotactic body radiation therapy (SBRT). METHODS: A novel approach was proposed to calculate the actual delivered dose distribution for SBRT lung treatment. This approach can be specified in three steps. (1) At the treatment planning stage, a patient-specific motion model is created from planning 4DCT data. This model assumes that the displacement vector field (DVF) of any respiratory motion deformation can be described as a linear combination of some basis DVFs. (2) During the treatment procedure, 2D time-varying projection images (either kV or MV projections) are acquired, from which time-varying "fluoroscopic" 3D images of the patient are reconstructed using the motion model. The DVF of each timepoint in the time-varying reconstruction is an optimized linear combination of basis DVFs such that the 2D projection of the 3D volume at this timepoint matches the projection image. (3) 3D dose distribution is computed for each timepoint in the set of 3D reconstructed fluoroscopic images, from which the total effective 3D delivered dose is calculated by accumulating deformed dose distributions. This approach was first validated using two modified digital extended cardio-torso (XCAT) phantoms with lung tumors and different respiratory motions. The estimated doses were compared to the dose that would be calculated for routine 4DCT-based planning and to the actual delivered dose that was calculated using "ground truth" XCAT phantoms at all timepoints. The approach was also tested using one set of patient data, which demonstrated the application of our method in a clinical scenario. RESULTS: For the first XCAT phantom that has a mostly regular breathing pattern, the errors in 95% volume dose (D95) are 0.11% and 0.83%, respectively for 3D fluoroscopic images reconstructed from kV and MV projections compared to the ground truth, which is clinically comparable to 4DCT (0.093%). For the second XCAT phantom that has an irregular breathing pattern, the errors are 0.81% and 1.75% for kV and MV reconstructions, both of which are better than that of 4DCT (4.01%). In the case of real patient, although it is impossible to obtain the actual delivered dose, the dose estimation is clinically reasonable and demonstrates differences between 4DCT and MV reconstruction-based dose estimates. CONCLUSIONS: With the availability of kV or MV projection images, the proposed approach is able to assess delivered doses for all respiratory phases during treatment. Compared to the planning dose based on 4DCT, the dose estimation using reconstructed 3D fluoroscopic images was as good as 4DCT for regular respiratory pattern and was a better dose estimation for the irregular respiratory pattern.

A mass-conserving 4D XCAT phantom for dose calculation and accumulation.

PURPOSE: The XCAT phantom is a realistic 4D digital torso phantom that is widely used in imaging and therapy research. However, lung mass is not conserved between respiratory phases of the phantom, making detailed dosimetric simulations and dose accumulation unphysical. A framework is developed to correct this issue by enforcing local mass conservation in the XCAT lung. Dose calculations are performed to assess the implications of neglecting mass conservation, and to demonstrate an application of the phantom to calculate the accumulated delivered dose in an irregularly breathing patient. METHODS: A displacement vector field (DVF) between each respiratory state and a reference image is generated from the XCAT motion model and its divergence is calculated and used to correct the lung density. A series of phantoms with regular and irregular breathing (based on patient data) are generated and modified to conserve mass. Monte Carlo methods are used to simulate conventional and SBRT treatment delivery. The calculated dose is deformed and accumulated using the DVF. Results from the mass-conserving and original XCAT are compared. A 4DCT is simulated for the irregularly breathing patient, and a 4DCT-based dose estimate is compared with the accumulated delivered dose. RESULTS: The presented framework successfully conserves mass in the XCAT lung. The spatial distribution of the lung dose was qualitatively changed by the use of a mass conservation in the XCAT; however, the corresponding DVH did not change significantly. The comparison of the delivered dose with the 4DCT-based prediction shows similar lung metric results, however dose differences of 10% can be seen in some spatial regions. CONCLUSIONS: The XCAT phantom has been successfully modified so that it conserves lung mass during respiration, enabling it to be used as a tool to perform dose accumulation studies in the lung without relying on deformable image registration. Neglecting mass conservation can result in erroneous spatial distributions of the dose in the lung. Using this tool to simulate patient treatments reveals differences between the planned dose and the calculated delivered dose for the full treatment. The software is freely available from the authors.

Impact of beam quality on megavoltage radiotherapy treatment techniques utilizing gold nanoparticles for dose enhancement.

This study determines the optimal clinical scenarios for gold nanoparticle dose enhancement as a function of irradiation conditions and potential biological targets using megavoltage x-ray beams. Four hundred and eighty clinical beams were studied for different potential cellular or sub-cellular targets. Beam quality was determined based on a 6 MV linac with and without a flattening filter for various delivery conditions. Dose enhancement ratios DER = D(GNP)/D(water) were calculated for all cases using the GEANT4 Monte Carlo code and the CEPXS/ONEDANT radiation transport deterministic code. Dose enhancement using GEANT4 agreed with CEPXS/ONEDANT. DER for unflattened beams is ∼2 times larger than for flattened beams. The maximum DER values were calculated for split-IMRT fields (∼6) and for out-of-field areas of an unflattened linac (∼17). In-field DER values, at the surface of gold nanoparticles, ranged from 2.2 to 4.2 (flattened beam) and from 3 to 4.7 (unflattened beams). For a GNP cluster with thicknesses of 10 and 100 nm, the DER ranges from 14% to 287%. DER is the greatest for split-IMRT, larger depths, out-of-field areas and/or unflattened linac. Mapping of a GNP location in tumor and normal tissue is essential for efficient and safe delivery of nanoparticle-enhanced radiotherapy.

MOSFET assessment of radiation dose delivered to mice using the Small Animal Radiation Research Platform (SARRP).

The Small Animal Radiation Research Platform (SARRP) is a novel isocentric irradiation system that enables state-of-the-art image-guided radiotherapy research to be performed with animal models. This paper reports the results obtained from investigations assessing the radiation dose delivered by the SARRP to different anatomical target volumes in mice. Surgically implanted metal oxide semiconductor field effect transistors (MOSFET) dosimeters were employed for the dose assessment. The results reveal differences between the calculated and measured dose of -3.5 to 0.5%, -5.2 to -0.7%, -3.9 to 0.5%, -5.9 to 2.5%, -5.5 to 0.5%, and -4.3 to 0% for the left kidney, liver, pancreas, prostate, left lung, and brain, respectively. Overall, the findings show less than 6% difference between the delivered and calculated dose, without tissue heterogeneity corrections. These results provide a useful assessment of the need for tissue heterogeneity corrections in SARRP dose calculations for clinically relevant tumor model sites.

Localized dose enhancement to tumor blood vessel endothelial cells via megavoltage X-rays and targeted gold nanoparticles: new potential for external beam radiotherapy.

PURPOSE: Tumor endothelial cell damage during radiation therapy may contribute significantly to tumor eradication and treatment efficacy. Gold nanoparticles (AuNPs) delivered preferentially to the walls of tumor blood vessels produce low-energy, short-range photoelectrons during external beam radiotherapy, boosting dose to the tumor microvasculature. In this study dosimetry at the single-cell level is used to estimate the anticipated AuNP-mediated dose enhancement to tumor endothelial cells during 6-MV X-ray irradiation. METHODS AND MATERIALS: Endothelial cells are modeled as thin slabs with 100-nm-diameter AuNPs attached within the blood vessel. The number of photoelectrons emitted per AuNP per gray of X-rays is computed at multiple points along the external beam central axis by use of a Monte Carlo-generated energy fluence spectrum. The energy deposited from AuNP emissions to the endothelium is calculated based on an analytic method incorporating the energy-loss formula of Cole. The endothelial dose enhancement factor (EDEF) is the ratio of the overall (externally plus internally generated) dose to endothelial cells in the presence of AuNPs to the dose without AuNPs (from the external beam only). RESULTS: At 20-cm depth, the EDEF is 1.7 (70% dose increase) for an intravascular AuNP concentration of 30 mg/g. Most of this dose enhancement arises from the low-energy (approximately 100 keV) portion of the linear accelerator X-ray spectrum. Furthermore, for AuNP concentrations ranging from 7 to 140 mg/g, EDEF values of 1.2 to 4.4 (20-340% dose increase) are calculated. CONCLUSIONS: In contrast to calculations assuming that AuNPs distributed homogeneously throughout the target volume (macrodosimetry), our cellular microdosimetry calculations predict a major dose enhancement to tumor microvasculature from conventional linear accelerator X-rays. This effect may enable the delivery of ablative therapeutic doses to these sensitive microstructures while maintaining established dose constraints for the organs at risk.