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Desai V, Labby Z, Culberson W, DeWerd L, Kry S. Multi-institution single geometry plan complexity characteristics based on IROC phantoms. Med Phys 2024; 51:5693-5707. [PMID: 38669453 DOI: 10.1002/mp.17086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 03/12/2024] [Accepted: 03/27/2024] [Indexed: 04/28/2024] Open
Abstract
BACKGROUND Clinical intensity modulated radiation therapy plans have been described using various complexity metrics to help identify problematic radiotherapy plans. Most previous studies related to the quantification of plan complexity and their utility have relied on institution-specific plans which can be highly variable depending on the machines, planning techniques, delivery modalities, and measurement devices used. In this work, 1723 plans treating one of only four standardized geometries were simultaneously analyzed to investigate how radiation plan complexity metrics vary across four different sets of common objectives. PURPOSE To assess the treatment plan complexity characteristics of plans developed for Imaging and Radiation Oncology Core (IROC) phantoms. Specifically, to understand the variability in plan complexity between institutions for a common plan objective, and to evaluate how various complexity metrics differentiate relevant groups of plans. METHODS 1723 plans treating one of four standardized IROC phantom geometries representing four different anatomical sites of treatment were analyzed. For each plan, 22 MLC-descriptive plan complexity metrics were calculated, and principal component analysis (PCA) was applied to the 22 metrics in order to evaluate differences in plan complexity between groups. Across all metrics, pairwise comparisons of the IROC phantom data were made for the following classifications of the data: anatomical phantom treated, treatment planning system (TPS), and the combination of MLC model and treatment planning system. An objective k-means clustering algorithm was also applied to the data to determine if any meaningful distinctions could be made between different subgroups. The IROC phantom database was also compared to a clinical database from the University of Wisconsin-Madison (UW) which included plans treating the same four anatomical sites as the IROC phantoms using a TrueBeam™ STx and Pinnacle3 TPS. RESULTS The IROC head and neck and spine plans were distinct from the prostate and lung plans based on comparison of the 22 metrics. All IROC phantom plan group complexity metric distributions were highly variable despite all plans being designed for identical geometries and plan objectives. The clusters determined by the k-means algorithm further supported that the IROC head and neck and spine plans involved similar amounts of complexity and were largely distinct from the prostate and lung plans, but no further distinctions could be made. Plan complexity in the head and neck and spine IROC phantom plans were similar to the complexity encountered in the UW clinical plans. CONCLUSIONS There is substantial variability in plan complexity between institutions when planning for the same objective. For each IROC anatomical phantom treated, the magnitude of variability in plan complexity between institutions is similar to the variability in plan complexity encountered within a single institution database containing several hundred unique clinical plans treating corresponding anatomies in actual patients.
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Affiliation(s)
- Vimal Desai
- Department of Radiation Oncology, Sidney Kimmel Medical College, Thomas Jefferson University, Hospitals, Philadelphia, Pennsylvania, USA
| | - Zacariah Labby
- Department of Human Oncology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Wesley Culberson
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Larry DeWerd
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Stephen Kry
- Department of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center Houston, Houston, Texas, USA
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Cho H, Lee JS, Kim JS, Kim D, Chang JS, Byun HK, Lee IJ, Kim YB, Kim C, Lee H, Kim H. Generating 3D images of VMAT plans for predictive models and activation maps associated with plan deliverability. Med Phys 2024. [PMID: 38978162 DOI: 10.1002/mp.17298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 05/20/2024] [Accepted: 06/28/2024] [Indexed: 07/10/2024] Open
Abstract
BACKGROUND Intensity modulation with dynamic multi-leaf collimator (MLC) and monitor unit (MU) changes across control points (CPs) characterizes volumetric modulated arc therapy (VMAT). The increased uncertainty in plan deliverability required patient-specific quality assurance (PSQA), which remained inefficient upon Quality Assurance (QA) failure. To prevent waste before QA, plan complexity metrics (PCMs) and machine learning models with the metrics were generated, which were lack of providing CP-specific information upon QA failures. PURPOSE By generating 3D images from digital imaging and comminications in medicine in radiation therapy (DICOM RT) plan, we proposed a predictive model that can estimate the deliverability of VMAT plans and visualize CP-specific regions associated with plan deliverability. METHODS The patient cohort consisted of 259 and 190 cases for left- and right-breast VMAT treatments, which were split into 235 and 166 cases for training and 24 cases from each treatment for testing the networks. Three-channel 3D images generated from DICOM RT plans were fed into a DenseNet-based deep learning network. To reflect VMAT plan complexity as an image, the first two channels described MLC and MU variations between two consecutive CPs, while the last channel assigned the beam field size. The network output was defined as binary classified PSQA results, indicating deliverability. The predictive performance was assessed by accuracy, sensitivity, specificity, F1-score, and area under the curve (AUC). The gradient-weighted class activation map (Grad-CAM) highlighted the regions of CPs in VMAT plans associated with deliverability, compared against PCMs by Spearman correlation. RESULTS The DenseNet-based predictive model yielded AUCs of 92.2% and 93.8%, F1-scores of 97.0% and 93.8% and accuracies of 95.8% and 91.7% for the left- and right-breast VMAT cases. Additionally, the specificity of 87.5% for both cases indicated that the predictive model accurately detected QA failing cases. The activation maps significantly differentiated QA failing-labeled from passing-labeled classes for the non-deliverable cases. The PCM with the highest correlation to the Grad-CAM varied from patient cases, implying that plan deliverability would be considered patient-specific. CONCLUSION This work demonstrated that the deep learning-based network based on visualization of dynamic VMAT plan information successfully predicted plan deliverability, which also provided control-point specific planning parameter information associated with plan deliverability in a patient-specific manner.
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Affiliation(s)
- Hyeonjeong Cho
- Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jae Sung Lee
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jin Sung Kim
- Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Deok Kim
- Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jee Suk Chang
- Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Hwa Kyung Byun
- Department of Radiation Oncology, Yongin Severance Hospital, Yonsei University College of Medicine, Gyonggi-do, Republic of Korea
| | - Ik Jae Lee
- Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Yong Bae Kim
- Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Changhwan Kim
- Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Ho Lee
- Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Hojin Kim
- Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
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Li C, Yu S, Shen J, Liang B, Fu X, Hua L, Hu H, Jiang P, Lei R, Guan Y, Li T, Li Q, Shi A, Zhang Y. Clinical association between plan complexity and the local-recurrence-free-survival of non-small-cell lung cancer patients receiving stereotactic body radiation therapy. Phys Med 2024; 122:103377. [PMID: 38838467 DOI: 10.1016/j.ejmp.2024.103377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 02/18/2024] [Accepted: 05/20/2024] [Indexed: 06/07/2024] Open
Abstract
PURPOSE To investigate the clinical impact of plan complexity on the local recurrence-free survival (LRFS) of non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiation therapy (SBRT). METHODS Data from 123 treatment plans for 113 NSCLC patients were analyzed. Plan-averaged beam modulation (PM), plan beam irregularity (PI), monitor unit/Gy (MU/Gy) and spherical disproportion (SD) were calculated. The γ passing rates (GPR) were measured using ArcCHECK 3D phantom with 2 %/2mm criteria. High complexity (HC) and low complexity (LC) groups were statistically stratified based on the aforementioned metrics, using cutoffs determined by their significance in correlation with survival time, as calculated using the R-3.6.1 packages. Kaplan-Meier analysis, Cox regression, and Random Survival Forest (RSF) models were employed for the analysis of local recurrence-free survival (LRFS). Propensity-score-matched pairs were generated to minimize bias in the analysis. RESULTS The median follow-up time for all patients was 25.5 months (interquartile range 13.4-41.2). The prognostic capacity of PM was suggested using RSF, based on Variable Importance and Minimal Depth methods. The 1-, 2-, and 3-year LRFS rates in the HC group were significantly lower than those in the LC group (p = 0.023), when plan complexity was defined by PM. However, no significant difference was observed between the HC and LC groups when defined by other metrics (p > 0.05). All γ passing rates exceeded 90.5 %. CONCLUSIONS This study revealed a significant association between higher PM and worse LRFS in NSCLC patients treated with SBRT. This finding offers additional clinical evidence supporting the potential optimization of pre-treatment quality assurance protocols.
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Affiliation(s)
- Chenguang Li
- Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China; Department of Physics and Astronomy, University of British Columbia, 6224 Agricultural Road, Vancouver, BC V6T1Z1, Canada; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Shutong Yu
- Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Junyue Shen
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Baosheng Liang
- Department of Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Xinhui Fu
- Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Ling Hua
- Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Huimin Hu
- Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Ping Jiang
- Department of Radiation Oncology, Peking University Third Hospital, Haidian District, Beijing 100191, China
| | - Runhong Lei
- Department of Radiation Oncology, Peking University Third Hospital, Haidian District, Beijing 100191, China
| | - Ying Guan
- Beijing United Family Hospital, Beijing 100015, China
| | - Tian Li
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong 999077, China
| | - Quanfu Li
- Department of Medical Oncology, Ordos Central Hospital, Ordos 017000, China.
| | - Anhui Shi
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China.
| | - Yibao Zhang
- Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China.
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Muthu S, Mudhana G. Dosimetric Systems in Pre-Treatment QA for Stereotactic Treatments: Correlation Agreements and Target Volume Dependency. Asian Pac J Cancer Prev 2024; 25:1425-1432. [PMID: 38680004 PMCID: PMC11162722 DOI: 10.31557/apjcp.2024.25.4.1425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Accepted: 04/11/2024] [Indexed: 05/01/2024] Open
Abstract
AIM This study comprehensively investigated pre-treatment quality assurance (QA) for 100 cancer patients undergoing stereotactic treatments (SRS/SRT) using various detectors. METHODS The study conducted QA for SRS/SRT treatments planned with a 6MV SRS beam at a dose rate of 1,000 MU/min, utilizing Eclipse v13.6 Treatment Planning System (TPS). Point dose measurements employed 0.01cm3 and 0.13cm3 cylindrical ionization chambers, while planar dose verification utilized Gafchromic EBT-XD Film and Portal Imager (aS1000). Plans were categorized by target volume, and a thorough analysis compared point dose agreements, planar dose gamma pass rates, and their correlations with chamber volume mean dose, detector type, and point dose agreement. Additionally, the consistency between different ionization chambers was assessed. RESULTS Point dose agreement generally improved with increasing target volume, except for volumes over 10cm3 with 0.01cm3 chambers, showing a contrary trend. Significant differences (p<0.05) were observed between TPS and measured doses for both chambers. Gamma pass rate improved with increasing target volume in EBT XD and aS1000 analyses, except for the >10cm3 group in EBT XD. EBT XD demonstrated better agreement with TPS for target volumes up to 10cm3 compared to aS1000, with a statistically significant difference (p<0.05) between the detectors. Strong correlations were found between chamber point dose and chamber volume mean dose agreement, as well as between the two gamma criteria analyses of the same detector type in the planar dose correlation analysis. However, weak correlations were discovered for other analyses. CONCLUSION This study found weak correlation between different detector types in pre-treatment QA for point dose and planar dose evaluation. However, within a specific detector type, strong correlation was observed for different point dose evaluation methods and gamma criteria. This highlights the importance of cautious interpretation of QA results, particularly for SRS QA, due to the lack of correlation between detector types.
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Affiliation(s)
- Sivakumar Muthu
- Department of Physics, School of Advanced Sciences, Vellore Institute of Technology, Chennai - 600 127, India.
- Department of Radiotherapy, Sri Shankara Cancer Hospital & Research Centre, Bangalore - 560 004, India.
| | - Gopinath Mudhana
- Department of Physics, School of Advanced Sciences, Vellore Institute of Technology, Chennai - 600 127, India.
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Tan HQ, Lew KS, Wong YM, Chong WC, Koh CWY, Chua CGA, Yeap PL, Ang KW, Lee JCL, Park SY. Detecting outliers beyond tolerance limits derived from statistical process control in patient-specific quality assurance. J Appl Clin Med Phys 2024; 25:e14154. [PMID: 37683120 PMCID: PMC10860546 DOI: 10.1002/acm2.14154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 08/18/2023] [Accepted: 08/21/2023] [Indexed: 09/10/2023] Open
Abstract
BACKGROUND Tolerance limit is defined on pre-treatment patient specific quality assurance results to identify "out of the norm" dose discrepancy in plan. An out-of-tolerance plan during measurement can often cause treatment delays especially if replanning is required. In this study, we aim to develop an outlier detection model to identify out-of-tolerance plan early during treatment planning phase to mitigate the above-mentioned risks. METHODS Patient-specific quality assurance results with portal dosimetry for stereotactic body radiotherapy measured between January 2020 and December 2021 were used in this study. Data were divided into thorax and pelvis sites and gamma passing rates were recorded using 2%/2 mm, 2%/1 mm, and 1%/1 mm gamma criteria. Statistical process control method was used to determine six different site and criterion-specific tolerance and action limits. Using only the inliers identified with our determined tolerance limits, we trained three different outlier detection models using the plan complexity metrics extracted from each treatment field-robust covariance, isolation forest, and one class support vector machine. The hyperparameters were optimized using the F1-score calculated from both the inliers and validation outliers' data. RESULTS 308 pelvis and 200 thorax fields were used in this study. The tolerance (action) limits for 2%/2 mm, 2%/1 mm, and 1%/1 mm gamma criteria in the pelvis site are 99.1% (98.1%), 95.8% (91.1%), and 91.7% (86.1%), respectively. The tolerance (action) limits in the thorax site are 99.0% (98.7%), 97.0% (96.2%), and 91.5% (87.2%). One class support vector machine performs the best among all the algorithms. The best performing model in the thorax (pelvis) site achieves a precision of 0.56 (0.54), recall of 1.0 (1.0), and F1-score of 0.72 (0.70) when using the 2%/2 mm (2%/1 mm) criterion. CONCLUSION The model will help the planner to identify an out-of-tolerance plan early so that they can refine the plan further during the planning stage without risking late discovery during measurement.
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Affiliation(s)
- Hong Qi Tan
- Division of Radiation OncologyNational Cancer Centre SingaporeSingaporeSingapore
- Oncology Academic Clinical ProgrammeDuke‐NUS Medical SchoolSingaporeSingapore
| | - Kah Seng Lew
- Division of Radiation OncologyNational Cancer Centre SingaporeSingaporeSingapore
- Division of Physics and Applied PhysicsNanyang Technological UniversitySingaporeSingapore
| | - Yun Ming Wong
- Division of Physics and Applied PhysicsNanyang Technological UniversitySingaporeSingapore
| | - Wen Chuan Chong
- Division of Radiation OncologyNational Cancer Centre SingaporeSingaporeSingapore
| | - Calvin Wei Yang Koh
- Division of Radiation OncologyNational Cancer Centre SingaporeSingaporeSingapore
| | | | - Ping Lin Yeap
- Division of Radiation OncologyNational Cancer Centre SingaporeSingaporeSingapore
| | - Khong Wei Ang
- Division of Radiation OncologyNational Cancer Centre SingaporeSingaporeSingapore
| | - James Cheow Lei Lee
- Division of Radiation OncologyNational Cancer Centre SingaporeSingaporeSingapore
- Division of Physics and Applied PhysicsNanyang Technological UniversitySingaporeSingapore
| | - Sung Yong Park
- Division of Radiation OncologyNational Cancer Centre SingaporeSingaporeSingapore
- Oncology Academic Clinical ProgrammeDuke‐NUS Medical SchoolSingaporeSingapore
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Guo J, Zhu M, Zeng W, Wang H, Qin S, Li Z, Tang Y, Ying B, Sang J, Ji M, Meng K, Hui Z, Wang J, Zhou J, Zhou Y, Huan J. Multileaf Collimator Modeling and Commissioning for Complex Radiation Treatment Plans Using 2-Dimensional (2D) Diode Array MapCHECK2. Technol Cancer Res Treat 2024; 23:15330338231225864. [PMID: 38311933 PMCID: PMC10846010 DOI: 10.1177/15330338231225864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 09/27/2023] [Accepted: 12/17/2023] [Indexed: 02/06/2024] Open
Abstract
Purpose: This study aims to develop a data-collecting package ExpressMLC and investigate the applicability of MapCHECK2 for multileaf collimator (MLC) modeling and commissioning for complex radiation treatment plans. Materials and methods: The MLC model incorporates realistic parameters to account for sophisticated MLC features. A set of 8 single-beam plans, denoted by ExpressMLC, is created for the determination of parameters. For the commissioning of the MLC model, 4 intensity modulated radiation therapy (IMRT) plans specified by the AAPM TG 119 report were transferred to a computed tomography study of MapCHECK2, recalculated, and compared to measurements on a Varian accelerator. Both per-beam and composite-beam dose verification were conducted. Results: Through sufficient characterization of the MLC model, under 3%/2 mm and 2%/2 mm criteria, MapCHECK2 can be used to accurately verify per beam dose with gamma passing rate better than 90.9% and 89.3%, respectively, while the Gafchromic EBT3 films can achieve gamma passing rate better than 89.3% and 85.7%, respectively. Under the same criteria, MapCHECK2 can achieve composite beam dose verification with a gamma passing rate better than 95.9% and 90.3%, while the Gafchromic EBT3 films can achieve a gamma passing rate better than 96.1% and 91.8%; the p-value from the Mann Whitney test between gamma passing rates of the per beam dose verification using full MapCHECK2 package calibrated MLC model and film calibrated MLC model is .44 and .47, respectively; the p-value between those of the true composite beam dose verification is .62 and .36, respectively. Conclusion: It is confirmed that the 2-dimensional (2D) diode array MapCHECK2 can be used for data collection for MLC modeling with the combination of the ExpressMLC package of plans, whose doses are sufficient for the determination of MLC parameters. It could be a fitting alternative to films to boost the efficiency of MLC modeling and commissioning without sacrificing accuracy.
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Affiliation(s)
- Jian Guo
- Department of Radiation Oncology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Meng Zhu
- Qiusuo Health Technologies Inc., Suzhou, China
| | - Weijin Zeng
- Department of Radiation Oncology, Yihui Foundation Hospital, Shanwei, China
| | - He Wang
- Qiusuo Health Technologies Inc., Suzhou, China
| | - Songbing Qin
- Department of Radiation Oncology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Zhibin Li
- Department of Radiation Oncology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Yu Tang
- Qiusuo Health Technologies Inc., Suzhou, China
| | - Binbin Ying
- Department of Stomatology, Ningbo First Hospital, Ningbo, China
| | - Jiugao Sang
- Department of Radiation Oncology, Rudong County Hospital, Nantong, China
| | - Ming Ji
- Qiusuo Health Technologies Inc., Suzhou, China
| | - Kuo Meng
- Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhouguang Hui
- Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jianyang Wang
- Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Juying Zhou
- Department of Radiation Oncology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Yin Zhou
- Homology Medical Technologies Inc., Ningbo, China
| | - Jian Huan
- Department of Radiation Oncology, Suzhou Science and Technology Town Hospital, Suzhou, China
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Panetta JV, Veltchev I, Price RA, Ma CMC. 2D IMRT QA passing rate dependency on coronal plane. Phys Med 2023; 110:102594. [PMID: 37116388 DOI: 10.1016/j.ejmp.2023.102594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Revised: 04/10/2023] [Accepted: 04/17/2023] [Indexed: 04/30/2023] Open
Abstract
Intensity modulated radiation therapy (IMRT) delivery involves a complex series of beam angles and multileaf collimator (MLC) arrangements, requiring quality assurance to be performed to validate delivery before treatment. The purpose of this work is to investigate the effect of dose gradient on quality assurance (QA) passing rate. Many (n = 40) IMRT plans were delivered and measured using a 2D planar array of ion chambers; additionally, eleven plans were measured at several coronal planes. For each measurement, dose gradient was assessed using a number of metrics and passing rate assessed at both 3%/3 mm and 3%/2 mm criteria. The passing rates of the various IMRT plans were shown to be generally correlated to gradient, with an average distance correlation of 0.54 ± 0.04 for the lateral dose gradient. The passing rate for an individual plan was shown to vary with coronal slice, though the correlation to dose gradient was not predictable. Even though the passing rate was strongly related to dose gradient for many of the plans, the signs of the correlations were not always negative, as hypothesized. The coronal plane at which QA is performed affects passing rate, though dose gradient may not easily be used to predict slices at which passing rate is higher.
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Affiliation(s)
- Joseph V Panetta
- Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, PA 19111, USA.
| | - Iavor Veltchev
- Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, PA 19111, USA
| | - Robert A Price
- Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, PA 19111, USA
| | - C-M Charlie Ma
- Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, PA 19111, USA
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Stasko JT, Ferris WS, Adam DP, Culberson WS, Frigo SP. IMRT QA result prediction via MLC transmission decomposition. J Appl Clin Med Phys 2023:e13990. [PMID: 37031363 PMCID: PMC10402675 DOI: 10.1002/acm2.13990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 03/02/2023] [Accepted: 03/27/2023] [Indexed: 04/10/2023] Open
Abstract
BACKGROUND Quality assurance measurement of IMRT/VMAT treatment plans is resource intensive, and other more efficient methods to achieve the same confidence are desirable. PURPOSE We aimed to analyze treatment plans in the context of the treatment planning systems that created them, in order to predict which ones will fail a standard quality assurance measurement. To do so, we sought to create a tool external to the treatment planning system that could analyze a set of MLC positions and provide information that could be used to calculate various evaluation metrics. METHODS The tool was created in Python to read in DICOM plan files and determine the beam fluence fraction incident on each of seven different zones, each classified based on the RayStation MLC model. The fractions, termed grid point fractions, were validated by analyzing simple test plans. The average grid point fractions, over all control points for 46 plans were then computed. These values were then compared with gamma analysis pass percentages and median dose differences to determine if any significant correlations existed. RESULTS Significant correlation was found between the grid point fraction metrics and median dose differences, but not with gamma analysis pass percentages. Correlations were positive or negative, suggesting differing model parameter value sensitivities, as well as potential insight into the treatment planning system dose model. CONCLUSIONS By decomposing MLC control points into different transmission zones, it is possible to create a metric that predicts whether the analyzed plan will pass a quality assurance measurement from a dose calculation accuracy standpoint. The tool and metrics developed in this work have potential applications in comparing clinical beam models or identifying their weak points. Implementing the tool within a treatment planning system would also provide more potential plan optimization parameters.
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Affiliation(s)
- John T Stasko
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - William S Ferris
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - David P Adam
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Wesley S Culberson
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Sean P Frigo
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Human Oncology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
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Matsuura T, Kawahara D, Saito A, Yamada K, Ozawa S, Nagata Y. A synthesized gamma distribution-based patient-specific VMAT QA using a generative adversarial network. Med Phys 2023; 50:2488-2498. [PMID: 36609669 DOI: 10.1002/mp.16210] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 12/23/2022] [Accepted: 12/25/2022] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Artificial intelligence (AI)-based gamma passing rate (GPR) prediction has been proposed as a time-efficient virtual patient-specific QA method for the delivery of volumetric modulation arc therapy (VMAT). However, there is a limitation that the GPR value loses the locational information of dose accuracy. PURPOSE The objective was to predict the failing points in the gamma distribution and the GPR using a synthesized gamma distribution of VMAT QA with a deep convolutional generative adversarial network (GAN). METHODS The fluence maps of 270 VMAT beams for prostate cancer were measured using an electronic portal imaging device and analyzed using gamma evaluation with 3%/2-mm, 2%/1-mm, 1%/1-mm, and 1%/0.5-mm tolerances. The 270 gamma distributions were divided into two datasets: 240 training datasets for creating a model and 30 test datasets for evaluation. The image prediction network for the fluence maps calculated by the treatment planning system (TPS) to the gamma distributions was created using a GAN. The sensitivity, specificity, and accuracy of detecting failing points were evaluated using measured and synthesized gamma distributions. In addition, the difference between measured GPR (mGPR) and predicted GPR (pGPR) values calculated from the synthesized gamma distributions was evaluated. RESULTS The root mean squared errors between mGPR and pGPR were 1.0%, 2.1%, 3.5%, and 3.6% for the 3%/2-mm, 2%/1-mm, 1%/1-mm, and 1%/0.5-mm tolerances, respectively. The accuracies for detecting failing points were 98.9%, 96.9%, 94.7%, and 93.7% for 3%/2-mm, 2%/1-mm, 1%/1-mm, and 1%/0.5-mm tolerances, respectively. The sensitivity and specificity were the highest for 1%/0.5-mm and 3%/2-mm tolerances, which were 82.7% and 99.6%, respectively. CONCLUSIONS We developed a novel system using a GAN to generate a synthesized gamma distribution-based patient-specific VMAT QA. The system is promising from the point of view of quality assurance in radiotherapy because it shows high performance and can detect failing points.
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Affiliation(s)
- Takaaki Matsuura
- Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan.,Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Daisuke Kawahara
- Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Akito Saito
- Department of Radiation Oncology, Hiroshima University Hospital, Hiroshima, Japan
| | - Kiyoshi Yamada
- Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan
| | - Shuichi Ozawa
- Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan.,Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Yasushi Nagata
- Hiroshima High-Precision Radiotherapy Cancer Center, Hiroshima, Japan.,Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
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Das S, Kharade V, Pandey VP, KV A, Pasricha RK, Gupta M. Gamma Index Analysis as a Patient-Specific Quality Assurance Tool for High-Precision Radiotherapy: A Clinical Perspective of Single Institute Experience. Cureus 2022; 14:e30885. [PMID: 36337776 PMCID: PMC9626372 DOI: 10.7759/cureus.30885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/30/2022] [Indexed: 11/07/2022] Open
Abstract
Purpose Patient-specific quality assurance (QA) by gamma (γ) analysis is an important component of high-precision radiotherapy. It is important to standardize institute-specific protocol. In this study, we describe our institutional experience of patient-specific QA for high-precision radiotherapy from a clinical perspective. Methods The planning data of 56 patients treated with intensity-modulated radiotherapy (IMRT)/volumetric modulated arc therapy (VMAT) were included. γ index analysis was done using Octavius 4D IMRT QA phantom (PTW, Freiburg, Germany) using 3 mm/3% criteria. Local, global, and volumetric gammas were calculated and compared. The relationship of γ index in the transverse, coronal, and sagittal direction and anatomical region of treatment was explored. Results Global three-dimensional (3D) γ indices in the coronal, sagittal, and transverse axes were 96.73 ± 2.35, 95.66 ± 3.01, and 93.36 ± 4.87 (p < 0.05). The average local two-dimensional (2D) γ index was 78.23 ± 5.44 and the global γ index was 92.41 ± 2.41 (p < 0.005). The average local 3D γ index was 84.99 ± 4.24 and the global 3D γ index was 95.25 ± 1.72 (p < 0.005, paired t-test). The average local volumetric γ index was 84.29 ± 4.73 and the global volumetric γ index was 95.96 ± 2.08 (p < 0.005). 3D global gamma index was significantly different in different anatomical regions (p < 0.05). Conclusion Our study shows that γ index analysis is a useful parameter for routine clinical IMRT QA. The choice of type of γ index depends on the context of use and degree of stringency in measurement. Average 2D and 3D global γ were different in anatomical regions. The average 3D γ index was significantly different in axes. No difference was observed with techniques of IMRT/VMAT. Localization of failed points in CT anatomy can be advantageous for clinical decision-making.
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11
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Thongsawad S, Srisatit S, Fuangrod T. Predicting gamma evaluation results of patient-specific head and neck volumetric-modulated arc therapy quality assurance based on multileaf collimator patterns and fluence map features: A feasibility study. J Appl Clin Med Phys 2022; 23:e13622. [PMID: 35584035 PMCID: PMC9278677 DOI: 10.1002/acm2.13622] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 03/29/2022] [Accepted: 04/07/2022] [Indexed: 12/24/2022] Open
Abstract
The purpose of this study was to develop a predictive model for patient-specific VMAT QA results using multileaf collimator (MLC) effect and texture analysis. The MLC speed, acceleration and texture analysis features were extracted from 106 VMAT plans as predictors. Gamma passing rate (GPR) was collected as a response class with gamma criteria of 2%/2 mm and 3%/2 mm. The model was trained using two machine learning methods: AdaBoost classification and bagged regression trees model. GPR was classified into the "PASS" and "FAIL" for the classification model using the institutional warning level. The accuracy of the model was assessed using sensitivity and specificity. In addition, the accuracy of the regression model was determined using the difference between predicted and measured GPR. For the AdaBoost classification model, the sensitivity/specificity was 94.12%/100% and 63.63%/53.13% at gamma criteria of 2%/2 mm and 3%/2 mm, respectively. For the bagged regression trees model, the sensitivity/specificity was 94.12%/91.89% and 61.18%/68.75% at gamma criteria of 2%/2 mm and 3%/2 mm, respectively. The root mean square error (RMSE) of difference between predicted and measured GPR was found at 2.44 and 1.22 for gamma criteria of 2%/2 mm and 3%/2 mm, respectively. The promising result was found at tighter gamma criteria 2%/2 mm with 94.12% sensitivity (both bagged regression trees and AdaBoost classification model) and 100% specificity (AdaBoost classification model).
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Affiliation(s)
- Sangutid Thongsawad
- Department of Nuclear Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand.,Princess Srisavangavadhana College of Medicine, Chulabhorn Royal Academy, Bangkok, Thailand
| | - Somyot Srisatit
- Department of Nuclear Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand
| | - Todsaporn Fuangrod
- Princess Srisavangavadhana College of Medicine, Chulabhorn Royal Academy, Bangkok, Thailand
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12
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Li C, Tao C, Bai T, Li Z, Tong Y, Zhu J, Yin Y, Lu J. Beam complexity and monitor unit efficiency comparison in two different volumetric modulated arc therapy delivery systems using automated planning. BMC Cancer 2021; 21:261. [PMID: 33691654 PMCID: PMC7945217 DOI: 10.1186/s12885-021-07991-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 02/28/2021] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND To investigate the beam complexity and monitor unit (MU) efficiency issues for two different volumetric modulated arc therapy (VMAT) delivery technologies for patients with left-sided breast cancer (BC) and nasopharyngeal carcinoma (NPC). METHODS Twelve left-sided BC and seven NPC cases were enrolled in this study. Each delivered treatment plan was optimized in the Pinnacle3 treatment planning system with the Auto-Planning module for the Trilogy and Synergy systems. Similar planning dose objectives and beam configurations were used for each site in the two different delivery systems to produce clinically acceptable plans. The beam complexity was evaluated in terms of the segment area (SA), segment width (SW), leaf sequence variability (LSV), aperture area variability (AAV), and modulation complexity score (MCS) based on the multileaf collimator sequence and MU. Plan delivery and a gamma evaluation were performed using a helical diode array. RESULTS With similar plan quality, the average SAs for the Trilogy plans were smaller than those for the Synergy plans: 55.5 ± 21.3 cm2 vs. 66.3 ± 17.9 cm2 (p < 0.05) for the NPC cases and 100.7 ± 49.2 cm2 vs. 108.5 ± 42.7 cm2 (p < 0.05) for the BC cases, respectively. The SW was statistically significant for the two delivery systems (NPC: 6.87 ± 1.95 cm vs. 6.72 ± 2.71 cm, p < 0.05; BC: 8.84 ± 2.56 cm vs. 8.09 ± 2.63 cm, p < 0.05). The LSV was significantly smaller for Trilogy (NPC: 0.84 ± 0.033 vs. 0.86 ± 0.033, p < 0.05; BC: 0.89 ± 0.026 vs. 0.90 ± 0.26, p < 0.05). The mean AAV was significantly larger for Trilogy than for Synergy (NPC: 0.18 ± 0.064 vs. 0.14 ± 0.037, p < 0.05; BC: 0.46 ± 0.15 vs. 0.33 ± 0.13, p < 0.05). The MCS values for Trilogy were higher than those for Synergy: 0.14 ± 0.016 vs. 0.12 ± 0.017 (p < 0.05) for the NPC cases and 0.42 ± 0.106 vs. 0.30 ± 0.087 (p < 0.05) for the BC cases. Compared with the Synergy plans, the average MUs for the Trilogy plans were larger: 828.6 ± 74.1 MU and 782.9 ± 85.2 MU (p > 0.05) for the NPC cases and 444.8 ± 61.3 MU and 393.8 ± 75.3 MU (p > 0.05) for the BC cases. The gamma index agreement scores were never below 91% using 3 mm/3% (global) distance to agreement and dose difference criteria and a 10% lower dose exclusion threshold. CONCLUSIONS The Pinnacle3 Auto-Planning system can optimize BC and NPC plans to achieve the same plan quality using both the Trilogy and Synergy systems. We found that these two systems resulted in different SAs, SWs, LSVs, AAVs and MCSs. As a result, we suggested that the beam complexity should be considered in the development of further methodologies while optimizing VMAT autoplanning.
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Affiliation(s)
- Chengqiang Li
- Department of Radiation Oncology Physics, Shandong Cancer Hospital and Institute, Cancer Hospital affiliated to Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117, China
| | - Cheng Tao
- Department of Radiation Oncology Physics, Shandong Cancer Hospital and Institute, Cancer Hospital affiliated to Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117, China
| | - Tong Bai
- Department of Radiation Oncology Physics, Shandong Cancer Hospital and Institute, Cancer Hospital affiliated to Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117, China
| | - Zhenjiang Li
- Department of Radiation Oncology Physics, Shandong Cancer Hospital and Institute, Cancer Hospital affiliated to Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117, China
| | - Ying Tong
- Department of Radiation Oncology Physics, Shandong Cancer Hospital and Institute, Cancer Hospital affiliated to Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117, China
| | - Jian Zhu
- Department of Radiation Oncology Physics, Shandong Cancer Hospital and Institute, Cancer Hospital affiliated to Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117, China
| | - Yong Yin
- Department of Radiation Oncology Physics, Shandong Cancer Hospital and Institute, Cancer Hospital affiliated to Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117, China.
| | - Jie Lu
- Department of Radiation Oncology Physics, Shandong Cancer Hospital and Institute, Cancer Hospital affiliated to Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117, China.
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Tamura M, Matsumoto K, Otsuka M, Monzen H. Plan complexity quantification of dual-layer multi-leaf collimator for volumetric modulated arc therapy with Halcyon linac. Phys Eng Sci Med 2020; 43:947-957. [DOI: 10.1007/s13246-020-00891-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 06/23/2020] [Indexed: 12/31/2022]
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Desai VK, Labby ZE, DeWerd LA, Culberson WS. On the implementation of the plan‐class specific reference field using multidimensional clustering of plan features and alternative strategies for improved dosimetry in modulated clinical linear accelerator treatments. Med Phys 2020; 47:3621-3635. [DOI: 10.1002/mp.14207] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Revised: 04/14/2020] [Accepted: 04/20/2020] [Indexed: 11/08/2022] Open
Affiliation(s)
- Vimal K. Desai
- Department of Human Oncology School of Medicine and Public Health University of Wisconsin‐Madison Madison WI 53792 USA
| | - Zacariah E. Labby
- Department of Human Oncology School of Medicine and Public Health University of Wisconsin‐Madison Madison WI 53792 USA
| | - Larry A. DeWerd
- Department of Medical Physics School of Medicine and Public Health University of Wisconsin‐Madison Madison WI 53705 USA
| | - Wesley S. Culberson
- Department of Medical Physics School of Medicine and Public Health University of Wisconsin‐Madison Madison WI 53705 USA
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15
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Kamima T, Murakami Y, Arima M, Sato Y, Yoshioka M, Sato T. [Impact of Aperture Shape Controller on Volumetric Modulated Arc Therapy Treatment Planning for Nasopharyngeal Cancer]. Nihon Hoshasen Gijutsu Gakkai Zasshi 2020; 76:356-365. [PMID: 32307363 DOI: 10.6009/jjrt.2020_jsrt_76.4.356] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
PURPOSE The aperture shape controller (ASC) decreases the complexity of the multi-leaf collimator (MLC) aperture for volumetric modulated arc therapy (VMAT). The purpose of this study was to evaluate the effect of ASC settings on the VMAT plan quality. METHOD First, VMAT plans were created (ASC=off) for three test patterns of The American Association of Physicists in Medicine (AAPM) Task Group 119 (TG-119) and 20 cases of nasopharyngeal cancer. Next, for these VMAT plans, only the ASC settings were changed from very low (complexity reduction: low) to very high (complexity reduction: high) in five steps, and VMAT plans were created respectively. To evaluate the created VMAT plans per each ASC settings, we analyzed the modulation complexity score (MCSV) and dosimetric parameters for the planning target volume (PTV) and organ at risk (OAR). RESULT In three test patterns, there were no major dosimetric differences between the VMAT plans. In nasopharyngeal cancer, the mean MCSV were 0.413, 0.325, 0.320, 0.307, 0.303, and 0.272 for very high, high, moderate, low, very low, off settings, respectively. Therefore, the most complex MLC aperture was off, followed by very low, low, moderate, high, and very high. In terms of dosimetric parameters, the VMAT plans created using the very high setting showed an increase of D2% in the PTV and worse OAR sparing than that using other ASC settings. On the other hand, the dosimetric results for the very low to moderate setting obtained similar results to those for the off setting, respectively. CONCLUSION The ASC was able to decrease the complexity of the MLC aperture according to the setting level. From very low to moderate settings, a plan equivalent to the off setting could be created in terms of dose parameters.
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Affiliation(s)
- Tatsuya Kamima
- Radiation Oncology Department, The Cancer Institute Hospital, Japanese Foundation for Cancer Research
| | - Yu Murakami
- Radiation Oncology Department, The Cancer Institute Hospital, Japanese Foundation for Cancer Research
| | - Masato Arima
- Radiation Oncology Department, The Cancer Institute Hospital, Japanese Foundation for Cancer Research
| | - Yosuke Sato
- Radiation Oncology Department, The Cancer Institute Hospital, Japanese Foundation for Cancer Research
| | - Minoru Yoshioka
- Radiation Oncology Department, The Cancer Institute Hospital, Japanese Foundation for Cancer Research
| | - Tomoharu Sato
- Radiation Oncology Department, The Cancer Institute Hospital, Japanese Foundation for Cancer Research.,Department of Radiology, Toyo Public Health College
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Shiba E, Saito A, Furumi M, Kawahara D, Miki K, Murakami Y, Ohguri T, Ozawa S, Tsuneda M, Yahara K, Nishio T, Korogi Y, Nagata Y. Predictive gamma passing rate for three‐dimensional dose verification with finite detector elements via improved dose uncertainty potential accumulation model. Med Phys 2020; 47:1349-1356. [DOI: 10.1002/mp.13985] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 12/03/2019] [Accepted: 12/14/2019] [Indexed: 11/08/2022] Open
Affiliation(s)
- Eiji Shiba
- Department of Radiation Oncology Hospital of the University of Occupational and Environmental Health Fukuoka 807‐8556Japan
- Department of Radiation Oncology Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima 734‐8551Japan
| | - Akito Saito
- Department of Radiation Oncology Hiroshima University Hospital Hiroshima 734‐8551Japan
| | - Makoto Furumi
- Department of Radiation Oncology Hospital of the University of Occupational and Environmental Health Fukuoka 807‐8556Japan
| | - Daisuke Kawahara
- Department of Radiation Oncology Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima 734‐8551Japan
| | - Kentaro Miki
- Department of Radiation Oncology Hiroshima University Hospital Hiroshima 734‐8551Japan
| | - Yuji Murakami
- Department of Radiation Oncology Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima 734‐8551Japan
| | - Takayuki Ohguri
- Department of Radiation Oncology Hospital of the University of Occupational and Environmental Health Fukuoka 807‐8556Japan
| | - Shuichi Ozawa
- Department of Radiation Oncology Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima 734‐8551Japan
- Hiroshima High‐Precision Radiotherapy Cancer Center Hiroshima 732‐0057Japan
| | - Masato Tsuneda
- Department of Radiation Oncology Tokyo Women's Medical University Shinjuku Tokyo 162‐8666Japan
| | - Katsuya Yahara
- Department of Radiation Oncology Hospital of the University of Occupational and Environmental Health Fukuoka 807‐8556Japan
| | - Teiji Nishio
- Department of Medical Physics Graduate School of Medical Science Tokyo Women's Medical University Tokyo 162‐8666Japan
| | - Yukunori Korogi
- Department of Radiation Oncology Hospital of the University of Occupational and Environmental Health Fukuoka 807‐8556Japan
| | - Yasushi Nagata
- Department of Radiation Oncology Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima 734‐8551Japan
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Tang D, Yang Z, Dai X, Cao Y. Evaluation of Delta 4DVH Anatomy in 3D Patient-Specific IMRT Quality Assurance. Technol Cancer Res Treat 2020; 19:1533033820945816. [PMID: 32720589 PMCID: PMC7388137 DOI: 10.1177/1533033820945816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
Purpose: To evaluate the performance of Delta4DVH Anatomy in
patient-specific intensity-modulated radiotherapy quality assurance. Materials and Methods: Dose comparisons were performed between Anatomy doses calculated with
treatment plan dose measured modification and pencil beam algorithms,
treatment planning system doses, film doses, and ion chamber measured doses
in homogeneous and inhomogeneous geometries. The sensitivity of Anatomy
doses to machine errors and output calibration errors was also
investigated. Results: For a Volumetric Modulated Arc Therapy (VMAT) plan evaluated on the
Delta4 geometry, the conventional gamma passing rate was
99.6%. For a water-equivalent slab geometry, good agreements were found
between dose profiles in film, treatment planning system, and Anatomy
treatment plan dose measured modification and pencil beam calculations.
Gamma passing rate for Anatomy treatment plan dose measured modification and
pencil beam doses versus treatment planning system doses was 100%. However,
gamma passing rate dropped to 97.2% and 96% for treatment plan dose measured
modification and pencil beam calculations in inhomogeneous head & neck
phantom, respectively. For the 10 patients’ quality assurance plans, good
agreements were found between ion chamber measured doses and the planned
ones (deviation: 0.09% ± 1.17%). The averaged gamma passing rate for
conventional and Anatomy treatment plan dose measured modification and
pencil beam gamma analyses in Delta4 geometry was 99.6% ± 0.89%,
98.54% ± 1.60%, and 98.95% ± 1.27%, respectively, higher than averaged gamma
passing rate of 97.75% ± 1.23% and 93.04% ± 2.69% for treatment plan dose
measured modification and pencil beam in patients’ geometries, respectively.
Anatomy treatment plan dose measured modification dose profiles agreed well
with those in treatment planning system for both Delta4 and
patients’ geometries, while pencil beam doses demonstrated substantial
disagreement in patients’ geometries when compared to treatment planning
system doses. Both treatment planning system doses are sensitive to
multileaf collimator and monitor unit (MU) errors for high and medium dose
metrics but not sensitive to the gantry and collimator rotation error
smaller than 3°. Conclusions: The new Delta4DVH Anatomy with treatment plan dose measured
modification algorithm is a useful tool for the anatomy-based
patient-specific quality assurance. Cautions should be taken when using
pencil beam algorithm due to its limitations in handling heterogeneity and
in high-dose gradient regions.
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Affiliation(s)
- Du Tang
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, China
| | - Zhen Yang
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, China
| | - Xunzhang Dai
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, China
| | - Ying Cao
- Department of Oncology, Xiangya Hospital, Central South University, Changsha, China
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Chiavassa S, Bessieres I, Edouard M, Mathot M, Moignier A. Complexity metrics for IMRT and VMAT plans: a review of current literature and applications. Br J Radiol 2019; 92:20190270. [PMID: 31295002 PMCID: PMC6774599 DOI: 10.1259/bjr.20190270] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Revised: 07/04/2019] [Accepted: 07/09/2019] [Indexed: 12/21/2022] Open
Abstract
Modulated radiotherapy with multileaf collimators is widely used to improve target conformity and normal tissue sparing. This introduced an additional degree of complexity, studied by multiple teams through different properties. Three categories of complexity metrics were considered in this review: fluence, deliverability and accuracy metrics. The first part of this review is dedicated to the inventory of these complexity metrics. Different applications of these metrics emerged. Influencing the optimizer by integrating complexity metrics into the cost function has been little explored and requires more investigations. In modern treatment planning system, it remains confined to MUs or treatment time limitation. A large majority of studies calculated metrics only for analysis, without plan modification. The main application was to streamline the patient specific quality assurance workload, investigating the capability of complexity metrics to predict patient specific quality assurance results. Additionally complexity metrics were used to analyze behaviour of TPS optimizer, compare TPS, operators and plan properties, and perform multicentre audit. Their potential was also explored in the context of adaptive radiotherapy and automation planning. The second part of the review gives an overview of these studies based on the complexity metrics.
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Affiliation(s)
- Sophie Chiavassa
- Department of Medical Physics, Institut de Cancérologie de l’Ouest Centre René Gauducheau, 44805 Saint-Herblain, France
| | - Igor Bessieres
- Departement of Medical Physics, Centre Georges-François Leclerc, 1 rue Professeur Marion, 21000 Dijon, France
| | - Magali Edouard
- Department of Radiation Oncology, Gustave Roussy, 114 rue Édouard-Vaillant, 94805 Villejuif, France
| | - Michel Mathot
- Liege University Hospital, Domaine du Sart Tilman - B.35 - B-4000 LIEGE1, Belgium
| | - Alexandra Moignier
- Department of Medical Physics, Institut de Cancérologie de l’Ouest Centre René Gauducheau, 44805 Saint-Herblain, France
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Evaluation of organ-at-risk dose reduction with jaw tracking technique in flattening filter-free beams in lung stereotactic body radiation therapy. Phys Med 2019; 61:70-76. [PMID: 31151582 DOI: 10.1016/j.ejmp.2019.04.018] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Revised: 04/20/2019] [Accepted: 04/22/2019] [Indexed: 11/24/2022] Open
Abstract
PURPOSE (i) to investigate the capability of organ-at-risk (OAR) dose reduction with the jaw tracking (JT) technique in flattening filter-free (FFF) beams in lung stereotactic body radiation therapy (SBRT), (ii) to propose a novel metric to quantify the jaw movements during JT, and (iii) to examine the relationships between the quantified jaw movements and reduction rate of OAR doses. METHODS The individual SBRT plans with volumetric modulated arc therapy using the JT technique (JT-VMAT) and VMAT plans with a fixed jaw (FJ-VMAT) were created for 15 patients, and dosimetric parameters were compared. A jaw tracking complexity score (JTCS) was defined and compared with the multi-leaf collimator (MLC) modulation complexity score (MCS). The correlations between the JTCS and reduction rate of OAR doses were examined. RESULTS The decrease of OARs doses was statistically significant in the JT-VMAT plans (1.2% in V20 of the lung and <1% in all other OARs). The correlations between the JTCS and MCS were not significant. There were significant correlations between the JTCS and the reduction rates in V20, V2.5, and Dmean of the lung, D1% of the spinal cord, and D90% of the body. CONCLUSIONS A significant decrease of dosimetric parameters of OARs was found with JT-VMAT in FFF beams. This reduction is very small and probably not clinically relevant. JTCS, a novel metric to quantify the jaw movements during JT, was proposed, and the complexity of jaw movements did not correlate with that of the movements of MLC leaves. There were significant correlations between the JTCS and some dosimetric parameters of OARs.
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Giglioli FR, Gallio E, Franco P, Badellino S, Ricardi U, Fiandra C. Clinical evaluation of a transmission detector system and comparison with a homogeneous 3D phantom dosimeter. Phys Med 2019; 58:159-164. [DOI: 10.1016/j.ejmp.2019.01.016] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Revised: 01/23/2019] [Accepted: 01/26/2019] [Indexed: 11/16/2022] Open
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Shiba E, Saito A, Furumi M, Murakami Y, Ohguri T, Tsuneda M, Yahara K, Nishio T, Korogi Y, Nagata Y. Predictive gamma passing rate by dose uncertainty potential accumulation model. Med Phys 2018; 46:999-1005. [PMID: 30536878 DOI: 10.1002/mp.13333] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Revised: 12/03/2018] [Accepted: 12/03/2018] [Indexed: 11/10/2022] Open
Abstract
PURPOSE Intensity-modulated radiation therapy (IMRT) utilizes many small fields for producing a uniform dose distribution. Therefore, there are many field junctions in the target region, and resulting dose uncertainties are accumulated. However, such accumulation of the dose uncertainty has not been implemented in the current practice of IMRT dose verification. The purpose of this study is to develop a method to predict the gamma passing rate (GPR) using a dose uncertainty accumulation model. METHODS Thirty-three intensity-modulated (IM) beams for head-and-neck cases with step-and-shoot techniques were used in this study. The treatment plan was created using the XiO treatment planning system (TPS). The IM beam was produced by the ONCOR Impression Plus linear accelerator. MapCHECK was used to measure the dose distribution. The distribution of a dose uncertainty potential (DUP) was generated by in-house software that accumulated field shapes weighted by a segmental monitor unit, followed by Gaussian folding. The width of the Gaussian was determined from the width of the lateral penumbra. The dose difference between the calculated and measured doses was compared with the estimated DUP at each point. The GPR of each beam was predicted for 2%/2-mm, 3%/2-mm, and 3%/3-mm tolerances by its own DUP histogram and a GPR-vs-DUP correlation of other beams using the leave-one-out cross-validation method. The predicted GPR was compared with the measured GPR to evaluate the performance of this prediction method. The criteria for the predicted GPR corresponding to a measured GPR ≥ 90% were estimated to examine the feasibility of estimating the measured GPR by this GPR prediction method. RESULTS The DUP was confirmed to have proportionality to the standard deviation (SD) of the dose difference. The SDs of the difference between the measured and predicted GPRs were 3.1, 1.7, and 1.4% for 2%/2-mm, 3%/2-mm, and 3%/3-mm tolerances, respectively. The criteria of the predicted GPR corresponding to the measured GPR ≥ 90% were 94.1 and 95.0% with confidence levels of 99 and 99.9%, respectively. CONCLUSION In this study, we confirmed the good proportionality between the dose difference and the estimated DUP. The results showed a feasibility to predict the dose difference from DUP as estimated by a DUP accumulation model. The predicted GPR developed in this study showed good accuracy for planar dose distributions of head and neck IMRT. The prediction method developed in this study is considered to be feasible as a substitute for the current practice of measurement-based verification of the dose distribution with gamma analysis.
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Affiliation(s)
- Eiji Shiba
- Department of Radiation Oncology, Hospital of the University of Occupational and Environmental Health, Fukuoka, 807-8556, Japan.,Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, 734-8551, Japan
| | - Akito Saito
- Department of Radiation Oncology, Hiroshima University Hospital, Hiroshima, 734-8551, Japan
| | - Makoto Furumi
- Department of Radiation Oncology, Hospital of the University of Occupational and Environmental Health, Fukuoka, 807-8556, Japan
| | - Yuji Murakami
- Department of Radiation Oncology, Institute of Biomedical and Health Sciences, Hiroshima University, Hiroshima, 734-8551, Japan
| | - Takayuki Ohguri
- Department of Radiation Oncology, Hospital of the University of Occupational and Environmental Health, Fukuoka, 807-8556, Japan
| | - Masato Tsuneda
- Department of Radiation Oncology, Tokyo Women's Medical University, Shinjuku, Tokyo, 162-8666, Japan
| | - Katsuya Yahara
- Department of Radiation Oncology, Hospital of the University of Occupational and Environmental Health, Fukuoka, 807-8556, Japan
| | - Teiji Nishio
- Department of Medical Physics, Graduate School of Medical Science, Tokyo Women's Medical University, Tokyo, 162-8666, Japan
| | - Yukunori Korogi
- Department of Radiation Oncology, Hospital of the University of Occupational and Environmental Health, Fukuoka, 807-8556, Japan
| | - Yasushi Nagata
- Department of Radiation Oncology, Institute of Biomedical and Health Sciences, Hiroshima University, Hiroshima, 734-8551, Japan
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22
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Glenn MC, Hernandez V, Saez J, Followill DS, Howell RM, Pollard-Larkin JM, Zhou S, Kry SF. Treatment plan complexity does not predict IROC Houston anthropomorphic head and neck phantom performance. Phys Med Biol 2018; 63:205015. [PMID: 30230475 PMCID: PMC6287268 DOI: 10.1088/1361-6560/aae29e] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Previous works indicate that intensity-modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) plans that are highly complex may produce more errors in dose calculation and treatment delivery. Multiple complexity metrics have been proposed and associated with IMRT QA results, but their relationships with plan performance using in situ dose measurements have not been thoroughly investigated. This study aimed to evaluate the relationships between IMRT treatment plan complexity and anthropomorphic phantom performance in order to assess the extent to which plan complexity is related to dosimetric performance in the IROC phantom credentialing program. Sixteen complexity metrics, including the modulation complexity score (MCS), several modulation indices, and total monitor units (MU) delivered, were evaluated for 343 head and neck phantom irradiations, comprising both IMRT (step-and-shoot and sliding window techniques) and VMAT. Spearman's correlations were used to explore the relationship between complexity and plan performance, as measured by the dosimetric differences between the treatment planning system (TPS) and thermoluminescent dosimeter (TLD) measurement, as well as film gamma analysis. Relationships were likewise determined for several combinations of subpopulations, based on the linear accelerator model, TPS used, and delivery modality. Evaluation of the complexity metrics presented here yielded no significant relationships (p > 0.01, Bonferroni-corrected) and all correlations were weak (less than ±0.30). These results indicate that complexity metrics have limited predictive utility in assessing plan performance in multi-institutional comparisons of IMRT plans. Other factors affecting plan accuracy, such as dosimetric modeling or multileaf collimator (MLC) performance, should be investigated to determine a more probable cause for dose delivery errors.
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Affiliation(s)
- Mallory C. Glenn
- The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030
| | - Victor Hernandez
- Department of Medical Physics, Hospital Universitari Sant Joan de Reus, Tarragona, Spain
| | - Jordi Saez
- Department of Radiation Oncology, Hospital Clmic de Barcelona, Barcelona, Spain
| | - David S. Followill
- The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030
| | - Rebecca M. Howell
- The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030
| | - Julianne M. Pollard-Larkin
- The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030
| | - Shouhao Zhou
- The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030
| | - Stephen F. Kry
- The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX 77030
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030
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23
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Absolute dose verification of static intensity modulated radiation therapy (IMRT) with ion chambers of various volumes and TLD detectors. Rep Pract Oncol Radiother 2018; 23:242-250. [PMID: 29991928 DOI: 10.1016/j.rpor.2018.04.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2016] [Revised: 01/12/2018] [Accepted: 04/08/2018] [Indexed: 11/22/2022] Open
Abstract
Aim This study aims at examining absolute dose verification of step-and-shoot intensity modulated radiation treatment (IMRT) of prostate and brain patients by use of ion chambers of two different volumes and thermoluminescent detectors (TLD). Background The volume of the ion chamber (IC) is very important for absolute dose verification of IMRT plans since the IC has a volume average effect. With TLD detectors absolute dose verification can be done measuring the dose of multiple points simultaneously. Materials and methods Ion chambers FC65-P of volume 0.65 cc and semiflex of volume 0.125 cc as well as TLDs were used to measure the central axis absolute dose of IMRT quality assurance (QA) plans. The results were compared with doses calculated by a treatment planning system (TPS). The absolute doses of off axis points located 2 cm and 4 cm away from the isocenter were measured with TLDs. Results The measurements of the 0.125 cc ion chamber were found to be closer to TPS calculations compared to the 0.65 cc ion chamber, for both patient groups. For both groups the root mean square (RMS) differences between doses of the TPS and the TLD detectors are within 3.0% for the central axis and points 2 cm away from the isocenter of each axis. Larger deviations were found at the field edges, which have steep dose gradient. Conclusions The 0.125 cc ion chamber measures the absolute dose of the isocenter more accurately compared to the 0.65 cc chamber. TLDs have good accuracy (within 3.0%) for absolute dose measurements of in-field points.
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24
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Giglioli FR, Clemente S, Esposito M, Fiandra C, Marino C, Russo S, Strigari L, Villaggi E, Stasi M, Mancosu P. Frontiers in planning optimization for lung SBRT. Phys Med 2017; 44:163-170. [PMID: 28566240 DOI: 10.1016/j.ejmp.2017.05.064] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2016] [Revised: 05/19/2017] [Accepted: 05/22/2017] [Indexed: 12/25/2022] Open
Abstract
Emerging data are showing the safety and the efficacy of Stereotactic Body Radiation therapy (SBRT) in lung cancer management. In this context, the very high doses delivered to the Planning Target Volume, make the planning phase essential for achieving high dose levels conformed to the shape of the target in order to have a good prognosis for tumor control and to avoid an overdose in relevant healthy adjacent tissue. In this non-systematic review we analyzed the technological and the physics aspects of SBRT planning for lung cancer. In particular, the aims of the study were: (i) to evaluate prescription strategies (homogeneous or inhomogeneous), (ii) to outline possible geometrical solutions by comparing the dosimetric results (iii) to describe the technological possibilities for a safe and effective treatment, (iv) to present the issues concerning radiobiological planning and the automation of the planning process.
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Affiliation(s)
| | | | | | - Christian Fiandra
- Dep. of Oncology Radiation Oncology Unit, University of Torino, Italy
| | | | | | - Lidia Strigari
- Laboratory of Medical Physics and Expert Systems, Regina Elena National Cancer, Institute IFO, Rome, Italy
| | | | - Michele Stasi
- Medical Physics Dept., Azienda Ospedaliera Ordine Mauriziano di Torino, Torino, Italy
| | - Pietro Mancosu
- Medical Physics Unit of Radiotherapy Dept., Humanitas Clinical and Research Hospital, Rozzano (MI), Italy
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25
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Sumida I, Yamaguchi H, Das IJ, Kizaki H, Aboshi K, Tsujii M, Yamada Y, Tamari K, Seo Y, Isohashi F, Yoshioka Y, Ogawa K. Organ-specific modulation complexity score for the evaluation of dose delivery. JOURNAL OF RADIATION RESEARCH 2017; 58:675-684. [PMID: 28199706 PMCID: PMC5737647 DOI: 10.1093/jrr/rrw129] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2016] [Revised: 11/12/2016] [Accepted: 12/18/2016] [Indexed: 05/04/2023]
Abstract
The purpose of this study was to correlate the modulation complexity score (MCS) with organ location and to predict potential dose errors for organs before beam delivery for intensity-modulated radiation therapy (IMRT) dosimetry. Sixteen head and neck cancer patients treated with IMRT were selected. Distribution of the relative dose error on each beam was performed using forward projection to the planned dose to compute the predicted dose after doing per-beam quality assurance. Original organ-specific modulation complexity score (oMCS) was created based on a modified MLC, which depended on organ location. First, MCS was calculated based on the change in leaf position between adjacent MLC leaves. Second, the segment edge map (SEM) calculated from the intensity map for each beam was applied to the calculation volume. The oMCS with segment edge (oMCSedge) was derived from the product of oMCS and SEM. The correlation between the dose errors (planned and predicted) and oMCSedge values was evaluated for the target and organs at risk. We have also expanded the original MCS concept to oMCSedge including the organ location. We observed a moderate correlation between the dose errors and oMCSedge for all organs and volumes of interest except the gross tumor volume, brain stem, and spinal cord. In other organs, a moderate improvement in sensitivity was observed on the SEM, which was correlated with dose errors. Although the implementation of oMCSedge would be impractical for normal clinical settings, it is expected that oMCSedge would help a treatment planner to judge whether or not the treatment plan would be acceptably delivered.
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Affiliation(s)
- Iori Sumida
- Department of Radiation Oncology, Osaka University Graduate School of Medicine, 2-2 Yamada-oka, Suita, Osaka, 565-0871,Japan
| | - Hajime Yamaguchi
- Department of Radiation Oncology, NTT West Osaka Hospital, 2-6-40 Karasugatsuji, Tennoji-ku, Osaka, 543-8922, Japan
| | - Indra J Das
- Department of Radiation Oncology, New York University Langone Medical Center, 160 E 34th Street, New York, NY 10016, USA
| | - Hisao Kizaki
- Department of Radiation Oncology, NTT West Osaka Hospital, 2-6-40 Karasugatsuji, Tennoji-ku, Osaka, 543-8922, Japan
| | - Keiko Aboshi
- Department of Radiation Oncology, NTT West Osaka Hospital, 2-6-40 Karasugatsuji, Tennoji-ku, Osaka, 543-8922, Japan
| | - Mari Tsujii
- Department of Radiation Oncology, NTT West Osaka Hospital, 2-6-40 Karasugatsuji, Tennoji-ku, Osaka, 543-8922, Japan
| | - Yuji Yamada
- Department of Radiation Oncology, NTT West Osaka Hospital, 2-6-40 Karasugatsuji, Tennoji-ku, Osaka, 543-8922, Japan
| | - Keisuke Tamari
- Department of Radiation Oncology, Osaka University Graduate School of Medicine, 2-2 Yamada-oka, Suita, Osaka, 565-0871,Japan
| | - Yuji Seo
- Department of Radiation Oncology, Osaka University Graduate School of Medicine, 2-2 Yamada-oka, Suita, Osaka, 565-0871,Japan
| | - Fumiaki Isohashi
- Department of Radiation Oncology, Osaka University Graduate School of Medicine, 2-2 Yamada-oka, Suita, Osaka, 565-0871,Japan
| | - Yasuo Yoshioka
- Department of Radiation Oncology, Osaka University Graduate School of Medicine, 2-2 Yamada-oka, Suita, Osaka, 565-0871,Japan
| | - Kazuhiko Ogawa
- Department of Radiation Oncology, Osaka University Graduate School of Medicine, 2-2 Yamada-oka, Suita, Osaka, 565-0871,Japan
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26
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Defoor DL, Stathakis S, Roring JE, Kirby NA, Mavroidis P, Obeidat M, Papanikolaou N. Investigation of error detection capabilities of phantom, EPID and MLC log file based IMRT QA methods. J Appl Clin Med Phys 2017; 18:172-179. [PMID: 28585300 PMCID: PMC5874853 DOI: 10.1002/acm2.12114] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2016] [Revised: 04/17/2017] [Accepted: 04/20/2017] [Indexed: 11/21/2022] Open
Abstract
A patient specific quality assurance (QA) should detect errors that originate anywhere in the treatment planning process. However, the increasing complexity of treatment plans has increased the need for improvements in the accuracy of the patient specific pretreatment verification process. This has led to the utilization of higher resolution QA methods such as the electronic portal imaging device (EPID) as well as MLC log files and it is important to know the types of errors that can be detected with these methods. In this study, we will compare the ability of three QA methods (Delta4 ®, MU-EPID, Dynalog QA) to detect specific errors. Multileaf collimator (MLC) errors, gantry angle, and dose errors were introduced into five volumetric modulated arc therapy (VMAT) plans for a total of 30 plans containing errors. The original plans (without errors) were measured five times with each method to set a threshold for detectability using two standard deviations from the mean and receiver operating characteristic (ROC) derived limits. Gamma passing percentages as well as percentage error of planning target volume (PTV) were used for passing determination. When applying the standard 95% pass rate at 3%/3 mm gamma analysis errors were detected at a rate of 47, 70, and 27% for the Delta4 , MU-EPID and Dynalog QA respectively. When using thresholds set at 2 standard deviations from our base line measurements errors were detected at a rate of 60, 30, and 47% for the Delta4 , MU-EPID and Dynalog QA respectively. When using ROC derived thresholds errors were detected at a rate of 60, 27, and 47% for the Delta4 , MU-EPID and Dynalog QA respectively. When using dose to the PTV and the Dynalog method 11 of the 15 small MLC errors were detected while none were caught using gamma analysis. A combination of the EPID and Dynalog QA methods (scaling Dynalog doses using EPID images) matches the detection capabilities of the Delta4 by adding additional comparison metrics. These additional metrics are vital in relating the QA measurement to the dose received by the patient which is ultimately what is being confirmed.
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Affiliation(s)
- Dewayne L. Defoor
- Cancer Therapy and Research Center – Department of Radiation OncologyUniversity of Texas Health Science Center – San AntonioSan AntonioTXUSA
| | - Sotirios Stathakis
- Cancer Therapy and Research Center – Department of Radiation OncologyUniversity of Texas Health Science Center – San AntonioSan AntonioTXUSA
| | - Joseph E. Roring
- Cancer Therapy and Research Center – Department of Radiation OncologyUniversity of Texas Health Science Center – San AntonioSan AntonioTXUSA
| | - Neil A. Kirby
- Cancer Therapy and Research Center – Department of Radiation OncologyUniversity of Texas Health Science Center – San AntonioSan AntonioTXUSA
| | - Panayiotis Mavroidis
- Department of Radiation OncologyUniversity of North Carolina School of MedicineChapel HillNCUA
| | - Mohammad Obeidat
- Cancer Therapy and Research Center – Department of Radiation OncologyUniversity of Texas Health Science Center – San AntonioSan AntonioTXUSA
| | - Nikos Papanikolaou
- Cancer Therapy and Research Center – Department of Radiation OncologyUniversity of Texas Health Science Center – San AntonioSan AntonioTXUSA
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