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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

SU-E-T-496: A Study of Two Commercial Dose Calculation Algorithms in Low Density Phantom

Purpose: Some lung cancer patients have very low lung density due to comorbidities. We investigate calculation accuracy of Eclipse AAA and Acuros(AXB) using a phantom that simulates this situation. Methods: A 2.5 x 5.0 x 5 cm (long) solid water inhomogeneity positioned 10 cm deep in a Balsa lung phantom (density 0.099 gm/cc) was irradiated with an off-center field such that the central axis was parallel to one side of the inhomogeneity. Radiochromic films were placed at 2.5cm(S1) and 5cm(S2) depths. After CT scanning, Hounsfield Units(HU) were converted to electron(ρe) and mass(ρm) density using in-house(IH) and vendor-supplied(V) calibration curves. IH electron densities were generated using a commercial electron density phantom. The phantom was exposed to 6 MV 3x3 and 20x20 fields. Dose distributions were calculated using the AAA and AXB algorithms. Results: The HU of BW is -910±40 which translates to ρe of 0.088±0.050(IH) and 0.090±0.050(V), and ρm of 0.101±0.045(IH) and 0.103±0.039(V). Both ρe(V) and ρm(V) are higher than ρe(IH) and ρm(IH) respectively by 1.4-5.3% and 0.5-12.3%. The average calculated dose inside the solid water ‘tumor’ are within 3.7% and 2.4% of measurements for both calibrations and field sizes using AAA and AXB. Within 10mm outside the ‘tumor’, AAA on average underestimates by 18.3% and 17.0% respectively for 3x3 using IH and V. AXB underestimates by 5.9%(S1)-6.6%(S2) and 13.1%(S1)-16.0%(S2) respectively using IH and V. For 20x20, AAA and AXB underestimate by 2.8%(S1)-4.4%(S2) and 0.3%(S1)-1.4%(S2) respectively with either calibration. Conclusion: The difference in the HU calibration between V and IH is not of clinical significance in normal field sizes. In the low density region of small fields, the calculations from both algorithms differ significantly from measurements. This may be attributed to the insufficient lateral electron transport modeled by two algorithms resulting in the over-estimation in penumbra expansion.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

MO-G-17A-07: Improved Image Quality in Brain F-18 FDG PET Using Penalized-Likelihood Image Reconstruction Via a Generalized Preconditioned Alternating Projection Algorithm: The First Patient Results

Purpose: To investigate the performance of a new penalized-likelihood PET image reconstruction algorithm using the 1{sub 1}-norm total-variation (TV) sum of the 1st through 4th-order gradients as the penalty. Simulated and brain patient data sets were analyzed. Methods: This work represents an extension of the preconditioned alternating projection algorithm (PAPA) for emission-computed tomography. In this new generalized algorithm (GPAPA), the penalty term is expanded to allow multiple components, in this case the sum of the 1st to 4th order gradients, to reduce artificial piece-wise constant regions (“staircase” artifacts typical for TV) seen in PAPA images penalized with only the 1st order gradient. Simulated data were used to test for “staircase” artifacts and to optimize the penalty hyper-parameter in the root-mean-squared error (RMSE) sense. Patient FDG brain scans were acquired on a GE D690 PET/CT (370 MBq at 1-hour post-injection for 10 minutes) in time-of-flight mode and in all cases were reconstructed using resolution recovery projectors. GPAPA images were compared PAPA and RMSE-optimally filtered OSEM (fully converged) in simulations and to clinical OSEM reconstructions (3 iterations, 32 subsets) with 2.6 mm XYGaussian and standard 3-point axial smoothing post-filters. Results: The results from the simulated data show a significant reduction in the 'staircase' artifact for GPAPA compared to PAPA and lower RMSE (up to 35%) compared to optimally filtered OSEM. A simple power-law relationship between the RMSE-optimal hyper-parameters and the noise equivalent counts (NEC) per voxel is revealed. Qualitatively, the patient images appear much sharper and with less noise than standard clinical images. The convergence rate is similar to OSEM. Conclusions: GPAPA reconstructions using the 1{sub 1}-norm total-variation sum of the 1st through 4th-order gradients as the penalty show great promise for the improvement of image quality over that currently achieved with clinical OSEM reconstructions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Development of a golden beam data set for the commissioning of a proton double-scattering system in a pencil-beam dose calculation algorithm

Purpose: The purpose of this investigation is to determine if a single set of beam data, described by a minimal set of equations and fitting variables, can be used to commission different installations of a proton double-scattering system in a commercial pencil-beam dose calculation algorithm. Methods: The beam model parameters required to commission the pencil-beam dose calculation algorithm (virtual and effective SAD, effective source size, and pristine-peak energy spread) are determined for a commercial double-scattering system. These parameters are measured in a first room and parameterized as function of proton energy and nozzle settings by fitting four analytical equations to the measured data. The combination of these equations and fitting values constitutes the golden beam data (GBD). To determine the variation in dose delivery between installations, the same dosimetric properties are measured in two additional rooms at the same facility, as well as in a single room at another facility. The difference between the room-specific measurements and the GBD is evaluated against tolerances that guarantee the 3D dose distribution in each of the rooms matches the GBD-based dose distribution within clinically reasonable limits. The pencil-beam treatment-planning algorithm is commissioned with the GBD. The three-dimensional dose distribution in water is evaluated in the four treatment rooms and compared to the treatment-planning calculated dose distribution. Results: The virtual and effective SAD measurements fall between 226 and 257 cm. The effective source size varies between 2.4 and 6.2 cm for the large-field options, and 1.0 and 2.0 cm for the small-field options. The pristine-peak energy spread decreases from 1.05% at the lowest range to 0.6% at the highest. The virtual SAD as well as the effective source size can be accurately described by a linear relationship as function of the inverse of the residual energy. An additional linear correction term as function of RM-step thickness is required for accurate parameterization of the effective SAD. The GBD energy spread is given by a linear function of the exponential of the beam energy. Except for a few outliers, the measured parameters match the GBD within the specified tolerances in all of the four rooms investigated. For a SOBP field with a range of 15 g/cm{sup 2} and an air gap of 25 cm, the maximum difference in the 80%–20% lateral penumbra between the GBD-commissioned treatment-planning system and measurements in any of the four rooms is 0.5 mm. Conclusions: The beam model parameters of the double-scattering system can be parameterized with a limited set of equations and parameters. This GBD closely matches the measured dosimetric properties in four different rooms.

43 PARTICLE ACCELERATORS↗
DOE OSTI2014

Poster — Thur Eve — 70: Automatic lung bronchial and vessel bifurcations detection algorithm for deformable image registration assessment

Purpose: To investigate an automatic bronchial and vessel bifurcations detection algorithm for deformable image registration (DIR) assessment to improve lung cancer radiation treatment. Methods: 4DCT datasets were acquired and exported to Varian treatment planning system (TPS) EclipseTM for contouring. The lungs TPS contour was used as the prior shape for a segmentation algorithm based on hierarchical surface deformation that identifies the deformed lungs volumes of the 10 breathing phases. Hounsfield unit (HU) threshold filter was applied within the segmented lung volumes to identify blood vessels and airways. Segmented blood vessels and airways were skeletonised using a hierarchical curve-skeleton algorithm based on a generalized potential field approach. A graph representation of the computed skeleton was generated to assign one of three labels to each node: the termination node, the continuation node or the branching node. Results: 320 ± 51 bifurcations were detected in the right lung of a patient for the 10 breathing phases. The bifurcations were visually analyzed. 92 ± 10 bifurcations were found in the upper half of the lung and 228 ± 45 bifurcations were found in the lower half of the lung. Discrepancies between ten vessel trees were mainly ascribed to large deformation and in regions where the HU varies. Conclusions: We established an automatic method for DIR assessment using the morphological information of the patient anatomy. This approach allows a description of the lung's internal structure movement, which is needed to validate the DIR deformation fields for accurate 4D cancer treatment planning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Clinical evaluation of the iterative metal artifact reduction algorithm for CT simulation in radiotherapy

Purpose: To clinically evaluate an iterative metal artifact reduction (IMAR) algorithm prototype in the radiation oncology clinic setting by testing for accuracy in CT number retrieval, relative dosimetric changes in regions affected by artifacts, and improvements in anatomical and shape conspicuity of corrected images. Methods: A phantom with known material inserts was scanned in the presence/absence of metal with different configurations of placement and sizes. The relative change in CT numbers from the reference data (CT with no metal) was analyzed. The CT studies were also used for dosimetric tests where dose distributions from both photon and proton beams were calculated. Dose differences and gamma analysis were calculated to quantify the relative changes between doses calculated on the different CT studies. Data from eight patients (all different treatment sites) were also used to quantify the differences between dose distributions before and after correction with IMAR, with no reference standard. A ranking experiment was also conducted to analyze the relative confidence of physicians delineating anatomy in the near vicinity of the metal implants. Results: IMAR corrected images proved to accurately retrieve CT numbers in the phantom study, independent of metal insert configuration, size of the metal, and acquisition energy. For plastic water, the mean difference between corrected images and reference images was −1.3 HU across all scenarios (N = 37) with a 90% confidence interval of [−2.4, −0.2] HU. While deviations were relatively higher in images with more metal content, IMAR was able to effectively correct the CT numbers independent of the quantity of metal. Residual errors in the CT numbers as well as some induced by the correction algorithm were found in the IMAR corrected images. However, the dose distributions calculated on IMAR corrected images were closer to the reference data in phantom studies. Relative spatial difference in the dose distributions in the regions affected by the metal artifacts was also observed in patient data. However, in absence of a reference ground truth (CT set without metal inserts), these differences should not be interpreted as improvement/deterioration of the accuracy of calculated dose. With limited data presented, it was observed that proton dosimetry was affected more than photons as expected. Physicians were significantly more confident contouring anatomy in the regions affected by artifacts. While site specific preferences were detected, all indicated that they would consistently use IMAR corrected images. Conclusions: IMAR correction algorithm could be readily implemented in an existing clinical workflow upon commercial release. While residual errors still exist in IMAR corrected images, these images present with better overall conspicuity of the patient/phantom geometry and offer more accurate CT numbers for improved local dosimetry. The variety of different scenarios included herein attest to the utility of the evaluated IMAR for a wide range of radiotherapy clinical scenarios.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Multi-GPU implementation of a VMAT treatment plan optimization algorithm

Purpose: Volumetric modulated arc therapy (VMAT) optimization is a computationally challenging problem due to its large data size, high degrees of freedom, and many hardware constraints. High-performance graphics processing units (GPUs) have been used to speed up the computations. However, GPU’s relatively small memory size cannot handle cases with a large dose-deposition coefficient (DDC) matrix in cases of, e.g., those with a large target size, multiple targets, multiple arcs, and/or small beamlet size. The main purpose of this paper is to report an implementation of a column-generation-based VMAT algorithm, previously developed in the authors’ group, on a multi-GPU platform to solve the memory limitation problem. While the column-generation-based VMAT algorithm has been previously developed, the GPU implementation details have not been reported. Hence, another purpose is to present detailed techniques employed for GPU implementation. The authors also would like to utilize this particular problem as an example problem to study the feasibility of using a multi-GPU platform to solve large-scale problems in medical physics. Methods: The column-generation approach generates VMAT apertures sequentially by solving a pricing problem (PP) and a master problem (MP) iteratively. In the authors’ method, the sparse DDC matrix is first stored on a CPU in coordinate list format (COO). On the GPU side, this matrix is split into four submatrices according to beam angles, which are stored on four GPUs in compressed sparse row format. Computation of beamlet price, the first step in PP, is accomplished using multi-GPUs. A fast inter-GPU data transfer scheme is accomplished using peer-to-peer access. The remaining steps of PP and MP problems are implemented on CPU or a single GPU due to their modest problem scale and computational loads. Barzilai and Borwein algorithm with a subspace step scheme is adopted here to solve the MP problem. A head and neck (H and N) cancer case is then used to validate the authors’ method. The authors also compare their multi-GPU implementation with three different single GPU implementation strategies, i.e., truncating DDC matrix (S1), repeatedly transferring DDC matrix between CPU and GPU (S2), and porting computations involving DDC matrix to CPU (S3), in terms of both plan quality and computational efficiency. Two more H and N patient cases and three prostate cases are used to demonstrate the advantages of the authors’ method. Results: The authors’ multi-GPU implementation can finish the optimization process within ∼1 min for the H and N patient case. S1 leads to an inferior plan quality although its total time was 10 s shorter than the multi-GPU implementation due to the reduced matrix size. S2 and S3 yield the same plan quality as the multi-GPU implementation but take ∼4 and ∼6 min, respectively. High computational efficiency was consistently achieved for the other five patient cases tested, with VMAT plans of clinically acceptable quality obtained within 23–46 s. Conversely, to obtain clinically comparable or acceptable plans for all six of these VMAT cases that the authors have tested in this paper, the optimization time needed in a commercial TPS system on CPU was found to be in an order of several minutes. Conclusions: The results demonstrate that the multi-GPU implementation of the authors’ column-generation-based VMAT optimization can handle the large-scale VMAT optimization problem efficiently without sacrificing plan quality. The authors’ study may serve as an example to shed some light on other large-scale medical physics problems that require multi-GPU techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-I-05: A Correction Algorithm for Kilovoltage Cone-Beam Computed Tomography Dose Calculations in Cervical Cancer Patients

Purpose: To investigate the accuracy and feasibility of dose calculations using kilovoltage cone beam computed tomography in cervical cancer radiotherapy using a correction algorithm. Methods: The Hounsfield units (HU) and electron density (HU-density) curve was obtained for both planning CT (pCT) and kilovoltage cone beam CT (CBCT) using a CIRS-062 calibration phantom. The pCT and kV-CBCT images have different HU values, and if the HU-density curve of CBCT was directly used to calculate dose in CBCT images may have a deviation on dose distribution. It is necessary to normalize the different HU values between pCT and CBCT. A HU correction algorithm was used for CBCT images (cCBCT). Fifteen intensity-modulated radiation therapy (IMRT) plans of cervical cancer were chosen, and the plans were transferred to the pCT and cCBCT data sets without any changes for dose calculations. Phantom and patient studies were carried out. The dose differences and dose distributions were compared between cCBCT plan and pCT plan. Results: The HU number of CBCT was measured by several times, and the maximum change was less than 2%. To compare with pCT, the CBCT and cCBCT has a discrepancy, the dose differences in CBCT and cCBCT images were 2.48%±0.65% (range: 1.3%∼3.8%) and 0.48%±0.21% (range: 0.1%∼0.82%) for phantom study, respectively. For dose calculation in patient images, the dose differences were 2.25%±0.43% (range: 1.4%∼3.4%) and 0.63%±0.35% (range: 0.13%∼0.97%), respectively. And for the dose distributions, the passing rate of cCBCT was higher than the CBCTs. Conclusion: The CBCT image for dose calculation is feasible in cervical cancer radiotherapy, and the correction algorithm offers acceptable accuracy. It will become a useful tool for adaptive radiation therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-94: Geometric and Dosimetric Evaluation of Deformation Image Registration Algorithms Using Virtual Phantoms Generated From Patients with Lung Cancer

Purpose: To generate virtual phantoms with clinically relevant deformation and use them to objectively evaluate geometric and dosimetric uncertainties of deformable image registration (DIR) algorithms. Methods: Ten lung cancer patients undergoing adaptive 3DCRT planning were selected. For each patient, a pair of planning CT (pCT) and replanning CT (rCT) were used as the basis for virtual phantom generation. Manually adjusted meshes were created for selected ROIs (e.g. PTV, lungs, spinal cord, esophagus, and heart) on pCT and rCT. The mesh vertices were input into a thin-plate spline algorithm to generate a reference displacement vector field (DVF). The reference DVF was used to deform pCT to generate a simulated replanning CT (srCT) that was closely matched to rCT. Three DIR algorithms (Demons, B-Spline, and intensity-based) were applied to these ten virtual phantoms. The images, ROIs, and doses were mapped from pCT to srCT using the DVFs computed by these three DIRs and compared to those mapped using the reference DVF. Results: The average Dice coefficients for selected ROIs were from 0.85 to 0.96 for Demons, from 0.86 to 0.97 for intensity-based, and from 0.76 to 0.95 for B-Spline. The average Hausdorff distances for selected ROIs were from 2.2 to 5.4 mm for Demons, from 2.3 to 6.8 mm for intensity-based, and from 2.4 to 11.4 mm for B-Spline. The average absolute dose errors for selected ROIs were from 0.2 to 0.6 Gy for Demons, from 0.1 to 0.5 Gy for intensity-based, and from 0.5 to 1.5 Gy for B-Spline. Conclusion: Virtual phantoms were modeled after patients with lung cancer and were clinically relevant for adaptive radiotherapy treatment replanning. Virtual phantoms with known DVFs serve as references and can provide a fair comparison when evaluating different DIRs. Demons and intensity-based DIRs were shown to have smaller geometric and dosimetric uncertainties than B-Spline. Z Shen: None; K Bzdusek: an employee of Philips Healthcare; J Greskovich: None; P Xia: received research grants from Philips Healthcare and Siemens Healthcare.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-219: Comprehensive Validation of the Electron Monte Carlo Dose Calculation Algorithm in RayStation Treatment Planning System for An Elekta Linear Accelerator with AgilityTM Treatment Head

Purpose: This study evaluated the performance of the electron Monte Carlo dose calculation algorithm in RayStation v4.0 for an Elekta machine with Agility™ treatment head. Methods: The machine has five electron energies (6–8 MeV) and five applicators (6×6 to 25×25 cm {sup 2}). The dose (cGy/MU at d{sub max}), depth dose and profiles were measured in water using an electron diode at 100 cm SSD for nine square fields ≥2×2 cm{sup 2} and four complex fields at normal incidence, and a 14×14 cm{sup 2} field at 15° and 30° incidence. The dose was also measured for three square fields ≥4×4 cm{sup 2} at 98, 105 and 110 cm SSD. Using selected energies, the EBT3 radiochromic film was used for dose measurements in slab-shaped inhomogeneous phantoms and a breast phantom with surface curvature. The measured and calculated doses were analyzed using a gamma criterion of 3%/3 mm. Results: The calculated and measured doses varied by <3% for 116 of the 120 points, and <5% for the 4×4 cm{sup 2} field at 110 cm SSD at 9–18 MeV. The gamma analysis comparing the 105 pairs of in-water isodoses passed by >98.1%. The planar doses measured from films placed at 0.5 cm below a lung/tissue layer (12 MeV) and 1.0 cm below a bone/air layer (15 MeV) showed excellent agreement with calculations, with gamma passing by 99.9% and 98.5%, respectively. At the breast-tissue interface, the gamma passing rate is >98.8% at 12–18 MeV. The film results directly validated the accuracy of MU calculation and spatial dose distribution in presence of tissue inhomogeneity and surface curvature - situations challenging for simpler pencil-beam algorithms. Conclusion: The electron Monte Carlo algorithm in RayStation v4.0 is fully validated for clinical use for the Elekta Agility™ machine. The comprehensive validation included small fields, complex fields, oblique beams, extended distance, tissue inhomogeneity and surface curvature.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-579: On the Relative Sensitivity of Monte Carlo and Pencil Beam Dose Calculation Algorithms to CT Metal Artifacts in Volumetric-Modulated Arc Spine Radiosurgery (RS)

Purpose: Investigating the relative sensitivity of Monte Carlo (MC) and Pencil Beam (PB) dose calculation algorithms to low-Z (titanium) metallic artifacts is important for accurate and consistent dose reporting in post¬operative spinal RS. Methods: Sensitivity analysis of MC and PB dose calculation algorithms on the Monaco v.3.3 treatment planning system (Elekta CMS, Maryland Heights, MO, USA) was performed using CT images reconstructed without (plain) and with Orthopedic Metal Artifact Reduction (OMAR; Philips Healthcare system, Cleveland, OH, USA). 6MV and 10MV volumetric-modulated arc (VMAT) RS plans were obtained for MC and PB on the plain and OMAR images (MC-plain/OMAR and PB-plain/OMAR). Results: Maximum differences in dose to 0.2cc (D0.2cc) of spinal cord and cord +2mm for 6MV and 10MV VMAT plans were 0.1Gy between MC-OMAR and MC-plain, and between PB-OMAR and PB-plain. Planning target volume (PTV) dose coverage changed by 0.1±0.7% and 0.2±0.3% for 6MV and 10MV from MC-OMAR to MC-plain, and by 0.1±0.1% for both 6MV and 10 MV from PB-OMAR to PB-plain, respectively. In no case for both MC and PB the D0.2cc to spinal cord was found to exceed the planned tolerance changing from OMAR to plain CT in dose calculations. Conclusion: Dosimetric impacts of metallic artifacts caused by low-Z metallic spinal hardware (mainly titanium alloy) are not clinically important in VMAT-based spine RS, without significant dependence on dose calculation methods (MC and PB) and photon energy ≥ 6MV. There is no need to use one algorithm instead of the other to reduce uncertainty for dose reporting. The dose calculation method that should be used in spine RS shall be consistent with the usual clinical practice.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

MO-FG-204-03: Using Edge-Preserving Algorithm for Significantly Improved Image-Domain Material Decomposition in Dual Energy CT

Purpose: To significantly improve dual energy CT (DECT) imaging by establishing a new theoretical framework of image-domain material decomposition with incorporation of edge-preserving techniques. Methods: The proposed algorithm, HYPR-NLM, combines the edge-preserving non-local mean filter (NLM) with the HYPR-LR (Local HighlY constrained backPRojection Reconstruction) framework. Image denoising using HYPR-LR framework depends on the noise level of the composite image which is the average of the different energy images. For DECT, the composite image is the average of high- and low-energy images. To further reduce noise, one may want to increase the window size of the filter of the HYPR-LR, leading resolution degradation. By incorporating the NLM filtering and the HYPR-LR framework, HYPR-NLM reduces the boost material decomposition noise using energy information redundancies as well as the non-local mean. We demonstrate the noise reduction and resolution preservation of the algorithm with both iodine concentration numerical phantom and clinical patient data by comparing the HYPR-NLM algorithm to the direct matrix inversion, HYPR-LR and iterative image-domain material decomposition (Iter-DECT). Results: The results show iterative material decomposition method reduces noise to the lowest level and provides improved DECT images. HYPR-NLM significantly reduces noise while preserving the accuracy of quantitative measurement and resolution. For the iodine concentration numerical phantom, the averaged noise levels are about 2.0, 0.7, 0.2 and 0.4 for direct inversion, HYPR-LR, Iter- DECT and HYPR-NLM, respectively. For the patient data, the noise levels of the water images are about 0.36, 0.16, 0.12 and 0.13 for direct inversion, HYPR-LR, Iter-DECT and HYPR-NLM, respectively. Difference images of both HYPR-LR and Iter-DECT show edge effect, while no significant edge effect is shown for HYPR-NLM, suggesting spatial resolution is well preserved for HYPR-NLM. Conclusion: HYPR-NLM provides an effective way to reduce the generic magnified image noise of dual–energy material decomposition while preserving resolution. This work is supported in part by NIH grants 7R01HL111141 and 1R01-EB016777. This work is also supported by the Natural Science Foundation of China (NSFC Grant No. 81201091), Fundamental Research Funds for the Central Universities in China, and Fund Project for Excellent Abroad Scholar Personnel in Science and Technology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

The SRT reconstruction algorithm for semiquantification in PET imaging

Purpose: The spline reconstruction technique (SRT) is a new, fast algorithm based on a novel numerical implementation of an analytic representation of the inverse Radon transform. The mathematical details of this algorithm and comparisons with filtered backprojection were presented earlier in the literature. In this study, the authors present a comparison between SRT and the ordered-subsets expectation–maximization (OSEM) algorithm for determining contrast and semiquantitative indices of {sup 18}F-FDG uptake. Methods: The authors implemented SRT in the software for tomographic image reconstruction (STIR) open-source platform and evaluated this technique using simulated and real sinograms obtained from the GE Discovery ST positron emission tomography/computer tomography scanner. All simulations and reconstructions were performed in STIR. For OSEM, the authors used the clinical protocol of their scanner, namely, 21 subsets and two iterations. The authors also examined images at one, four, six, and ten iterations. For the simulation studies, the authors analyzed an image-quality phantom with cold and hot lesions. Two different versions of the phantom were employed at two different hot-sphere lesion-to-background ratios (LBRs), namely, 2:1 and 4:1. For each noiseless sinogram, 20 Poisson realizations were created at five different noise levels. In addition to making visual comparisons of the reconstructed images, the authors determined contrast and bias as a function of the background image roughness (IR). For the real-data studies, sinograms of an image-quality phantom simulating the human torso were employed. The authors determined contrast and LBR as a function of the background IR. Finally, the authors present plots of contrast as a function of IR after smoothing each reconstructed image with Gaussian filters of six different sizes. Statistical significance was determined by employing the Wilcoxon rank-sum test. Results: In both simulated and real studies, SRT exhibits higher contrast and lower bias than OSEM at the cold lesions. This improvement is achieved at the expense of increasing the noise in the reconstructed images. For the hot lesions, SRT exhibits a small improvement in contrast and LBR over OSEM with 21 subsets and two iterations; however, this improvement is not statistically significant. As the number of iterations increases, the performance of OSEM improves over SRT but again without statistical significance. The curves of contrast and LBR as a function of IR after Gaussian blurring indicate that the advantage of SRT in the cold regions is maintained even after decreasing the noise level by Gaussian blurring. Conclusions: SRT, at the expense of slightly increased noise in the reconstructed images, reconstructs images of higher contrast and lower bias than the clinical protocol of OSEM. This improvement is particularly evident for images involving cold regions. Thus, it appears that SRT should be particularly useful for the quantification of low-count and cold regions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Validation of a method for in vivo 3D dose reconstruction for IMRT and VMAT treatments using on-treatment EPID images and a model-based forward-calculation algorithm

Purpose: Radiation treatments are trending toward delivering higher doses per fraction under stereotactic radiosurgery and hypofractionated treatment regimens. There is a need for accurate 3D in vivo patient dose verification using electronic portal imaging device (EPID) measurements. This work presents a model-based technique to compute full three-dimensional patient dose reconstructed from on-treatment EPID portal images (i.e., transmission images). Methods: EPID dose is converted to incident fluence entering the patient using a series of steps which include converting measured EPID dose to fluence at the detector plane and then back-projecting the primary source component of the EPID fluence upstream of the patient. Incident fluence is then recombined with predicted extra-focal fluence and used to calculate 3D patient dose via a collapsed-cone convolution method. This method is implemented in an iterative manner, although in practice it provides accurate results in a single iteration. The robustness of the dose reconstruction technique is demonstrated with several simple slab phantom and nine anthropomorphic phantom cases. Prostate, head and neck, and lung treatments are all included as well as a range of delivery techniques including VMAT and dynamic intensity modulated radiation therapy (IMRT). Results: Results indicate that the patient dose reconstruction algorithm compares well with treatment planning system computed doses for controlled test situations. For simple phantom and square field tests, agreement was excellent with a 2%/2 mm 3D chi pass rate ≥98.9%. On anthropomorphic phantoms, the 2%/2 mm 3D chi pass rates ranged from 79.9% to 99.9% in the planning target volume (PTV) region and 96.5% to 100% in the low dose region (>20% of prescription, excluding PTV and skin build-up region). Conclusions: An algorithm to reconstruct delivered patient 3D doses from EPID exit dosimetry measurements was presented. The method was applied to phantom and patient data sets, as well as for dynamic IMRT and VMAT delivery techniques. Results indicate that the EPID dose reconstruction algorithm presented in this work is suitable for clinical implementation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Evaluation of a commercial MRI Linac based Monte Carlo dose calculation algorithm with GEANT 4

Purpose: This paper provides a comparison between a fast, commercial, in-patient Monte Carlo dose calculation algorithm (GPUMCD) and GEANT4. It also evaluates the dosimetric impact of the application of an external 1.5 T magnetic field. Methods: A stand-alone version of the Elekta™ GPUMCD algorithm, to be used within the Monaco treatment planning system to model dose for the Elekta™ magnetic resonance imaging (MRI) Linac, was compared against GEANT4 (v10.1). This was done in the presence or absence of a 1.5 T static magnetic field directed orthogonally to the radiation beam axis. Phantoms with material compositions of water, ICRU lung, ICRU compact-bone, and titanium were used for this purpose. Beams with 2 MeV monoenergetic photons as well as a 7 MV histogrammed spectrum representing the MRI Linac spectrum were emitted from a point source using a nominal source-to-surface distance of 142.5 cm. Field sizes ranged from 1.5 × 1.5 to 10 × 10 cm{sup 2}. Dose scoring was performed using a 3D grid comprising 1 mm{sup 3} voxels. The production thresholds were equivalent for both codes. Results were analyzed based upon a voxel by voxel dose difference between the two codes and also using a volumetric gamma analysis. Results: Comparisons were drawn from central axis depth doses, cross beam profiles, and isodose contours. Both in the presence and absence of a 1.5 T static magnetic field the relative differences in doses scored along the beam central axis were less than 1% for the homogeneous water phantom and all results matched within a maximum of ±2% for heterogeneous phantoms. Volumetric gamma analysis indicated that more than 99% of the examined volume passed gamma criteria of 2%—2 mm (dose difference and distance to agreement, respectively). These criteria were chosen because the minimum primary statistical uncertainty in dose scoring voxels was 0.5%. The presence of the magnetic field affects the dose at the interface depending upon the density of the material on either sides of the interface. This effect varies with the field size. For example, at the water-lung interface a 33.94% increase in dose was observed (relative to the D{sub max}), by both GPUMCD and GEANT4 for the field size of 2 × 2 cm{sup 2} (compared to no B-field case), which increased to 47.83% for the field size of 5 × 5 cm{sup 2} in the presence of the magnetic field. Similarly, at the lung-water interface, the dose decreased by 19.21% (relative to D{sub max}) for a field size of 2 × 2 cm{sup 2} and by 30.01% for 5 × 5 cm{sup 2} field size. For more complex combinations of materials the dose deposition also becomes more complex. Conclusions: The GPUMCD algorithm showed good agreement against GEANT4 both in the presence and absence of a 1.5 T external magnetic field. The application of 1.5 T magnetic field significantly alters the dose at the interfaces by either increasing or decreasing the dose depending upon the density of the material on either side of the interfaces.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

SU-C-BRC-04: Efficient Dose Calculation Algorithm for FFF IMRT with a Simplified Bivariate Gaussian Source Model

Purpose: To develop an efficient and accurate independent dose calculation algorithm with a simplified analytical source model for the quality assurance and safe delivery of Flattening Filter Free (FFF)-IMRT on an Elekta Versa HD. Methods: The source model consisted of a point source and a 2D bivariate Gaussian source, respectively modeling the primary photons and the combined effect of head scatter, monitor chamber backscatter and collimator exchange effect. The in-air fluence was firstly calculated by back-projecting the edges of beam defining devices onto the source plane and integrating the visible source distribution. The effect of the rounded MLC leaf end, tongue-and-groove and interleaf transmission was taken into account in the back-projection. The in-air fluence was then modified with a fourth degree polynomial modeling the cone-shaped dose distribution of FFF beams. Planar dose distribution was obtained by convolving the in-air fluence with a dose deposition kernel (DDK) consisting of the sum of three 2D Gaussian functions. The parameters of the source model and the DDK were commissioned using measured in-air output factors (Sc) and cross beam profiles, respectively. A novel method was used to eliminate the volume averaging effect of ion chambers in determining the DDK. Planar dose distributions of five head-and-neck FFF-IMRT plans were calculated and compared against measurements performed with a 2D diode array (MapCHECK™) to validate the accuracy of the algorithm. Results: The proposed source model predicted Sc for both 6MV and 10MV with an accuracy better than 0.1%. With a stringent gamma criterion (2%/2mm/local difference), the passing rate of the FFF-IMRT dose calculation was 97.2±2.6%. Conclusion: The removal of the flattening filter represents a simplification of the head structure which allows the use of a simpler source model for very accurate dose calculation. The proposed algorithm offers an effective way to ensure the safe delivery of FFF-IMRT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-P-39: End-To-End Validation of a 6 MV High Dose Rate Photon Beam, Configured for Eclipse AAA Algorithm Using Golden Beam Data, for SBRT Treatments Using RapidArc

Purpose: To use end-to-end testing to validate a 6 MV high dose rate photon beam, configured for Eclipse AAA algorithm using Golden Beam Data (GBD), for SBRT treatments using RapidArc. Methods: Beam data was configured for Varian Eclipse AAA algorithm using the GBD provided by the vendor. Transverse and diagonals dose profiles, PDDs and output factors down to a field size of 2×2 cm2 were measured on a Varian Trilogy Linac and compared with GBD library using 2% 2mm 1D gamma analysis. The MLC transmission factor and dosimetric leaf gap were determined to characterize the MLC in Eclipse. Mechanical and dosimetric tests were performed combining different gantry rotation speeds, dose rates and leaf speeds to evaluate the delivery system performance according to VMAT accuracy requirements. An end-to-end test was implemented planning several SBRT RapidArc treatments on a CIRS 002LFC IMRT Thorax Phantom. The CT scanner calibration curve was acquired and loaded in Eclipse. PTW 31013 ionization chamber was used with Keithley 35617EBS electrometer for absolute point dose measurements in water and lung equivalent inserts. TPS calculated planar dose distributions were compared to those measured using EPID and MapCheck, as an independent verification method. Results were evaluated with gamma criteria of 2% dose difference and 2mm DTA for 95% of points. Results: GBD set vs. measured data passed 2% 2mm 1D gamma analysis even for small fields. Machine performance tests show results are independent of machine delivery configuration, as expected. Absolute point dosimetry comparison resulted within 4% for the worst case scenario in lung. Over 97% of the points evaluated in dose distributions passed gamma index analysis. Conclusion: Eclipse AAA algorithm configuration of the 6 MV high dose rate photon beam using GBD proved efficient. End-to-end test dose calculation results indicate it can be used clinically for SBRT using RapidArc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-85: Evaluation of the Velocity Deformable Image Registration Algorithm

Purpose: To perform validation and commissioning of a commercial deformable image registration (DIR) algorithm (Velocity, Varian Medical Systems) for numerous clinical sites using single and multi-modality images. Methods: In this retrospective study, the DIR algorithm was evaluated for 10 patients in each of the following body sites: head and neck (HN), prostate, liver, and gynecological (GYN). HN DIRs were evaluated from planning (p)CT to re-pCT and pCTs to daily CBCTs using dice similarity coefficients (DSC) of corresponding anatomical structures. Prostate DIRs were evaluated from pCT to CBCTs using DSC and target registration error (TRE) of implanted RF beacons within the prostate. Liver DIRs were evaluated from pMR to pCT using DSC and TRE of vessel bifurcations. GYN DIRs were evaluated between fractionated brachytherapy MRIs using DSC of corresponding anatomical structures. Results: Analysis to date has given average DSCs for HN pCT-to-(re)pCT DIR for the brainstem, cochleas, constrictors, spinal canal, cord, esophagus, larynx, parotids, and submandibular glands as 0.88, 0.65, 0.67, 0.91, 0.77, 0.69, 0.77, 0.87, and 0.71, respectively. Average DSCs for HN pCT-to-CBCT DIR for the constrictors, spinal canal, esophagus, larynx, parotids, and submandibular glands were 0.64, 0.90, 0.62, 0.82, 0.75, and 0.69, respectively. For prostate pCT-to-CBCT DIR the DSC for the bladder, femoral heads, prostate, and rectum were 0.71, 0.82, 0.69, and 0.61, respectively. Average TRE using implanted beacons was 3.35 mm. For liver pCT-to-pMR, the average liver DSC was 0.94 and TRE was 5.26 mm. For GYN MR-to-MR DIR the DSC for the bladder, sigmoid colon, GTV, and rectum were 0.79, 0.58, 0.67, and 0.76, respectively. Conclusion: The Velocity DIR algorithm has been evaluated over a number of anatomical sites. This work functions to document the uncertainties in the DIR in the commissioning process so that these can be accounted for in the development of downstream clinical processes. This work was supported in part by a co-development agreement with Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-115: Target Volume and Artifact Evaluation of a New Device-Less 4D CT Algorithm

Purpose: 4DCT is often used in radiation therapy treatment planning to define the extent of motion of the visible tumor (IGTV). Recent available software allows 4DCT images to be created without the use of an external motion surrogate. This study aims to compare this device-less algorithm to a standard device-driven technique (RPM) in regards to artifacts and the creation of treatment volumes. Methods: 34 lung cancer patients who had previously received a cine 4DCT scan on a GE scanner with an RPM determined respiratory signal were selected. Cine images were sorted into 10 phases based on both the RPM signal and the device-less algorithm. Contours were created on standard and device-less maximum intensity projection (MIP) images using a region growing algorithm and manual adjustment to remove other structures. Variations in measurements due to intra-observer differences in contouring were assessed by repeating a subset of 6 patients 2 additional times. Artifacts in each phase image were assessed using normalized cross correlation at each bed position transition. A score between +1 (artifacts “better” in all phases for device-less) and −1 (RPM similarly better) was assigned for each patient based on these results. Results: Device-less IGTV contours were 2.1 ± 1.0% smaller than standard IGTV contours (not significant, p = 0.15). The Dice similarity coefficient (DSC) was 0.950 ± 0.006 indicating good similarity between the contours. Intra-observer variation resulted in standard deviations of 1.2 percentage points in percent volume difference and 0.005 in DSC measurements. Only two patients had improved artifacts with RPM, and the average artifact score (0.40) was significantly greater than zero. Conclusion: Device-less 4DCT can be used in place of the standard method for target definition due to no observed difference between standard and device-less IGTVs. Phase image artifacts were significantly reduced with the device-less method.

60 APPLIED LIFE SCIENCES↗