Results for “Dose Code” — Page 43

DOE OSTI2015

SU-E-I-32: Benchmarking Head CT Doses: A Pooled Vs. Protocol Specific Analysis of Radiation Doses in Adult Head CT Examinations

Purpose: The aim of this study was to collect CT dose index data from adult head exams to establish benchmarks based on either: (a) values pooled from all head exams or (b) values for specific protocols. One part of this was to investigate differences in scan frequency and CT dose index data for inpatients versus outpatients. Methods: We collected CT dose index data (CTDIvol) from adult head CT examinations performed at our medical facilities from Jan 1st to Dec 31th, 2014. Four of these scanners were used for inpatients, the other five were used for outpatients. All scanners used Tube Current Modulation. We used X-ray dose management software to mine dose index data and evaluate CTDIvol for 15807 inpatients and 4263 outpatients undergoing Routine Brain, Sinus, Facial/Mandible, Temporal Bone, CTA Brain and CTA Brain-Neck protocols, and combined across all protocols. Results: For inpatients, Routine Brain series represented 84% of total scans performed. For outpatients, Sinus scans represented the largest fraction (36%). The CTDIvol (mean ± SD) across all head protocols was 39 ± 30 mGy (min-max: 3.3–540 mGy). The CTDIvol for Routine Brain was 51 ± 6.2 mGy (min-max: 36–84 mGy). The values for Sinus were 24 ± 3.2 mGy (min-max: 13–44 mGy) and for Facial/Mandible were 22 ± 4.3 mGy (min-max: 14–46 mGy). The mean CTDIvol for inpatients and outpatients was similar across protocols with one exception (CTA Brain-Neck). Conclusion: There is substantial dose variation when results from all protocols are pooled together; this is primarily a function of the differences in technical factors of the protocols themselves. When protocols are analyzed separately, there is much less variability. While analyzing pooled data affords some utility, reviewing protocols segregated by clinical indication provides greater opportunity for optimization and establishing useful benchmarks.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-268: A Feasibility Study of Independent Dose Verification for Vero4DRT

Purpose: Vero4DRT (Mitsubishi Heavy Industries Ltd.) has been released for a few years. The treatment planning system (TPS) of Vero4DRT is dedicated, so the measurement is the only method of dose verification. There have been no reports of independent dose verification using Clarksonbased algorithm for Vero4DRT. An independent dose verification software program of the general-purpose linac using a modified Clarkson-based algorithm was modified for Vero4DRT. In this study, we evaluated the accuracy of independent dose verification program and the feasibility of the secondary check for Vero4DRT. Methods: iPlan (Brainlab AG) was used as the TPS. PencilBeam Convolution was used for dose calculation algorithm of IMRT and X-ray Voxel Monte Carlo was used for the others. Simple MU Analysis (SMU, Triangle Products, Japan) was used as the independent dose verification software program in which CT-based dose calculation was performed using a modified Clarkson-based algorithm. In this study, 120 patients’ treatment plans were collected in our institute. The treatments were performed using the conventional irradiation for lung and prostate, SBRT for lung and Step and shoot IMRT for prostate. Comparison in dose between the TPS and the SMU was done and confidence limits (CLs, Mean ± 2SD %) were compared to those from the general-purpose linac. Results: As the results of the CLs, the conventional irradiation (lung, prostate), SBRT (lung) and IMRT (prostate) show 2.2 ± 3.5% (CL of the general-purpose linac: 2.4 ± 5.3%), 1.1 ± 1.7% (−0.3 ± 2.0%), 4.8 ± 3.7% (5.4 ± 5.3%) and −0.5 ± 2.5% (−0.1 ± 3.6%), respectively. The CLs for Vero4DRT show similar results to that for the general-purpose linac. Conclusion: The independent dose verification for the new linac is clinically available as a secondary check and we performed the check with the similar tolerance level of the general-purpose linac. This research is partially supported by Japan Agency for Medical Research and Development (AMED)

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Comparison of the calculated absorbed dose using the Cadplan™ treatment planning software and Tld-100 measurements in an Alderson-Rando phantom for a bronchogenic treatment

To verify the accuracy of the absorbed doses D calculated by a TPS Cadplan for a bronchogenic treatment (in an Alderson-Rando phantom) are chosen ten points with the following D's and localizations. Point 1, posterior position on the left edge with 136.4 Gy. Points: 2, 3 and 4 in the left lung with 104.9, 104.3 and 105.8 Gy, respectively; points 5 and 6 at the mediastinum with 192.4 and 173.5 Gy; points 7, 8 and 9 in the right lung with 105.8, 104.2 and 104.7 Gy, and 10 at posterior position on right edge with 143.7 Gy. IAEA type capsules with TLD 100 powder are placed, planned and irradiated. The evaluation of the absorbed dose is carried out a curve of calibration for the LiF response (nC) {sup vs} {sup DW}, to several cavity theories. The traceability for the DW is obtained with a secondary standard calibrated at the NRC (Canada). The dosimetric properties for the materials considered are determined from the Hounsfield numbers reported by the TPS. The stopping power ratios are calculated for nominal spectrum to 6 MV photons. The percent variations among the planned and determined D in all the cases they are < ± 3%.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

SU-E-I-66: Radiomics and Image Registration Updates for the Computational Environment for Radiotherapy Research (CERR)

Purpose: To present new tools in CERR for Radiomics, image registration and other software updates and additions. Methods: Radiomics: CERR supports generating 3-D texture metrics based on gray scale co-occurance. Two new ways to calculate texture features were added: (1) Local Texture Averaging: Local texture is calculated around a voxel within the userdefined bounding box. The final texture metrics are the average of local textures for all the voxels. This is useful to detect any local texture patterns within an image. (2) Image Smoothing: A convolution ball of user-defined radius is rolled over an image to smooth out artifacts. The texture metrics are then computed on the smooth image. Image Registration: (1) Support was added to import deformation vector fields as well as non-deformable transformation matrices generated by vendor software and stored in standard DICOM format. (2) Support was added to use image within masks while computing image deformations. CT to MR registration is supported. This registration uses morphological edge information within the images to guide the deformation process. In addition to these features, other noteworthy additions to CERR include (1) Irregularly shaped ROI: This is done by taking intersection between infinitely extended irregular polygons drawn on any of the two views. Such an ROI is more conformal and useful in avoiding any unwanted parts of images that cannot be avoided with the conventional cubic box. The ROI is useful to generate Radiomics metrics. (2) Ability to insert RTDOSE in DICOM format to existing CERR plans. (3) Ability to import multi-frame PET-CT and SPECT-CT while maintaining spatial registration between the two modalities. (4) Ability to compile CERR on Unix-like systems. Results: The new features and updates are available via https://www.github.com/adityaapte/cerr . Conclusion: Features added to CERR increase its utility in Radiomics, Image-Registration and Outcomes modeling.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2015

TU-F-CAMPUS-T-05: Replacement Computational Phantoms to Estimate Dose in Out-Of-Field Organs and Tissues

Purpose: To estimate the absorbed dose in organs and tissues at risk for radiogenic cancer for children receiving photon radiotherapy for localized brain tumors (LBTs) by supplementing their missing body anatomies with those of replacement computational phantoms. Applied beyond the extent of the RT Images collected by computed tomography simulation, these phantoms included RT Image and RT Structure Set objects that encompassed sufficient extents and contours for dosimetric calculations. Method: Nine children, aged 2 to 14 years, who received three-dimensional conformal radiotherapy for low-grade LBTs, were randomly selected for this study under Institutional-Review-Board protocol. Because the extents of their RT Images were cranial only, they were matched for size and sex with patients from a previous study with larger extents and for whom contours of organs at risk for radiogenic cancer had already been delineated. Rigid fusion was performed between the patients’ data and those of the replacement computational phantoms using commercial software. In-field dose was calculated with a clinically-commissioned treatment planning system, and out-of-field dose was estimated with an analytical model. Results: Averaged over all nine children and normalized for a therapeutic dose of 54 Gy prescribed to the PTV, where the PTV is the GTV, the highest mean organ doses were 3.27, 2.41, 1.07, 1.02, 0.24, and 0.24 Gy in the non-tumor remainder, red bone marrow, thyroid, skin, breasts, and lungs, respectively. The mean organ doses ranged by a factor of 3 between the smallest and largest children. Conclusion: For children receiving photon radiotherapy for LBTs, we found their doses in organs at risk for second cancer to be non-negligible, especially in the non-tumor remainder, red bone marrow, thyroid, skin, breasts, and lungs. This study demonstrated the feasibility for patient dosimetry studies to augment missing patient anatomy by applying size- and sex-matched replacement computational phantoms with pre-contoured organs. Funding is in part by the Fogarty International Center award K01TW008409, and the Portland Chapter of the Achievement Rewards for College Scientists. The content is solely the responsibility of the authors, and does not necessarily represent the official views of the sponsors. The authors declare no conflict of interest.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

An Advanced Machine Learning and Artificial Intelligence System for Demonstrating Radiation Regulatory Compliance in DOE Accelerator Facilities

In this Phase II proposal, Applied Research LLC (ARLLC), Thomas Jefferson National Accelerator Facility (Jefferson Lab), and Old Dominion University (ODU) propose the combination of domain knowledge (beam characteristics, fixed structural shielding, earthen burden (the soil and foliage added to the dome of the experimental halls as additional shielding), etc.), machine learning (ML) and/or artificial intelligence (AI) to correlate a variety of multi-modal onsite signals and the radiation fields seen in accessible areas of the accelerator site and the site boundary. The ML/AI will consider the complex influence of environmental parameters affecting the radon contribution of the measurements, focusing on actual data obtained from Jefferson Lab. In Phase I, the coded beam and location data were fed into a deep learning model to predict doses at several designated locations in Jefferson Lab’s facility. Moreover, a dense radiation map was generated using only a sparse collection of the samples in a facility. In Phase II, we will develop a software prototype containing a radiation prediction algorithm, dense radiation map algorithms, and background noise prediction algorithms, with actual data used to evaluate the prototype. This work will provide a framework for evaluation of radiation measurement results around the site based on learned responses. In addition, the proposed approach allows more granular mapping of radiation levels. Better understanding and communication of these levels is related to the overall approach in keeping doses to personnel ALARA.

43 PARTICLE ACCELERATORS↗

DOE OSTI2015

FPGA-based prototype of portable environmental radiation monitor

This new portable radiological environmental monitor consists of 2 main components, Gamma ionization chamber and a FPGA-based electronic enclosure linked to convivial software for treatment and analyzing. The HPIC ion chamber is the heart of this radiation measurement system and is running in range from 0 to 100 mR/h, so that the sensitivity at the output is 20 mV/μR/h, with a nearly flat energy response from 0,07 to 10 MEV. This paper presents a contribution for developing a new nuclear measurement data acquisition system based on Cyclone III FPGA Starter Kit ALTERA, and a user-friendly software to run real-time control and data processing. It was developed to substitute the older radiation monitor RSS-112 PIC installed in CNESTEN's Laboratory in order to improve some of its functionalities related to acquisition time and data memory capacity. As for the associated acquisition software, it was conceived under the virtual LabView platform from National Instrument, and offers a variety of system setup for radiation environmental monitoring. It gives choice to display both the statistical data and the dose rate. Statistical data shows a summary of current data, current time/date and dose integrator values, and the dose rate displays the current dose rate in large numbers for viewing from a distance as well as the date and time. The prototype version of this new instrument and its data processing software has been successfully tested and validated for viewing and monitoring the environmental radiation of Moroccan nuclear center. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2010

Shielding Studies for Superconducting RF Cavities at Fermilab

A semi-empirical method that allows us to predict intensity of generated field emission in superconducting RF cavities is described. Spatial, angular and energy distributions of the generated radiation are calculated with the FISHPACT code. The Monte Carlo code MARS15 is used for modeling the radiation transport in matter. A comparison with dose rate measurements performed in the Fermilab Vertical Test Facility for ILC-type cavities with accelerating gradients up to 35 MV/m is presented as well.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2015

MO-D-213-05: Sensitivity of Routine IMRT QA Metrics to Couch and Collimator Rotations

Purpose: To assess the sensitivity of gamma index and other IMRT QA metrics to couch and collimator rotations. Methods: Two brain IMRT plans with couch and/or collimator rotations in one or more of the fields were evaluated using the IBA MatriXX ion chamber array and its associated software (OmniPro-I’mRT). The plans were subjected to routine QA by 1) Creating a composite planar dose in the treatment planning system (TPS) with the couch/collimator rotations and 2) Creating the planar dose after “zeroing” the rotations. Plan deliveries to MatriXX were performed with all rotations set to zero on a Varian 21ex linear accelerator. This in effect created TPS-created planar doses with an induced rotation error. Point dose measurements for the delivered plans were also performed in a solid water phantom. Results: The IMRT QA of the plans with couch and collimator rotations showed clear discrepancies in the planar dose and 2D dose profile overlays. The gamma analysis, however, did pass with the criteria of 3%/3mm (for 95% of the points), albeit with a lower percentage pass rate, when one or two of the fields had a rotation. Similar results were obtained with tighter criteria of 2%/2mm. Other QA metrics such as percentage difference or distance-to-agreement (DTA) histograms produced similar results. The point dose measurements did not obviously indicate the error due to location of dose measurement (on the central axis) and the size of the ion chamber used (0.6 cc). Conclusion: Relying on Gamma analysis, percentage difference, or DTA to determine the passing of an IMRT QA may miss critical errors in the plan delivery due to couch/collimator rotations. A combination of analyses for composite QA plans, or per-beam analysis, would detect these errors.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-P-35: A Multi-Institutional Plan Quality Checking Tool Built On Oncospace: A Shared Radiation Oncology Database System

Purpose: Late toxicity from radiation to critical structures limits the possible dose in Radiation Therapy. Perfectly conformal treatment of a target is not realizable, so the clinician must accept a certain level of collateral radiation to nearby OARs. But how much? General guidelines exist for healthy tissue sparing which guide RT treatment planning, but are these guidelines good enough to create the optimal plan given the individualized patient anatomy? We propose a means to evaluate the planned dose level to an OAR using a multi-institutional data-store of previously treated patients, so a clinician might reconsider planning objectives. Methods: The tool is built on Oncospace, a federated data-store system, which consists of planning data import, web based analysis tools, and a database containing:1) DVHs: dose by percent volume delivered to each ROI for each patient previously treated and included in the database.2) Overlap Volume Histograms (OVHs): Anatomical measure defined as the percent volume of an ROI within a given distance to target structures.Clinicians know what OARs are important to spare. For any ROI, Oncospace knows for which patients’ anatomy that ROI was harder to plan in the past (the OVH is less). The planned dose should be close to the least dose of previous patients. The tool displays the dose those OARs were subjected to, and the clinician can make a determination about the planning objectives used.Multiple institutions contribute to the Oncospace Consortium, and their DVH and OVH data are combined and color coded in the output. Results: The Oncospace website provides a plan quality display tool which identifies harder to treat patients, and graphically displays the dose delivered to them for comparison with the proposed plan. Conclusion: The Oncospace Consortium manages a data-store of previously treated patients which can be used for quality checking new plans. Grant funding by Elekta.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-J-33: Comparison Between Soft Tissue Alignment and Bony Alignment for Pancreatic Cancer Radiotherapy

Purpose An IGRT modality for pancreatic cancer treatment with dose escalation at our institution is in-room daily CT imaging. The purpose of this study is to assess the difference between soft tissue alignment and bony alignment for pancreatic tumor localization. Methods Eighteen patients with pancreatic tumors who underwent IMRT treatment with an inspiration breath-hold technique between July 2012 and February 2015 are included in this study. Prior to each treatment, a CT scan was acquired. The CT image guidance started with auto-alignment to either the bony anatomy (vertebral bodies) or fiducials (for the six patients with the stent in/near the tumor) and then, when necessary, manual adjustments were made based on soft tissue alignment using clinical software (CT-Assisted Targeting system). The difference between soft tissue alignment and bony/fiducial alignment was evaluated. Results Of all 380 treatments, manual adjustment was made in 225 treatments, ranging from 11% (3 treatments out of 28) to 96% (27 treatments out of 28) per patient. The mean of the difference between soft tissue alignment and bony/fiducial alignment per patient ranged from −3.6 to 0.3 mm, −1.5 to 2.8 mm, and −3.3 to 3.4 mm in the AP, SI, and RL directions, respectively. The maximum difference over all treatments was −9.5, −14.6, and −14.6 mm in the AP, SI, and RL directions, respectively. Conclusion About 60% of the time, manual adjustment based on soft tissue alignment was required. The extent of manual adjustment was usually small but varied significantly from patient to patient. The ultimate goal of the IGRT modality using daily CT imaging is not to fully cover the target but to spare organs-at-risk as much as possible to avoid them moving into higher dose gradients than accepted in the treatment plan. To this end, manual adjustment based on soft tissue alignment is critically important.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-T-502: Initial Results of a Comparison of Treatment Plans Produced From Automated Prioritized Planning Method and a Commercial Treatment Planning System

Purpose We developed an automated treatment planning system based on a hierarchical goal programming approach. To demonstrate the feasibility of our method, we report the comparison of prostate treatment plans produced from the automated treatment planning system with those produced by a commercial treatment planning system. Methods In our approach, we prioritized the goals of the optimization, and solved one goal at a time. The purpose of prioritization is to ensure that higher priority dose-volume planning goals are not sacrificed to improve lower priority goals. The algorithm has four steps. The first step optimizes dose to the target structures, while sparing key sensitive organs from radiation. In the second step, the algorithm finds the best beamlet weight to reduce toxicity risks to normal tissue while holding the objective function achieved in the first step as a constraint, with a small amount of allowed slip. Likewise, the third and fourth steps introduce lower priority normal tissue goals and beam smoothing. We compared with prostate treatment plans from Memorial Sloan Kettering Cancer Center developed using Eclipse, with a prescription dose of 72 Gy. A combination of liear, quadratic, and gEUD objective functions were used with a modified open source solver code (IPOPT). Results Initial plan results on 3 different cases show that the automated planning system is capable of competing or improving on expert-driven eclipse plans. Compared to the Eclipse planning system, the automated system produced up to 26% less mean dose to rectum and 24% less mean dose to bladder while having the same D95 (after matching) to the target. Conclusion We have demonstrated that Pareto optimal treatment plans can be generated automatically without a trial-and-error process. The solver finds an optimal plan for the given patient, as opposed to database-driven approaches that set parameters based on geometry and population modeling.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-T-380: Evaluation of BEBIG HDR 60Co System for AccuBoost Therapy

Purpose: In this project, the possibility of utilizing the BEBIG 60Co HDR system for AccuBoostTM treatment has been evaluated. Methods: Dose distributions in various breast sizes have been calculated for both Co-60 and Ir-192 sources using the MCNP5 code. These calculations were performed in breast tissues with thicknesses of 4cm, 6cm, and 8cm. The initial calculations were performed with the same applicator dimensions as the existing applicators used with the HDR Ir-192 system. The activity of the Co-60 source was selected such that the dose at the breast center was the same as the values from 192Ir. Then, the applicator thicknesses were increased to twice of those used with HDR Ir-192 system, for reducing skin and chest doses by Co-60 system. Dose to breast skin and chest wall were compared for both applicators types, with and without inclusion of a focusing cone at the applicator center. Results: The results showed that loading HDR Co-60 source inside the thin applicators impose higher doses to breast skin and chest wall compared to the 192Ir source. The area of the chest wall covered by 10Gy when treated by Co-60 with the thin and thick applicators, or treated by Ir-192 with thin applicator are 79cm2, 39cm2, and 3.8cm2, respectively. These values are reduced to 34cm2, 0cm2, and 0cm2 by using the focusing cone. It is worth noting that the breast skin areas covered by the 60Gy isodose line are 9.9cm2 and 7.8cm2 for Co-60 with the thin and thick applicators, respectively, while it is 20cm2 for Ir-192 when no focusing cone is present. These values are 0cm2, 0cm2, and 11cm2 in the presence of the focusing cone. Conclusion: The results indicate that using Co-60 with the thicker applicators is beneficial because of the higher half-life of Co-60, and the reduced maximum skin dose when compared with Ir-192.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-T-762: Toward Volume-Based Independent Dose Verification as Secondary Check

Purpose: Lung SBRT plan has been shifted to volume prescription technique. However, point dose agreement is still verified using independent dose verification at the secondary check. The volume dose verification is more affected by inhomogeneous correction rather than point dose verification currently used as the check. A feasibility study for volume dose verification was conducted in lung SBRT plan. Methods: Six SBRT plans were collected in our institute. Two dose distributions with / without inhomogeneous correction were generated using Adaptive Convolve (AC) in Pinnacle3. Simple MU Analysis (SMU, Triangle Product, Ishikawa, JP) was used as the independent dose verification software program, in which a modified Clarkson-based algorithm was implemented and radiological path length was computed using CT images independently to the treatment planning system. The agreement in point dose and mean dose between the AC with / without the correction and the SMU were assessed. Results: In the point dose evaluation for the center of the GTV, the difference shows the systematic shift (4.5% ± 1.9 %) in comparison of the AC with the inhomogeneous correction, on the other hands, there was good agreement of 0.2 ± 0.9% between the SMU and the AC without the correction. In the volume evaluation, there were significant differences in mean dose for not only PTV (14.2 ± 5.1 %) but also GTV (8.0 ± 5.1 %) compared to the AC with the correction. Without the correction, the SMU showed good agreement for GTV (1.5 ± 0.9%) as well as PTV (0.9% ± 1.0%). Conclusion: The volume evaluation for secondary check may be possible in homogenous region. However, the volume including the inhomogeneous media would make larger discrepancy. Dose calculation algorithm for independent verification needs to be modified to take into account the inhomogeneous correction.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-AB-201-01: Treatment Planning System Commissioning and QA: Challenges and Opportunities

Treatment planning systems (TPS) are a cornerstone of modern radiation therapy. Errors in their commissioning or use can have a devastating impact on many patients. To support safe and high quality care, medical physicists must conduct efficient and proper commissioning, good clinical integration, and ongoing quality assurance (QA) of the TPS. AAPM Task Group 53 and related publications have served as seminal benchmarks for TPS commissioning and QA over the past two decades. Over the same time, continuing innovations have made the TPS even more complex and more central to the clinical process. Medical goals are now expressed in terms of the dose and margins around organs and tissues that are delineated from multiple imaging modalities (CT, MR and PET); and even temporally resolved (i.e., 4D) imaging. This information is passed on to optimization algorithms to establish accelerator movements that are programmed directly for IMRT, VMAT and stereotactic treatments. These advances have made commissioning and QA of the TPS much more challenging. This education session reviews up-to-date experience and guidance on this subject; including the recently published AAPM Medical Physics Practice Guideline (MPPG) #5 “Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams”. Treatment Planning System Commissioning and QA: Challenges and Opportunities (Greg Salomons) This session will provide some key background and review publications describing prominent incidents relating to TPS commissioning and QA. Traditional approaches have been hardware and feature oriented. They aim to establish a functional configuration and establish specifications for regular testing of features (like dose calculation) to assure stable operation and detect failures. With the advent of more complex systems, more patient-specific testing has also been adopted. A number of actual TPS defects will be presented along with heuristics for identifying similar defects in the future. Finally, the Gamma test has become a popular metric for reporting TPS Commissioning and QA results. It simplifies complex testing into a numerical index, but noisy data and casual application can make it misleading. A brief review of the issues around the use of the Gamma test will be presented. TPS commissioning and QA: A process orientation and application of control charts (Michael Sharpe) A framework for commissioning a treatment planning system will be presented, focusing on preparations, practical aspects of configuration, priorities, specifications, and establishing performance. The complexity of the modern TPS make modular testing of features inadequate, and modern QA tools can provide “too much information” about the performance of techniques like IMRT and VMAT. We have adopted a process orientation and quality tools, like control charts, for ongoing TPS QA and assessment of patient-specific tests. The trending nature of these tools reveals the overall performance of the TPS system, and quantifies the variations that arise from individual plans, discrete calculations, and experimentation based on discrete measurements. Examples demonstrating application of these tools to TPS QA will be presented. TPS commissioning and QA: Incorporating the entire planning process (Sasa Mutic) The TPS and its features do not perform in isolation. Instead, the features and modules are key components in a complex process that begins with CT Simulation and extends to treatment delivery, along with image guidance and verification. Most importantly, the TPS is used by people working in a multi-disciplinary environment. It is very difficult to predict the outcomes of human interactions with software. Therefore, an interdisciplinary approach to training, commissioning and QA will be presented, along with an approach to the physics chart check and end-to-end testing as a tool for TPS QA. The role of standardization and automation in QA will also be discussed. The recommendations of MPPG #5 and practical implementation strategies (Jennifer Smilowitz) The recently published recommendations from Task Group No. 244, Medical Physics Practice Guideline on Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams will be presented. The recommendations focus on the validation of commissioning data and dose calculations. Tolerance values for non-IMRT beam configurations are summarized based on established criteria and data collected by the IROC. More stringent evaluation criteria for IMRT dose calculations are suggested to test the limitations of the TPS dose algorithms for advanced delivery conditions. The MPPG encourages users to create a suite of validation tests for dose calculation for various conditions for static photon beams, heterogeneities, IMRT/VMAT and electron beams. This test suite is intended to be used for subsequent testing, including TPS software upgrades. In the past, the recommendations of some reports have not been widely implemented due to practical limitations. Implementation strategies, tools and processes developed by multiple centers for efficient and “do-able” MPPG #5 testing will be presented, as well as a discussion on the overall validation experience. Learning Objectives: Identify some of the key documents relevant for TPS commissioning and QA Understand strategies for testing TPS software Gain a practical knowledge of the Gamma test criteria Increase familiarity with the process of commissioning a TPS Learn about the use of Control Charts for TPS QA Review the role of the TPS in the overall planning process Increase awareness of the link between TPS QA and chart checking Gain an increased appreciation for the importance of interdisciplinary communication Understand the new recommendations from MPPG #5 on TPS Dose Algorithm Commissioning and QC/QA Learn practical implementation processes and tools for MPPG #5 validation recommendations.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-AB-201-04: The Recommendations of MPPG #5 and Practical Implementation Strategies

Treatment planning systems (TPS) are a cornerstone of modern radiation therapy. Errors in their commissioning or use can have a devastating impact on many patients. To support safe and high quality care, medical physicists must conduct efficient and proper commissioning, good clinical integration, and ongoing quality assurance (QA) of the TPS. AAPM Task Group 53 and related publications have served as seminal benchmarks for TPS commissioning and QA over the past two decades. Over the same time, continuing innovations have made the TPS even more complex and more central to the clinical process. Medical goals are now expressed in terms of the dose and margins around organs and tissues that are delineated from multiple imaging modalities (CT, MR and PET); and even temporally resolved (i.e., 4D) imaging. This information is passed on to optimization algorithms to establish accelerator movements that are programmed directly for IMRT, VMAT and stereotactic treatments. These advances have made commissioning and QA of the TPS much more challenging. This education session reviews up-to-date experience and guidance on this subject; including the recently published AAPM Medical Physics Practice Guideline (MPPG) #5 “Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams”. Treatment Planning System Commissioning and QA: Challenges and Opportunities (Greg Salomons) This session will provide some key background and review publications describing prominent incidents relating to TPS commissioning and QA. Traditional approaches have been hardware and feature oriented. They aim to establish a functional configuration and establish specifications for regular testing of features (like dose calculation) to assure stable operation and detect failures. With the advent of more complex systems, more patient-specific testing has also been adopted. A number of actual TPS defects will be presented along with heuristics for identifying similar defects in the future. Finally, the Gamma test has become a popular metric for reporting TPS Commissioning and QA results. It simplifies complex testing into a numerical index, but noisy data and casual application can make it misleading. A brief review of the issues around the use of the Gamma test will be presented. TPS commissioning and QA: A process orientation and application of control charts (Michael Sharpe) A framework for commissioning a treatment planning system will be presented, focusing on preparations, practical aspects of configuration, priorities, specifications, and establishing performance. The complexity of the modern TPS make modular testing of features inadequate, and modern QA tools can provide “too much information” about the performance of techniques like IMRT and VMAT. We have adopted a process orientation and quality tools, like control charts, for ongoing TPS QA and assessment of patient-specific tests. The trending nature of these tools reveals the overall performance of the TPS system, and quantifies the variations that arise from individual plans, discrete calculations, and experimentation based on discrete measurements. Examples demonstrating application of these tools to TPS QA will be presented. TPS commissioning and QA: Incorporating the entire planning process (Sasa Mutic) The TPS and its features do not perform in isolation. Instead, the features and modules are key components in a complex process that begins with CT Simulation and extends to treatment delivery, along with image guidance and verification. Most importantly, the TPS is used by people working in a multi-disciplinary environment. It is very difficult to predict the outcomes of human interactions with software. Therefore, an interdisciplinary approach to training, commissioning and QA will be presented, along with an approach to the physics chart check and end-to-end testing as a tool for TPS QA. The role of standardization and automation in QA will also be discussed. The recommendations of MPPG #5 and practical implementation strategies (Jennifer Smilowitz) The recently published recommendations from Task Group No. 244, Medical Physics Practice Guideline on Commissioning and QA of Treatment Planning Dose Calculations: Megavoltage Photon and Electron Beams will be presented. The recommendations focus on the validation of commissioning data and dose calculations. Tolerance values for non-IMRT beam configurations are summarized based on established criteria and data collected by the IROC. More stringent evaluation criteria for IMRT dose calculations are suggested to test the limitations of the TPS dose algorithms for advanced delivery conditions. The MPPG encourages users to create a suite of validation tests for dose calculation for various conditions for static photon beams, heterogeneities, IMRT/VMAT and electron beams. This test suite is intended to be used for subsequent testing, including TPS software upgrades. In the past, the recommendations of some reports have not been widely implemented due to practical limitations. Implementation strategies, tools and processes developed by multiple centers for efficient and “do-able” MPPG #5 testing will be presented, as well as a discussion on the overall validation experience. Learning Objectives: Identify some of the key documents relevant for TPS commissioning and QA Understand strategies for testing TPS software Gain a practical knowledge of the Gamma test criteria Increase familiarity with the process of commissioning a TPS Learn about the use of Control Charts for TPS QA Review the role of the TPS in the overall planning process Increase awareness of the link between TPS QA and chart checking Gain an increased appreciation for the importance of interdisciplinary communication Understand the new recommendations from MPPG #5 on TPS Dose Algorithm Commissioning and QC/QA Learn practical implementation processes and tools for MPPG #5 validation recommendations.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

SU-F-19A-05: Experimental and Monte Carlo Characterization of the 1 Cm CivaString 103Pd Brachytherapy Source

Purpose: To determine the in-air azimuthal anisotropy and in-water dose distribution for the 1 cm length of the CivaString {sup 103}Pd brachytherapy source through measurements and Monte Carlo (MC) simulations. American Association of Physicists in Medicine Task Group No. 43 (TG-43) dosimetry parameters were also determined for this source. Methods: The in-air azimuthal anisotropy of the source was measured with a NaI scintillation detector and simulated with the MCNP5 radiation transport code. Measured and simulated results were normalized to their respective mean values and compared. The TG-43 dose-rate constant, line-source radial dose function, and 2D anisotropy function for this source were determined from LiF:Mg,Ti thermoluminescent dosimeter (TLD) measurements and MC simulations. The impact of {sup 103}Pd well-loading variability on the in-water dose distribution was investigated using MC simulations by comparing the dose distribution for a source model with four wells of equal strength to that for a source model with strengths increased by 1% for two of the four wells. Results: NaI scintillation detector measurements and MC simulations of the in-air azimuthal anisotropy showed that ≥95% of the normalized data were within 1.2% of the mean value. TLD measurements and MC simulations of the TG-43 dose-rate constant, line-source radial dose function, and 2D anisotropy function agreed to within the experimental TLD uncertainties (k=2). MC simulations showed that a 1% variability in {sup 103}Pd well-loading resulted in changes of <0.1%, <0.1%, and <0.3% in the TG-43 dose-rate constant, radial dose distribution, and polar dose distribution, respectively. Conclusion: The CivaString source has a high degree of azimuthal symmetry as indicated by the NaI scintillation detector measurements and MC simulations of the in-air azimuthal anisotropy. TG-43 dosimetry parameters for this source were determined from TLD measurements and MC simulations. {sup 103}Pd well-loading variability results in minimal variations in the in-water dose distribution according to MC simulations. This work was partially supported by CivaTech Oncology, Inc. through an educational grant for Joshua Reed, John Micka, Wesley Culberson, and Larry DeWerd and through research support for Mark Rivard.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2025

Subject-specific modeling framework for particle deposition using computational fluid dynamics

Quantifying particle deposition and dose in the respiratory tract requires a physiologically realistic representation and reproducible computational workflows. However, existing modeling frameworks, such as the International Commission on Radiological Protection (ICRP) compartmental models and the Multiple Path Particle Dosimetry (MPPD) tool, lack detailed deposition profiles and subject-specific capabilities. The combination of advances in computer vision algorithms applied to the respiratory tract and Computational Fluid and Particle Dynamics (CFPD) allows high-fidelity simulations of particle behavior in anatomically accurate geometries derived from individual CT scans. The segmentation, preprocessing, and file preparation task for a CFPD simulation was often time-consuming, and no prior studies to-date have yet presented a fully automated framework. This work presents a fully automated workflow to obtain individualized particle deposition profiles in the human respiratory tract. The pipeline starts with segmenting upper and lower airway geometries using morphological and deep learning-based methods, generating three-dimensional (3D) models from CT imaging data. Next, a series of algorithms are presented to quality check and prepare the 3D geometry for a CFD or CFPD simulation. The preprocessing step includes correcting geometric artifacts, enforcing a physically consistent mesh, and automatically identifying and capping multiple outlets, which is required for CFD/CFPD simulations. These processed models are then input into open-source (OpenFOAM) or commercial (StarCCM+) CFD solvers, where flow and transient particle transport equations — including turbulence and particle–wall interactions are solved under realistic breathing conditions. Finally, the resulting particle deposition profiles can be integrated with Monte Carlo radiation transport codes and state-of-the-art computational phantoms to assess organ-specific absorbed doses in scenarios of radioactive aerosol inhalation. The presented work streamlines respiratory tract segmentation, preprocessing for CFD/CFPD simulations, and integration with dose assessment workflows, reducing manual intervention and improving access to high-fidelity, subject-specific modeling. The high precision in predicted particle deposition and dose distributions can improve personalized treatment strategies in respiratory medicine and refine dose estimates for radiation protection.

AI↗