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DOE OSTI2015

The ANACONDA algorithm for deformable image registration in radiotherapy

Purpose: The purpose of this work was to describe a versatile algorithm for deformable image registration with applications in radiotherapy and to validate it on thoracic 4DCT data as well as CT/cone beam CT (CBCT) data. Methods: ANAtomically CONstrained Deformation Algorithm (ANACONDA) combines image information (i.e., intensities) with anatomical information as provided by contoured image sets. The registration problem is formulated as a nonlinear optimization problem and solved with an in-house developed solver, tailored to this problem. The objective function, which is minimized during optimization, is a linear combination of four nonlinear terms: 1. image similarity term; 2. grid regularization term, which aims at keeping the deformed image grid smooth and invertible; 3. a shape based regularization term which works to keep the deformation anatomically reasonable when regions of interest are present in the reference image; and 4. a penalty term which is added to the optimization problem when controlling structures are used, aimed at deforming the selected structure in the reference image to the corresponding structure in the target image. Results: To validate ANACONDA, the authors have used 16 publically available thoracic 4DCT data sets for which target registration errors from several algorithms have been reported in the literature. On average for the 16 data sets, the target registration error is 1.17 ± 0.87 mm, Dice similarity coefficient is 0.98 for the two lungs, and image similarity, measured by the correlation coefficient, is 0.95. The authors have also validated ANACONDA using two pelvic cases and one head and neck case with planning CT and daily acquired CBCT. Each image has been contoured by a physician (radiation oncologist) or experienced radiation therapist. The results are an improvement with respect to rigid registration. However, for the head and neck case, the sample set is too small to show statistical significance. Conclusions: ANACONDA performs well in comparison with other algorithms. By including CT/CBCT data in the validation, the various aspects of the algorithm such as its ability to handle different modalities, large deformations, and air pockets are shown.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Poster — Thur Eve — 76: Dosimetric Comparison of Pinnacle and iPlan Algorithms with an Anthropomorphic Lung Phantom

Our goal is to compare the dosimetric accuracy of the Pinnacle-3 9.2 Collapsed Cone Convolution Superposition (CCCS) and the iPlan 4.1 Monte Carlo (MC) and Pencil Beam (PB) algorithms in an anthropomorphic lung phantom using measurement as the gold standard. Ion chamber measurements were taken for 6, 10, and 18 MV beams in a CIRS E2E SBRT Anthropomorphic Lung Phantom, which mimics lung, spine, ribs, and tissue. The plan implemented six beams with a 5×5 cm{sup 2} field size, delivering a total dose of 48 Gy. Data from the planning systems were computed at the treatment isocenter in the left lung, and two off-axis points, the spinal cord and the right lung. The measurements were taken using a pinpoint chamber. The best results between data from the algorithms and our measurements occur at the treatment isocenter. For the 6, 10, and 18 MV beams, iPlan 4.1 MC software performs the best with 0.3%, 0.2%, and 4.2% absolute percent difference from measurement, respectively. Differences between our measurements and algorithm data are much greater for the off-axis points. The best agreement seen for the right lung and spinal cord is 11.4% absolute percent difference with 6 MV iPlan 4.1 PB and 18 MV iPlan 4.1 MC, respectively. As energy increases absolute percent difference from measured data increases up to 54.8% for the 18 MV CCCS algorithm. This study suggests that iPlan 4.1 MC computes peripheral dose and target dose in the lung more accurately than the iPlan 4.1 PB and Pinnicale CCCS algorithms.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Development of a phantom to validate high-dose-rate brachytherapy treatment planning systems with heterogeneous algorithms

Purpose: This work presents the development of a phantom to verify the treatment planning system (TPS) algorithms used for high-dose-rate (HDR) brachytherapy. It is designed to measure the relative dose in a heterogeneous media. The experimental details used, simulation methods, and comparisons with a commercial TPS are also provided. Methods: To simulate heterogeneous conditions, four materials were used: Virtual Water™ (VM), BR50/50™, cork, and aluminum. The materials were arranged in 11 heterogeneity configurations. Three dosimeters were used to measure the relative response from a HDR {sup 192}Ir source: TLD-100™, Gafchromic{sup ®} EBT3 film, and an Exradin™ A1SL ionization chamber. To compare the results from the experimental measurements, the various configurations were modeled in the PENELOPE/penEasy Monte Carlo code. Images of each setup geometry were acquired from a CT scanner and imported into BrachyVision™ TPS software, which includes a grid-based Boltzmann solver Acuros™. The results of the measurements performed in the heterogeneous setups were normalized to the dose values measured in the homogeneous Virtual Water™ setup and the respective differences due to the heterogeneities were considered. Additionally, dose values calculated based on the American Association of Physicists in Medicine-Task Group 43 formalism were compared to dose values calculated with the Acuros™ algorithm in the phantom. Calculated doses were compared at the same points, where measurements have been performed. Results: Differences in the relative response as high as 11.5% were found from the homogeneous setup when the heterogeneous materials were inserted into the experimental phantom. The aluminum and cork materials produced larger differences than the plastic materials, with the BR50/50™ material producing results similar to the Virtual Water™ results. Our experimental methods agree with the PENELOPE/penEasy simulations for most setups and dosimeters. The TPS relative differences with the Acuros™ algorithm were similar in both experimental and simulated setups. The discrepancy between the BrachyVision™, Acuros™, and TG-43 dose responses in the phantom described by this work exceeded 12% for certain setups. Conclusions: The results derived from the phantom measurements show good agreement with the simulations and TPS calculations, using Acuros™ algorithm. Differences in the dose responses were evident in the experimental results when heterogeneous materials were introduced. These measurements prove the usefulness of the heterogeneous phantom for verification of HDR treatment planning systems based on model-based dose calculation algorithms.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

Improvement of registration accuracy in accelerated partial breast irradiation using the point-based rigid-body registration algorithm for patients with implanted fiducial markers

Purpose: To investigate image-registration errors when using fiducial markers with a manual method and the point-based rigid-body registration (PRBR) algorithm in accelerated partial breast irradiation (APBI) patients, with accompanying fiducial deviations. Methods: Twenty-two consecutive patients were enrolled in a prospective trial examining 10-fraction APBI. Titanium clips were implanted intraoperatively around the seroma in all patients. For image-registration, the positions of the clips in daily kV x-ray images were matched to those in the planning digitally reconstructed radiographs. Fiducial and gravity registration errors (FREs and GREs, respectively), representing resulting misalignments of the edge and center of the target, respectively, were compared between the manual and algorithm-based methods. Results: In total, 218 fractions were evaluated. Although the mean FRE/GRE values for the manual and algorithm-based methods were within 3 mm (2.3/1.7 and 1.3/0.4 mm, respectively), the percentages of fractions where FRE/GRE exceeded 3 mm using the manual and algorithm-based methods were 18.8%/7.3% and 0%/0%, respectively. Manual registration resulted in 18.6% of patients with fractions of FRE/GRE exceeding 5 mm. The patients with larger clip deviation had significantly more fractions showing large FRE/GRE using manual registration. Conclusions: For image-registration using fiducial markers in APBI, the manual registration results in more fractions with considerable registration error due to loss of fiducial objectivity resulting from their deviation. The authors recommend the PRBR algorithm as a safe and effective strategy for accurate, image-guided registration and PTV margin reduction.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-97: Quality Assurance of Deformable Image Registration Algorithms: How Realistic Should Phantoms Be?

Purpose: Deformable image registration (DIR) has widespread uses in radiotherapy for applications such as dose accumulation studies, multi-modality image fusion, and organ segmentation. The quality assurance (QA) of such algorithms, however, remains largely unimplemented. This work aims to determine how detailed a physical phantom needs to be to accurately perform QA of a DIR algorithm. Methods: Virtual prostate and head-and-neck phantoms, made from patient images, were used for this study. Both sets consist of an undeformed and deformed image pair. The images were processed to create additional image pairs with one through five homogeneous tissue levels using Otsu’s method. Realistic noise was then added to each image. The DIR algorithms from MIM and Velocity (Deformable Multipass) were applied to the original phantom images and the processed ones. The resulting deformations were then compared to the known warping. A higher number of tissue levels creates more contrast in an image and enables DIR algorithms to produce more accurate results. For this reason, error (distance between predicted and known deformation) is utilized as a metric to evaluate how many levels are required for a phantom to be a realistic patient proxy. Results: For the prostate image pairs, the mean error decreased from 1–2 tissue levels and remained constant for 3+ levels. The mean error reduction was 39% and 26% for Velocity and MIM respectively. For head and neck, mean error fell similarly through 2 levels and flattened with total reduction of 16% and 49% for Velocity and MIM. For Velocity, 3+ levels produced comparable accuracy as the actual patient images, whereas MIM showed further accuracy improvement. Conclusion: The number of tissue levels needed to produce an accurate patient proxy depends on the algorithm. For Velocity, three levels were enough, whereas five was still insufficient for MIM.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-252: Developing a Pencil Beam Dose Calculation Algorithm for CyberKnife System

Purpose: Currently there are two dose calculation algorithms available in the Cyberknife planning system: ray-tracing and Monte Carlo, which is either not accurate or time-consuming for irregular field shaped by the MLC that was recently introduced. The purpose of this study is to develop a fast and accurate pencil beam dose calculation algorithm which can handle irregular field. Methods: A pencil beam dose calculation algorithm widely used in Linac system is modified. The algorithm models both primary (short range) and scatter (long range) components with a single input parameter: TPR{sub 20}/{sub 10}. The TPR{sub 20}/{sub 20}/{sub 10} value was first estimated to derive an initial set of pencil beam model parameters (PBMP). The agreement between predicted and measured TPRs for all cones were evaluated using the root mean square of the difference (RMSTPR), which was then minimized by adjusting PBMPs. PBMPs are further tuned to minimize OCR RMS (RMSocr) by focusing at the outfield region. Finally, an arbitrary intensity profile is optimized by minimizing RMSocr difference at infield region. To test model validity, the PBMPs were obtained by fitting to only a subset of cones (4) and applied to all cones (12) for evaluation. Results: With RMS values normalized to the dmax and all cones combined, the average RMSTPR at build-up and descending region is 2.3% and 0.4%, respectively. The RMSocr at infield, penumbra and outfield region is 1.5%, 7.8% and 0.6%, respectively. Average DTA in penumbra region is 0.5mm. There is no trend found in TPR or OCR agreement among cones or depths. Conclusion: We have developed a pencil beam algorithm for Cyberknife system. The prediction agrees well with commissioning data. Only a subset of measurements is needed to derive the model. Further improvements are needed for TPR buildup region and OCR penumbra. Experimental validations on MLC shaped irregular field needs to be performed. This work was partially supported by the National Natural Science Foundation of China (61171005) and the China Scholarship Council (CSC)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-317: Dosimetric Evaluation of Acuros XB Advanced Dose Calculation Algorithm in Head and Neck Patients

Purpose: The Acuros XB photon dose calculation algorithm is a newly implemented calculation technique within the Eclipse treatment planning system using deterministic solutions to the linear Boltzmann transport equations. The goal of this study is to assess the clinical impact of dose differences arising from a retrospective comparison of calculations performed using the Analytical Anisotropic Algorithm (AAA) and Acuros XB on patients. Methods: Ten head and neck patients receiving intensity modulated radiation therapy were selected as a pilot study. Initial evaluation was based on the percentage of the planning target volume (PTV) covered by the prescription dose, minimum dose within the PTV, and dose differences in critical structures. For patients receiving boost plans, dosimetric evaluations were performed on the plan sum of the primary and boost plans. Results: Among the ten patients there were a total of 21 PTVs corresponding to primary and boost volumes. Using the same normalization within Eclipse, the average percentage of the PTVs receiving the prescription dose were 95.6% for AAA and Acuros XB. The average minimum doses within the PTVs, expressed as a percentage of the prescription to the volume, were 82.3% and 83.6% for AAA and Acuros XB respectively. Neither comparison showed differences with statistical significance when subjected to a paired t-test. Statistical significance was found in the average difference of the maximum dose for the mandible (242.5cGy, p=0.0005) and cord with a 5mm radial expansion (105.0cGy, p=0.0005) and in the median dose for the left parotid (25.0cGy, p=0.0423) and oral cavity (36.3cGy, p=0.002). Conclusion: The Acuros XB dose calculation algorithm did not exhibit significant differences in PTV coverage when compared to the AAA algorithm. Significant differences in critical structures are likely attributed to the structures proximity to high atomic number materials or air cavities, regions of known difficulty for the AAA algorithm.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-456: Impact of Dose Calculation Algorithms On Biologically Optimized VMAT Plans for Esophageal Cancer

Purpose: To evaluate the impact of dose calculation algorithm on the dose distribution of biologically optimized Volumatric Modulated Arc Therapy (VMAT) plans for Esophgeal cancer. Methods: Eighteen retrospectively treated patients with carcinoma esophagus were studied. VMAT plans were optimized using biological objectives in Monaco (5.0) TPS for 6MV photon beam (Elekta Infinity). These plans were calculated for final dose using Monte Carlo (MC), Collapsed Cone Convolution (CCC) & Pencil Beam Convolution (PBC) algorithms from Monaco and Oncentra Masterplan TPS. A dose grid of 2mm was used for all algorithms and 1% per plan uncertainty maintained for MC calculation. MC based calculations were considered as the reference for CCC & PBC. Dose volume histogram (DVH) indices (D95, D98, D50 etc) of Target (PTV) and critical structures were compared to study the impact of all three algorithms. Results: Beam models were consistent with measured data. The mean difference observed in reference with MC calculation for D98, D95, D50 & D2 of PTV were 0.37%, −0.21%, 1.51% & 1.18% respectively for CCC and 3.28%, 2.75%, 3.61% & 3.08% for PBC. Heart D25 mean difference was 4.94% & 11.21% for CCC and PBC respectively. Lung Dmean mean difference was 1.5% (CCC) and 4.1% (PBC). Spinal cord D2 mean difference was 2.35% (CCC) and 3.98% (PBC). Similar differences were observed for liver and kidneys. The overall mean difference found for target and critical structures was 0.71±1.52%, 2.71±3.10% for CCC and 3.18±1.55%, 6.61±5.1% for PBC respectively. Conclusion: We observed a significant overestimate of dose distribution by CCC and PBC as compared to MC. The dose prediction of CCC is closer (<3%) to MC than that of PBC. This can be attributed to poor performance of CCC and PBC in inhomogeneous regions around esophagus. CCC can be considered as an alternate in the absence of MC algorithm.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Validation of clinical acceptability of an atlas-based segmentation algorithm for the delineation of organs at risk in head and neck cancer

Purpose: The aim of this study was to assess whether clinically acceptable segmentations of organs at risk (OARs) in head and neck cancer can be obtained automatically and efficiently using the novel “similarity and truth estimation for propagated segmentations” (STEPS) compared to the traditional “simultaneous truth and performance level estimation” (STAPLE) algorithm. Methods: First, 6 OARs were contoured by 2 radiation oncologists in a dataset of 100 patients with head and neck cancer on planning computed tomography images. Each image in the dataset was then automatically segmented with STAPLE and STEPS using those manual contours. Dice similarity coefficient (DSC) was then used to compare the accuracy of these automatic methods. Second, in a blind experiment, three separate and distinct trained physicians graded manual and automatic segmentations into one of the following three grades: clinically acceptable as determined by universal delineation guidelines (grade A), reasonably acceptable for clinical practice upon manual editing (grade B), and not acceptable (grade C). Finally, STEPS segmentations graded B were selected and one of the physicians manually edited them to grade A. Editing time was recorded. Results: Significant improvements in DSC can be seen when using the STEPS algorithm on large structures such as the brainstem, spinal canal, and left/right parotid compared to the STAPLE algorithm (all p < 0.001). In addition, across all three trained physicians, manual and STEPS segmentation grades were not significantly different for the brainstem, spinal canal, parotid (right/left), and optic chiasm (all p > 0.100). In contrast, STEPS segmentation grades were lower for the eyes (p < 0.001). Across all OARs and all physicians, STEPS produced segmentations graded as well as manual contouring at a rate of 83%, giving a lower bound on this rate of 80% with 95% confidence. Reduction in manual interaction time was on average 61% and 93% when automatic segmentations did and did not, respectively, require manual editing. Conclusions: The STEPS algorithm showed better performance than the STAPLE algorithm in segmenting OARs for radiotherapy of the head and neck. It can automatically produce clinically acceptable segmentation of OARs, with results as relevant as manual contouring for the brainstem, spinal canal, the parotids (left/right), and optic chiasm. A substantial reduction in manual labor was achieved when using STEPS even when manual editing was necessary.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Analytic reconstruction algorithms for triple-source CT with horizontal data truncation

Purpose: This paper explores a triple-source imaging method with horizontal data truncation to enlarge the field of view (FOV) for big objects. Methods: The study is conducted by using theoretical analysis, mathematical deduction, and numerical simulations. The proposed algorithms are implemented in c + + and MATLAB. While the basic platform is constructed in MATLAB, the computationally intensive segments are coded in c + +, which are linked via a MEX interface. Results: A triple-source circular scanning configuration with horizontal data truncation is developed, where three pairs of x-ray sources and detectors are unevenly distributed on the same circle to cover the whole imaging object. For this triple-source configuration, a fan-beam filtered backprojection-type algorithm is derived for truncated full-scan projections without data rebinning. The algorithm is also extended for horizontally truncated half-scan projections and cone-beam projections in a Feldkamp-type framework. Using their method, the FOV is enlarged twofold to threefold to scan bigger objects with high speed and quality. The numerical simulation results confirm the correctness and effectiveness of the developed algorithms. Conclusions: The triple-source scanning configuration with horizontal data truncation cannot only keep most of the advantages of a traditional multisource system but also cover a larger FOV for big imaging objects. In addition, because the filtering is shift-invariant, the proposed algorithms are very fast and easily parallelized on graphic processing units.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Technical Note: A novel leaf sequencing optimization algorithm which considers previous underdose and overdose events for MLC tracking radiotherapy

Purpose: Multileaf collimator (MLC) tracking radiotherapy is complex as the beam pattern needs to be modified due to the planned intensity modulation as well as the real-time target motion. The target motion cannot be planned; therefore, the modified beam pattern differs from the original plan and the MLC sequence needs to be recomputed online. Current MLC tracking algorithms use a greedy heuristic in that they optimize for a given time, but ignore past errors. To overcome this problem, the authors have developed and improved an algorithm that minimizes large underdose and overdose regions. Additionally, previous underdose and overdose events are taken into account to avoid regions with high quantity of dose events. Methods: The authors improved the existing MLC motion control algorithm by introducing a cumulative underdose/overdose map. This map represents the actual projection of the planned tumor shape and logs occurring dose events at each specific regions. These events have an impact on the dose cost calculation and reduce recurrence of dose events at each region. The authors studied the improvement of the new temporal optimization algorithm in terms of the L1-norm minimization of the sum of overdose and underdose compared to not accounting for previous dose events. For evaluation, the authors simulated the delivery of 5 conformal and 14 intensity-modulated radiotherapy (IMRT)-plans with 7 3D patient measured tumor motion traces. Results: Simulations with conformal shapes showed an improvement of L1-norm up to 8.5% after 100 MLC modification steps. Experiments showed comparable improvements with the same type of treatment plans. Conclusions: A novel leaf sequencing optimization algorithm which considers previous dose events for MLC tracking radiotherapy has been developed and investigated. Reductions in underdose/overdose are observed for conformal and IMRT delivery.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

SU-C-207B-05: Tissue Segmentation of Computed Tomography Images Using a Random Forest Algorithm: A Feasibility Study

Purpose: Develop an automated Random Forest algorithm for tissue segmentation of CT examinations. Methods: Seven materials were classified for segmentation: background, lung/internal gas, fat, muscle, solid organ parenchyma, blood/contrast, and bone using Matlab and the Trainable Weka Segmentation (TWS) plugin of FIJI. The following classifier feature filters of TWS were investigated: minimum, maximum, mean, and variance each evaluated over a pixel radius of 2n, (n = 0–4). Also noise reduction and edge preserving filters, Gaussian, bilateral, Kuwahara, and anisotropic diffusion, were evaluated. The algorithm used 200 trees with 2 features per node. A training data set was established using an anonymized patient’s (male, 20 yr, 72 kg) chest-abdomen-pelvis CT examination. To establish segmentation ground truth, the training data were manually segmented using Eclipse planning software, and an intra-observer reproducibility test was conducted. Six additional patient data sets were segmented based on classifier data generated from the training data. Accuracy of segmentation was determined by calculating the Dice similarity coefficient (DSC) between manual and auto segmented images. Results: The optimized autosegmentation algorithm resulted in 16 features calculated using maximum, mean, variance, and Gaussian blur filters with kernel radii of 1, 2, and 4 pixels, in addition to the original CT number, and Kuwahara filter (linear kernel of 19 pixels). Ground truth had a DSC of 0.94 (range: 0.90–0.99) for adult and 0.92 (range: 0.85–0.99) for pediatric data sets across all seven segmentation classes. The automated algorithm produced segmentation with an average DSC of 0.85 ± 0.04 (range: 0.81–1.00) for the adult patients, and 0.86 ± 0.03 (range: 0.80–0.99) for the pediatric patients. Conclusion: The TWS Random Forest auto-segmentation algorithm was optimized for CT environment, and able to segment seven material classes over a range of body habitus and CT protocol parameters with an average DSC of 0.86 ± 0.04 (range: 0.80–0.99).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-D-202-04: Validation of Deformable Image Registration Algorithms for Head and Neck Adaptive Radiotherapy in Routine Clinical Setting

Purpose: To evaluate the ROI contours and accumulated dose difference using different deformable image registration (DIR) algorithms for head and neck (H&N) adaptive radiotherapy. Methods: Eight H&N cancer patients were randomly selected from the affiliated hospital. During the treatment, patients were rescanned every week with ROIs well delineated by radiation oncologist on each weekly CT. New weekly treatment plans were also re-designed with consistent dose prescription on the rescanned CT and executed for one week on Siemens CT-on-rails accelerator. At the end, we got six weekly CT scans from CT1 to CT6 including six weekly treatment plans for each patient. The primary CT1 was set as the reference CT for DIR proceeding with the left five weekly CTs using ANACONDA and MORFEUS algorithms separately in RayStation and the external skin ROI was set to be the controlling ROI both. The entire calculated weekly dose were deformed and accumulated on corresponding reference CT1 according to the deformation vector field (DVFs) generated by the two different DIR algorithms respectively. Thus we got both the ANACONDA-based and MORFEUS-based accumulated total dose on CT1 for each patient. At the same time, we mapped the ROIs on CT1 to generate the corresponding ROIs on CT6 using ANACONDA and MORFEUS DIR algorithms. DICE coefficients between the DIR deformed and radiation oncologist delineated ROIs on CT6 were calculated. Results: For DIR accumulated dose, PTV D95 and Left-Eyeball Dmax show significant differences with 67.13 cGy and 109.29 cGy respectively (Table1). For DIR mapped ROIs, PTV, Spinal cord and Left-Optic nerve show difference with −0.025, −0.127 and −0.124 (Table2). Conclusion: Even two excellent DIR algorithms can give divergent results for ROI deformation and dose accumulation. As more and more TPS get DIR module integrated, there is an urgent need to realize the potential risk using DIR in clinical.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-133: Adaptive Radiation Therapy with a Four-Dimensional Dose Calculation Algorithm That Optimizes Dose Distribution Considering Breathing Motion

Purpose: To model patient motion and produce four-dimensional (4D) optimized dose distributions that consider motion-artifacts in the dose calculation during the treatment planning process. Methods: An algorithm for dose calculation is developed where patient motion is considered in dose calculation at the stage of the treatment planning. First, optimal dose distributions are calculated for the stationary target volume where the dose distributions are optimized considering intensity-modulated radiation therapy (IMRT). Second, a convolution-kernel is produced from the best-fitting curve which matches the motion trajectory of the patient. Third, the motion kernel is deconvolved with the initial dose distribution optimized for the stationary target to produce a dose distribution that is optimized in four-dimensions. This algorithm is tested with measured doses using a mobile phantom that moves with controlled motion patterns. Results: A motion-optimized dose distribution is obtained from the initial dose distribution of the stationary target by deconvolution with the motion-kernel of the mobile target. This motion-optimized dose distribution is equivalent to that optimized for the stationary target using IMRT. The motion-optimized and measured dose distributions are tested with the gamma index with a passing rate of >95% considering 3% dose-difference and 3mm distance-to-agreement. If the dose delivery per beam takes place over several respiratory cycles, then the spread-out of the dose distributions is only dependent on the motion amplitude and not affected by motion frequency and phase. This algorithm is limited to motion amplitudes that are smaller than the length of the target along the direction of motion. Conclusion: An algorithm is developed to optimize dose in 4D. Besides IMRT that provides optimal dose coverage for a stationary target, it extends dose optimization to 4D considering target motion. This algorithm provides alternative to motion management techniques such as beam-gating or breath-holding and has potential applications in adaptive radiation therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-175: Evaluation of Metal Artifact Reduction Algorithms in Computed Tomography and Their Application to Radiation Therapy Treatment Planning

Purpose: High-Z (metal) implants in CT scans cause significant streak-like artifacts in the reconstructed dataset. This results in both inaccurate CT Hounsfield units for the tissue as well as obscuration of the target and organs at risk (OARs) for radiation therapy planning. Herein we analyze two metal artifact reduction algorithms: GE’s Smart MAR and a Metal Deletion Technique (MDT) for geometric and Hounsfield Unit (HU) accuracy. Methods: A CT-to-electron density phantom, with multiple inserts of various densities and a custom Cerrobend insert (Zeff=76.8), is utilized in this continuing study. The phantom is scanned without metal (baseline) and again with the metal insert. Using one set of projection data, reconstructed CT volumes are created with filtered-back-projection (FBP) and the MAR and the MDT algorithms. Regions-of-Interest (ROIs) are evaluated for each insert for HU accuracy; the metal insert’s Full-Width-Half-Maximum (FWHM) is used to evaluate the geometric accuracy. Streak severity is quantified with an HU error metric over the phantom volume. Results: The original FBP reconstruction has a Root-Mean-Square-Error (RMSE) of 57.55 HU (STD=29.19, range=−145.8 to +79.2) compared to baseline. The MAR reconstruction has a RMSE of 20.98 HU (STD=13.92, range=−18.3 to +61.7). The MDT reconstruction has a RMSE of 10.05 HU (STD=10.5, range=−14.8 to +18.6). FWHM for baseline=162.05; FBP=161.84 (−0.13%); MAR=162.36 (+0.19%); MDT=162.99 (+0.58%). Streak severity metric for FBP=19.73 (22.659% bad pixels); MAR=8.743 (9.538% bad); MDT=4.899 (5.303% bad). Conclusion: Image quality, in terms of HU accuracy, in the presence of high-Z metal objects in CT scans is improved by metal artifact reduction reconstruction algorithms. The MDT algorithm had the highest HU value accuracy (RMSE=10.05 HU) and best streak severity metric, but scored the worst in terms of geometric accuracy. Qualitatively, the MAR and MDT algorithms increased detectability of inserts, although there is a loss of in-plane resolution near the metallic insert.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-209: Multicriteria Optimization Algorithm for Intensity Modulated Radiation Therapy Using Pencil Proton Beam Scanning

Purpose: To provide a multicriteria optimization algorithm for intensity modulated radiation therapy using pencil proton beam scanning. Methods: Intensity modulated radiation therapy using pencil proton beam scanning requires efficient optimization algorithms to overcome the uncertainties in the Bragg peaks locations. This work is focused on optimization algorithms that are based on Monte Carlo simulation of the treatment planning and use the weights and the dose volume histogram (DVH) control points to steer toward desired plans. The proton beam treatment planning process based on single objective optimization (representing a weighted sum of multiple objectives) usually leads to time-consuming iterations involving treatment planning team members. We proved a time efficient multicriteria optimization algorithm that is developed to run on NVIDIA GPU (Graphical Processing Units) cluster. The multicriteria optimization algorithm running time benefits from up-sampling of the CT voxel size of the calculations without loss of fidelity. Results: We will present preliminary results of Multicriteria optimization for intensity modulated proton therapy based on DVH control points. The results will show optimization results of a phantom case and a brain tumor case. Conclusion: The multicriteria optimization of the intensity modulated radiation therapy using pencil proton beam scanning provides a novel tool for treatment planning. Work support by a grant from Varian Inc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-JeP1-07: Development of a Programmable Motion Testbed for the Validation of Ultrasound Tracking Algorithms

Purpose: To develop an advanced testbed that combines a 3D motion stage and ultrasound phantom to optimize and validate 2D and 3D tracking algorithms for real-time motion management during radiation therapy. Methods: A Siemens S2000 Ultrasound scanner utilizing a 9L4 transducer was coupled with the Washington University 4D Phantom to simulate patient motion. The transducer was securely fastened to the 3D stage and positioned to image three cylinders of varying contrast in a Gammex 404GS LE phantom. The transducer was placed within a water bath above the phantom in order to maintain sufficient coupling for the entire range of simulated motion. A programmed motion sequence was used to move the transducer during image acquisition and a cine video was acquired for one minute to allow for long sequence tracking. Images were analyzed using a normalized cross-correlation block matching tracking algorithm and compared to the known motion of the transducer relative to the phantom. Results: The setup produced stable ultrasound motion traces consistent with those programmed into the 3D motion stage. The acquired ultrasound images showed minimal artifacts and an image quality that was more than suitable for tracking algorithm verification. Comparisons of a block matching tracking algorithm with the known motion trace for the three features resulted in an average tracking error of 0.59 mm. Conclusion: The high accuracy and programmability of the 4D phantom allows for the acquisition of ultrasound motion sequences that are highly customizable; allowing for focused analysis of some common pitfalls of tracking algorithms such as partial feature occlusion or feature disappearance, among others. The design can easily be modified to adapt to any probe such that the process can be extended to 3D acquisition. Further development of an anatomy specific phantom better resembling true anatomical landmarks could lead to an even more robust validation. This work is partially funded by NIH grant R01CA190298.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Resolution recovery for Compton camera using origin ensemble algorithm

Purpose: Compton cameras (CCs) use electronic collimation to reconstruct the images of activity distribution. Although this approach can greatly improve imaging efficiency, due to complex geometry of the CC principle, image reconstruction with the standard iterative algorithms, such as ordered subset expectation maximization (OSEM), can be very time-consuming, even more so if resolution recovery (RR) is implemented. We have previously shown that the origin ensemble (OE) algorithm can be used for the reconstruction of the CC data. Here we propose a method of extending our OE algorithm to include RR. Methods: To validate the proposed algorithm we used Monte Carlo simulations of a CC composed of multiple layers of pixelated CZT detectors and designed for imaging small animals. A series of CC acquisitions of small hot spheres and the Derenzo phantom placed in air were simulated. Images obtained from (a) the exact data, (b) blurred data but reconstructed without resolution recovery, and (c) blurred and reconstructed with resolution recovery were compared. Furthermore, the reconstructed contrast-to-background ratios were investigated using the phantom with nine spheres placed in a hot background. Results: Our simulations demonstrate that the proposed method allows for the recovery of the resolution loss that is due to imperfect accuracy of event detection. Additionally, tests of camera sensitivity corresponding to different detector configurations demonstrate that the proposed CC design has sensitivity comparable to PET. When the same number of events were considered, the computation time per iteration increased only by a factor of 2 when OE reconstruction with the resolution recovery correction was performed relative to the original OE algorithm. We estimate that the addition of resolution recovery to the OSEM would increase reconstruction times by 2–3 orders of magnitude per iteration. Conclusions: The results of our tests demonstrate the improvement of image resolution provided by the OE reconstructions with resolution recovery. The quality of images and their contrast are similar to those obtained from the OE reconstructions from scans simulated with perfect energy and spatial resolutions.

60 APPLIED LIFE SCIENCES↗