Engineering topics

Rangaraj, D

Publications and source records attributed to Rangaraj, D.

7 records

DOE OSTI2016

SU-F-J-14: Kilovoltage Cone-Beam CT Dose Estimation of Varian On-Board Imager Using GMctdospp Monte Carlo Framework

Purpose: Although cone-beam CT (CBCT) imaging became popular in radiation oncology, its imaging dose estimation is still challenging. The goal of this study is to assess the kilovoltage CBCT doses using GMctdospp - an EGSnrc based Monte Carlo (MC) framework. Methods: Two Varian OBI x-ray tube models were implemented in the GMctpdospp framework of EGSnrc MC System. The x-ray spectrum of 125 kVp CBCT beam was acquired from an EGSnrc/BEAMnrc simulation and validated with IPEM report 78. Then, the spectrum was utilized as an input spectrum in GMctdospp dose calculations. Both full and half bowtie pre-filters of the OBI system were created by using egs-prism module. The x-ray tube MC models were verified by comparing calculated dosimetric profiles (lateral and depth) to ion chamber measurements for a static x-ray beam irradiation to a cuboid water phantom. An abdominal CBCT imaging doses was simulated in GMctdospp framework using a 5-year-old anthropomorphic phantom. The organ doses and effective dose (ED) from the framework were assessed and compared to the MOSFET measurements and convolution/superposition dose calculations. Results: The lateral and depth dose profiles in the water cuboid phantom were well matched within 6% except a few areas - left shoulder of the half bowtie lateral profile and surface of water phantom. The organ doses and ED from the MC framework were found to be closer to MOSFET measurements and CS calculations within 2 cGy and 5 mSv respectively. Conclusion: This study implemented and validated the Varian OBI x-ray tube models in the GMctdospp MC framework using a cuboid water phantom and CBCT imaging doses were also evaluated in a 5-year-old anthropomorphic phantom. In future study, various CBCT imaging protocols will be implemented and validated and consequently patient CT images will be used to estimate the CBCT imaging doses in patients.

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-279: Impact of Beam Energy Drifts On IMRT Delivery Accuracy

Purpose: According to TG-40 percent-depth-dose (PDD) tolerance is ±2% but TG-142 is ±1%. Now the question is, which one is relevant in IMRT era? The primary objective of this study is to evaluate dosimetric impact of beam-energy-drifts on IMRT-delivery. Methods: Beam-energy drifts were simulated by adjusting Linac’s bending-magnet-current (BMC) followed by tuning the pulse-forming network and adjusting gun-current. PDD change of −0.6% and +1.2% were tested. Planar-dosimetry measurements were performed using an ionization-chamber-array in solid-water phantoms. Study includes 10-head-and-neck and 3-breast cancer patients. en-face beam-deliveries were also tested at 1.3cm and 5.3cm depths. Composite and single-field dose-distributions were compared against the plans to determine %Gamma pass-rates (%GPRs). For plan dose comparisons, changes in %Gamma pass-rates (cPGPRs) were computed/reported to exclude the differences between dose-computation and delivery. Dose distributions of the drifted-energies were compared against their baseline measurements to determine the% GPRs. A Gamma criteria of 3%/3mm was considered for plan-dose comparisons while 3%/1mm used for measured dose intercomparisons. Results: For composite-dose delivery, average cPGPRs were 0.41%±2.48% and −2.54%±3.65% for low-energy (LE) and high-energy (HE) drifts, respectively. For measured dose inter-comparisons, the average%GPRs were 98.4%±2.2% (LE-drift) and 95.8%±4.0 (HE-drift). The average %GPR of 92.6%±4.3% was noted for the worst-case scenario comparing LE-drift to HE-drift. All en-face beams at 5.3 cm depth have cPGPRs within ±4% of the baseline-energy measurements. However, greater variations were noted for 1.3cm depth. Average %GPRs for drifted energies were >99% at 5.3cm and >97% at 1.3cm depths. However, for the worst-case scenario (LE-drift to HE-drift) these numbers dropped to 95.2% at 5.3cm and 93.1% at 1.3cm depths. Conclusion: The dosimetric impact of beam-energy drifts was found to be within clinically acceptable tolerance. However, this study includes a single energy with limited range of PDD change. Further studies are on going and the results will be presented. Received funding from Varian Medical Systems, Palo Alto, CA.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-308: Mobius FX Evaluation and Comparison Against a Commercial 4D Detector Array for VMAT Plan QA

Purpose: To evaluate the use of MobiusFX as a pre-treatment verification IMRT QA tool and compare it with a commercial 4D detector array for VMAT plan QA. Methods: 15 VMAT plan QA of different treatment sites were delivered and measured by traditional means with the 4D detector array ArcCheck (Sun Nuclear corporation) and at the same time measurement in linac treatment logs (Varian Dynalogs files) were analyzed from the same delivery with MobiusFX software (Mobius Medical Systems). VMAT plan QAs created in Eclipse treatment planning system (Varian) in a TrueBeam linac machine (Varian) were delivered and analyzed with the gamma analysis routine from SNPA software (Sun Nuclear corporation). Results: Comparable results in terms of the gamma analysis with 99.06% average gamma passing with 3%,3mm passing rate is observed in the comparison among MobiusFX, ArcCheck measurements, and the Treatment Planning System dose calculated. When going to a stricter criterion (1%,1mm) larger discrepancies are observed in different regions of the measurements with an average gamma of 66.24% between MobiusFX and ArcCheck. Conclusion: This work indicates the potential for using MobiusFX as a routine pre-treatment patient specific IMRT method for quality assurance purposes and its advantages as a phantom-less method which reduce the time for IMRT QA measurement. MobiusFX is capable of produce similar results of those by traditional methods used for patient specific pre-treatment verification VMAT QA. Even the gamma results comparing to the TPS are similar the analysis of both methods show that the errors being identified by each method are found in different regions. Traditional methods like ArcCheck are sensitive to setup errors and dose difference errors coming from the linac output. On the other hand linac log files analysis record different errors in the VMAT QA associated with the MLCs and gantry motion that by traditional methods cannot be detected.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-475: An Evaluation of the Overlap Between the Acceptance Testing and Commissioning Processes for Conventional Medical Linear Accelerators

Purpose: This work’s objective is to determine the overlap of processes, in terms of sub-processes and time, between acceptance testing and commissioning of a conventional medical linear accelerator and to evaluate the time saved by consolidating the two processes. Method: A process map for acceptance testing for medical linear accelerators was created from vendor documentation (Varian and Elekta). Using AAPM TG-106 and inhouse commissioning procedures, a process map was created for commissioning of said accelerators. The time to complete each sub-process in each process map was evaluated. Redundancies in the processes were found and the time spent on each were calculated. Results: Mechanical testing significantly overlaps between the two processes - redundant work here amounts to 9.5 hours. Many beam non-scanning dosimetry tests overlap resulting in another 6 hours of overlap. Beam scanning overlaps somewhat - acceptance tests include evaluating PDDs and multiple profiles but for only one field size while commissioning beam scanning includes multiple field sizes and depths of profiles. This overlap results in another 6 hours of rework. Absolute dosimetry, field outputs, and end to end tests are not done at all in acceptance testing. Finally, all imaging tests done in acceptance are repeated in commissioning, resulting in about 8 hours of rework. The total time overlap between the two processes is about 30 hours. Conclusion: The process mapping done in this study shows that there are no tests done in acceptance testing that are not also recommended to do for commissioning. This results in about 30 hours of redundant work when preparing a conventional linear accelerator for clinical use. Considering these findings in the context of the 5000 linacs in the United states, consolidating acceptance testing and commissioning would have allowed for the treatment of an additional 25000 patients using no additional resources.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TU-D-201-06: HDR Plan Prechecks Using Eclipse Scripting API

Purpose: Automate brachytherapy treatment plan quality check using Eclipse v13.6 scripting API based on pre-configured rules to minimize human error and maximize efficiency. Methods: The HDR Precheck system is developed based on a rules-driven approach using Eclipse scripting API. This system checks for critical plan parameters like channel length, first source position, source step size and channel mapping. The planned treatment time is verified independently based on analytical methods. For interstitial or SAVI APBI treatment plans, a Patterson-Parker system calculation is performed to verify the planned treatment time. For endobronchial treatments, an analytical formula from TG-59 is used. Acceptable tolerances were defined based on clinical experiences in our department. The system was designed to show PASS/FAIL status levels. Additional information, if necessary, is indicated appropriately in a separate comments field in the user interface. Results: The HDR Precheck system has been developed and tested to verify the treatment plan parameters that are routinely checked by the clinical physicist. The report also serves as a reminder or checklist for the planner to perform any additional critical checks such as applicator digitization or scenarios where the channel mapping was intentionally changed. It is expected to reduce the current manual plan check time from 15 minutes to <1 minute. Conclusion: Automating brachytherapy plan prechecks significantly reduces treatment plan precheck time and reduces human errors. When fully developed, this system will be able to perform TG-43 based second check of the treatment planning system’s dose calculation using random points in the target and critical structures. A histogram will be generated along with tabulated mean and standard deviation values for each structure. A knowledge database will also be developed for Brachyvision plans which will then be used for knowledge-based plan quality checks to further reduce treatment planning errors and increase confidence in the planned treatment.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2016

WE-H-BRC-04: Implement Lean Methodology to Make Our Current Process of CT Simulation to Treatment More Efficient

Purpose: Our goal is to implement lean methodology to make our current process of CT simulation to treatment more efficient. Methods: In this study, we implemented lean methodology and tools and employed flowchart in excel for process-mapping. We formed a group of physicians, physicists, dosimetrists, therapists and a clinical physics assistant and huddled bi-weekly to map current value streams. We performed GEMBA walks and observed current processes from scheduling patient CT Simulations to treatment plan approval. From this, the entire workflow was categorized into processes, sub-processes, and tasks. For each process we gathered data on touch time, first time quality, undesirable effects (UDEs), and wait-times from relevant members of each task. UDEs were binned per frequency of their occurrence. We huddled to map future state and to find solutions to high frequency UDEs. We implemented visual controls, hard stops, and documented issues found during chart checks prior to treatment plan approval. Results: We have identified approximately 64 UDEs in our current workflow that could cause delays, re-work, compromise the quality and safety of patient treatments, or cause wait times between 1 – 6 days. While some UDEs are unavoidable, such as re-planning due to patient weight loss, eliminating avoidable UDEs is our goal. In 2015, we found 399 issues with patient treatment plans, of which 261, 95 and 43 were low, medium and high severity, respectively. We also mapped patient-specific QA processes for IMRT/Rapid Arc and SRS/SBRT, involving 10 and 18 steps, respectively. From these, 13 UDEs were found and 5 were addressed that solved 20% of issues. Conclusion: We have successfully implemented lean methodology and tools. We are further mapping treatment site specific workflows to identify bottlenecks, potential breakdowns and personnel allocation and employ tools like failure mode effects analysis to mitigate risk factors to make this process efficient.

60 APPLIED LIFE SCIENCES↗