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DOE OSTI2014

SU-E-I-82: Improving CT Image Quality for Radiation Therapy Using Iterative Reconstruction Algorithms and Slightly Increasing Imaging Doses

Purpose: Iterative reconstruction (IR) algorithms are developed to improve CT image quality (IQ) by reducing noise without diminishing spatial resolution or contrast. For CT in radiation therapy (RT), slightly increasing imaging dose to improve IQ may be justified if it can substantially enhance structure delineation. The purpose of this study is to investigate and to quantify the IQ enhancement as a result of increasing imaging doses and using IR algorithms. Methods: CT images were acquired for phantoms, built to evaluate IQ metrics including spatial resolution, contrast and noise, with a variety of imaging protocols using a CT scanner (Definition AS Open, Siemens) installed inside a Linac room. Representative patients were scanned once the protocols were optimized. Both phantom and patient scans were reconstructed using the Sinogram Affirmed Iterative Reconstruction (SAFIRE) and the Filtered Back Projection (FBP) methods. IQ metrics of the obtained CTs were compared. Results: IR techniques are demonstrated to preserve spatial resolution as measured by the point spread function and reduce noise in comparison to traditional FBP. Driven by the reduction in noise, the contrast to noise ratio is doubled by adopting the highest SAFIRE strength. As expected, increasing imaging dose reduces noise for both SAFIRE and FBP reconstructions. The contrast to noise increases from 3 to 5 by increasing the dose by a factor of 4. Similar IQ improvement was observed on the CTs for selected patients with pancreas and prostrate cancers. Conclusion: The IR techniques produce a measurable enhancement to CT IQ by reducing the noise. Increasing imaging dose further reduces noise independent of the IR techniques. The improved CT enables more accurate delineation of tumors and/or organs at risk during RT planning and delivery guidance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-I-92: Is Photon Starvation Preventing Metal Artifact Reduction Algorithm From Working in KVCT?

Purpose: High density/high atomic number metallic objects create shading and streaking metal artifacts in the CT image that can cause inaccurate delineation of anatomical structures or inaccurate radiation dose calculation. A modified iterative maximum-likelihood polychromatic algorithm for CT (mIMPACT) that models the energy response of detectors, photon interaction processes and beam polychromaticity has successfully reduced metal artifacts in MVCT. Our extension of mIMPACT in kVCT did not significantly reduce metal artifacts for high density metal like steel. We hypothesize that photon starvation may result in the measured data in a commercial kVCT imaging beam. Methods: We measured attenuation of a range of steel plate thicknesses, sandwiched between two 12cm thick solid water blocks, using a Phillips Big Bore CTTM scanner in scout acquisition mode with 120kVp and 200mAs. The transmitted signal (y) was normalized to the air scan signal (y{sub 0}) to get attenuation [i.e., ln(y/y{sub 0})] data for a detector. Results: Below steel plate thickness of 13.4mm, the variations in measured attenuation as a function of view number are characterized by a quantum noise and show increased attenuation with metal thickness. On or above this thickness the attenuation shows discrete levels in addition to the quantum noise. Some views have saturated attenuation value. The histograms of the measured attenuation for up to 36.7mm of steel show this trend. The detector signal is so small that the quantization levels in the analog to digital (A-to-D) converter are visible, a clear indication of photon starvation. Conclusion: Photons reaching the kVCT detector after passing through a thick metal plate are either so low in number that the signal measured has large quantum noise, or are completely absorbed inside the plate creating photon starvation. This is un-interpretable by the mIMPACT algorithm and cannot reduce metal artifacts in kVCT for certain realistic thicknesses of steel hip implants. Moti Raj Paudel is supported by the Vanier Canada Graduate Scholarship, the Endowed Graduate Scholarship in Oncology and the Dissertation Fellowship at the University of Alberta. The authors acknowledge the CIHR operating grant number MOP 53254.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

SU-E-J-23: An Accurate Algorithm to Match Imperfectly Matched Images for Lung Tumor Detection Without Markers

Purpose: In order to locate lung tumors on projection images without internal markers, digitally reconstructed radiograph (DRR) is created and compared with projection images. Since lung tumors always move and their locations change on projection images while they are static on DRRs, a special DRR (background DRR) is generated based on modified anatomy from which lung tumors are removed. In addition, global discrepancies exist between DRRs and projections due to their different image originations, scattering, and noises. This adversely affects comparison accuracy. A simple but efficient comparison algorithm is reported. Methods: This method divides global images into a matrix of small tiles and similarities will be evaluated by calculating normalized cross correlation (NCC) between corresponding tiles on projections and DRRs. The tile configuration (tile locations) will be automatically optimized to keep the tumor within a single tile which has bad matching with the corresponding DRR tile. A pixel based linear transformation will be determined by linear interpolations of tile transformation results obtained during tile matching. The DRR will be transformed to the projection image level and subtracted from it. The resulting subtracted image now contains only the tumor. A DRR of the tumor is registered to the subtracted image to locate the tumor. Results: This method has been successfully applied to kV fluoro images (about 1000 images) acquired on a Vero (Brainlab) for dynamic tumor tracking on phantom studies. Radiation opaque markers are implanted and used as ground truth for tumor positions. Although, other organs and bony structures introduce strong signals superimposed on tumors at some angles, this method accurately locates tumors on every projection over 12 gantry angles. The maximum error is less than 2.6 mm while the total average error is 1.0 mm. Conclusion: This algorithm is capable of detecting tumor without markers despite strong background signals.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-142: Performance Study of Automatic Image-Segmentation Algorithms in Motion Tracking Via MR-IGRT

Purpose: Evaluate commonly used segmentation algorithms on a commercially available real-time MR image guided radiotherapy (MR-IGRT) system (ViewRay), compare the strengths and weaknesses of each method, with the purpose of improving motion tracking for more accurate radiotherapy. Methods: MR motion images of bladder, kidney, duodenum, and liver tumor were acquired for three patients using a commercial on-board MR imaging system and an imaging protocol used during MR-IGRT. A series of 40 frames were selected for each case to cover at least 3 respiratory cycles. Thresholding, Canny edge detection, fuzzy k-means (FKM), k-harmonic means (KHM), and reaction-diffusion level set evolution (RD-LSE), along with the ViewRay treatment planning and delivery system (TPDS) were included in the comparisons. To evaluate the segmentation results, an expert manual contouring of the organs or tumor from a physician was used as a ground-truth. Metrics value of sensitivity, specificity, Jaccard similarity, and Dice coefficient were computed for comparison. Results: In the segmentation of single image frame, all methods successfully segmented the bladder and kidney, but only FKM, KHM and TPDS were able to segment the liver tumor and the duodenum. For segmenting motion image series, the TPDS method had the highest sensitivity, Jarccard, and Dice coefficients in segmenting bladder and kidney, while FKM and KHM had a slightly higher specificity. A similar pattern was observed when segmenting the liver tumor and the duodenum. The Canny method is not suitable for consistently segmenting motion frames in an automated process, while thresholding and RD-LSE cannot consistently segment a liver tumor and the duodenum. Conclusion: The study compared six different segmentation methods and showed the effectiveness of the ViewRay TPDS algorithm in segmenting motion images during MR-IGRT. Future studies include a selection of conformal segmentation methods based on image/organ-specific information, different filtering methods and their influences on the segmentation results. Parag Parikh receives research grant from ViewRay. Sasa Mutic has consulting and research agreements with ViewRay. Yanle Hu receives travel reimbursement from ViewRay. Iwan Kawrakow and James Dempsey are ViewRay employees.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-81: Comparison of Microdosimetric Quantities Calculated Using the Track Structure Monte Carlo Algorithms Geant4-DNA and NOREC

Purpose: Microdosimetric quantities, such as the lineal energy, have been shown to correlate with the biological response to radiation and the relative biological effect of different radiation types. Track-structure Monte Carlo simulations are an important tool for investigating these responses and for developing mechanistic models to explain them. However, some of the cross-sectional data used in these algorithms has large uncertainties; thus, it is important to investigate how the implementation of the different codes affects the quantities of interest. Methods: Two of the most widely-used publicly available track-structure Monte Carlo codes, Geant4-DNA and NOREC, were used generate electron tracks for two particle sources. One source was a mono-energetic parallel beam of electrons with energies from 5 to 500-keV, and the lineal energy for each track was calculated in 1-mm-spheres arranged in planar arrays at multiple distances from the source. The second source was mono-energetic, uniformly-distributed, and isotropic source, and the lineal energy was scored in a single 30-mm-sphere for energies between 300-eV and 5-keV. Results: The dose-mean lineal energy for the parallel-beam simulations almost all agreed within 5%. For the uniformly-distributed source, at the lowest energies there was strong agreement between the algorithms, but the Geant4-DNA simulations showed slightly more high-energy events for more energetic electrons, but the dose-mean lineal energy agreed to within 4% for all energies. Conclusion: While there were slight differences in the results between the codes, these were consistent with previous studies of the stopping power and angular scattering distributions. Importantly, the computation time for Geant4-DNA was larger than for NOREC, largely due to approximations used in the NOREC for energies below 10-eV. This study shows that these approximation does not have a major impact on the microdosimetry on the energy and length scales investigated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

SU-E-T-164: Evaluation of Electron Dose Distribution Using Two Algorithms

Purpose: To appreciate the difference of electron dose distributions calculated from the Monte Carlo and Electron 3D algorithms of radiotherapy in a heterogeneous phantom. Methods: A phantom consisted of two different materials (lungs mimicked by low-density cork and others by polystyrene) with an 11x16 cm field size (SSD = 100 cm) was utilized to estimate the two-dimensional dose distributions under 6 and 18 MeV beams. On behalf of two different types of tissue, the heterogeneous phantom was comprised of 3 identical slabs in the longitudinal direction with a thickness of 1 cm for each slab and 2 with a thickness of 2.5 cm. The Monte Carlo/MCTP application package constituted of five codes was performed to simulate the electron beams of a Varian Clinac 23IX. A 20x20 cm2 type III (open walled) applicator was used in these simulations. It has been shown elsewhere that the agreement of the phase space data between the calculation results of MCTP application package and the measured data were within 2% on depth-dose and transverse profiles, as well as output factor calculations. The electron 3D algorithm owned by Pinnacle 8.0m and the MCTP application package were applied for the two-dimensional dose distributions calculation. The curves at 50% and 100%-prescribed dose were observed for 6 and 18 MeV beams, respectively. Results: The MC calculations results were compared with the electron 3D calculations in terms of two-dimensional dose distributions for 6 and 18 MeV beams showed excellent agreement except in distal boundary where it was the very junction of the high and low-density region. Conclusions: The Monte Carlo/MCTP method could be used to better reflect the dose variation caused by heterogeneous tissues. Conclusion: A case study showed that the Monte Carlo/MCTP method could be used to better reflect the dose variation caused by heterogeneous tissues.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-165: Evaluation of Inhomogeneity Calculations for Electron Beams in Raystation Monte Carlo Algorithm

Purpose: To evaluate the accuracy of the Raystation electron Monte Carlo algorithm for bone and air inhomogeneity. Methods: A solid water phantom slab was drilled to contain two openings of 1.3cm diameter, 0.6cm apart. The center of the opening is at 1cm depth from the surface. Two Teflon rods of exact same diameter were inserted to investigate bone inhomogeneity. Slab is 2cm total in thickness and was placed on top of 10cm solid water. Plans were created in Raystation with clinical settings previously established for 6, 9, 12, 15 and 18MeV Elekta Infinity beams. Coronal profiles were extracted posteriorly to the inhomogeneity. EBT3 films were irradiated under the same conditions and analyzed using FilmQAPro using the red channel. Calibration films were used for all energies. Same plans and films were performed for a Varian accelerator with same energies and Eclipse Monte Carlo. Results: Air Inhomogeneities: For lower energies, Raystation- Film agreement is less than 1% for the regions of the air cavity. In the lateral interface border, Raystation underestimates dose by approximately 2%. Eclipse results are similar. For higher energies, Raystation-Film agreement remains the same across the air cavity and interface. Eclipse-Film difference increases with energy up to 5% for 18MeV, with Eclipse calculating higher doses than the film at the interface. Bone Inhomogeneities: For lower energies, Raystation underestimates the dose behind the bone up to 12%. Eclipse underestimates the dose in the same area up to 18%. For higher energies, the dose difference behind the bone decreases to 1% for Raystation and 3% for Eclipse. At the lateral interface, Raystation underestimates the dose by 2.2% and Eclipse underestimates the dose by 5%. Conclusion: Raystation prediction for air and bone is acceptable. Maximum deviations are consistent with algorithm limitations. Differences between calculations and measurement are closer for Raystation than for Eclipse.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TU-A-9A-03: Development and Verification of a Forward Model That Assists in Iterative Post-Processing Algorithms Used to Reduce Blur in Compton Backscatter Imaging Systems

Purpose: In Compton Backscatter Imaging (CBI), the source and detector reside on the same side of the patient. We previously demonstrated the applicability of CBI systems for medical purposes using an industrial system. To assist in post-processing images from a CBI system, a forward model based on radiation absorption and scatter principles has been developed. Methods: The forward model was developed in C++ using raytracing to track particles. The algorithm accepts phantoms of any size and resolution to calculate the fraction of incident photons scattered back to the detector, and can perform these calculations for any detector geometry and source specification. To validate the model, results were compared to MCNP-X, which is a Monte Carlo based simulation software, for various combinations of source specifications, detector geometries, and phantom compositions. Results: The model verified that the backscatter signal to the detector was based on three interaction probabilities: a) attenuation of photons going into the phantom, b) Compton scatter of photons toward the detector, and c) attenuation of photons coming out of the phantom. The results from the MCNP-X simulations and the forward model varied from 1 to 5%. This difference was less than 1% for energies higher than 30 keV, but was up to 4% for lower energies. At 50 keV, the difference was less than 1% for multiple detector widths and for both homogeneous and heterogeneous phantoms. Conclusion: As part of the optimization of a medical CBI system, an efficient and accurate forward model was constructed in C++ to estimate the output of CBI system. The model characterized individual components contributing to CBI output and increased computational efficiency over Monte Carlo simulations. It is now used in the development of novel post-processing algorithms that reduce image blur by reversing undesired contribution from outside the region of interest.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2014

TU-F-18A-04: Use of An Image-Based Material-Decomposition Algorithm for Multi-Energy CT to Determine Basis Material Densities

Purpose: Published methods for image-based material decomposition with multi-energy CT images have required the assumption of volume conservation or accurate knowledge of the x-ray spectra and detector response. The purpose of this work was to develop an image-based material-decomposition algorithm that can overcome these limitations. Methods: An image-based material decomposition algorithm was developed that requires only mass conservation (rather than volume conservation). With this method, using multi-energy CT measurements made with n=4 energy bins, the mass density of each basis material and of the mixture can be determined without knowledge of the tube spectra and detector response. A digital phantom containing 12 samples of mixtures from water, calcium, iron, and iodine was used in the simulation (Siemens DRASIM). The calibration was performed by using pure materials at each energy bin. The accuracy of the technique was evaluated in noise-free and noisy data under the assumption of an ideal photon-counting detector. Results: Basis material densities can be estimated accurately by either theoretic calculation or calibration with known pure materials. The calibration approach requires no prior information about the spectra and detector response. Regression analysis of theoretical values versus estimated values results in excellent agreement for both noise-free and noisy data. For the calibration approach, the R-square values are 0.9960+/−0.0025 and 0.9476+/−0.0363 for noise-free and noisy data, respectively. Conclusion: From multi-energy CT images with n=4 energy bins, the developed image-based material decomposition method accurately estimated 4 basis material density (3 without k-edge and 1 with in the range of the simulated energy bins) even without any prior information about spectra and detector response. This method is applicable to mixtures of solutions and dissolvable materials, where volume conservation assumptions do not apply. CHM receives research support from NIH and Siemens Healthcare.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Poster — Thur Eve — 07: Simultaneous reconstruction of both true and scattered coincidences using a Generalized Scatter reconstruction algorithm in PET

Introduction: Scattered coincidences in PET are generally taken as noise, which reduces image contrast and compromises quantification. We have developed a method, with promising results, to reconstruct activity distribution from scattered PET events instead of simply correcting for them. The implementation of this method on clinical PET scanners is however limited by the currently available detector energy resolution. With low energy resolution we lose the ability to distinguish scattered coincidences from true events based on the measured photon energy. In addition the two circular arcs used to confine the source position for a scattered event cannot be accurately defined. Method: This paper presents a modification to this approach which accounts for limited energy resolution. A measured event is split into a true and a scattered component each with different probabilities based on the position of the pair of photon energies in the energy spectrum. For the scattered component, we model the photon energy with a Gaussian distribution and the upper and lower energy limits can be estimated and used to define inner and outer circular arcs to confine the source position. The true and scattered components for each measured event were reconstructed using our Generalized Scatter reconstruction algorithm. Results and Conclusion: The results show that the contrast and noise properties were improved by 6–9% and 2–4% respectively. This demonstrates that the performance of the algorithm is less sensitive to the energy resolution and that incorporating scattered photons into reconstruction brings more benefits than simply rejecting them.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Poster — Thur Eve — 09: Evaluation of electrical impedance and computed tomography fusion algorithms using an anthropomorphic phantom

Integration of biological conductivity information provided by Electrical Impedance Tomography (EIT) with anatomical information provided by Computed Tomography (CT) imaging could improve the ability to characterize tissues in clinical applications. In this paper, we report results of our study which compared the fusion of EIT with CT using three different image fusion algorithms, namely: weighted averaging, wavelet fusion, and ROI indexing. The ROI indexing method of fusion involves segmenting the regions of interest from the CT image and replacing the pixels with the pixels of the EIT image. The three algorithms were applied to a CT and EIT image of an anthropomorphic phantom, constructed out of five acrylic contrast targets with varying diameter embedded in a base of gelatin bolus. The imaging performance was assessed using Detectability and Structural Similarity Index Measure (SSIM). Wavelet fusion and ROI-indexing resulted in lower Detectability (by 35% and 47%, respectively) yet higher SSIM (by 66% and 73%, respectively) than weighted averaging. Our results suggest that wavelet fusion and ROI-indexing yielded more consistent and optimal fusion performance than weighted averaging.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

SU-E-I-04: Improving CT Quality for Radiation Therapy of Patients with High Body Mass Index Using Iterative Reconstruction Algorithms

Purpose: Iterative reconstruction (IR) algorithms are developed to improve CT image quality (IQ) by reducing noise without diminishing spatial resolution or contrast. The CT IQ for patients with a high Body Mass Index (BMI) can suffer from increased noise due to photon starvation. The purpose of this study is to investigate and to quantify the IQ enhancement for high BMI patients through the application of IR algorithms. Methods: CT raw data collected for 6 radiotherapy (RT) patients with BMI, greater than or equal to 30 were retrospectively analyzed. All CT data were acquired using a CT scanner (Somaton Definition AS Open, Siemens) installed in a linac room (CT-on-rails) using standard imaging protocols. The CT data were reconstructed using the Sinogram Affirmed Iterative Reconstruction (SAFIRE) and Filtered Back Projection (FBP) methods. IQ metrics of the obtained CTs were compared and correlated with patient depth and BMI. The patient depth was defined as the largest distance from anterior to posterior along the bilateral symmetry axis. Results: IR techniques are demonstrated to preserve contrast and reduce noise in comparison to traditional FBP. Driven by the reduction in noise, the contrast to noise ratio is roughly doubled by adopting the highest SAFIRE strength. A significant correlation was observed between patient depth and IR noise reduction through Pearson’s correlation test (R = 0.9429/P = 0.0167). The mean patient depth was 30.4 cm and the average relative noise reduction for the strongest iterative reconstruction was 55%. Conclusion: The IR techniques produce a measureable enhancement to CT IQ by reducing the noise. Dramatic noise reduction is evident for the high BMI patients. The improved CT IQ enables more accurate delineation of tumors and organs at risk and more accuarte dose calculations for RT planning and delivery guidance. Supported by Siemens.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-203: Comparison of a Commercial MRI-Linear Accelerator Based Monte Carlo Dose Calculation Algorithm and Geant4

Purpose: An MRI-linear accelerator is currently being developed by the vendor Elekta™. The treatment planning system that will be used to model dose for this unit uses a Monte Carlo dose calculation algorithm, GPUMCD, that allows for the application of a magnetic field. We tested this radiation transport code against an independent Monte-Carlo toolkit Geant4 (v.4.10.01) both with and without the magnetic field applied. Methods: The setup comprised a 6 MeV mono-energetic photon beam emerging from a point source impinging on a homogeneous water phantom at 100 cm SSD. The comparisons were drawn from the percentage depth doses (PDD) for three different field sizes (1.5 x 1.5 cm{sup 2}, 5 x 5 cm{sup 2}, 10 x 10 cm{sup 2}) and dose profiles at various depths. A 1.5 T magnetic field was applied perpendicular to the direction of the beam. The transport thresholds were kept the same for both codes. Results: All of the normalized PDDs and profiles agreed within ± 1 %. In the presence of the magnetic field, PDDs rise more quickly reducing the depth of maximum dose. Near the beam exit point in the phantom a hot spot is created due to the electron return effect. This effect is more pronounced for the larger field sizes. Profiles selected parallel to the external field show no effect, however, the ones selected perpendicular to the direction of the applied magnetic field are shifted towards the direction of the Lorentz force applied by the magnetic field on the secondary electrons. It is observed that these profiles are not symmetric which indicates a lateral build up of the dose. Conclusion: There is a good general agreement between the PDDs/profiles calculated by both algorithms thus far. We are proceeding towards clinically relevant comparisons in a heterogeneous phantom for polyenergetic beams. Funding for this work has been provided by Elekta.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-290: Dosimetric Accuracy of Acuros XB and Analytical Anisotropic Algorithm in Stereotactic Ablative Radiotherapy of Small Lung Lesions

Purpose: The accuracy of dose calculation for lung stereotactic ablative radiotherapy (SABR) of small lesions critically depends on the proper modeling of the lateral scatter in heterogeneous media. In recent years, grid-based Boltzman solvers such as Acuros XB (AXB) have been introduced for enhanced modeling of radiation transport in heterogeneous media. The purpose of this study is to evaluate the dosimetric impact of dose calculation between AXB and convolution-superposition algorithms such as analytical anisotropic algorithm (AAA) for small lesion sizes and different beam energies. Methods: Five lung SABR VMAT cases with GTV ranged from 0.8cm to 2.5cm in diameter were studied. For each case, doses were calculated by AAA, AXB (V11031) and Monte Carlo simulation (MC) with the same plan parameters for 10MV and 6MV. The dose calculation accuracy were evaluated by comparing DVHs and dose distributions with MC as the benchmark. The accuracy of calculated dose was also validated by EBT3 film measurement with a field size of 3cmx3cm in a thorax phantom. Results: For 10MV and GTV less than 1cm, dose calculated by AXB agrees well with MC compared to AAA. Dose difference calculated with AXB and AAA could be up to 30%. For GTV greater than 2cm, calculation results of AXB and AAA agree within 5% in GTV. For 6MV, the difference between calculated doses by AXB and AAA is less 10% for GTV less than 1cm. Based on film measurements, lung dose was overestimated 10% and 20% by AAA for 6MV and 10MV. Conclusion: Lateral scatter and transport is modeled more accurately by AXB than AAA in heterogeneous media, especially for small field size and high energy beams. The accuracy depends on the assigned material in calculation. If grid-based Boltzman solvers or MC are not available for calculation, lower energy beams should be used for treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-397: Evaluation of Planned Dose Distributions by Monte Carlo (0.5%) and Ray Tracing Algorithm for the Spinal Tumors with CyberKnife

Purpose: To analyze and evaluate dose distribution between Ray Tracing (RT) and Monte Carlo (MC) algorithms of 0.5% uncertainty on a critical structure of spinal cord and gross target volume and planning target volume. Methods: Twenty four spinal tumor patients were treated with stereotactic body radiotherapy (SBRT) by CyberKnife in 2013 and 2014. The MC algorithm with 0.5% of uncertainty is used to recalculate the dose distribution for the treatment plan of the patients using the same beams, beam directions, and monitor units (MUs). Results: The prescription doses are uniformly larger for MC plans than RT except one case. Up to a factor of 1.19 for 0.25cc threshold volume and 1.14 for 1.2cc threshold volume of dose differences are observed for the spinal cord. Conclusion: The MC recalculated dose distributions are larger than the original MC calculations for the spinal tumor cases. Based on the accuracy of the MC calculations, more radiation dose might be delivered to the tumor targets and spinal cords with the increase prescription dose.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-800: Verification of Acurose XB Dose Calculation Algorithm at Air Cavity-Tissue Interface Using Film Measurement for Small Fields of 6-MV Flattening Filter-Free Beams

Purpose: To verify the dose accuracy of Acuros XB (AXB) dose calculation algorithm at air-tissue interface using inhomogeneous phantom for 6-MV flattening filter-free (FFF) beams. Methods: An inhomogeneous phantom included air cavity was manufactured for verifying dose accuracy at the air-tissue interface. The phantom was composed with 1 and 3 cm thickness of air cavity. To evaluate the central axis doses (CAD) and dose profiles of the interface, the dose calculations were performed for 3 × 3 and 4 × 4 cm{sup 2} fields of 6 MV FFF beams with AAA and AXB in Eclipse treatment plainning system. Measurements in this region were performed with Gafchromic film. The root mean square errors (RMSE) were analyzed with calculated and measured dose profile. Dose profiles were divided into inner-dose profile (>80%) and penumbra (20% to 80%) region for evaluating RMSE. To quantify the distribution difference, gamma evaluation was used and determined the agreement with 3%/3mm criteria. Results: The percentage differences (%Diffs) between measured and calculated CAD in the interface, AXB shows more agreement than AAA. The %Diffs were increased with increasing the thickness of air cavity size and it is similar for both algorithms. In RMSEs of inner-profile, AXB was more accurate than AAA. The difference was up to 6 times due to overestimation by AAA. RMSEs of penumbra appeared to high difference for increasing the measurement depth. Gamma agreement also presented that the passing rates decreased in penumbra. Conclusion: This study demonstrated that the dose calculation with AXB shows more accurate than with AAA for the air-tissue interface. The 2D dose distributions with AXB for both inner-profile and penumbra showed better agreement than with AAA relative to variation of the measurement depths and air cavity sizes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-F-BRD-09: A Random Walk Model Algorithm for Proton Dose Calculation

Purpose: To develop a random walk model algorithm for calculating proton dose with balanced computation burden and accuracy. Methods: Random walk (RW) model is sometimes referred to as a density Monte Carlo (MC) simulation. In MC proton dose calculation, the use of Gaussian angular distribution of protons due to multiple Coulomb scatter (MCS) is convenient, but in RW the use of Gaussian angular distribution requires an extremely large computation and memory. Thus, our RW model adopts spatial distribution from the angular one to accelerate the computation and to decrease the memory usage. From the physics and comparison with the MC simulations, we have determined and analytically expressed those critical variables affecting the dose accuracy in our RW model. Results: Besides those variables such as MCS, stopping power, energy spectrum after energy absorption etc., which have been extensively discussed in literature, the following variables were found to be critical in our RW model: (1) inverse squared law that can significantly reduce the computation burden and memory, (2) non-Gaussian spatial distribution after MCS, and (3) the mean direction of scatters at each voxel. In comparison to MC results, taken as reference, for a water phantom irradiated by mono-energetic proton beams from 75 MeV to 221.28 MeV, the gamma test pass rate was 100% for the 2%/2mm/10% criterion. For a highly heterogeneous phantom consisting of water embedded by a 10 cm cortical bone and a 10 cm lung in the Bragg peak region of the proton beam, the gamma test pass rate was greater than 98% for the 3%/3mm/10% criterion. Conclusion: We have determined key variables in our RW model for proton dose calculation. Compared with commercial pencil beam algorithms, our RW model much improves the dose accuracy in heterogeneous regions, and is about 10 times faster than MC simulations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-AB-BRA-08: Results of a Multi-Institutional Study for the Evaluation of Deformable Image Registration Algorithms for Structure Delineation Via Computational Phantoms

Purpose: To investigate the accuracy of various algorithms for deformable image registration (DIR), to propagate regions of interest (ROIs) in computational phantoms based on patient images using different commercial systems. This work is part of an Italian multi-institutional study to test on common datasets the accuracy, reproducibility and safety of DIR applications in Adaptive Radiotherapy. Methods: Eleven institutions with three available commercial solutions provided data to assess the agreement of DIR-propagated ROIs with automatically drown ROIs considered as ground-truth for the comparison. The DIR algorithms were tested on real patient data from three different anatomical districts: head and neck, thorax and pelvis. For every dataset two specific Deformation Vector Fields (DVFs) provided by ImSimQA software were applied to the reference data set. Three different commercial software were used in this study: RayStation, Velocity and Mirada. The DIR-mapped ROIs were then compared with the reference ROIs using the Jaccard Conformity Index (JCI). Results: More than 600 DIR-mapped ROIs were analyzed. Putting together all JCI data of all institutions for the first DVF, the mean JCI was 0.87 ± 0.7 (1 SD) while for the second DVF JCI was 0.8 ± 0.13 (1 SD). Several considerations on different structures are available from collected data: the standard deviation among different institutions on specific structure raise as the larger is the applied DVF. The higher value is 10% for bladder. Conclusion: Although the complexity of deformation of human body is very difficult to model, this work illustrates some clinical scenarios with well-known DVFs provided by specific software. CI parameter gives the inter-user variability and may put in evidence the need of improving the working protocol in order to reduce the inter-institution JCI variability.

60 APPLIED LIFE SCIENCES↗