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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Multi-objective optimization of root phenotypes for nutrient capture using evolutionary algorithms

Root phenotypes are avenues to the development of crop cultivars with improved nutrient capture, which is an important goal for global agriculture. The fitness landscape of root phenotypes is highly complex and multidimensional. It is difficult to predict which combinations of traits (phene states) will create the best performing integrated phenotypes in various environments. Brute force methods to map the fitness landscape by simulating millions of phenotypes in multiple environments are computationally challenging. Evolutionary optimization algorithms may provide more efficient avenues to explore high dimensional domains such as the root phenotypic space. We coupled the three-dimensional functional–structural plant model, SimRoot, to the Borg Multi-Objective Evolutionary Algorithm (MOEA) and the evolutionary search over several generations facilitated the identification of optimal root phenotypes balancing trade-offs across nutrient uptake, biomass accumulation, and root carbon costs in environments varying in nutrient availability. Our results show that several combinations of root phenes generate optimal integrated phenotypes where performance in one objective comes at the cost of reduced performance in one or more of the remaining objectives, and such combinations differed for mobile and non-mobile nutrients and for maize (a monocot) and bean (a dicot). Functional–structural plant models can be used with multi-objective optimization to identify optimal root phenotypes under various environments, including future climate scenarios, which will be useful in developing the more resilient, efficient crops urgently needed in global agriculture.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Pareto Optimal and Dual-Objective Geometric and Structural Design of an Underwater Kite for Closed-Loop Flight Performance

This paper presents the formulation and results for a control-aware optimization of the combined geometric and structural design of an energy-harvesting underwater kite. Because kite-based energy-harvesting systems, both airborne and underwater, possess strong coupling between closed-loop flight control, geometric design, and structural design, consideration of all three facets of the design within a single codesign framework is highly desirable. However, while prior literature has addressed one or two attributes of the design at a time, this work constitutes the first comprehensive effort aimed at addressing all three. In particular, focusing on the goals of power maximization and mass minimization, we present a codesign formulation that fuses a geometric optimization tool, structural optimization tool, and closed-loop flight efficiency map. The resulting integrated codesign tool is used to address two mathematical optimization formulations that exhibit subtle differences: a Pareto optimal formulation and a dual-objective formulation that focuses on a weighted power-to-mass ratio as the techno-economic metric of merit. Further, based on the resulting geometric and structural designs, using a mediumfidelity closed-loop simulation tool, the proposed formulation is shown to achieve more than three times the powerto-mass ratio of a previously published, unoptimized benchmark design.

42 ENGINEERING↗
DOE OSTI2013

Westinghouse waste simulation and optimization software tool

Applications for dynamic simulation can be found in virtually all areas of process engineering. The tangible benefits of using dynamic simulation can be seen in tighter design, smoother start-ups and optimized operation. Thus, proper implementation of dynamic simulation can deliver substantial benefits. These benefits are typically derived from improved process understanding. Simulation gives confidence in evidence based decisions and enables users to try out lots of 'what if' scenarios until one is sure that a decision is the right one. In radioactive waste treatment tasks different kinds of waste with different volumes and properties have to be treated, e.g. from NPP operation or D and D activities. Finding a commercially and technically optimized waste treatment concept is a time consuming and difficult task. The Westinghouse Waste Simulation and Optimization Software Tool will enable the user to quickly generate reliable simulation models of various process applications based on equipment modules. These modules can be built with ease and be integrated into the simulation model. This capability ensures that this tool is applicable to typical waste treatment tasks. The identified waste streams and the selected treatment methods are the basis of the simulation and optimization software. After implementing suitable equipment data into the model, process requirements and waste treatment data are fed into the simulation to finally generate primary simulation results. A sensitivity analysis of automated optimization features of the software generates the lowest possible lifecycle cost for the simulated waste stream. In combination with proven waste management equipments and integrated waste management solutions, this tool provides reliable qualitative results that lead to an effective planning and minimizes the total project planning risk of any waste management activity. It is thus the ideal tool for designing a waste treatment facility in an optimum manner, taking account of the detailed waste stream and specific requirements. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Optimal band selection for target detection with a LWIR multispectral imager

Multispectral imaging can offer many benefits in cost, complexity, resolution, size, weight, and power, relative to hyperspectral imaging. When designing a multispectral system, spectral bandpasses can be selected using optimization algorithms configured to maximally separate target detection scores between target and background regions. A hyperspectral image (HSI) can serve as the source of data from which band groupings can be tested for optimality. The output of an adaptive cosine estimator target detection algorithm is used in an objective function. Three optimization algorithms are compared: particle swarm, dual annealing, and differential evolution. A global optimum is also found using a brute force approach on the Livermore Computing Syrah supercomputer. Three materials are investigated: calcite, gypsum, and limestone. This is done for 3-, 4-, and 5-band systems. The data originate from a longwave infrared HSI of a material display board. The optimization algorithms were run 30 times for every scenario. Performance statistics (maximum, minimum, mean, standard deviation, and median) based on the separation values are given. Additional characterization was performed using receiver operator characteristic (ROC) curves and the area under the ROC curve. While good performance was obtained for the three optimization algorithms, the dual annealing algorithm produced the highest and most consistent detection separation scores on average.

47 OTHER INSTRUMENTATION↗
DOE OSTI2012

Biological-based optimization and volumetric modulated arc therapy delivery for stereotactic body radiation therapy

Purpose: To describe biological-based optimization and Monte Carlo (MC) dose calculation-based treatment planning for volumetric modulated arc therapy (VMAT) delivery of stereotactic body radiation therapy (SBRT) in lung, liver, and prostate patients. Methods: Optimization strategies and VMAT planning parameters using a biological-based optimization MC planning system were analyzed for 24 SBRT patients. Patients received a median dose of 45 Gy [range, 34-54 Gy] for lung tumors in 1-5 fxs and a median dose of 52 Gy [range, 48-60 Gy] for liver tumors in 3-6 fxs. Prostate patients received a fractional dose of 10 Gy in 5 fxs. Biological-cost functions were used for plan optimization, and its dosimetric quality was evaluated using the conformity index (CI), the conformation number (CN), the ratio of the volume receiving 50% of the prescription dose over the planning target volume (Rx/PTV50). The quality and efficiency of the delivery were assessed according to measured quality assurance (QA) passing rates and delivery times. For each disease site, one patient was replanned using physical cost function and compared to the corresponding biological plan. Results: Median CI, CN, and Rx/PTV50 for all 24 patients were 1.13 (1.02-1.28), 0.79 (0.70-0.88), and 5.3 (3.1-10.8), respectively. The median delivery rate for all patients was 410 MU/min with a maximum possible rate of 480 MU/min (85%). Median QA passing rate was 96.7%, and it did not significantly vary with the tumor site. Conclusions: VMAT delivery of SBRT plans optimized using biological-motivated cost-functions result in highly conformal dose distributions. Plans offer shorter treatment-time benefits and provide efficient dose delivery without compromising the plan conformity for tumors in the prostate, lung, and liver, thereby improving patient comfort and clinical throughput. The short delivery times minimize the risk of patient setup and intrafraction motion errors often associated with long SBRT treatment delivery times.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Improving IMRT-plan quality with MLC leaf position refinement post plan optimization

Purpose: In intensity-modulated radiation therapy (IMRT) planning, reducing the pencil-beam size may lead to a significant improvement in dose conformity, but also increase the time needed for the dose calculation and plan optimization. The authors develop and evaluate a postoptimization refinement (POpR) method, which makes fine adjustments to the multileaf collimator (MLC) leaf positions after plan optimization, enhancing the spatial precision and improving the plan quality without a significant impact on the computational burden. Methods: The authors' POpR method is implemented using a commercial treatment planning system based on direct aperture optimization. After an IMRT plan is optimized using pencil beams with regular pencil-beam step size, a greedy search is conducted by looping through all of the involved MLC leaves to see if moving the MLC leaf in or out by half of a pencil-beam step size will improve the objective function value. The half-sized pencil beams, which are used for updating dose distribution in the greedy search, are derived from the existing full-sized pencil beams without need for further pencil-beam dose calculations. A benchmark phantom case and a head-and-neck (HN) case are studied for testing the authors' POpR method. Results: Using a benchmark phantom and a HN case, the authors have verified that their POpR method can be an efficient technique in the IMRT planning process. Effectiveness of POpR is confirmed by noting significant improvements in objective function values. Dosimetric benefits of POpR are comparable to those of using a finer pencil-beam size from the optimization start, but with far less computation and time. Conclusions: The POpR is a feasible and practical method to significantly improve IMRT-plan quality without compromising the planning efficiency.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

A linear programming model for optimizing HDR brachytherapy dose distributions with respect to mean dose in the DVH-tail

Purpose: Recent research has shown that the optimization model hitherto used in high-dose-rate (HDR) brachytherapy corresponds weakly to the dosimetric indices used to evaluate the quality of a dose distribution. Although alternative models that explicitly include such dosimetric indices have been presented, the inclusion of the dosimetric indices explicitly yields intractable models. The purpose of this paper is to develop a model for optimizing dosimetric indices that is easier to solve than those proposed earlier.Methods: In this paper, the authors present an alternative approach for optimizing dose distributions for HDR brachytherapy where dosimetric indices are taken into account through surrogates based on the conditional value-at-risk concept. This yields a linear optimization model that is easy to solve, and has the advantage that the constraints are easy to interpret and modify to obtain satisfactory dose distributions.Results: The authors show by experimental comparisons, carried out retrospectively for a set of prostate cancer patients, that their proposed model corresponds well with constraining dosimetric indices. All modifications of the parameters in the authors' model yield the expected result. The dose distributions generated are also comparable to those generated by the standard model with respect to the dosimetric indices that are used for evaluating quality.Conclusions: The authors' new model is a viable surrogate to optimizing dosimetric indices and quickly and easily yields high quality dose distributions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Dose optimization in cardiac x-ray imaging

Purpose: The aim of this research was to optimize x-ray image quality to dose ratios in the cardiac catheterization laboratory. This study examined independently the effects of peak x-ray tube voltage (kVp), copper (Cu), and gadolinium (Gd) x-ray beam filtration on the image quality to radiation dose balance for adult patient sizes.Methods: Image sequences of polymethyl methacrylate (PMMA) phantoms representing two adult patient sizes were captured using a modern flat panel detector based x-ray imaging system. Tin and copper test details were used to simulate iodine-based contrast medium and stents/guide wires respectively, which are used in clinical procedures. Noise measurement for a flat field image and test detail contrast were used to calculate the contrast to noise ratio (CNR). Entrance surface dose (ESD) and effective dose measurements were obtained to calculate the figure of merit (FOM), CNR{sup 2}/dose. This FOM determined the dose efficiency of x-ray spectra investigated. Images were captured with 0.0, 0.1, 0.25, 0.4, and 0.9 mm Cu filtration and with a range of gadolinium oxysulphide (Gd{sub 2}O{sub 2}S) filtration.Results: Optimum x-ray spectra were the same for the tin and copper test details. Lower peak tube voltages were generally favored. For the 20 cm phantom, using 2 Lanex Fast Back Gd{sub 2}O{sub 2}S screens as x-ray filtration at 65 kVp provided the highest FOM considering ESD and effective dose. Considering ESD, this FOM was only marginally larger than that from using 0.4 mm Cu at 65 kVp. For the 30 cm phantom, using 0.25 mm copper filtration at 80 kVp was most optimal; considering effective dose the FOM was highest with no filtration at 65 kVp.Conclusions: These settings, adjusted for x-ray tube loading limits and clinically acceptable image quality, should provide a useful option for optimizing patient dose to image quality in cardiac x-ray imaging. The same optimal x-ray beam spectra were found for both the tin and copper details, suggesting that iodine contrast based imaging and visualization of interventional devices could potentially be optimized for dose using similar x-ray beam spectra.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Multicriteria optimization of the spatial dose distribution

Purpose: Treatment planning for radiation therapy involves trade-offs with respect to different clinical goals. Typically, the dose distribution is evaluated based on few statistics and dose–volume histograms. Particularly for stereotactic treatments, the spatial dose distribution represents further criteria, e.g., when considering the gradient between subregions of volumes of interest. The authors have studied how to consider the spatial dose distribution using a multicriteria optimization approach.Methods: The authors have extended a stepwise multicriteria optimization approach to include criteria with respect to the local dose distribution. Based on a three-dimensional visualization of the dose the authors use a software tool allowing interaction with the dose distribution to map objectives with respect to its shape to a constrained optimization problem. Similarly, conflicting criteria are highlighted and the planner decides if and where to relax the shape of the dose distribution.Results: To demonstrate the potential of spatial multicriteria optimization, the tool was applied to a prostate and meningioma case. For the prostate case, local sparing of the rectal wall and shaping of a boost volume are achieved through local relaxations and while maintaining the remaining dose distribution. For the meningioma, target coverage is improved by compromising low dose conformality toward noncritical structures. A comparison of dose–volume histograms illustrates the importance of spatial information for achieving the trade-offs.Conclusions: The results show that it is possible to consider the location of conflicting criteria during treatment planning. Particularly, it is possible to conserve already achieved goals with respect to the dose distribution, to visualize potential trade-offs, and to relax constraints locally. Hence, the proposed approach facilitates a systematic exploration of the optimal shape of the dose distribution.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

A critical evaluation of worst case optimization methods for robust intensity-modulated proton therapy planning

Purpose: To critically evaluate and compare three worst case optimization methods that have been previously employed to generate intensity-modulated proton therapy treatment plans that are robust against systematic errors. The goal of the evaluation is to identify circumstances when the methods behave differently and to describe the mechanism behind the differences when they occur. Methods: The worst case methods optimize plans to perform as well as possible under the worst case scenario that can physically occur (composite worst case), the combination of the worst case scenarios for each objective constituent considered independently (objectivewise worst case), and the combination of the worst case scenarios for each voxel considered independently (voxelwise worst case). These three methods were assessed with respect to treatment planning for prostate under systematic setup uncertainty. An equivalence with probabilistic optimization was used to identify the scenarios that determine the outcome of the optimization. Results: If the conflict between target coverage and normal tissue sparing is small and no dose-volume histogram (DVH) constraints are present, then all three methods yield robust plans. Otherwise, they all have their shortcomings: Composite worst case led to unnecessarily low plan quality in boundary scenarios that were less difficult than the worst case ones. Objectivewise worst case generally led to nonrobust plans. Voxelwise worst case led to overly conservative plans with respect to DVH constraints, which resulted in excessive dose to normal tissue, and less sharp dose fall-off than the other two methods. Conclusions: The three worst case methods have clearly different behaviors. These behaviors can be understood from which scenarios that are active in the optimization. No particular method is superior to the others under all circumstances: composite worst case is suitable if the conflicts are not very severe or there are DVH constraints whereas voxelwise worst case is advantageous if there are severe conflicts but no DVH constraints. The advantages of composite and voxelwise worst case outweigh those of objectivewise worst case.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-617: A Feasibility Study of Navigation Based Multi Criteria Optimization for Advanced Cervical Cancer IMRT Planning

Purpose: This study aims to validate multi-criteria optimization (MCO) against standard intensity modulated radiation therapy (IMRT) optimization for advanced cervical cancer in RayStation (v2.4, RaySearch Laboratories, Sweden). Methods: 10 advanced cervical cancer patients IMRT plans were randomly selected, these plans were designed with step and shoot optimization, new plans were then designed with MCO based on these plans,while keeping optimization conditions unchanged,comparison was made between both kinds of plans including the dose volume histogram parameters of PTV and OAR,and were analysed by pairing-t test. Results: We normalize the plan so that 95% volume of PTV achieved the prescribed dose(50Gy). The volume of radiation 10, 20, 30, and 40 Gy of the rectum were reduced by 14.7%,26.8%,21.1%,10.5% respectively(P≥0.05). The mean dose of rectum were reduced by 7.2Gy(P≤0.05). There were no significant differences for the dosimetric parameters for the bladder. Conclusion: In comparision with standard IMRT optimization, MCO reduces the dose of organs at risk with the same PTV coverage,but the result needs further clinical evalution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-618: Dosimetric Comparison of Manual and Beam Angle Optimization of Gantry Angles in IMRT for Cervical Cancer

Purpose: To evaluate the dosimetric characteristics of intensity-modulated radiotherapy (IMRT) treatment plan with beam angle optimization. Methods: Ten post-operation patients with cervical cancer were included in this analysis. Two IMRT plans using seven beams were designed in each patient. A standard coplanar equi-space beam angles were used in the first plan (plan 1), whereas the selection of beam angle was optimized by beam angle optimization algorithm in Varian Eclipse treatment planning system for the same number of beams in the second plan (plan 2). Two plans were designed for each patient with the same dose-volume constraints and prescription dose. All plans were normalized to the mean dose to PTV. The dose distribution in the target, the dose to the organs at risk and total MU were compared. Results: For conformity and homogeneity in PTV, no statistically differences were observed in the two plans. For the mean dose in bladder, plan 2 were significantly lower than plan 1(p<0.05). No statistically significant differences were observed between two plans for the mean doses in rectum, left and right femur heads. Compared with plan1, the average monitor units reduced 16% in plan 2. Conclusion: The IMRT plan based on beam angle optimization for cervical cancer could reduce the dose delivered to bladder and also reduce MU. Therefore there were some dosimetric advantages in the IMRT plan with beam angle optimization for cervical cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Sci—Fri AM: Mountain — 05: Unified Optimization and Delivery of Intensity-modulated Radiation Therapy and Volume-modulated Arc Therapy

Purpose: To study the feasibility of a unified intensity-modulated arc therapy (UIMAT) that combines IMRT and VMAT optimization and delivery in order to produce efficient and superior radiation treatment plans. Methods: Inverse planning for UIMAT was prototyped on the Pinnacle treatment planning system (Philips Medical Systems). UIMAT integrates IMRT and VMAT delivery in the same arc where IMRT was delivered with gantry speed close to zero. Optimal gantry angles for the IMRT phases were selected automatically by the inverse optimization algorithm. Optimization of the VMAT phases and IMRT phases were done simultaneously using Pinnacle's direct machine parameter optimization algorithm. Five treatment plans each for prostate, head and neck, and lung were generated using our unified technique and compared with clinical VMAT or IMRT plans. Delivery verification was performed on an ArcCheck phantom (Sun Nuclear) and delivered in clinical mode on a Varian TrueBeam linear accelerator. Results: In this prototype implementation, compared to the VMAT or IMRT plans, with the plans normalized to the same dose coverage to the planning target volumes, the UIMAT plans produced improved OAR sparing for head and neck cases, while for lung and prostate cases, the dosimetric improvements for OARs were not as significant. In this proof-of-concept work, we demonstrated that a novel radiation therapy delivery technique combining VMAT and IMRT delivery in the same arc is feasible. Initial results showed UIMAT has the potential to be superior to either standard IMRT or VMAT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Novel tools for stepping source brachytherapy treatment planning: Enhanced geometrical optimization and interactive inverse planning

Purpose: Dose optimization for stepping source brachytherapy can nowadays be performed using automated inverse algorithms. Although much quicker than graphical optimization, an experienced treatment planner is required for both methods. With automated inverse algorithms, the procedure to achieve the desired dose distribution is often based on trial-and-error. Methods: A new approach for stepping source prostate brachytherapy treatment planning was developed as a quick and user-friendly alternative. This approach consists of the combined use of two novel tools: Enhanced geometrical optimization (EGO) and interactive inverse planning (IIP). EGO is an extended version of the common geometrical optimization method and is applied to create a dose distribution as homogeneous as possible. With the second tool, IIP, this dose distribution is tailored to a specific patient anatomy by interactively changing the highest and lowest dose on the contours. Results: The combined use of EGO–IIP was evaluated on 24 prostate cancer patients, by having an inexperienced user create treatment plans, compliant to clinical dose objectives. This user was able to create dose plans of 24 patients in an average time of 4.4 min/patient. An experienced treatment planner without extensive training in EGO–IIP also created 24 plans. The resulting dose-volume histogram parameters were comparable to the clinical plans and showed high conformance to clinical standards. Conclusions: Even for an inexperienced user, treatment planning with EGO–IIP for stepping source prostate brachytherapy is feasible as an alternative to current optimization algorithms, offering speed, simplicity for the user, and local control of the dose levels.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Optimization of leaf margins for lung stereotactic body radiotherapy using a flattening filter-free beam

Purpose: The authors sought to determine the optimal collimator leaf margins which minimize normal tissue dose while achieving high conformity and to evaluate differences between the use of a flattening filter-free (FFF) beam and a flattening-filtered (FF) beam. Methods: Sixteen lung cancer patients scheduled for stereotactic body radiotherapy underwent treatment planning for a 7 MV FFF and a 6 MV FF beams to the planning target volume (PTV) with a range of leaf margins (−3 to 3 mm). Forty grays per four fractions were prescribed as a PTV D95. For PTV, the heterogeneity index (HI), conformity index, modified gradient index (GI), defined as the 50% isodose volume divided by target volume, maximum dose (Dmax), and mean dose (Dmean) were calculated. Mean lung dose (MLD), V20 Gy, and V5 Gy for the lung (defined as the volumes of lung receiving at least 20 and 5 Gy), mean heart dose, and Dmax to the spinal cord were measured as doses to organs at risk (OARs). Paired t-tests were used for statistical analysis. Results: HI was inversely related to changes in leaf margin. Conformity index and modified GI initially decreased as leaf margin width increased. After reaching a minimum, the two values then increased as leaf margin increased (“V” shape). The optimal leaf margins for conformity index and modified GI were −1.1 ± 0.3 mm (mean ± 1 SD) and −0.2 ± 0.9 mm, respectively, for 7 MV FFF compared to −1.0 ± 0.4 and −0.3 ± 0.9 mm, respectively, for 6 MV FF. Dmax and Dmean for 7 MV FFF were higher than those for 6 MV FF by 3.6% and 1.7%, respectively. There was a positive correlation between the ratios of HI, Dmax, and Dmean for 7 MV FFF to those for 6 MV FF and PTV size (R = 0.767, 0.809, and 0.643, respectively). The differences in MLD, V20 Gy, and V5 Gy for lung between FFF and FF beams were negligible. The optimal leaf margins for MLD, V20 Gy, and V5 Gy for lung were −0.9 ± 0.6, −1.1 ± 0.8, and −2.1 ± 1.2 mm, respectively, for 7 MV FFF compared to −0.9 ± 0.6, −1.1 ± 0.8, and −2.2 ± 1.3 mm, respectively, for 6 MV FF. With the heart inside the radiation field, the mean heart dose showed a V-shaped relationship with leaf margins. The optimal leaf margins were −1.0 ± 0.6 mm for both beams. Dmax to the spinal cord showed no clear trend for changes in leaf margin. Conclusions: The differences in doses to OARs between FFF and FF beams were negligible. Conformity index, modified GI, MLD, lung V20 Gy, lung V5 Gy, and mean heart dose showed a V-shaped relationship with leaf margins. There were no significant differences in optimal leaf margins to minimize these parameters between both FFF and FF beams. The authors’ results suggest that a leaf margin of −1 mm achieves high conformity and minimizes doses to OARs for both FFF and FF beams.

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-J-16: Automatic Image Contrast Enhancement Based On Automatic Parameter Optimization for Radiation Therapy Setup Verification

Purpose: In RT patient setup 2D images, tissues often cannot be seen well due to the lack of image contrast. Contrast enhancement features provided by image reviewing software, e.g. Mosaiq and ARIA, require manual selection of the image processing filters and parameters thus inefficient and cannot be automated. In this work, we developed a novel method to automatically enhance the 2D RT image contrast to allow automatic verification of patient daily setups as a prerequisite step of automatic patient safety assurance. Methods: The new method is based on contrast limited adaptive histogram equalization (CLAHE) and high-pass filtering algorithms. The most important innovation is to automatically select the optimal parameters by optimizing the image contrast. The image processing procedure includes the following steps: 1) background and noise removal, 2) hi-pass filtering by subtracting the Gaussian smoothed Result, and 3) histogram equalization using CLAHE algorithm. Three parameters were determined through an iterative optimization which was based on the interior-point constrained optimization algorithm: the Gaussian smoothing weighting factor, the CLAHE algorithm block size and clip limiting parameters. The goal of the optimization is to maximize the entropy of the processed Result. Results: A total 42 RT images were processed. The results were visually evaluated by RT physicians and physicists. About 48% of the images processed by the new method were ranked as excellent. In comparison, only 29% and 18% of the images processed by the basic CLAHE algorithm and by the basic window level adjustment process, were ranked as excellent. Conclusion: This new image contrast enhancement method is robust and automatic, and is able to significantly outperform the basic CLAHE algorithm and the manual window-level adjustment process that are currently used in clinical 2D image review software tools.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-435: Flattening Filter Free Beams for Head and Neck IMRT and VMAT Optimization

Purpose: To investigate if there is benefits of using flattening filter free (FFF) versus flattening filter (FF) beams during plan optimization for head and neck targets. Methods: Five head and neck cancer patients previously treated were selected for this study. Each plan was optimized for volumetric modulated arc therapy (VMAT) using 2 full arcs. Target volumes and the organs at risk (OAR) were outlined by the same physician. The prescription doses for each patient and the dose limits for each OAR were specified by the physician. For each patient four plans were created by varying the photon beam energy (6MV vs 10MV) and the use of FF or FFF. For each patient the prescription dose and OAR dose limits remained unchanged. Furthermore, the number of optimization iterations remained the same for each plan without user interference. The plans were compared using dose volume histograms, conformity and homogeneity indices. Results: Our results showed that the plans optimized with FF beams produced more homogeneous dose distributions in the PTV than the ones with FFF beams (0.92 vs. 0.86 and 0.92 vs.85 for 6MVFF, 6MVFFF, 10MVFF and 10MVFFF respectively). The conformity was better for FFF beams than for FF beams (1.26 vs. 1.20 and 1.27 vs. 1.21 for 6MVFF, 6MVFFF, 10MVFF and 10MVFFF respectively). The overall minimum, maximum and means doses were reduced for the FFF plans by approximately 4% to 6%. All FFF plans allowed more sparing of organs at risk by 7% to 9% on average. Only one 10MVFFF plan had a 1% higher dose than the respective 10MVFF for the spinal cord. Conclusion: The 6MVFFF and 10MVFFF beams illustrated the improvement of normal tissue sparing while achieving similar target dose distribution compared to 6MVFF and 10MVFF beams. Further investigation is required to determine the magnitude of improvement. case specific, fluence-based optimization improved both PTV and OAR dosimetry in 80% of cases.

60 APPLIED LIFE SCIENCES↗