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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. [PMID: 38669453 DOI: 10.1002/mp.17086] [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: 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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Oonsiri S, Kingkaew S, Vimolnoch M, Chatchumnan N, Plangpleng N, Oonsiri P. Effectiveness of multi-criteria optimization in combination with knowledge-based modeling in radiotherapy of left-sided breast including regional nodes. Phys Imaging Radiat Oncol 2024; 30:100595. [PMID: 38872709 PMCID: PMC11169521 DOI: 10.1016/j.phro.2024.100595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 05/27/2024] [Accepted: 05/27/2024] [Indexed: 06/15/2024] Open
Abstract
Multi-criteria optimization (MCO) is a method that was added to treatment planning to create high-quality treatment plans. This study aimed to investigate the effectiveness of MCO in combination with knowledge-based planning (KBP) in radiotherapy for left-sided breasts, including regional nodes. Dose/volume parameters were evaluated for manual plans (MP), KBP, and KBP + MCO. Planning target volume doses of MP had better coverage while KBP + MCO plans demonstrated the lowest organ at risk doses. KBP and KBP + MCO plans had increasing complexity as expressed in the number of monitor units.
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Affiliation(s)
- Sornjarod Oonsiri
- Division of Radiation Oncology, Department of Radiology, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand
| | - Sakda Kingkaew
- Division of Radiation Oncology, Department of Radiology, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand
| | - Mananchaya Vimolnoch
- Division of Radiation Oncology, Department of Radiology, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand
| | - Nichakan Chatchumnan
- Division of Radiation Oncology, Department of Radiology, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand
| | - Nuttha Plangpleng
- Division of Radiation Oncology, Department of Radiology, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand
| | - Puntiwa Oonsiri
- Division of Radiation Oncology, Department of Radiology, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand
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Sun W, Mo Z, Li Y, Xiao J, Jia L, Huang S, Liao C, Du J, He S, Chen L, Zhang W, Yang X. Machine learning-based ensemble prediction model for the gamma passing rate of VMAT-SBRT plan. Phys Med 2024; 117:103204. [PMID: 38154373 DOI: 10.1016/j.ejmp.2023.103204] [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: 08/09/2023] [Revised: 10/29/2023] [Accepted: 12/21/2023] [Indexed: 12/30/2023] Open
Abstract
PURPOSE The purpose of this study was to accurately predict or classify the beam GPR with an ensemble model by using machine learning for SBRT(VMAT) plans. METHODS A total of 128 SBRT VMAT plans with 330 arc beams were retrospectively selected, and 216 radiomics and 34 plan complexity features were calculated for each arc beam. Three models for GPR prediction and classification using support vector machine algorithm were as follows: (1) plan complexity feature-based model (plan model); (2) radiomics feature-based model (radiomics model); and (3) an ensemble model combining the two models (ensemble model). The prediction performance was evaluated by calculating the mean absolute error (MAE), root mean square error (RMSE), and Spearman's correlation coefficient (SC), and the classification performance was measured by calculating the area under the receiver operating characteristic curve (AUC), accuracy, specificity, and sensitivity. RESULTS The MAE, RMSE and SC at the 2 %/2 mm gamma criterion in the test dataset were 1.4 %, 2.57 %, and 0.563, respectively, for the plan model; 1.42 %, and 2.51 %, and 0.508, respectively, for the radiomics model; and 1.33 %, 2.49 %, and 0.611, respectively, for the ensemble model. The accuracy, specificity, sensitivity, and AUC at the 2 %/2 mm gamma criterion in the test dataset were 0.807, 0.824, 0.681, and 0.854, respectively, for the plan model; 0.860, 0.893, 0.624, and 0.877, respectively, for the radiomics model; and 0.852, 0.871, 0.710, and 0.896, respectively, for the ensemble model. CONCLUSIONS The ensemble model can improve the prediction and classification performance for the GPR of SBRT (VMAT).
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Affiliation(s)
- Wenzhao Sun
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China; Guangdong Esophageal Cancer Institute, Guangzhou, China.
| | - Zijie Mo
- Shenzhen United Imaging Research Institute of Innovative Medical Equipment, Shenzhen, China
| | - Yongbao Li
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Jifeng Xiao
- Shenzhen United Imaging Research Institute of Innovative Medical Equipment, Shenzhen, China
| | - Lecheng Jia
- Shenzhen United Imaging Research Institute of Innovative Medical Equipment, Shenzhen, China
| | - Sijuan Huang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Can Liao
- Shanghai United Imaging Healthcare Co., Ltd., Shanghai, China
| | - Jinlong Du
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Shumeng He
- United Imaging Research Institute of Intelligent Imaging, Beijing, China
| | - Li Chen
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Wei Zhang
- Shanghai United Imaging Healthcare Co., Ltd., Shanghai, China
| | - Xin Yang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
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Wesolowska P, Slusarczyk-Kacprzyk W, Fillmann M, Kazantsev P, Bulski W. Results of the IAEA supported national end-to-end audit of the IMRT technique in Poland. Phys Med 2023; 116:103168. [PMID: 37984129 DOI: 10.1016/j.ejmp.2023.103168] [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: 03/16/2023] [Revised: 10/09/2023] [Accepted: 11/05/2023] [Indexed: 11/22/2023] Open
Abstract
The dosimetry audit services were established in Poland in 1991, since then new audits have been introduced. The recently developed IAEA audit methodology for IMRT H&N treatments was tested nationally. Anthropomorphic SHANE phantom (CIRS) was used to perform measurements in 8 hospitals which voluntarily participated in the study. Each participant had to complete successfully pre-visit activities to take part in an onsite visit. During the visit, auditors together with the local staff, did a CT scan using local protocol, recalculated the plan and verified all the relevant parameters and performed measurements with an ionization chamber and films in SHANE. The adoption of IAEA methodology to the national circumstances was done with no major issues. Participants plans were verified and the results of ionization chamber were all within the 5 % tolerance limit for PTV (max 4,5%) and 7 % for OAR (max 5,3%). Film global gamma results (3 %, 3 mm, 90 % acceptance limit) were within 91,5-99,7% range. The IAEA established acceptance criteria which were achievable for most tests except for CTtoRED conversion curve. The locally performed study allowed establishing new limits. The audit gave interesting results and showed that the procedure is very thorough and capable to identify issues related with suboptimal treatment preparation and delivery. The new limits for CTtoRED conversion curve were adopted for national study. Such an audit gives an opportunity to verify the quality of locally implemented procedures and should be available for Polish hospitals on a daily basis.
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Affiliation(s)
- Paulina Wesolowska
- Department of Medical Physics, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland.
| | | | - Marta Fillmann
- Department of Medical Physics, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland
| | - Pavel Kazantsev
- Dosimetry Laboratory, Dosimetry and Medical Radiation Physics Section, Division of Human Health, International Atomic Energy Agency, Vienna, Austria
| | - Wojciech Bulski
- Department of Medical Physics, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland
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Huang S, Mai X, Liu H, Sun W, Zhu J, Du J, Lin X, Du Y, Zhang K, Yang X, Huang X. Plan quality and treatment efficiency assurance of two VMAT optimization for cervical cancer radiotherapy. J Appl Clin Med Phys 2023; 24:e14050. [PMID: 37248800 PMCID: PMC10562038 DOI: 10.1002/acm2.14050] [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: 01/16/2023] [Revised: 03/21/2023] [Accepted: 05/11/2023] [Indexed: 05/31/2023] Open
Abstract
To investigate the difference of the fluence map optimization (FMO) and Stochastic platform optimization (SPO) algorithm in a newly-introduced treatment planning system (TPS). METHODS 34 cervical cancer patients with definitive radiation were retrospectively analyzed. Each patient has four plans: FMO with fixed jaw plans (FMO-FJ) and no fixed jaw plans (FMO-NFJ); SPO with fixed jaw plans (SPO-FJ) and no fixed jaw plans (SPO-NFJ). Dosimetric parameters, Modulation Complexity Score (MCS), Gamma Pass Rate (GPR) and delivery time were analyzed among the four plans. RESULTS For target coverage, SPO-FJ plans are the best ones (P ≤ 0.00). FMO plans are better than SPO-NFJ plans (P ≤ 0.00). For OARs sparing, SPO-FJ plans are better than FMO plans for mostly OARs (P ≤ 0.04). Additionally, SPO-FJ plans are better than SPO-NFJ plans (P ≤ 0.02), except for rectum V45Gy. Compared to SPO-NFJ plans, the FMO plans delivered less dose to bladder, rectum, colon V40Gy and pelvic bone V40Gy (P ≤ 0.04). Meanwhile, the SPO-NFJ plans showed superiority in MU, delivery time, MCS and GPR in all plans. In terms of delivery time and MCS, the SPO-FJ plans are better than FMO plans. FMO-FJ plans are better than FMO-NFJ plans in delivery efficiency. MCSs are strongly correlated with PCTV length, which are negatively with PCTV length (P ≤ 0.03). The delivery time and MUs of the four plans are strongly correlated (P ≤ 0.02). Comparing plans with fixed or no fixed jaw in two algorithms, no difference was found in FMO plans in target coverage and minor difference in Kidney_L Dmean, Mu and delivery time between PCTV width≤15.5 cm group and >15.5 cm group. For SPO plans, SPO-FJ plans showed more superiority in target coverage and OARs sparing than the SPO-NFJ plans in the two groups. CONCLUSIONS SPO-FJ plans showed superiority in target coverage and OARs sparing, as well as higher delivery efficiency in the four plans.
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Affiliation(s)
- Sijuan Huang
- Department of Radiation Oncology, Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer MedicineGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangzhouGuangdongChina
| | - Xiuying Mai
- Department of Radiation Oncology, Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer MedicineGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangzhouGuangdongChina
| | - Hongdong Liu
- Department of Radiation Oncology, Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer MedicineGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangzhouGuangdongChina
| | - Wenzhao Sun
- Department of Radiation Oncology, Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer MedicineGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangzhouGuangdongChina
| | - Jinhan Zhu
- Department of Radiation Oncology, Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer MedicineGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangzhouGuangdongChina
| | - Jinlong Du
- Department of Radiation Oncology, Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer MedicineGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangzhouGuangdongChina
| | - Xi Lin
- Department of Radiation Oncology, Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer MedicineGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangzhouGuangdongChina
- School of Biomedical EngineeringGuangzhou Xinhua CollegeGuangzhouGuangdongChina
| | - Yujie Du
- Department of Radiation Oncology, Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer MedicineGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangzhouGuangdongChina
| | | | - Xin Yang
- Department of Radiation Oncology, Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer MedicineGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangzhouGuangdongChina
| | - Xiaoyan Huang
- Department of Radiation Oncology, Sun Yat‐sen University Cancer CenterState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer MedicineGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangzhouGuangdongChina
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Ono T, Nakamura M, Ono Y, Nakamura K, Mizowaki T. Development of a plan complexity mitigation algorithm based on gamma passing rate predictions for volumetric-modulated arc therapy. Med Phys 2022; 49:1793-1802. [PMID: 35064567 DOI: 10.1002/mp.15466] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 12/28/2021] [Accepted: 12/29/2021] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND AND PURPOSE Volumetric-modulated arc therapy (VMAT) is a complex rotational therapy technique in which highly conformal dose distribution can be realized by varying the speed of gantry rotation, multileaf collimator (MLC) shape, and dose rate. However, the complexity of the technique creates a discrepancy between the calculated and measured doses. Thus, to mitigate the plan complexity in VMAT, this study aimed to develop an algorithm and evaluate its usefulness by conducting a feasibility study. MATERIALS AND METHODS A total of 50 patients who underwent VMAT between September 2015 and December 2020 were arbitrarily selected for this study. Specifically, patients with less than 85% gamma passing rate (GPR) at 5%/1 mm or 3%/2 mm criterion were selected randomly. Using the GPR prediction model, problematic MLC positions that contribute to a decrease in GPR were identified. Those problematic MLC positions were optimized using a limited nonlinear algorithm under mechanical limitations. Additionally, the dose prescription for the target was re-normalized. The VMAT modulated complexity score (MCSv ), averaged aperture area (AA), and monitor unit per gray (MU/Gy) were evaluated as plan complexity parameters. Calculated doses in patient geometry were evaluated for the target and its surrounding region. In addition, an ArcCHECK cylindrical diode array was used to measure the dose, and GPRs at 5%/1 mm and 3%/2 mm criteria were evaluated to analyze the difference between the mitigated and original plans. The difference was calculated using the mean ± standard deviation. RESULTS The differences between the MCSv , AA, and MU/cGy values for the mitigated and original plans were 0.8 ± 1.7 (× 10-2 ), 42.7 ± 57.9, and -5.6 ± 8.5, respectively. Regarding the calculated dose, the dose volume parameters were consistent within 1% for the target and the surrounding region. The differences between the mitigated and original plans were 1.8 ± 2.9% and 1.3 ± 1.8% for GPRs at 5%/1 mm and 3%/2 mm, respectively. CONCLUSIONS This feasibility study resulted in the development of an algorithm with the potential to mitigate plan complexity and improve the GPR for VMAT under minor leaf position modifications. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Tomohiro Ono
- Department of Radiation Oncology and Image-Applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Mitsuhiro Nakamura
- Department of Information Technology and Medical Engineering, Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yuka Ono
- Department of Radiation Oncology and Image-Applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Kiyonao Nakamura
- Department of Radiation Oncology and Image-Applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Takashi Mizowaki
- Department of Radiation Oncology and Image-Applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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Chen A, Li Z, He Y, Chen F, Chen L. Effect of the number of control points on the plan quality of intensity-modulated radiotherapy for nasopharyngeal carcinoma. JOURNAL OF RADIATION RESEARCH AND APPLIED SCIENCES 2021. [DOI: 10.1080/16878507.2021.1954802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Along Chen
- Department of Radiation Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou China
| | - Zhenghuan Li
- Department of Radiation Oncology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou China
| | - Yadi He
- School of Biomedical Engineering, South Medical University, Guangzhou China
| | - Fei Chen
- School of Biomedical Engineering, Xinhua College of Sun Yat-sen University, Guangzhou China
| | - Li Chen
- Department of Radiation Oncology, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou China
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Evaluation of treatment plan quality for head and neck IMRT: a multicenter study. Med Dosim 2021; 46:310-317. [PMID: 33838998 DOI: 10.1016/j.meddos.2021.03.003] [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] [Received: 08/19/2020] [Revised: 01/06/2021] [Accepted: 03/05/2021] [Indexed: 11/23/2022]
Abstract
Intensity-modulated radiotherapy (IMRT) treatment planning for head and neck cancer is challenging and complex due to many organs at risk (OAR) in this region. The experience and skills of planners may result in substantial variability of treatment plan quality. This study assessed the performance of IMRT planning in Malaysia and observed plan quality variation among participating centers. The computed tomography dataset containing contoured target volumes and OAR was provided to participating centers. This is to control variations in contouring the target volumes and OARs by oncologists. The planner at each center was instructed to complete the treatment plan based on clinical practice with a given prescription, and the plan was analyzed against the planning goals provided. The quality of completed treatment plans was analyzed using the plan quality index (PQI), in which a score of 0 indicated that all dose objectives and constraints were achieved. A total of 23 plans were received from all participating centers comprising 14 VMAT, 7 IMRT, and 2 tomotherapy plans. The PQI indexes of these plans ranged from 0 to 0.65, indicating a wide variation of plan quality nationwide. Results also reported 5 out of 21 plans achieved all dose objectives and constraints showing more professional training is needed for planners in Malaysia. Understanding of treatment planning system and computational physics could also help in improving the quality of treatment plans for IMRT delivery.
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Kairn T, Livingstone AG, Crowe SB. Monte Carlo calculations of radiotherapy dose in "homogeneous" anatomy. Phys Med 2020; 78:156-165. [PMID: 33035927 DOI: 10.1016/j.ejmp.2020.09.019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 09/05/2020] [Accepted: 09/21/2020] [Indexed: 01/27/2023] Open
Abstract
Given the substantial literature on the use of Monte Carlo (MC) simulations to verify treatment planning system (TPS) calculations of radiotherapy dose in heterogeneous regions, such as head and neck and lung, this study investigated the potential value of running MC simulations of radiotherapy treatments of nominally homogeneous pelvic anatomy. A pre-existing in-house MC job submission and analysis system, built around BEAMnrc and DOSXYZnrc, was used to evaluate the dosimetric accuracy of a sample of 12 pelvic volumetric arc therapy (VMAT) treatments, planned using the Varian Eclipse TPS, where dose was calculated with both the Analytical Anisotropic Algorithm (AAA) and the Acuros (AXB) algorithm. In-house TADA (Treatment And Dose Assessor) software was used to evaluate treatment plan complexity, in terms of the small aperture score (SAS), modulation index (MI) and a novel exposed leaf score (ELS/ELA). Results showed that the TPS generally achieved closer agreement with the MC dose distribution when treatments were planned for smaller (single-organ) targets rather than larger targets that included nodes or metastases. Analysis of these MC results with reference to the complexity metrics indicated that while AXB was useful for reducing dosimetric uncertainties associated with density heterogeneity, the residual TPS dose calculation uncertainties resulted from treatment plan complexity and TPS model simplicity. The results of this study demonstrate the value of using MC methods to recalculate and check the dose calculations provided by commercial radiotherapy TPSs, even when the treated anatomy is assumed to be comparatively homogeneous, such as in the pelvic region.
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Affiliation(s)
- Tanya Kairn
- Royal Brisbane and Women's Hospital, Butterfield Street, Herston, QLD 4029, Australia; Queensland University of Technology, 2 George Street, Brisbane, QLD 4000, Australia.
| | | | - Scott B Crowe
- Royal Brisbane and Women's Hospital, Butterfield Street, Herston, QLD 4029, Australia; Queensland University of Technology, 2 George Street, Brisbane, QLD 4000, Australia
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Santos T, Ventura T, Mateus J, Capela M, Lopes MDC. On the complexity of helical tomotherapy treatment plans. J Appl Clin Med Phys 2020; 21:107-118. [PMID: 32363800 PMCID: PMC7386195 DOI: 10.1002/acm2.12895] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 04/09/2020] [Accepted: 04/13/2020] [Indexed: 11/08/2022] Open
Abstract
PURPOSE Multiple metrics are proposed to characterize and compare the complexity of helical tomotherapy (HT) plans created for different treatment sites. METHODS A cohort composed of 208 HT plans from head and neck (105), prostate (51) and brain (52) tumor sites was considered. For each plan, 14 complexity metrics were calculated. Those metrics evaluate the percentage of leaves with small opening times or approaching the projection duration, the percentage of closed leaves, the amount of tongue-and-groove effect, and the overall modulation of the planned sinogram. To enable data visualization, an approach based on principal component analysis was followed to reduce the dataset dimensionality. This allowed the calculation of a global plan complexity score. The correlation between plan complexity and pretreatment verification results using the Spearman's rank correlation coefficients was investigated. RESULTS According to the global score, the most complex plans were the head and neck tumor cases, followed by the prostate and brain lesions irradiated with stereotactic technique. For almost all individual metrics, head and neck plans confirmed to be the plans with the highest complexity. Nevertheless, prostate cases had the highest percentage of leaves with an opening time approaching the projection duration, whereas the stereotactic brain plans had the highest percentage of closed leaves per projection. Significant correlations between some of the metrics and the pretreatment verification results were identified for the stereotactic brain group. CONCLUSIONS The proposed metrics and the global score demonstrated to be useful to characterize and quantify the complexity of HT plans of different treatment sites. The reported differences inter- and intra-group may be valuable to guide the planning process aiming at reducing uncertainties and harmonize planning strategies.
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Affiliation(s)
- Tania Santos
- Physics Department, University of Coimbra, Coimbra, Portugal.,Medical Physics Department, IPOCFG, E.P.E, Coimbra, Portugal
| | - Tiago Ventura
- Medical Physics Department, IPOCFG, E.P.E, Coimbra, Portugal
| | - Josefina Mateus
- Medical Physics Department, IPOCFG, E.P.E, Coimbra, Portugal
| | - Miguel Capela
- Medical Physics Department, IPOCFG, E.P.E, Coimbra, Portugal
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