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.

Formulation of simvastatin within high density lipoprotein enables potent tumour radiosensitisation.

Preclinical, clinical and epidemiologic studies have established the potent anticancer and radiosensitisation effects of HMG-CoA reductase inhibitors (statins). However, the low bioavailability of oral statin formulations is a key barrier to achieving effective doses within tumour. To address this issue and ascertain the radiosensitisation potential of simvastatin, we developed a parenteral high density lipoprotein nanoparticle (HDL NP) formulation of this commonly used statin. A scalable method for the preparation of the simvastatin-HDL NPs was developed using a 3D printed microfluidic mixer. This enables the production of litre scale amounts of particles with minimal batch to batch variation. Simvastatin-HDL NPs enhanced the radiobiological response in 2D/3D head and neck squamous cell carcinoma (HNSCC) in vitro models. The simvastatin-HDL NPs radiosensitisation was comparable to that of 10 and 5 times higher doses of free drug in 2D and 3D cultures, respectively, which could be partially explained by more efficient cellular uptake of the statin in the nanoformulation as well as by the inherent biological activity of the HDL NPs on the cholesterol pathway. The radiosensitising potency of the simvastatin-HDL nanoformulation was validated in an immunocompetent MOC-1 HNSCC tumour bearing mouse model. This data supports the rationale of repurposing statins through reformulation within HDL NPs. Statins are safe and readily available molecules including as generic, and their use as radiosensitisers could lead to much needed effective and affordable approaches to improve treatment of solid tumours.

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.

AAPM Task Group 264: The safe clinical implementation of MLC tracking in radiotherapy.

The era of real-time radiotherapy is upon us. Robotic and gimbaled linac tracking are clinically established technologies with the clinical realization of couch tracking in development. Multileaf collimators (MLCs) are a standard equipment for most cancer radiotherapy systems, and therefore MLC tracking is a potentially widely available technology. MLC tracking has been the subject of theoretical and experimental research for decades and was first implemented for patient treatments in 2013. The AAPM Task Group 264 Safe Clinical Implementation of MLC Tracking in Radiotherapy Report was charged to proactively provide the broader radiation oncology community with (a) clinical implementation guidelines including hardware, software, and clinical indications for use, (b) commissioning and quality assurance recommendations based on early user experience, as well as guidelines on Failure Mode and Effects Analysis, and (c) a discussion of potential future developments. The deliverables from this report include: an explanation of MLC tracking and its historical development; terms and definitions relevant to MLC tracking; the clinical benefit of, clinical experience with and clinical implementation guidelines for MLC tracking; quality assurance guidelines, including example quality assurance worksheets; a clinical decision pathway, future outlook and overall recommendations.

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.

Author Correction: Selective Priming of Tumor Blood Vessels by Radiation Therapy Enhances Nanodrug Delivery.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Noninvasive imaging of tumor hypoxia after nanoparticle-mediated tumor vascular disruption.

We have previously demonstrated that endothelial targeting of gold nanoparticles followed by external beam irradiation can cause specific tumor vascular disruption in mouse models of cancer. The induced vascular damage may lead to changes in tumor physiology, including tumor hypoxia, thereby compromising future therapeutic interventions. In this study, we investigate the dynamic changes in tumor hypoxia mediated by targeted gold nanoparticles and clinical radiation therapy (RT). By using noninvasive whole-body fluorescence imaging, tumor hypoxia was measured at baseline, on day 2 and day 13, post-tumor vascular disruption. A 2.5-fold increase (P<0.05) in tumor hypoxia was measured two days after combined therapy, resolving by day 13. In addition, the combination of vascular-targeted gold nanoparticles and radiation therapy resulted in a significant (P<0.05) suppression of tumor growth. This is the first study to demonstrate the tumor hypoxic physiological response and recovery after delivery of vascular-targeted gold nanoparticles followed by clinical radiation therapy in a human non-small cell lung cancer athymic Foxn1nu mouse model.

Author Correction: Image-guided radiotherapy platform using single nodule conditional lung cancer mouse models.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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.

Selective Priming of Tumor Blood Vessels by Radiation Therapy Enhances Nanodrug Delivery.

Effective drug delivery is restricted by pathophysiological barriers in solid tumors. In human pancreatic adenocarcinoma, poorly-permeable blood vessels limit the intratumoral permeation and penetration of chemo or nanotherapeutic drugs. New and clinically viable strategies are urgently sought to breach the neoplastic barriers that prevent effective drug delivery. Here, we present an original idea to boost drug delivery by selectively knocking down the tumor vascular barrier in a human pancreatic cancer model. Clinical radiation activates the tumor endothelial-targeted gold nanoparticles to induce a physical vascular damage due to the high photoelectric interactions. Active modulation of these tumor neovessels lead to distinct changes in tumor vascular permeability. Noninvasive MRI and fluorescence studies, using a short-circulating nanocarrier with MR-sensitive gadolinium and a long-circulating nanocarrier with fluorescence-sensitive nearinfrared dye, demonstrate more than two-fold increase in nanodrug delivery, post tumor vascular modulation. Functional changes in altered tumor blood vessels and its downstream parameters, particularly, changes in Ktrans (permeability), Kep (flux rate), and Ve (extracellular interstitial volume), reflect changes that relate to augmented drug delivery. The proposed dual-targeted therapy effectively invades the tumor vascular barrier and improve nanodrug delivery in a human pancreatic tumor model and it may also be applied to other nonresectable, intransigent tumors that barely respond to standard drug therapies.

Characterizing a novel scintillating glass for application to megavoltage cone-beam computed tomography.

PURPOSE: The purpose of this study was to evaluate the performance of a prototype electric portal imaging device (EPID) with a high detective quantum efficiency (DQE) scintillator, LKH-5. Specifically, image quality in context of both planar and megavoltage (MV) cone-beam computed tomography (CBCT) is analyzed. METHODS: Planar image quality in terms of modulation transfer function (MTF), noise power spectrum (NPS), and DQE are measured and compared to an existing EPID (AS-1200) using the 6 MV beamline for a Varian TrueBeam linac. Imager performance is contextualized for three-dimensional (3D), MV-CBCT performance by measuring imager lag and analyzing the expected degradation of the DQE as a function of dose. Finally, comparisons between reconstructed images of the Catphan phantom in terms of qualitative quality and signal-difference-to-noise ratio (SDNR) are made for 6 MV images using both conventional and LKH-5 EPIDs as well as for the kilovoltage (kV) on-board imager (OBI). RESULTS: Analysis of the NPS reveals linearity at all measured doses using the prototype LKH-5 detector. While the first zero of the MTF is much lower for the LKH-5 detector than the conventional EPID (0.6 cycles/mm vs 1.6 cycles/mm), the normalized NPS (NNPS) multiplied by total quanta (qNNPS) of the LKH-5 detector is roughly a factor of seven to eight times lower, yielding a DQE(0) of approximately 8%. First, second, and third frame lag were measured at approximately 23%, 5%, and 1%, respectively, although no noticeable image artifacts were apparent in reconstructed volumes. Analysis of low-dose performance reveals that DQE(0) remains at 80% of its maximum value at a dose as low as 7.5 × 10-6  MU. For a 400 projection technique, this represents a total scan dose of 0.0030 MU, suggesting that if imaging doses are increased to a value typical of kV-CBCT scans (~2.7 cGy), the LKH-5 detector will retain quantum noise limited performance. Finally, comparing Catphan scans, the prototype detector exhibits much lower image noise than the conventional EPID, resulting in improved small object representation. Furthermore, SDNR of H2 O and polystyrene cylinders improved from -1.95 and 2.94 to -15 and 18.7, respectively. CONCLUSIONS: Imaging performance of the prototype LKH-5 detector was measured and analyzed for both planar and 3D contexts. Improving noise transfer of the detector results in concurrent improvement of DQE(0). For 3D imaging, temporal characteristics were adequate for artifact-free performance and at relevant doses, the detector retained quantum noise limited performance. Although quantitative MTF measurements suggest poorer resolution, small object representation of the prototype imager is qualitatively improved over the conventional detector due to the measured reduction in noise.

Feasibility of closed-MLC tracking using high sensitivity and multi-layer electronic portal imagers.

In radiation therapy, improvements in treatment conformality are often limited by movement of target tissue. To better treat the target, tumor tracking strategies involving beam's-eye-view (BEV) have been explored. However, localization surrogates like implanted fiducial markers may sometimes leave the field-of-view (FOV), as defined by the linear accelerator (LINAC) multi-leaf collimator (MLC). Radiation leakage through the MLC has been measured previously at approximately 1%-2%. High sensitivity prototype detectors imagers may improve the ability to visualize objects outside of the MLC FOV during treatment. The present study presents a proof-of-concept for tracking fiducial markers outside the MLC FOV by employing high sensitivity detectors using a high-efficiency, prototype scintillating glass called LKH-5 and also investigates the impact of multi-layer imager (MLI) architecture. It was found that by improving the detector efficiency, using either of these methods results in a reduction of dose required for fiducial marker visibility. Further, image correction by a rectangular median filter will improve fiducial marker representation in the MLC blocked images. Quantified by measuring the peak-to-sidelobe ratio (PSR) of the normalized cross correlation (NCC) between a template of the fiducial marker with the blocked MLC acquisition, visibility has been found at a threshold of roughly 5 for all configurations with a 3 × 3 cm2 ROI. For typical gadolinium oxysulfide (GOS) detectors in single and simulated 4-layer configurations, the minimum dose required for visualization was 20 and 10 MU, respectively. For LKH-5 detectors in single and simulated 4-layer configurations, this minimum dose was reduced to 4 and 2 MU, respectively. With a 6 MV flattening filter free (FFF) beam dose rate of 1400 MU min-1, the maximum detector frame rate while maintaining fiducial visibility is approximately 12 fps for a 4-layer LKH-5 configuration.

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.

Relationship between the Temporal Changes in Positron-Emission-Tomography-Imaging-Based Textural Features and Pathologic Response and Survival in Esophageal Cancer Patients.

PURPOSE: Although change in standardized uptake value (SUV) measures and PET-based textural features during treatment have shown promise in tumor response prediction, it is unclear which quantitative measure is the most predictive. We compared the relationship between PET-based features and pathologic response and overall survival with the SUV measures in esophageal cancer. METHODS: Fifty-four esophageal cancer patients received PET/CT scans before and after chemoradiotherapy. Of these, 45 patients underwent surgery and were classified into complete, partial, and non-responders to the preoperative chemoradiation. SUVmax and SUVmean, two cooccurrence matrix (Entropy and Homogeneity), two run-length matrix (RLM) (high-gray-run emphasis and Short-run high-gray-run emphasis), and two size-zone matrix (high-gray-zone emphasis and short-zone high-gray emphasis) textures were computed. The relationship between the relative difference of each measure at different treatment time points and the pathologic response and overall survival was assessed using the area under the receiver-operating-characteristic curve (AUC) and Kaplan-Meier statistics, respectively. RESULTS: All Textures, except Homogeneity, were better related to pathologic response than SUVmax and SUVmean. Entropy was found to significantly distinguish non-responders from the complete (AUC = 0.79, p = 1.7 × 10(-4)) and partial (AUC = 0.71, p = 0.01) responders. Non-responders can also be significantly differentiated from partial and complete responders by the change in the run-length and size-zone matrix textures (AUC = 0.71-0.76, p ≤ 0.02). Homogeneity, SUVmax, and SUVmean failed to differentiate between any of the responders (AUC = 0.50-0.57, p ≥ 0.46). However, none of the measures were found to significantly distinguish between complete and partial responders with AUC <0.60 (p = 0.37). Median Entropy and RLM textures significantly discriminated patients with good and poor survival (log-rank p < 0.02), while all other textures and survival were poorly related (log-rank p > 0.25). CONCLUSION: For the patients studied, temporal changes in Entropy and all RLM were better correlated with pathological response and survival than the SUV measures. The hypothesis that these metrics can be used as clinical predictors of better patient outcomes will be tested in a larger patient dataset in the future.

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.

Use of registration-based contour propagation in texture analysis for esophageal cancer pathologic response prediction.

Change in PET-based textural features has shown promise in predicting cancer response to treatment. However, contouring tumour volumes on longitudinal scans is time-consuming. This study investigated the usefulness of contour propagation in texture analysis for the purpose of pathologic response prediction in esophageal cancer. Forty-five esophageal cancer patients underwent PET/CT scans before and after chemo-radiotherapy. Patients were classified into responders and non-responders after the surgery. Physician-defined tumour ROIs on pre-treatment PET were propagated onto the post-treatment PET using rigid and ten deformable registration algorithms. PET images were converted into 256 discrete values. Co-occurrence, run-length, and size zone matrix textures were computed within all ROIs. The relative difference of each texture at different treatment time-points was used to predict the pathologic responders. Their predictive value was assessed using the area under the receiver-operating-characteristic curve (AUC). Propagated ROIs from different algorithms were compared using Dice similarity index (DSI). Contours propagated by the fast-demons, fast-free-form and rigid algorithms did not fully capture the high FDG uptake regions of tumours. Fast-demons propagated ROIs had the least agreement with other contours (DSI = 58%). Moderate to substantial overlap were found in the ROIs propagated by all other algorithms (DSI = 69%-79%). Rigidly propagated ROIs with co-occurrence texture failed to significantly differentiate between responders and non-responders (AUC = 0.58, q-value = 0.33), while the differentiation was significant with other textures (AUC = 0.71-0.73, p < 0.009). Among the deformable algorithms, fast-demons (AUC = 0.68-0.70, q-value < 0.03) and fast-free-form (AUC = 0.69-0.74, q-value < 0.04) were the least predictive. ROIs propagated by all other deformable algorithms with any texture significantly predicted pathologic responders (AUC = 0.72-0.78, q-value < 0.01). Propagated ROIs using deformable registration for all textures can lead to accurate prediction of pathologic response, potentially expediting the temporal texture analysis process. However, fast-demons, fast-free-form, and rigid algorithms should be applied with care due to their inferior performance compared to other algorithms.

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.