Engineering topics

Jiang, S

Publications and source records attributed to Jiang, S.

At least 19 records

DOE OSTI2016

SU-C-BRC-06: OpenCL-Based Cross-Platform Monte Carlo Simulation Package for Carbon Ion Therapy

Purpose: Monte Carlo (MC) simulation is considered to be the most accurate method for calculation of absorbed dose and fundamental physical quantities related to biological effects in carbon ion therapy. Its long computation time impedes clinical and research applications. We have developed an MC package, goCMC, on parallel processing platforms, aiming at achieving accurate and efficient simulations for carbon therapy. Methods: goCMC was developed under OpenCL framework. It supported transport simulation in voxelized geometry with kinetic energy up to 450 MeV/u. Class II condensed history algorithm was employed for charged particle transport with stopping power computed via Bethe-Bloch equation. Secondary electrons were not transported with their energy locally deposited. Energy straggling and multiple scattering were modeled. Production of secondary charged particles from nuclear interactions was implemented based on cross section and yield data from Geant4. They were transported via the condensed history scheme. goCMC supported scoring various quantities of interest e.g. physical dose, particle fluence, spectrum, linear energy transfer, and positron emitting nuclei. Results: goCMC has been benchmarked against Geant4 with different phantoms and beam energies. For 100 MeV/u, 250 MeV/u and 400 MeV/u beams impinging to a water phantom, range difference was 0.03 mm, 0.20 mm and 0.53 mm, and mean dose difference was 0.47%, 0.72% and 0.79%, respectively. goCMC can run on various computing devices. Depending on the beam energy and voxel size, it took 20∼100 seconds to simulate 10{sup 7} carbons on an AMD Radeon GPU card. The corresponding CPU time for Geant4 with the same setup was 60∼100 hours. Conclusion: We have developed an OpenCL-based cross-platform carbon MC simulation package, goCMC. Its accuracy, efficiency and portability make goCMC attractive for research and clinical applications in carbon therapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-C-BRA-06: Automatic Brain Tumor Segmentation for Stereotactic Radiosurgery Applications

Purpose: Stereotactic radiosurgery (SRS), which delivers a potent dose of highly conformal radiation to the target in a single fraction, requires accurate tumor delineation for treatment planning. We present an automatic segmentation strategy, that synergizes intensity histogram thresholding, super-voxel clustering, and level-set based contour evolving methods to efficiently and accurately delineate SRS brain tumors on contrast-enhance T1-weighted (T1c) Magnetic Resonance Images (MRI). Methods: The developed auto-segmentation strategy consists of three major steps. Firstly, tumor sites are localized through 2D slice intensity histogram scanning. Then, super voxels are obtained through clustering the corresponding voxels in 3D with reference to the similarity metrics composited from spatial distance and intensity difference. The combination of the above two could generate the initial contour surface. Finally, a localized region active contour model is utilized to evolve the surface to achieve the accurate delineation of the tumors. The developed method was evaluated on numerical phantom data, synthetic BRATS (Multimodal Brain Tumor Image Segmentation challenge) data, and clinical patients’ data. The auto-segmentation results were quantitatively evaluated by comparing to ground truths with both volume and surface similarity metrics. Results: DICE coefficient (DC) was performed as a quantitative metric to evaluate the auto-segmentation in the numerical phantom with 8 tumors. DCs are 0.999±0.001 without noise, 0.969±0.065 with Rician noise and 0.976±0.038 with Gaussian noise. DC, NMI (Normalized Mutual Information), SSIM (Structural Similarity) and Hausdorff distance (HD) were calculated as the metrics for the BRATS and patients’ data. Assessment of BRATS data across 25 tumor segmentation yield DC 0.886±0.078, NMI 0.817±0.108, SSIM 0.997±0.002, and HD 6.483±4.079mm. Evaluation on 8 patients with total 14 tumor sites yield DC 0.872±0.070, NMI 0.824±0.078, SSIM 0.999±0.001, and HD 5.926±6.141mm. Conclusion: The developed automatic segmentation strategy, which yields accurate brain tumor delineation in evaluation cases, is promising for its application in SRS treatment planning.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-D-BRC-01: An Automatic Beam Model Commissioning Method for Monte Carlo Simulations in Pencil-Beam Scanning Proton Therapy

Purpose: Monte Carlo (MC) simulation is typically regarded as the most accurate dose calculation method for proton therapy. Yet for real clinical cases, the overall accuracy also depends on that of the MC beam model. Commissioning a beam model to faithfully represent a real beam requires finely tuning a set of model parameters, which could be tedious given the large number of pencil beams to commmission. This abstract reports an automatic beam-model commissioning method for pencil-beam scanning proton therapy via an optimization approach. Methods: We modeled a real pencil beam with energy and spatial spread following Gaussian distributions. Mean energy, and energy and spatial spread are model parameters. To commission against a real beam, we first performed MC simulations to calculate dose distributions of a set of ideal (monoenergetic, zero-size) pencil beams. Dose distribution for a real pencil beam is hence linear superposition of doses for those ideal pencil beams with weights in the Gaussian form. We formulated the commissioning task as an optimization problem, such that the calculated central axis depth dose and lateral profiles at several depths match corresponding measurements. An iterative algorithm combining conjugate gradient method and parameter fitting was employed to solve the optimization problem. We validated our method in simulation studies. Results: We calculated dose distributions for three real pencil beams with nominal energies 83, 147 and 199 MeV using realistic beam parameters. These data were regarded as measurements and used for commission. After commissioning, average difference in energy and beam spread between determined values and ground truth were 4.6% and 0.2%. With the commissioned model, we recomputed dose. Mean dose differences from measurements were 0.64%, 0.20% and 0.25%. Conclusion: The developed automatic MC beam-model commissioning method for pencil-beam scanning proton therapy can determine beam model parameters with satisfactory accuracy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-D-206-01: Employing a Novel Consensus Optimization Strategy to Achieve Iterative Cone Beam CT Reconstruction On a Multi-GPU Platform

Purpose: While compressed sensing-based cone-beam CT (CBCT) iterative reconstruction techniques have demonstrated tremendous capability of reconstructing high-quality images from undersampled noisy data, its long computation time still hinders wide application in routine clinic. The purpose of this study is to develop a reconstruction framework that employs modern consensus optimization techniques to achieve CBCT reconstruction on a multi-GPU platform for improved computational efficiency. Methods: Total projection data were evenly distributed to multiple GPUs. Each GPU performed reconstruction using its own projection data with a conventional total variation regularization approach to ensure image quality. In addition, the solutions from GPUs were subject to a consistency constraint that they should be identical. We solved the optimization problem with all the constraints considered rigorously using an alternating direction method of multipliers (ADMM) algorithm. The reconstruction framework was implemented using OpenCL on a platform with two Nvidia GTX590 GPU cards, each with two GPUs. We studied the performance of our method and demonstrated its advantages through a simulation case with a NCAT phantom and an experimental case with a Catphan phantom. Result: Compared with the CBCT images reconstructed using conventional FDK method with full projection datasets, our proposed method achieved comparable image quality with about one third projection numbers. The computation time on the multi-GPU platform was ∼55 s and ∼ 35 s in the two cases respectively, achieving a speedup factor of ∼ 3.0 compared with single GPU reconstruction. Conclusion: We have developed a consensus ADMM-based CBCT reconstruction method which enabled performing reconstruction on a multi-GPU platform. The achieved efficiency made this method clinically attractive.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-J-18: Feasibility of Open Mask Immobilization with Optical Imaging Guidance (OIG) for H&N Radiotherapy

Purpose: Full face and neck thermoplastic masks provide standard-of-care immobilization for patients receiving H&N IMRT. However, these masks are uncomfortable and increase skin dose. The purpose of this pilot study was to investigate the feasibility and setup accuracy of open face and neck mask immobilization with OIG. Methods: Ten patients were consented and enrolled to this IRB-approved protocol. Patients were immobilized with open masks securing only forehead and chin. Standard IMRT to 60–70 Gy in 30 fractions were delivered in all cases. Patient simulation information, including isocenter location and CT skin contours, were imported to a commercial OIG system. On the first day of treatment, patients were initially set up to surface markings and then OIG referenced to face and neck skin regions of interest (ROI) localized on simulation CT images, followed by in-room CBCT. CBCTs were acquired at least weekly while planar OBI was acquired on the days without CBCT. Following 6D robotic couch correction with kV imaging, a new optical real-time surface image was acquired to track intrafraction motion and to serve as a reference surface for setup at the next treatment fraction. Therapists manually recorded total treatment time as well as couch shifts based on kV imaging. Intrafractional ROI motion tracking was automatically recorded. Results: Setup accuracy of OIG was compared with CBCT results. The setup error based on OIG was represented as a 6D shift (vertical/longitudinal/lateral/rotation/pitch/roll). Mean error values were −0.70±3.04mm, −0.69±2.77mm, 0.33±2.67 mm, −0.14±0.94 o, −0.15±1.10o and 0.12±0.82o, respectively for the cohort. Average treatment time was 24.1±9.2 minutes, comparable to standard immobilization. The amplitude of intrafractional ROI motion was 0.69±0.36 mm, driven primarily by respiratory neck motion. Conclusion: OGI can potentially provide accurate setup and treatment tracking for open face and neck immobilization. Study accrual and patient/provider satisfaction survey collection remain ongoing. This study is supported by VisionRT, Ltd.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-J-54: Towards Real-Time Volumetric Imaging Using the Treatment Beam and KV Beam

Purpose: Existing real-time imaging uses dual (orthogonal) kV beam fluoroscopies and may result in significant amount of extra radiation to patients, especially for prolonged treatment cases. In addition, kV projections only provide 2D information, which is insufficient for in vivo dose reconstruction. We propose real-time volumetric imaging using prior knowledge of pre-treatment 4D images and real-time 2D transit data of treatment beam and kV beam. Methods: The pre-treatment multi-snapshot volumetric images are used to simulate 2D projections of both the treatment beam and kV beam, respectively, for each treatment field defined by the control point. During radiation delivery, the transit signals acquired by the electronic portal image device (EPID) are processed for every projection and compared with pre-calculation by cross-correlation for phase matching and thus 3D snapshot identification or real-time volumetric imaging. The data processing involves taking logarithmic ratios of EPID signals with respect to the air scan to reduce modeling uncertainties in head scatter fluence and EPID response. Simulated 2D projections are also used to pre-calculate confidence levels in phase matching. Treatment beam projections that have a low confidence level either in pre-calculation or real-time acquisition will trigger kV beams so that complementary information can be exploited. In case both the treatment beam and kV beam return low confidence in phase matching, a predicted phase based on linear regression will be generated. Results: Simulation studies indicated treatment beams provide sufficient confidence in phase matching for most cases. At times of low confidence from treatment beams, kV imaging provides sufficient confidence in phase matching due to its complementary configuration. Conclusion: The proposed real-time volumetric imaging utilizes the treatment beam and triggers kV beams for complementary information when the treatment beam along does not provide sufficient confidence for phase matching. This strategy minimizes the use of extra radiation to patients. This project is partially supported by a Varian MRA grant.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-J-72: A Clinical Usable Integrated Contouring Quality Evaluation Software for Radiotherapy

Purpose: To introduce the Auto Contour Evaluation (ACE) software, which is the clinical usable, user friendly, efficient and all-in-one toolbox for automatically identify common contouring errors in radiotherapy treatment planning using supervised machine learning techniques. Methods: ACE is developed with C# using Microsoft .Net framework and Windows Presentation Foundation (WPF) for elegant GUI design and smooth GUI transition animations through the integration of graphics engines and high dots per inch (DPI) settings on modern high resolution monitors. The industrial standard software design pattern, Model-View-ViewModel (MVVM) pattern, is chosen to be the major architecture of ACE for neat coding structure, deep modularization, easy maintainability and seamless communication with other clinical software. ACE consists of 1) a patient data importing module integrated with clinical patient database server, 2) a 2D DICOM image and RT structure simultaneously displaying module, 3) a 3D RT structure visualization module using Visualization Toolkit or VTK library and 4) a contour evaluation module using supervised pattern recognition algorithms to detect contouring errors and display detection results. ACE relies on supervised learning algorithms to handle all image processing and data processing jobs. Implementations of related algorithms are powered by Accord.Net scientific computing library for better efficiency and effectiveness. Results: ACE can take patient’s CT images and RT structures from commercial treatment planning software via direct user input or from patients’ database. All functionalities including 2D and 3D image visualization and RT contours error detection have been demonstrated with real clinical patient cases. Conclusion: ACE implements supervised learning algorithms and combines image processing and graphical visualization modules for RT contours verification. ACE has great potential for automated radiotherapy contouring quality verification. Structured with MVVM pattern, it is highly maintainable and extensible, and support smooth connections with other clinical software tools.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-J-111: A Novel Distance-Dose Weighting Method for Label Fusion in Multi- Atlas Segmentation for Prostate Radiation Therapy

Purpose: A novel distance-dose weighting method for label fusion was developed to increase segmentation accuracy in dosimetrically important regions for prostate radiation therapy. Methods: Label fusion as implemented in the original SIMPLE (OS) for multi-atlas segmentation relies iteratively on the majority vote to generate an estimated ground truth and DICE similarity measure to screen candidates. The proposed distance-dose weighting puts more values on dosimetrically important regions when calculating similarity measure. Specifically, we introduced distance-to-dose error (DDE), which converts distance to dosimetric importance, in performance evaluation. The DDE calculates an estimated DE error derived from surface distance differences between the candidate and estimated ground truth label by multiplying a regression coefficient. To determine the coefficient at each simulation point on the rectum, we fitted DE error with respect to simulated voxel shift. The DEs were calculated by the multi-OAR geometry-dosimetry training model previously developed in our research group. Results: For both the OS and the distance-dose weighted SIMPLE (WS) results, the evaluation metrics for twenty patients were calculated using the ground truth segmentation. The mean difference of DICE, Hausdorff distance, and mean absolute distance (MAD) between OS and WS have shown 0, 0.10, and 0.11, respectively. In partial MAD of WS which calculates MAD within a certain PTV expansion voxel distance, the lower MADs were observed at the closer distances from 1 to 8 than those of OS. The DE results showed that the segmentation from WS produced more accurate results than OS. The mean DE error of V75, V70, V65, and V60 were decreased by 1.16%, 1.17%, 1.14%, and 1.12%, respectively. Conclusion: We have demonstrated that the method can increase the segmentation accuracy in rectum regions adjacent to PTV. As a result, segmentation using WS have shown improved dosimetric accuracy than OS. The WS will provide dosimetrically important label selection strategy in multi-atlas segmentation. CPRIT grant RP150485.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-J-197: A Novel Intra-Beam Range Detection and Adaptation Strategy for Particle Therapy

Purpose: In-vivo range detection/verification is crucial in particle therapy for effective and safe delivery. The state-of-art techniques are not sufficient for in-vivo on-line range verification due to conflicts among patient dose, signal statistics and imaging time. We propose a novel intra-beam range detection and adaptation strategy for particle therapy. Methods: This strategy uses the planned mid-range spots as probing beams without adding extra radiation to patients. Such choice of probing beams ensures the Bragg peaks to remain inside the tumor even with significant range variation from the plan. It offers sufficient signal statistics for in-beam positron emission tomography (PET) due to high positron activity of therapeutic dose. The probing beam signal can be acquired and reconstructed using in-beam PET that allows for delineation of the Bragg peaks and detection of range shift with ease of detection enabled by single-layered spots. If the detected range shift is within a pre-defined tolerance, the remaining spots will be delivered as the original plan. Otherwise, a fast re-optimization using range-shifted beamlets and accounting for the probing beam dose is applied to consider the tradeoffs posed by the online anatomy. Simulated planning and delivery studies were used to demonstrate the effectiveness of the proposed techniques. Results: Simulations with online range variations due to shifts of various foreign objects into the beam path showed successful delineation of the Bragg peaks as a result of delivering probing beams. Without on-line delivery adaptation, dose distribution was significantly distorted. In contrast, delivery adaptation incorporating detected range shift recovered well the planned dose. Conclusion: The proposed intra-beam range detection and adaptation utilizing the planned mid-range spots as probing beams, which illuminate the beam range with strong and accurate PET signals, is a safe, practical, yet effective approach to address range uncertainty issues in particle therapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-65: AutomaticTreatment Planning for High-Dose Rate (HDR) Brachytherapy with a VaginalCylinder Applicator

Purpose: High dose rate (HDR) brachytherapy treatment planning is conventionally performed in a manual fashion. Yet it is highly desirable to perform computerized automated planning to improve treatment planning efficiency, eliminate human errors, and reduce plan quality variation. The goal of this research is to develop an automatic treatment planning tool for HDR brachytherapy with a cylinder applicator for vaginal cancer. Methods: After inserting the cylinder applicator into the patient, a CT scan was acquired and was loaded to an in-house developed treatment planning software. The cylinder applicator was automatically segmented using image-processing techniques. CTV was generated based on user-specified treatment depth and length. Locations of relevant points (apex point, prescription point, and vaginal surface point), central applicator channel coordinates, and dwell positions were determined according to their geometric relations with the applicator. Dwell time was computed through an inverse optimization process. The planning information was written into DICOM-RT plan and structure files to transfer the automatically generated plan to a commercial treatment planning system for plan verification and delivery. Results: We have tested the system retrospectively in nine patients treated with vaginal cylinder applicator. These cases were selected with different treatment prescriptions, lengths, depths, and cylinder diameters to represent a large patient population. Our system was able to generate treatment plans for these cases with clinically acceptable quality. Computation time varied from 3–6 min. Conclusion: We have developed a system to perform automated treatment planning for HDR brachytherapy with a cylinder applicator. Such a novel system has greatly improved treatment planning efficiency and reduced plan quality variation. It also served as a testbed to demonstrate the feasibility of automatic HDR treatment planning for more complicated cases.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-96: A New Paradigm of Weekly Chart Checking for Radiation Therapy Clinics

Purpose: To put forth an innovative clinical paradigm for weekly chart checking so that treatment status is periodically checked accurately and efficiently. This study also aims to help optimize the chart checking clinical workflow in a busy radiation therapy clinic. Methods: It is mandated by the Texas Administrative code to check patient charts of radiation therapy once a week or every five fractions, however it varies drastically among institutions in terms of when and how it is done. Some do it every day, but a lot of efforts are wasted on opening ineligible charts; some do it on a fixed day but the distribution of intervals between subsequent checks is not optimal. To establish an optimal chart checking procedure, a new paradigm was developed to achieve 1) charts are checked more accurately and more efficiently; 2) charts are checked on optimal days without any miss; 3) workload is evened out throughout a week when multiple physicists are involved. All active charts will be accessed by querying the R&V system. Priority is assigned to each chart based on the number of days before the next due date followed by sorting and workload distribution steps. New charts are also taken into account when distributing the workload so it is reasonably even throughout the week. Results: Our clinical workflow became more streamlined and smooth. In addition, charts get checked in a more timely fashion so that errors would get caught earlier should they occur. Conclusion: We developed a new weekly chart checking diagram. It helps physicists check charts in a timely manner, saves their time in busy clinics, and consequently reduces possible errors.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-193: Evaluation of a GPU-Based Fast Monte Carlo Code for Proton Therapy Biological Optimization

Purpose: Biological treatment plan optimization is of great interest for proton therapy. It requires extensive Monte Carlo (MC) simulations to compute physical dose and biological quantities. Recently, a gPMC package was developed for rapid MC dose calculations on a GPU platform. This work investigated its suitability for proton therapy biological optimization in terms of accuracy and efficiency. Methods: We performed simulations of a proton pencil beam with energies of 75, 150 and 225 MeV in a homogeneous water phantom using gPMC and FLUKA. Physical dose and energy spectra for each ion type on the central beam axis were scored. Relative Biological Effectiveness (RBE) was calculated using repair-misrepair-fixation model. Microdosimetry calculations were performed using Monte Carlo Damage Simulation (MCDS). Results: Ranges computed by the two codes agreed within 1 mm. Physical dose difference was less than 2.5 % at the Bragg peak. RBE-weighted dose agreed within 5 % at the Bragg peak. Differences in microdosimetric quantities such as dose average lineal energy transfer and specific energy were < 10%. The simulation time per source particle with FLUKA was 0.0018 sec, while gPMC was ∼ 600 times faster. Conclusion: Physical dose computed by FLUKA and gPMC were in a good agreement. The RBE differences along the central axis were small, and RBE-weighted dose difference was found to be acceptable. The combined accuracy and efficiency makes gPMC suitable for proton therapy biological optimization.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-350: Continuous Leaf Optimization (CLO) for IMRT Leaf Sequencing

Purpose: To study a new step-and-shoot IMRT leaf sequencing model that avoids the two main pitfalls of conventional leaf sequencing: (1) target fluence being stratified into a fixed number of discrete levels and/or (2) aperture leaf positions being restricted to a discrete set of locations. These assumptions induce error into the sequence or reduce the feasible region of potential plans, respectively. Methods: We develop a one-dimensional (single leaf pair) methodology that does not make assumptions (1) or (2) that can be easily extended to a multi-row model. The proposed continuous leaf optimization (CLO) methodology takes in an existing set of apertures and associated intensities, or solution “seed,” and improves the plan without the restrictiveness of 1or (2). It then uses a first-order descent algorithm to converge onto a locally optimal solution. A seed solution can come from models that assume (1) and (2), thus allowing the CLO model to improve upon existing leaf sequencing methodologies. Results: The CLO model was applied to 208 generated target fluence maps in one dimension. In all cases for all tested sequencing strategies, the CLO model made improvements on the starting seed objective function. The CLO model also was able to keep MUs low. Conclusion: The CLO model can improve upon existing leaf sequencing methods by avoiding the restrictions of (1) and (2). By allowing for more flexible leaf positioning, error can be reduced when matching some target fluence. This study lays the foundation for future models and solution methodologies that can incorporate continuous leaf positions explicitly into the IMRT treatment planning model. Supported by Cancer Prevention & Research Institute of Texas (CPRIT) - ID RP150485.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-428: An Optimization-Based Commissioning Tool for Finite Size Pencil Beam Dose Calculations

Purpose: Finite size pencil beam (FSPB) algorithms are commonly used to pre-calculate the beamlet dose distribution for IMRT treatment planning. FSPB commissioning, which usually requires fine tuning of the FSPB kernel parameters, is crucial to the dose calculation accuracy and hence the plan quality. Yet due to the large number of beamlets, FSPB commissioning could be very tedious. This abstract reports an optimization-based FSPB commissioning tool we have developed in MatLab to facilitate the commissioning. Methods: A FSPB dose kernel generally contains two types of parameters: the profile parameters determining the dose kernel shape, and a 2D scaling factors accounting for the longitudinal and off-axis corrections. The former were fitted using the penumbra of a reference broad beam’s dose profile with Levenberg-Marquardt algorithm. Since the dose distribution of a broad beam is simply a linear superposition of the dose kernel of each beamlet calculated with the fitted profile parameters and scaled using the scaling factors, these factors could be determined by solving an optimization problem which minimizes the discrepancies between the calculated dose of broad beams and the reference dose. Results: We have commissioned a FSPB algorithm for three linac photon beams (6MV, 15MV and 6MVFFF). Dose of four field sizes (6*6cm2, 10*10cm2, 15*15cm2 and 20*20cm2) were calculated and compared with the reference dose exported from Eclipse TPS system. For depth dose curves, the differences are less than 1% of maximum dose after maximum dose depth for most cases. For lateral dose profiles, the differences are less than 2% of central dose at inner-beam regions. The differences of the output factors are within 1% for all the three beams. Conclusion: We have developed an optimization-based commissioning tool for FSPB algorithms to facilitate the commissioning, providing sufficient accuracy of beamlet dose calculation for IMRT optimization.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2016

SU-F-T-598: Robotic Radiosurgery System Versus Pencil Beam Scanning Proton Therapy for Definitive Intracranial Treatments

Purpose: To characterize the dose distributions of Cyberknife and intensity-modulated-proton-therapy (IMPT). Methods: A total of 20 patients previously treated with Cyberknife were selected. The original planning-target-volume (PTV) was used in the ‘IMPT-ideal’ plan assuming a comparable image-guidance with Cyberknife. A 3mm expansion was made to create the proton-PTV for the ‘IMPT-3mm’ plan representing the current proton-therapy where a margin of 3mm is used to account for the inferior image-guidance. The proton range uncertainty was taken-care in beam-design by adding the proximal- and distal-margins (3%water-equivalent-depth+1mm) for both proton plans. The IMPT plans were generated to meet the same target coverage as the Cyberknife-plans. The plan quality of IMPT-ideal and IMPT-3mm were compared to the Cyberknife-plan. To characterize plan quality, we defined the ratio(R) of volumes encompassed by the selected isodose surfaces for Cyberknife and IMPT plans (VCK/VIMPT). Comparisons were made for both Cyberknife versus IMPT-ideal and Cyberknife versusIMPT-3mm to further discuss the impact of setup error margins used in proton therapy and the correlation with target size and location. Results: IMPT-ideal plans yield comparable plan quality as CK plans and slightly better OAR sparing while the IMPT-3mm plan results in a higher dose to the OARs, especially for centralized tumors. Comparing to the IMPT-ideal plans, a slightly larger 80% (Ravg=1.05) dose cloud and significantly larger 50% (Ravg=1.3) and 20% (Ravg=1.60) dose clouds are seen in CK plans. However, the 3mm expansion results in a larger high and medium dose clouds in IMPT-3mm plans (Ravg=0.65 for 80%-isodose; Ravg=0.93 for 50%-isodose). The trend increases with the size of the target and the distance from the brainstem to the center of target. Conclusion: Cyberknife is more preferable for treating centralized targets and proton therapy is advantageous for the large and peripheral targets. Advanced image guidance would improve the efficacy of proton therapy for intracranial treatments.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-650: The Comparison of Robotic Partial Breast Stereotactic Irradiation Using MLC Vs. Iris Cone

Purpose: To evaluate the dosimetric impact on treatment planning for partial breast stereotactic irradiation using Cyberknife with MLC versus Iris Cone. Methods: Ten patients whom underwent lumpectomy for DCIS or stage I invasive non-lobular epithelial breast cancer were included in this study. All patients were previously treated on the Cyberknife using Iris cone with the prescription dose of 37.5Gy in 5 fractions covering at least 95% of PTV on our phase I SBRT 5 fraction partial breast irradiation trial. Retrospectively, treatment planning was performed and compared using the new Cyberknife M6 MLC system for each patient. Using the same contours and critical organ constraints for both MLC and Iris cone plans, the dose on target and critical organs were analyzed accordingly. Results: Dose to critical organs such as ipsilateral lung, contralateral lung, heart, skin, ipsilateral breast, and rib were analyzed, as well as conformity index and high dose spillage of the target area. In 9 of 10 patients, the MLC plans had less total ipsilateral breast volume encompassing the 50% prescription isodose (mean:22.3±8.2% MLC vs. 31.6±8.0 Iris, p=0.00014) .The MLC plans mean estimated treatment delivery time was significantly less than the Iris plans (51±3.9min vs. 56.2±9min, p=0.03) Both MLC and Iris cone plans were able to meet all dose constraints and there was no statistical difference between those dose constraints. Conclusion: Both MLC and Iris Cone can deliver conformal dose to a partial breast target and satisfy the dose constraints of critical organs. The new Cyberknife with MLC can deliver a more conformal dose in the lower dose region and spare more ipsilateral breast tissue to the 50% prescription isodose. The treatment time for partial breast SBRT plans was also reduced using MLC. Project receives research support from Accuray Inc.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-G-201-01: An Automated Treatment Plan Quality Assurance Program for High-Dose Rate (HDR) Brachytherapy with a VaginalCylinder Applicator

Purpose: Plan specific quality assurance (QA) is an important step in high dose rate (HDR) brachytherapy to ensure the integrity of a treatment plan. The conventional approach is to assemble a set of plan screen-captures in a document and have an independent plan-checker to verify it. Not only is this approach cumbersome and time-consuming, using a document also limits the items that can be verified, hindering plan quality and patient safety. We have initiated efforts to develop a web-based HDR brachytherapy QA system called AutoBrachy QA, for comprehensive and efficient QA. This abstract reports a new plugin in this system for the QA of a cylinder HDR brachytherapy treatment. Methods: A cylinder plan QA module was developed using Python. It was plugged into our AutoBrachy QA system. This module extracted information from CT images and treatment plan. Image processing techniques were employed to obtain geometric parameters, e.g. cylinder diameter. A comprehensive set of eight geometrical and eight dosimetric features of the plan were validated against user specified planning parameter, such as prescription value, treatment depth and length, etc. A PDF document was generated, consisting of a summary QA sheet with all the QA results, as well as images showing plan details. Results: The cylinder QA program has been implemented in our clinic. To date, it has been used in 11 patient cases and was able to successfully perform QA tests in all of them. The QA program reduced the average plan QA time from 7 min using conventional manual approach to 0.5 min. Conclusion: Being a new module in our AutoBrachy QA system, an automated treatment plan QA module for cylinder HDR brachytherapy has been successfully developed and clinically implemented. This module improved clinical workflow and plan integrity compared to the conventional manual approach.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-G-BRA-12: Development of An Intra-Fractional Motion Tracking and Dose Reconstruction System for Adaptive Stereotactic Body Radiation Therapy in High-Risk Prostate Cancer

Purpose: A clinical trial on stereotactic body radiation therapy (SBRT) for high-risk prostate cancer is undergoing at our institution. In addition to escalating dose to the prostate, we have increased dose to intra-prostatic lesions. Intra-fractional prostate motion deteriorates well planned radiation dose, especially for the small intra-prostatic lesions. To solve this problem, we have developed a motion tracking and 4D dose-reconstruction system to facilitate adaptive re-planning. Methods: Patients in the clinical trial were treated with VMAT using four arcs and 10 FFF beam. KV triggered x-ray projections were taken every 3 sec during delivery to acquire 2D projections of 3D anatomy at the direction orthogonal to the therapeutic beam. Each patient had three implanted prostate markers. Our developed system first determined 2D projection locations of these markers and then 3D prostate translation and rotation via 2D/3D registration of the markers. Using delivery log files, our GPU-based Monte Carlo tool (goMC) reconstructed dose corresponding to each triggered image. The calculated 4D dose distributions were further aggregated to yield the delivered dose. Results: We first tested each module in our system. MC dose engine were commissioned to our treatment planning system with dose difference of <0.5%. For motion tracking, 1789 kV projections from 7 patients were acquired. The 2D marker location error was <1 mm. For 3D motion tracking, root mean square (RMS) errors along LR, AP, and CC directions were 0.26mm, 0.36mm, and 0.01mm respectively in simulation studies and 1.99mm, 1.37mm, and 0.22mm in phantom studies. We also tested the entire system workflow. Our system was able to reconstruct delivered dose. Conclusion: We have developed a functional intra-fractional motion tracking and 4D dose re-construction system to support our clinical trial on adaptive high-risk prostate cancer SBRT. Comprehensive evaluations have shown the capability and accuracy of our system.

60 APPLIED LIFE SCIENCES↗