skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: SU-G-TeP4-09: Development of a Plan Data Aggregator for Time Efficient Physics Second-Checks of Machine Parameters for External Beam Treatment Plans

Abstract

Purpose: Physics second-checks for external beam radiation therapy are performed, in-part, to verify that the machine parameters in the Record-and-Verify (R&V) system that will ultimately be sent to the LINAC exactly match the values initially calculated by the Treatment Planning System (TPS). While performing the second-check, a large portion of the physicists’ time is spent navigating and arranging display windows to locate and compare the relevant numerical values (MLC position, collimator rotation, field size, MU, etc.). Here, we describe the development of a software tool that guides the physicist by aggregating and succinctly displaying machine parameter data relevant to the physics second-check process. Methods: A data retrieval software tool was developed using Python to aggregate data and generate a list of machine parameters that are commonly verified during the physics second-check process. This software tool imported values from (i) the TPS RT Plan DICOM file and (ii) the MOSAIQ (R&V) Structured Query Language (SQL) database. The machine parameters aggregated for this study included: MLC positions, X&Y jaw positions, collimator rotation, gantry rotation, MU, dose rate, wedges and accessories, cumulative dose, energy, machine name, couch angle, and more. Results: A GUI interface was developed to generate a side-by-side display of themore » aggregated machine parameter values for each field, and presented to the physicist for direct visual comparison. This software tool was tested for 3D conformal, static IMRT, sliding window IMRT, and VMAT treatment plans. Conclusion: This software tool facilitated the data collection process needed in order for the physicist to conduct a second-check, thus yielding an optimized second-check workflow that was both more user friendly and time-efficient. Utilizing this software tool, the physicist was able to spend less time searching through the TPS PDF plan document and the R&V system and focus the second-check efforts on assessing the patient-specific plan-quality.« less

Authors:
; ;  [1];  [2];  [1];  [2];  [2]
  1. Rhode Island Hospital, Providence RI (United States)
  2. (United States)
Publication Date:
OSTI Identifier:
22649472
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
61 RADIATION PROTECTION AND DOSIMETRY; 60 APPLIED LIFE SCIENCES; COMPUTER CODES; DOSE RATES; EXTERNAL BEAM RADIATION THERAPY; LINEAR ACCELERATORS; PLANNING; ROTATION

Citation Formats

Belley, M, Schmidt, M, Knutson, N, University of Rhode Island, Kingston, RI, Price, M, University of Rhode Island, Kingston, RI, and Alpert Medical School of Brown University, Providence, RI. SU-G-TeP4-09: Development of a Plan Data Aggregator for Time Efficient Physics Second-Checks of Machine Parameters for External Beam Treatment Plans. United States: N. p., 2016. Web. doi:10.1118/1.4957134.
Belley, M, Schmidt, M, Knutson, N, University of Rhode Island, Kingston, RI, Price, M, University of Rhode Island, Kingston, RI, & Alpert Medical School of Brown University, Providence, RI. SU-G-TeP4-09: Development of a Plan Data Aggregator for Time Efficient Physics Second-Checks of Machine Parameters for External Beam Treatment Plans. United States. doi:10.1118/1.4957134.
Belley, M, Schmidt, M, Knutson, N, University of Rhode Island, Kingston, RI, Price, M, University of Rhode Island, Kingston, RI, and Alpert Medical School of Brown University, Providence, RI. 2016. "SU-G-TeP4-09: Development of a Plan Data Aggregator for Time Efficient Physics Second-Checks of Machine Parameters for External Beam Treatment Plans". United States. doi:10.1118/1.4957134.
@article{osti_22649472,
title = {SU-G-TeP4-09: Development of a Plan Data Aggregator for Time Efficient Physics Second-Checks of Machine Parameters for External Beam Treatment Plans},
author = {Belley, M and Schmidt, M and Knutson, N and University of Rhode Island, Kingston, RI and Price, M and University of Rhode Island, Kingston, RI and Alpert Medical School of Brown University, Providence, RI},
abstractNote = {Purpose: Physics second-checks for external beam radiation therapy are performed, in-part, to verify that the machine parameters in the Record-and-Verify (R&V) system that will ultimately be sent to the LINAC exactly match the values initially calculated by the Treatment Planning System (TPS). While performing the second-check, a large portion of the physicists’ time is spent navigating and arranging display windows to locate and compare the relevant numerical values (MLC position, collimator rotation, field size, MU, etc.). Here, we describe the development of a software tool that guides the physicist by aggregating and succinctly displaying machine parameter data relevant to the physics second-check process. Methods: A data retrieval software tool was developed using Python to aggregate data and generate a list of machine parameters that are commonly verified during the physics second-check process. This software tool imported values from (i) the TPS RT Plan DICOM file and (ii) the MOSAIQ (R&V) Structured Query Language (SQL) database. The machine parameters aggregated for this study included: MLC positions, X&Y jaw positions, collimator rotation, gantry rotation, MU, dose rate, wedges and accessories, cumulative dose, energy, machine name, couch angle, and more. Results: A GUI interface was developed to generate a side-by-side display of the aggregated machine parameter values for each field, and presented to the physicist for direct visual comparison. This software tool was tested for 3D conformal, static IMRT, sliding window IMRT, and VMAT treatment plans. Conclusion: This software tool facilitated the data collection process needed in order for the physicist to conduct a second-check, thus yielding an optimized second-check workflow that was both more user friendly and time-efficient. Utilizing this software tool, the physicist was able to spend less time searching through the TPS PDF plan document and the R&V system and focus the second-check efforts on assessing the patient-specific plan-quality.},
doi = {10.1118/1.4957134},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: With electronic medical records, patient information for the treatment planning process has become disseminated across multiple applications with limited quality control and many associated failure modes. We present the development of a single application with a centralized database to manage the planning process. Methods: The system was designed to replace current functionalities of (i) static directives representing the physician intent for the prescription and planning goals, localization information for delivery, and other information, (ii) planning objective reports, (iii) localization and image guidance documents and (iv) the official radiation therapy prescription in the medical record. Using the Eclipse Scripting Applicationmore » Programming Interface, a plug-in script with an associated domain-specific SQL Server database was created to manage the information in (i)–(iv). The system’s user interface and database were designed by a team of physicians, clinical physicists, database experts, and software engineers to ensure usability and robustness for clinical use. Results: The resulting system has been fully integrated within the TPS via a custom script and database. Planning scenario templates, version control, approvals, and logic-based quality control allow this system to fully track and document the planning process as well as physician approval of tradeoffs while improving the consistency of the data. Multiple plans and prescriptions are supported along with non-traditional dose objectives and evaluation such as biologically corrected models, composite dose limits, and management of localization goals. User-specific custom views were developed for the attending physician review, physicist plan checks, treating therapists, and peer review in chart rounds. Conclusion: A method was developed to maintain cohesive information throughout the planning process within one integrated system by using a custom treatment planning management application that interfaces directly with the TPS. Future work includes quantifying the improvements in quality, safety and efficiency that are possible with the routine clinical use of this system. Supported in part by NIH-P01-CA-059827.« less
  • Purpose: To automate the daily verification of each patient’s treatment by utilizing the trajectory log files (TLs) written by the Varian TrueBeam linear accelerator while reducing the number of false positives including jaw and gantry positioning errors, that are displayed in the Treatment History tab of Varian’s Chart QA module. Methods: Small deviations in treatment parameters are difficult to detect in weekly chart checks, but may be significant in reducing delivery errors, and would be critical if detected daily. Software was developed in house to read TLs. Multiple functions were implemented within the software that allow it to operate viamore » a GUI to analyze TLs, or as a script to run on a regular basis. In order to determine tolerance levels for the scripted analysis, 15,241 TLs from seven TrueBeams were analyzed. The maximum error of each axis for each TL was written to a CSV file and statistically analyzed to determine the tolerance for each axis accessible in the TLs to flag for manual review. The software/scripts developed were tested by varying the tolerance values to ensure veracity. After tolerances were determined, multiple weeks of manual chart checks were performed simultaneously with the automated analysis to ensure validity. Results: The tolerance values for the major axis were determined to be, 0.025 degrees for the collimator, 1.0 degree for the gantry, 0.002cm for the y-jaws, 0.01cm for the x-jaws, and 0.5MU for the MU. The automated verification of treatment parameters has been in clinical use for 4 months. During that time, no errors in machine delivery of the patient treatments were found. Conclusion: The process detailed here is a viable and effective alternative to manually checking treatment parameters during weekly chart checks.« less
  • Purpose: Redundant treatment verifications in conformal and intensity-modulated radiation therapy techniques are traditionally performed with single point calculations. New solutions can replace these checks with 3D treatment plan verifications. This work describes a software tool (Mobius3D, Mobius Medical Systems) that uses a GPU-accelerated collapsed cone algorithm to perform 3D independent verifications of TPS calculations. Methods: Mobius3D comes with reference beam models for common linear accelerators. The system uses an independently developed collapsed cone algorithm updated with recent enhancements. 144 isotropically-spaced cones are used for each voxel for calculations. These complex calculations can be sped up by using GPUs. Mobius3D calculatemore » dose using DICOM information coming from TPS (CT, RT Struct, RT Plan RT Dose). DVH-metrics and 3D gamma tests can be used to compare both TPS and secondary calculations. 170 patients treated with all common techniques as 3DCFRT (including wedged), static and dynamic IMRT and VMAT have been successfully verified with this solution. Results: Calculation times are between 3–5 minutes for 3DCFRT treatments and 15–20 for most complex dMLC and VMAT plans. For all PTVs mean dose and 90% coverage differences are (1.12±0.97)% and (0.68±1.19)%, respectively. Mean dose discrepancies for all OARs is (0.64±1.00)%. 3D gamma (global, 3%/3 mm) analysis shows a mean passing rate of (97.8 ± 3.0)% for PTVs and (99.0±3.0)% for OARs. 3D gamma pasing rate for all voxels in CT has a mean value of (98.5±1.6)%. Conclusion: Mobius3D is a powerful tool to verify all modalities of radiation therapy treatments. Dose discrepancies calculated by this system are in good agreement with TPS. The use of reference beam data results in time savings and can be used to avoid the propagation of errors in original beam data into our QA system. GPU calculations permit enhanced collapsed cone calculations with reasonable calculation times.« less
  • Purpose: To evaluate the effectiveness of an automated plan check tool to improve first-time plan quality as well as standardize and document performance of physics plan checks. Methods: The Plan Checker Tool (PCT) uses the Eclipse Scripting API to check and compare data from the treatment planning system (TPS) and treatment management system (TMS). PCT was created to improve first-time plan quality, reduce patient delays, increase efficiency of our electronic workflow, and to standardize and partially automate plan checks in the TPS. A framework was developed which can be configured with different reference values and types of checks. One examplemore » is the prescribed dose check where PCT flags the user when the planned dose and the prescribed dose disagree. PCT includes a comprehensive checklist of automated and manual checks that are documented when performed by the user. A PDF report is created and automatically uploaded into the TMS. Prior to and during PCT development, errors caught during plan checks and also patient delays were tracked in order to prioritize which checks should be automated. The most common and significant errors were determined. Results: Nineteen of 33 checklist items were automated with data extracted with the PCT. These include checks for prescription, reference point and machine scheduling errors which are three of the top six causes of patient delays related to physics and dosimetry. Since the clinical roll-out, no delays have been due to errors that are automatically flagged by the PCT. Development continues to automate the remaining checks. Conclusion: With PCT, 57% of the physics plan checklist has been partially or fully automated. Treatment delays have declined since release of the PCT for clinical use. By tracking delays and errors, we have been able to measure the effectiveness of automating checks and are using this information to prioritize future development. This project was supported in part by P01CA059827.« less
  • We report a methodology for comparing and combining dose information from external beam radiotherapy (EBRT) and interstitial brachytherapy (IB) components of prostate cancer treatment using the biological effective dose (BED). On a prototype early-stage prostate cancer patient treated with EBRT and low-dose rate I-125 brachytherapy, a 3-dimensional dose distribution was calculated for each of the EBRT and IB portions of treatment. For each component of treatment, the BED was calculated on a point-by-point basis to produce a BED distribution. These individual BED distributions could then be summed for combined therapies. BED dose-volume histograms (DVHs) of the prostate, urethra, rectum, andmore » bladder were produced and compared for various combinations of EBRT and IB. Transformation to BED enabled computation of the relative contribution of each modality to the prostate dose, as the relative weighting of EBRT and IB was varied. The BED-DVHs of the prostate and urethra demonstrated dramatically increased inhomogeneity with the introduction of even a small component of IB. However, increasing the IB portion relative to the EBRT component resulted in lower dose to the surrounding normal structures, as evidenced by the BED-DVHs of the bladder and rectum. Conformal EBRT and low-dose rate IB conventional dose distributions were successfully transformed to the common 'language' of BED distributions for comparison and for merging prostate cancer radiation treatment plans. The results of this analysis can assist physicians in quantitatively determining the best combination and weighting of radiation treatment modalities for individual patients.« less