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Xu Y, Jin W, Butkus M, De Ornelas M, Cyriac J, Studenski MT, Padgett K, Simpson G, Samuels S, Samuels M, Dogan N. Cone beam CT-based adaptive intensity modulated proton therapy assessment using automated planning for head-and-neck cancer. Radiat Oncol 2024; 19:13. [PMID: 38263237 PMCID: PMC10804468 DOI: 10.1186/s13014-024-02406-9] [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: 11/28/2022] [Accepted: 01/15/2024] [Indexed: 01/25/2024] Open
Abstract
BACKGROUND To assess the feasibility of CBCT-based adaptive intensity modulated proton therapy (IMPT) using automated planning for treatment of head and neck (HN) cancers. METHODS Twenty HN cancer patients who received radiotherapy and had pretreatment CBCTs were included in this study. Initial IMPT plans were created using automated planning software for all patients. Synthetic CTs (sCT) were then created by deforming the planning CT (pCT) to the pretreatment CBCTs. To assess dose calculation accuracy on sCTs, repeat CTs (rCTs) were deformed to the pretreatment CBCT obtained on the same day to create deformed rCT (rCTdef), serving as gold standard. The dose recalculated on sCT and on rCTdef were compared by using Gamma analysis. The accuracy of DIR generated contours was also assessed. To explore the potential benefits of adaptive IMPT, two sets of plans were created for each patient, a non-adapted IMPT plan and an adapted IMPT plan calculated on weekly sCT images. The weekly doses for non-adaptive and adaptive IMPT plans were accumulated on the pCT, and the accumulated dosimetric parameters of two sets were compared. RESULTS Gamma analysis of the dose recalculated on sCT and rCTdef resulted in a passing rate of 97.9% ± 1.7% using 3 mm/3% criteria. With the physician-corrected contours on the sCT, the dose deviation range of using sCT to estimate mean dose for the most organ at risk (OARs) can be reduced to (- 2.37%, 2.19%) as compared to rCTdef, while for V95 of primary or secondary CTVs, the deviation can be controlled within (- 1.09%, 0.29%). Comparison of the accumulated doses from the adaptive planning against the non-adaptive plans reduced mean dose to constrictors (- 1.42 Gy ± 2.79 Gy) and larynx (- 2.58 Gy ± 3.09 Gy). The reductions result in statistically significant reductions in the normal tissue complication probability (NTCP) of larynx edema by 7.52% ± 13.59%. 4.5% of primary CTVs, 4.1% of secondary CTVs, and 26.8% tertiary CTVs didn't meet the V95 > 95% constraint on non-adapted IMPT plans. All adaptive plans were able to meet the coverage constraint. CONCLUSION sCTs can be a useful tool for accurate proton dose calculation. Adaptive IMPT resulted in better CTV coverage, OAR sparing and lower NTCP for some OARs as compared with non-adaptive IMPT.
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Affiliation(s)
- Yihang Xu
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
- Department of Biomedical Engineering, College of Engineering, University of Miami, Coral Gables, FL, USA
| | - William Jin
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Michael Butkus
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Mariluz De Ornelas
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Jonathan Cyriac
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Matthew T Studenski
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Kyle Padgett
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Garrett Simpson
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Stuart Samuels
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Michael Samuels
- Department of Radiation Oncology, Banner MD Anderson Cancer Center, Gilbert, AZ, USA
| | - Nesrin Dogan
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA.
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Herrick M, Penfold S, Santos A, Hickson K. A systematic review of volumetric image guidance in proton therapy. Phys Eng Sci Med 2023; 46:963-975. [PMID: 37382744 PMCID: PMC10480289 DOI: 10.1007/s13246-023-01294-9] [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: 04/30/2023] [Accepted: 06/19/2023] [Indexed: 06/30/2023]
Abstract
In recent years, proton therapy centres have begun to shift from conventional 2D-kV imaging to volumetric imaging systems for image guided proton therapy (IGPT). This is likely due to the increased commercial interest and availability of volumetric imaging systems, as well as the shift from passively scattered proton therapy to intensity modulated proton therapy. Currently, there is no standard modality for volumetric IGPT, leading to variation between different proton therapy centres. This article reviews the reported clinical use of volumetric IGPT, as available in published literature, and summarises their utilisation and workflow where possible. In addition, novel volumetric imaging systems are also briefly summarised highlighting their potential benefits for IGPT and the challenges that need to be overcome before they can be used clinically.
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Affiliation(s)
- Mitchell Herrick
- Department of Radiation Oncology, Royal Adelaide Hospital, Adelaide, Australia.
- Department of Physics, University of Adelaide, Adelaide, Australia.
| | - Scott Penfold
- Department of Physics, University of Adelaide, Adelaide, Australia
- Australian Bragg Centre for Proton Therapy and Research, Adelaide, Australia
| | - Alexandre Santos
- Department of Radiation Oncology, Royal Adelaide Hospital, Adelaide, Australia
- Department of Physics, University of Adelaide, Adelaide, Australia
- Australian Bragg Centre for Proton Therapy and Research, Adelaide, Australia
| | - Kevin Hickson
- SA Medical Imaging, Adelaide, Australia
- University of South Australia, Allied Health & Human Performance, Adelaide, Australia
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Uh J, Wang C, Jordan JA, Pirlepesov F, Becksfort JB, Ates O, Krasin MJ, Hua CH. A hybrid method of correcting CBCT for proton range estimation with deep learning and deformable image registration. Phys Med Biol 2023; 68:10.1088/1361-6560/ace754. [PMID: 37442128 PMCID: PMC10846632 DOI: 10.1088/1361-6560/ace754] [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: 03/21/2023] [Accepted: 07/13/2023] [Indexed: 07/15/2023]
Abstract
Objective. This study aimed to develop a novel method for generating synthetic CT (sCT) from cone-beam CT (CBCT) of the abdomen/pelvis with bowel gas pockets to facilitate estimation of proton ranges.Approach. CBCT, the same-day repeat CT, and the planning CT (pCT) of 81 pediatric patients were used for training (n= 60), validation (n= 6), and testing (n= 15) of the method. The proposed method hybridizes unsupervised deep learning (CycleGAN) and deformable image registration (DIR) of the pCT to CBCT. The CycleGAN and DIR are respectively applied to generate the geometry-weighted (high spatial-frequency) and intensity-weighted (low spatial-frequency) components of the sCT, thereby each process deals with only the component weighted toward its strength. The resultant sCT is further improved in bowel gas regions and other tissues by iteratively feeding back the sCT to adjust incorrect DIR and by increasing the contribution of the deformed pCT in regions of accurate DIR.Main results. The hybrid sCT was more accurate than deformed pCT and CycleGAN-only sCT as indicated by the smaller mean absolute error in CT numbers (28.7 ± 7.1 HU versus 38.8 ± 19.9 HU/53.2 ± 5.5 HU;P≤ 0.012) and higher Dice similarity of the internal gas regions (0.722 ± 0.088 versus 0.180 ± 0.098/0.659 ± 0.129;P≤ 0.002). Accordingly, the hybrid method resulted in more accurate proton range for the beams intersecting gas pockets (11 fields in 6 patients) than the individual methods (the 90th percentile error in 80% distal fall-off, 1.8 ± 0.6 mm versus 6.5 ± 7.8 mm/3.7 ± 1.5 mm;P≤ 0.013). The gamma passing rates also showed a significant dosimetric advantage by the hybrid method (99.7 ± 0.8% versus 98.4 ± 3.1%/98.3 ± 1.8%;P≤ 0.007).Significance. The hybrid method significantly improved the accuracy of sCT and showed promises in CBCT-based proton range verification and adaptive replanning of abdominal/pelvic proton therapy even when gas pockets are present in the beam path.
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Affiliation(s)
- Jinsoo Uh
- Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, United States of America
| | - Chuang Wang
- Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, United States of America
| | - Jacob A Jordan
- Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, United States of America
- College of Medicine, The University of Tennessee Health Science Center, Memphis, TN, United States of America
| | - Fakhriddin Pirlepesov
- Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, United States of America
| | - Jared B Becksfort
- Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, United States of America
| | - Ozgur Ates
- Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, United States of America
| | - Matthew J Krasin
- Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, United States of America
| | - Chia-Ho Hua
- Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, United States of America
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Allen C, Yeo AU, Hardcastle N, Franich RD. Evaluating synthetic computed tomography images for adaptive radiotherapy decision making in head and neck cancer. Phys Imaging Radiat Oncol 2023; 27:100478. [PMID: 37655123 PMCID: PMC10465931 DOI: 10.1016/j.phro.2023.100478] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 07/19/2023] [Accepted: 07/22/2023] [Indexed: 09/02/2023] Open
Abstract
Background and purpose Adaptive radiotherapy (ART) decision-making benefits from dosimetric information to supplement image inspection when assessing the significance of anatomical changes. This study evaluated a dosimetry-based clinical decision workflow for ART utilizing deformable registration of the original planning computed tomography (CT) image to the daily Cone Beam CT (CBCT) to replace the need for a replan CT for dose estimation. Materials and methods We used 12 retrospective Head & Neck patient cases having a ground truth - a replan CT (rCT) in response to anatomical changes apparent in the daily CBCT - to evaluate the accuracy of dosimetric assessment conducted on synthetic CTs (sCT) generated by deforming the original planning CT Hounsfield Units to the daily CBCT anatomy.The original plan was applied to the sCT and dosimetric accuracy of the sCT was assessed by analyzing plan objectives for targets and organs-at-risk compared to calculations on the ground-truth rCT. Three commercial DIR algorithms were compared. Results For the best-performing algorithms, the majority of dose metrics calculated on the sCTs differed by less than 4 Gy (5.7% of 70 Gy prescription dose). An uncertainty of ±2.5 Gy (3.6% of 70 Gy prescription) is recommended as a conservative tolerance when evaluating dose metrics on sCTs for head and neck. Conclusions Synthetic CTs present a valuable addition to the adaptive radiotherapy workflow, and synthetic CT dose estimates can be effectively used in addition to the current practice of visually inspecting the overlay of the planning CT and CBCT to assess the significance of anatomical change.
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Affiliation(s)
- Caitlin Allen
- Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- School of Science, RMIT University, Melbourne, Victoria, Australia
| | - Adam U. Yeo
- Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- School of Science, RMIT University, Melbourne, Victoria, Australia
| | - Nicholas Hardcastle
- Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Centre for Medical Radiation Physics, University of Wollongong, NSW, Australia
| | - Rick D. Franich
- Physical Sciences, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- School of Science, RMIT University, Melbourne, Victoria, Australia
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Szmul A, Taylor S, Lim P, Cantwell J, Moreira I, Zhang Y, D’Souza D, Moinuddin S, Gaze MN, Gains J, Veiga C. Deep learning based synthetic CT from cone beam CT generation for abdominal paediatric radiotherapy. Phys Med Biol 2023; 68:105006. [PMID: 36996837 PMCID: PMC10160738 DOI: 10.1088/1361-6560/acc921] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 03/13/2023] [Accepted: 03/30/2023] [Indexed: 04/01/2023]
Abstract
Objective. Adaptive radiotherapy workflows require images with the quality of computed tomography (CT) for re-calculation and re-optimisation of radiation doses. In this work we aim to improve the quality of on-board cone beam CT (CBCT) images for dose calculation using deep learning.Approach. We propose a novel framework for CBCT-to-CT synthesis using cycle-consistent Generative Adversarial Networks (cycleGANs). The framework was tailored for paediatric abdominal patients, a challenging application due to the inter-fractional variability in bowel filling and small patient numbers. We introduced to the networks the concept of global residuals only learning and modified the cycleGAN loss function to explicitly promote structural consistency between source and synthetic images. Finally, to compensate for the anatomical variability and address the difficulties in collecting large datasets in the paediatric population, we applied a smart 2D slice selection based on the common field-of-view (abdomen) to our imaging dataset. This acted as a weakly paired data approach that allowed us to take advantage of scans from patients treated for a variety of malignancies (thoracic-abdominal-pelvic) for training purposes. We first optimised the proposed framework and benchmarked its performance on a development dataset. Later, a comprehensive quantitative evaluation was performed on an unseen dataset, which included calculating global image similarity metrics, segmentation-based measures and proton therapy-specific metrics.Main results. We found improved performance for our proposed method, compared to a baseline cycleGAN implementation, on image-similarity metrics such as Mean Absolute Error calculated for a matched virtual CT (55.0 ± 16.6 HU proposed versus 58.9 ± 16.8 HU baseline). There was also a higher level of structural agreement for gastrointestinal gas between source and synthetic images measured using the dice similarity coefficient (0.872 ± 0.053 proposed versus 0.846 ± 0.052 baseline). Differences found in water-equivalent thickness metrics were also smaller for our method (3.3 ± 2.4% proposed versus 3.7 ± 2.8% baseline).Significance. Our findings indicate that our innovations to the cycleGAN framework improved the quality and structure consistency of the synthetic CTs generated.
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Affiliation(s)
- Adam Szmul
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, United Kingdom
| | - Sabrina Taylor
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Pei Lim
- Department of Oncology, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Jessica Cantwell
- Radiotherapy, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Isabel Moreira
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Ying Zhang
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Derek D’Souza
- Radiotherapy Physics Services, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Syed Moinuddin
- Radiotherapy, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Mark N. Gaze
- Department of Oncology, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Jennifer Gains
- Department of Oncology, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Catarina Veiga
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
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6
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Ma C, Tian Z, Wang R, Feng Z, Jiang F, Hu Q, Yang F, Shi A, Wu H. A prediction model for dosimetric-based lung adaptive radiotherapy. Med Phys 2022; 49:6319-6333. [PMID: 35649103 DOI: 10.1002/mp.15714] [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: 11/09/2021] [Revised: 03/22/2022] [Accepted: 05/01/2022] [Indexed: 11/08/2022] Open
Abstract
PURPOSE Anatomical changes occurred during the treatment course of radiation therapy for lung cancer patients may introduce clinically unacceptable dosimetric deviations from the planned dose. Adaptive radiotherapy (ART) can compensate these dosimetric deviations in subsequent treatments via plan adaption. Determining whether and when to trigger plan adaption during the treatment course is essential to the effectiveness and efficiency of ART. In this study, we aimed to develop a prediction model as an auxiliary decision-making tool for lung ART to identify the patients with intrathoracic anatomical changes that would potentially benefit from the plan adaptions during the treatment course. METHODS Seventy-one pairs of weekly cone-beam computer tomography (CBCT) and planning CT (pCT) from 17 advanced non-small cell lung cancer patients were enrolled in this study. To assess the dosimetric impacts brought by anatomical changes observed on each CBCT, dose distribution of the original treatment plan on the CBCT anatomy was calculated on a virtual CT generated by deforming the corresponding pCT to the CBCT, and compared to that of the original plan. A replan was deemed needed for the CBCT anatomy once the recalculated dose distribution violated our dosimetric-based trigger criteria. A three-dimensional region of significant anatomical changes (region of interest, ROI) between each CBCT and the corresponding pCT was identified and 16 morphological features of the ROI were extracted. Additionally, eight features from the overlapped volume histograms (OVHs) of patient anatomy were extracted for each patient to characterize the patient specific anatomy. Based on the 24 extracted features and the evaluated replanning needs of the pCT-CBCT pairs, a nonlinear supporting vector machine was used to build a prediction model to identify the anatomical changes on CBCTs that would trigger plan adaptions. The most relevant features were selected using the sequential backward selection (SBS) algorithm and a shuffling-and-splitting validation scheme was used for model evaluation. RESULTS Fifty-Five CBCT-pCT pairs were identified of having a ROI, among which 21 CBCT anatomies required plan adaptions. For these 21 positive cases, statistically significant improvements in the sparing of lung, esophagus and spinal cord were achieved by plan adaptions. A high model performance of 0.929 AUC and 0.851 accuracy was achieved with six selected features including five ROI shape features and one OVH feature. Without involving the OVH features in the feature selection process, the mean AUC and accuracy of the model significantly decreased to 0.826 and 0.779, respectively. Further investigation showed that poor prediction performance with AUC of 0.76 was achieved by the univariate model in solving this binary classification task. CONCLUSION We built a prediction model based on the features of patient anatomy and the anatomical changes captured by on-treatment CBCT imaging to trigger plan adaption for lung cancer patients. This model effectively associated the anatomical changes with the dosimetric impacts for lung ART. This model can be a promising tool to assist the clinicians in making decisions for plan adaptions during the treatment courses. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Chaoqiong Ma
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, 100142, China.,Department of Radiation Oncology, Emory University, Atlanta, GA, 30322, USA
| | - Zhen Tian
- Department of Radiation Oncology, Emory University, Atlanta, GA, 30322, USA.,Department of Radiation & Cellular Oncology, University of Chicago, Chicago, IL, 60637, USA
| | - Ruoxi Wang
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, 100142, China
| | - Zhongsu Feng
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, 100142, China
| | - Fan Jiang
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, 100142, China
| | - Qiaoqiao Hu
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, 100142, China
| | - Fang Yang
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, 100142, China.,Department of Oncology, Daqing Oilfield General Hospital, Daqing, 163001, 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
| | - Hao Wu
- Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing, 100142, China.,Institute of Medical Technology, Peking University Health Science Center, Beijing, 100191, China
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Li H, Hrinivich WT, Chen H, Sheikh K, Ho MW, Ger R, Liu D, Hales RK, Voong KR, Halthore A, Deville C. Evaluating Proton Dose and Associated Range Uncertainty Using Daily Cone-Beam CT. Front Oncol 2022; 12:830981. [PMID: 35449577 PMCID: PMC9016186 DOI: 10.3389/fonc.2022.830981] [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] [Received: 12/07/2021] [Accepted: 03/02/2022] [Indexed: 11/13/2022] Open
Abstract
Purpose This study aimed to quantitatively evaluate the range uncertainties that arise from daily cone-beam CT (CBCT) images for proton dose calculation compared to CT using a measurement-based technique. Methods For head and thorax phantoms, wedge-shaped intensity-modulated proton therapy (IMPT) treatment plans were created such that the gradient of the wedge intersected and was measured with a 2D ion chamber array. The measured 2D dose distributions were compared with 2D dose planes extracted from the dose distributions using the IMPT plan calculated on CT and CBCT. Treatment plans of a thymoma cancer patient treated with breath-hold (BH) IMPT were recalculated on 28 CBCTs and 9 CTs, and the resulting dose distributions were compared. Results The range uncertainties for the head phantom were determined to be 1.2% with CBCT, compared to 0.5% for CT, whereas the range uncertainties for the thorax phantom were 2.1% with CBCT, compared to 0.8% for CT. The doses calculated on CBCT and CT were similar with similar anatomy changes. For the thymoma patient, the primary source of anatomy change was the BH uncertainty, which could be up to 8 mm in the superior-inferior (SI) direction. Conclusion We developed a measurement-based range uncertainty evaluation method with high sensitivity and used it to validate the accuracy of CBCT-based range and dose calculation. Our study demonstrated that the CBCT-based dose calculation could be used for daily dose validation in selected proton patients.
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Affiliation(s)
- Heng Li
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - William T Hrinivich
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Hao Chen
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Khadija Sheikh
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Meng Wei Ho
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Rachel Ger
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Dezhi Liu
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Russell Kenneth Hales
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Khinh Ranh Voong
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Aditya Halthore
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Curtiland Deville
- Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
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8
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Liu Y, Chen X, Zhu J, Yang B, Wei R, Xiong R, Quan H, Liu Y, Dai J, Men K. A two-step method to improve image quality of CBCT with phantom-based supervised and patient-based unsupervised learning strategies. Phys Med Biol 2022; 67. [PMID: 35354124 DOI: 10.1088/1361-6560/ac6289] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 03/30/2022] [Indexed: 11/12/2022]
Abstract
Objective.In this study, we aimed to develop deep learning framework to improve cone-beam computed tomography (CBCT) image quality for adaptive radiation therapy (ART) applications.Approach.Paired CBCT and planning CT images of 2 pelvic phantoms and 91 patients (15 patients for testing) diagnosed with prostate cancer were included in this study. First, well-matched images of rigid phantoms were used to train a U-net, which is the supervised learning strategy to reduce serious artifacts. Second, the phantom-trained U-net generated intermediate CT images from the patient CBCT images. Finally, a cycle-consistent generative adversarial network (CycleGAN) was trained with intermediate CT images and deformed planning CT images, which is the unsupervised learning strategy to learn the style of the patient images for further improvement. When testing or applying the trained model on patient CBCT images, the intermediate CT images were generated from the original CBCT image by U-net, and then the synthetic CT images were generated by the generator of CycleGAN with intermediate CT images as input. The performance was compared with conventional methods (U-net/CycleGAN alone trained with patient images) on the test set.Results.The proposed two-step method effectively improved the CBCT image quality to the level of CT scans. It outperformed conventional methods for region-of-interest contouring and HU calibration, which are important to ART applications. Compared with the U-net alone, it maintained the structure of CBCT. Compared with CycleGAN alone, our method improved the accuracy of CT number and effectively reduced the artifacts, making it more helpful for identifying the clinical target volume.Significance.This novel two-step method improves CBCT image quality by combining phantom-based supervised and patient-based unsupervised learning strategies. It has immense potential to be integrated into the ART workflow to improve radiotherapy accuracy.
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Affiliation(s)
- Yuxiang Liu
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, People's Republic of China.,School of Physics and Technology, Wuhan University, Wuhan 430072, People's Republic of China
| | - Xinyuan Chen
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, People's Republic of China
| | - Ji Zhu
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, People's Republic of China
| | - Bining Yang
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, People's Republic of China
| | - Ran Wei
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, People's Republic of China
| | - Rui Xiong
- School of Physics and Technology, Wuhan University, Wuhan 430072, People's Republic of China
| | - Hong Quan
- School of Physics and Technology, Wuhan University, Wuhan 430072, People's Republic of China
| | - Yueping Liu
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, People's Republic of China
| | - Jianrong Dai
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, People's Republic of China
| | - Kuo Men
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, People's Republic of China
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Abstract
Image registration is an important research topic in medical image-guided therapy, which is dedicated to registering the high-dose imaging sequences with low-dose/faster means. Registering computer tomography (CT) scanning sequences with cone beam computer tomography (CBCT) scanning sequences is a typical application and has been widely used in CBCT-guided radiotherapy. The main problem is the difference in image clarity of these two image sequences. To solve this problem, for the single projection image sequence matching tasks encountered in medical practice, a novel local quality based curved section encoding strategy is proposed in this paper, which is called the high-quality curved section (HQCS). As an optimized cross-section regularly encoded along the sequence of image, this curved section could be used in order to solve the matching problem. Referencing the independent ground truth provided by medical image physicians, with an experiment combined with the four most widely used indicators used on image registration, matching performance of HQCS on CT/CBCT datasets was tested with varying clarity. Experimental results show that the proposed HQCS can register the CT/CBCT effectively and outperforms the commonly used methods. Specifically, the proposed HQCS has low time complexity and higher scalability, which indicates that the application enhanced the task of diagnosis.
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10
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Stanforth A, Lin L, Beitler JJ, Janopaul-Naylor JR, Chang CW, Press RH, Patel SA, Zhao J, Eaton B, Schreibmann EE, Jung J, Bohannon D, Liu T, Yang X, McDonald MW, Zhou J. Onboard cone-beam CT-based replan evaluation for head and neck proton therapy. J Appl Clin Med Phys 2022; 23:e13550. [PMID: 35128788 PMCID: PMC9121026 DOI: 10.1002/acm2.13550] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 12/08/2021] [Accepted: 01/20/2022] [Indexed: 11/23/2022] Open
Abstract
Purpose Quality assurance computed tomography (QACT) is the current clinical practice in proton therapy to evaluate the needs for replan. QACT could falsely indicate replan because of setup issues that would be solved on the treatment machine. Deforming the treatment planning CT (TPCT) to the pretreatment CBCT may eliminate this issue. We investigated the performance of replan evaluation based on deformed TPCT (TPCTdir) for proton head and neck (H&N) therapy. Methods and materials Twenty‐eight H&N datasets along with pretreatment CBCT and QACT were used to validate the method. The changes in body volume were analyzed between the no‐replan and replan groups. The dose on the TPCTdir, the deformed QACT (QACTdir), and the QACT were calculated by applying the clinical plans to these image sets. Dosimetric parameters’ changes, including ΔD95, ΔDmean, and ΔD1 for the clinical target volumes (CTVs) were calculated. Receiver operating characteristic curves for replan evaluation based on ΔD95 on QACT and TPCTdir were calculated, using ΔD95 on QACTdir as the reference. A threshold for replan based on ΔD95 on TPCTdir is proposed. The specificities for the proposed method were calculated. Results The changes in the body contour were 95.8 ± 83.8 cc versus 305.0 ± 235.0 cc (p < 0.01) for the no‐replan and replan groups, respectively. The ΔD95, ΔDmean, and ΔD1 are all comparable for all the evaluations. The differences between TPCTdir and QACTdir evaluations were 0.30% ± 0.86%, 0.00 ± 0.22 Gy, and −0.17 ± 0.61 Gy for CTV ΔD95, ΔDmean, and ΔD1, respectively. The corresponding differences between the QACT and QACTdir were 0.12% ± 1.1%, 0.02 ± 0.32 Gy, and −0.01 ± 0.71 Gy. CTV ΔD95 > 2.6% in TPCTdir was chosen as the threshold to trigger QACT/replan. The corresponding specificity was 94% and 98% for the clinical practice and the proposed method, respectively. Conclusions The replan evaluation based on TPCTdir provides better specificity than that based on the QACT.
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Affiliation(s)
- Alexander Stanforth
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Liyong Lin
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Jonathan J Beitler
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - James R Janopaul-Naylor
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Chih-Wei Chang
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Robert H Press
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA.,New York Proton Center, New York, New York, USA
| | - Sagar A Patel
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Jennifer Zhao
- Department of Pre-Medicine, Cornell University, New York, New York, USA
| | - Bree Eaton
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Eduard E Schreibmann
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - James Jung
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Duncan Bohannon
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA.,Medical Physics Program, Georgia institute of Technology, Atlanta, Georgia, USA
| | - Tian Liu
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Xiaofeng Yang
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Mark W McDonald
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
| | - Jun Zhou
- Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, Georgia, USA
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11
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Gui LG, Shi M, Li J. Cone beam computed tomography and image registration based on target area for stereotactic body radiation therapy of lung cancer. JOURNAL OF RADIATION RESEARCH AND APPLIED SCIENCES 2021. [DOI: 10.1080/16878507.2021.1981754] [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)
- Long-Gang Gui
- Radiotherapy Center, Northern Jiangsu People’s Hospital, Yangzhou, China
| | - Miao Shi
- Radiotherapy Center, Northern Jiangsu People’s Hospital, Yangzhou, China
| | - Jun Li
- Radiotherapy Center, Northern Jiangsu People’s Hospital, Yangzhou, China
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12
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Schmitz H, Rabe M, Janssens G, Bondesson D, Rit S, Parodi K, Belka C, Dinkel J, Kurz C, Kamp F, Landry G. Validation of proton dose calculation on scatter corrected 4D cone beam computed tomography using a porcine lung phantom. Phys Med Biol 2021; 66. [PMID: 34293737 DOI: 10.1088/1361-6560/ac16e9] [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: 05/06/2021] [Accepted: 07/22/2021] [Indexed: 12/25/2022]
Abstract
Proton therapy treatment for lungs remains challenging as images enabling the detection of inter- and intra-fractional motion, which could be used for proton dose adaptation, are not readily available. 4D computed tomography (4DCT) provides high image quality but is rarely available in-room, while in-room 4D cone beam computed tomography (4DCBCT) suffers from image quality limitations stemming mostly from scatter detection. This study investigated the feasibility of using virtual 4D computed tomography (4DvCT) as a prior for a phase-per-phase scatter correction algorithm yielding a 4D scatter corrected cone beam computed tomography image (4DCBCTcor), which can be used for proton dose calculation. 4DCT and 4DCBCT scans of a porcine lung phantom, which generated reproducible ventilation, were acquired with matching breathing patterns. Diffeomorphic Morphons, a deformable image registration algorithm, was used to register the mid-position 4DCT to the mid-position 4DCBCT and yield a 4DvCT. The 4DCBCT was reconstructed using motion-aware reconstruction based on spatial and temporal regularization (MA-ROOSTER). Successively for each phase, digitally reconstructed radiographs of the 4DvCT, simulated without scatter, were exploited to correct scatter in the corresponding CBCT projections. The 4DCBCTcorwas then reconstructed with MA-ROOSTER using the corrected CBCT projections and the same settings and deformation vector fields as those already used for reconstructing the 4DCBCT. The 4DCBCTcorand the 4DvCT were evaluated phase-by-phase, performing proton dose calculations and comparison to those of a ground truth 4DCT by means of dose-volume-histograms (DVH) and gamma pass-rates (PR). For accumulated doses, DVH parameters deviated by at most 1.7% in the 4DvCT and 2.0% in the 4DCBCTcorcase. The gamma PR for a (2%, 2 mm) criterion with 10% threshold were at least 93.2% (4DvCT) and 94.2% (4DCBCTcor), respectively. The 4DCBCTcortechnique enabled accurate proton dose calculation, which indicates the potential for applicability to clinical 4DCBCT scans.
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Affiliation(s)
- Henning Schmitz
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Moritz Rabe
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | | | - David Bondesson
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Simon Rit
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, F-69373, LYON, France
| | - Katia Parodi
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching (Munich), Germany
| | - Claus Belka
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Julien Dinkel
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Christopher Kurz
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.,Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching (Munich), Germany
| | - Florian Kamp
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.,Department of Radiation Oncology, University Hospital Cologne, Cologne, Germany
| | - Guillaume Landry
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.,Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching (Munich), Germany
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13
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Neppl S, Kurz C, Köpl D, Yohannes I, Schneider M, Bondesson D, Rabe M, Belka C, Dietrich O, Landry G, Parodi K, Kamp F. Measurement-based range evaluation for quality assurance of CBCT-based dose calculations in adaptive proton therapy. Med Phys 2021; 48:4148-4159. [PMID: 34032301 DOI: 10.1002/mp.14995] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 04/08/2021] [Accepted: 05/10/2021] [Indexed: 12/30/2022] Open
Abstract
PURPOSE The implementation of volumetric in-room imaging for online adaptive radiotherapy makes extensive testing of this image data for treatment planning necessary. Especially for proton beams the higher sensitivity to stopping power properties of the tissue results in more stringent requirements. Current approaches mainly focus on recalculation of the plans on the new image data, lacking experimental verification, and ignoring the impact on the plan re-optimization process. The aim of this study was to use gel and film dosimetry coupled with a three-dimensional (3D) printed head phantom (based on the planning CT of the patient) for 3D range verification of intensity-corrected cone beam computed tomography (CBCT) image data for adaptive proton therapy. METHODS Single field uniform dose pencil beam scanning proton plans were optimized for three different patients on the patients' planning CT (planCT) and the patients' intensity-corrected CBCT (scCBCT) for the same target volume using the same optimization constraints. The CBCTs were corrected on projection level using the planCT as a prior. The dose optimized on planCT and recalculated on scCBCT was compared in terms of proton range differences (80% distal fall-off, recalculation). Moreover, the dose distribution resulting from recalculation of the scCBCT-optimized plan on the planCT and the original planCT dose distribution were compared (simulation). Finally, the two plans of each patient were irradiated on the corresponding patient-specific 3D printed head phantom using gel dosimetry inserts for one patient and film dosimetry for all three patients. Range differences were extracted from the measured dose distributions. The measured and the simulated range differences were corrected for range differences originating from the initial plans and evaluated. RESULTS The simulation approach showed high agreement with the standard recalculation approach. The median values of the range differences of these two methods agreed within 0.1 mm and the interquartile ranges (IQRs) within 0.3 mm for all three patients. The range differences of the film measurement were accurately matching with the simulation approach in the film plane. The median values of these range differences deviated less than 0.1 mm and the IQRs less than 0.4 mm. For the full 3D evaluation of the gel range differences, the median value and IQR matched those of the simulation approach within 0.7 and 0.5 mm, respectively. scCBCT- and planCT-based dose distributions were found to have a range agreement better than 3 mm (median and IQR) for all considered scenarios (recalculation, simulation, and measurement). CONCLUSIONS The results of this initial study indicate that an online adaptive proton workflow based on scatter-corrected CBCT image data for head irradiations is feasible. The novel presented measurement- and simulation-based method was shown to be equivalent to the standard literature recalculation approach. Additionally, it has the capability to catch effects of image differences on the treatment plan optimization. This makes the measurement-based approach particularly interesting for quality assurance of CBCT-based online adaptive proton therapy. The observed uncertainties could be kept within those of the registration and positioning. The proposed validation could also be applied for other alternative in-room images, e.g. for MR-based pseudoCTs.
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Affiliation(s)
- Sebastian Neppl
- Department of Radiation Oncology, University Hospital, LMU Munich, 81377, Munich, Germany.,Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU Munich), 85748, Garching bei München, Germany
| | - Christopher Kurz
- Department of Radiation Oncology, University Hospital, LMU Munich, 81377, Munich, Germany.,Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU Munich), 85748, Garching bei München, Germany
| | - Daniel Köpl
- Rinecker Proton Therapy Center, 81371, Munich, Germany
| | | | - Moritz Schneider
- Department of Radiology, University Hospital, LMU Munich, 81377, Munich, Germany.,Comprehensive Pneumology Center Munich (CPC-M), German Center for Lung Research (DZL), 81377, Munich, Germany
| | - David Bondesson
- Department of Radiology, University Hospital, LMU Munich, 81377, Munich, Germany.,Comprehensive Pneumology Center Munich (CPC-M), German Center for Lung Research (DZL), 81377, Munich, Germany
| | - Moritz Rabe
- Department of Radiation Oncology, University Hospital, LMU Munich, 81377, Munich, Germany.,Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU Munich), 85748, Garching bei München, Germany
| | - Claus Belka
- Department of Radiation Oncology, University Hospital, LMU Munich, 81377, Munich, Germany.,German Cancer Consortium (DKTK), Partner site Munich, 81377, Munich, Germany
| | - Olaf Dietrich
- Department of Radiology, University Hospital, LMU Munich, 81377, Munich, Germany
| | - Guillaume Landry
- Department of Radiation Oncology, University Hospital, LMU Munich, 81377, Munich, Germany.,Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU Munich), 85748, Garching bei München, Germany
| | - Katia Parodi
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München (LMU Munich), 85748, Garching bei München, Germany
| | - Florian Kamp
- Department of Radiation Oncology, University Hospital, LMU Munich, 81377, Munich, Germany
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14
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Xu Y, Diwanji T, Brovold N, Butkus M, Padgett KR, Schmidt RM, King A, Dal Pra A, Abramowitz M, Pollack A, Dogan N. Assessment of daily dose accumulation for robustly optimized intensity modulated proton therapy treatment of prostate cancer. Phys Med 2021; 81:77-85. [PMID: 33445124 DOI: 10.1016/j.ejmp.2020.11.035] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 11/02/2020] [Accepted: 11/28/2020] [Indexed: 12/30/2022] Open
Abstract
PURPOSE To implement a daily CBCT based dose accumulation technique in order to assess ideal robust optimization (RO) parameters for IMPT treatment of prostate cancer. METHODS Ten prostate cancer patients previously treated with VMAT and having daily CBCT were included. First, RO-IMPT plans were created with ± 3 mm and ± 5 mm patient setup and ± 3% proton range uncertainties, respectively. Second, the planning CT (pCT) was deformably registered to the CBCT to create a synthetic CT (sCT). Both daily and weekly sampling strategies were employed to determine optimal dose accumulation frequency. Doses were recalculated on sCTs for both ± 3 mm/±3% and ± 5 mm/±3% uncertainties and were accumulated back to the pCT. Accumulated doses generated from ± 3 mm/±3% and ± 5 mm/±3% RO-IMPT plans were evaluated using the clinical dose volume constraints for CTV, bladder, and rectum. RESULTS Daily accumulated dose based on both ± 3mm/±3% and ±5 mm/±3% uncertainties for RO-IMPT plans resulted in satisfactory CTV coverage (RO-IMPT3mm/3% CTVV95 = 99.01 ± 0.87% vs. RO-IMPT5mm/3% CTVV95 = 99.81 ± 0.2%, P = 0.002). However, the accumulated dose based on ± 3 mm/3% RO-IMPT plans consistently provided greater OAR sparing than ±5 mm/±3% RO-IMPT plans (RO-IMPT3mm/3% rectumV65Gy = 2.93 ± 2.39% vs. RO-IMPT5mm/3% rectumV65Gy = 4.38 ± 3%, P < 0.01; RO-IMPT3mm/3% bladderV65Gy = 5.2 ± 7.12% vs. RO-IMPT5mm/3% bladderV65Gy = 7.12 ± 9.59%, P < 0.01). The gamma analysis showed high dosimetric agreement between weekly and daily accumulated dose distributions. CONCLUSIONS This study demonstrated that for RO-IMPT optimization, ±3mm/±3% uncertainty is sufficient to create plans that meet desired CTV coverage while achieving superior sparing to OARs when compared with ± 5 mm/±3% uncertainty. Furthermore, weekly dose accumulation can accurately estimate the overall dose delivered to prostate cancer patients.
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Affiliation(s)
- Yihang Xu
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Tejan Diwanji
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Nellie Brovold
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Michael Butkus
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Kyle R Padgett
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Ryder M Schmidt
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Adam King
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Alan Dal Pra
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Matt Abramowitz
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Alan Pollack
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Nesrin Dogan
- Department of Radiation Oncology, University of Miami Miller School of Medicine, Miami, FL, USA.
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15
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Synthetic CT in assessment of anatomical and dosimetric variations in radiotherapy - procedure validation. POLISH JOURNAL OF MEDICAL PHYSICS AND ENGINEERING 2020. [DOI: 10.2478/pjmpe-2020-0022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Abstract
Introduction: One of many procedures to control the quality of radiotherapy is daily imaging of the patient’s anatomy. The CBCT (Cone Beam Computed Tomography) plays an important role in patient positioning, and dose delivery monitoring. Nowadays, CBCT is a baseline for the calculation of fraction and total dose. Thus, it provides the potential for more comprehensive monitoring of the delivered dose and adaptive radiotherapy. However, due to the poor quality and the presence of numerous artifacts, the replacement of the CBCT image with the corrected one is desired for dose calculation. The aim of the study was to validate a method for generating a synthetic CT image based on deformable image registration.
Material and methods: A Head & Torso Freepoint phantom, model 002H9K (Computerized Imaging Reference Systems, Norfolk, USA) with inserts was imaged with CT (Computed Tomography). Then, contouring and treatment plan were created in Eclipse (Varian Medical Systems, Palo Alto, CA, USA) treatment planning system. The phantom was scanned again with the CBCT. The planning CT was registered and deformed to the CBCT, resulting in a synthetic CT in Velocity software (Varian Medical Systems, Palo Alto, CA, USA). The dose distribution was recalculated based on the created CT image.
Results: Differences in structure volumes and dose statistics calculated both on CT and synthetic CT were evaluated. Discrepancies between the original and delivered plan from 0.0 to 2.5% were obtained. Dose comparison was performed on the DVH (Dose-Volume Histogram) for all delineated inserts.
Conclusions: Our findings suggest the potential utility of deformable registration and synthetic CT for providing dose reconstruction. This study reports on the limitation of the procedure related to the limited length of the CBCT volume and deformable fusion inaccuracies.
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Anthropomorphic lung phantom based validation of in-room proton therapy 4D-CBCT image correction for dose calculation. Z Med Phys 2020; 32:74-84. [PMID: 33248812 PMCID: PMC9948846 DOI: 10.1016/j.zemedi.2020.09.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 09/18/2020] [Accepted: 09/23/2020] [Indexed: 12/27/2022]
Abstract
PURPOSE Ventilation-induced tumour motion remains a challenge for the accuracy of proton therapy treatments in lung patients. We investigated the feasibility of using a 4D virtual CT (4D-vCT) approach based on deformable image registration (DIR) and motion-aware 4D CBCT reconstruction (MA-ROOSTER) to enable accurate daily proton dose calculation using a gantry-mounted CBCT scanner tailored to proton therapy. METHODS Ventilation correlated data of 10 breathing phases were acquired from a porcine ex-vivo functional lung phantom using CT and CBCT. 4D-vCTs were generated by (1) DIR of the mid-position 4D-CT to the mid-position 4D-CBCT (reconstructed with the MA-ROOSTER) using a diffeomorphic Morphons algorithm and (2) subsequent propagation of the obtained mid-position vCT to the individual 4D-CBCT phases. Proton therapy treatment planning was performed to evaluate dose calculation accuracy of the 4D-vCTs. A robust treatment plan delivering a nominal dose of 60Gy was generated on the average intensity image of the 4D-CT for an approximated internal target volume (ITV). Dose distributions were then recalculated on individual phases of the 4D-CT and the 4D-vCT based on the optimized plan. Dose accumulation was performed for 4D-vCT and 4D-CT using DIR of each phase to the mid position, which was chosen as reference. Dose based on the 4D-vCT was then evaluated against the dose calculated on 4D-CT both, phase-by-phase as well as accumulated, by comparing dose volume histogram (DVH) values (Dmean, D2%, D98%, D95%) for the ITV, and by a 3D-gamma index analysis (global, 3%/3mm, 5Gy, 20Gy and 30Gy dose thresholds). RESULTS Good agreement was found between the 4D-CT and 4D-vCT-based ITV-DVH curves. The relative differences ((CT-vCT)/CT) between accumulated values of ITV Dmean, D2%, D95% and D98% for the 4D-CT and 4D-vCT-based dose distributions were -0.2%, 0.0%, -0.1% and -0.1%, respectively. Phase specific values varied between -0.5% and 0.2%, -0.2% and 0.5%, -3.5% and 1.5%, and -5.7% and 2.3%. The relative difference of accumulated Dmean over the lungs was 2.3% and Dmean for the phases varied between -5.4% and 5.8%. The gamma pass-rates with 5Gy, 20Gy and 30Gy thresholds for the accumulated doses were 96.7%, 99.6% and 99.9%, respectively. Phase-by-phase comparison yielded pass-rates between 86% and 97%, 88% and 98%, and 94% and 100%. CONCLUSIONS Feasibility of the suggested 4D-vCT workflow using proton therapy specific imaging equipment was shown. Results indicate the potential of the method to be applied for daily 4D proton dose estimation.
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Farr JB, Moyers MF, Allgower CE, Bues M, Hsi WC, Jin H, Mihailidis DN, Lu HM, Newhauser WD, Sahoo N, Slopsema R, Yeung D, Zhu XR. Clinical commissioning of intensity-modulated proton therapy systems: Report of AAPM Task Group 185. Med Phys 2020; 48:e1-e30. [PMID: 33078858 DOI: 10.1002/mp.14546] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 08/17/2020] [Accepted: 08/18/2020] [Indexed: 02/06/2023] Open
Abstract
Proton therapy is an expanding radiotherapy modality in the United States and worldwide. With the number of proton therapy centers treating patients increasing, so does the need for consistent, high-quality clinical commissioning practices. Clinical commissioning encompasses the entire proton therapy system's multiple components, including the treatment delivery system, the patient positioning system, and the image-guided radiotherapy components. Also included in the commissioning process are the x-ray computed tomography scanner calibration for proton stopping power, the radiotherapy treatment planning system, and corresponding portions of the treatment management system. This commissioning report focuses exclusively on intensity-modulated scanning systems, presenting details of how to perform the commissioning of the proton therapy and ancillary systems, including the required proton beam measurements, treatment planning system dose modeling, and the equipment needed.
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Affiliation(s)
- Jonathan B Farr
- Department of Medical Physics, Applications of Detectors and Accelerators to Medicine, Meyrin, 1217, Switzerland
| | | | - Chris E Allgower
- Richard L. Roudebush VA Medical Center, Indianapolis, IN, 46202, USA
| | - Martin Bues
- Department of Radiation Oncology, Mayo Clinic, Scottsdale, AZ, 85259, USA
| | - Wen-Chien Hsi
- University of Florida Proton Therapy Institute, University of Florida, Jacksonville, FL, 32206, USA
| | - Hosang Jin
- Department of Radiation Oncology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, USA
| | - Dimitris N Mihailidis
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Hsiao-Ming Lu
- Department of Radiation Oncology, Hefei Ion Medical Center, 1700 Changning Avenue, Gaoxin District, Hefei, Anhui, 230088, China
| | - Wayne D Newhauser
- Department of Physics & Astronomy, Louisiana State University, Baton Rouge, LA, 70803, USA.,Mary Bird Perkins Cancer Center, Baton Rouge, LA, 70809, USA
| | - Narayan Sahoo
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Roelf Slopsema
- Department of Radiation Oncology, Emory Proton Therapy Center, Emory University, Atlanta, GA, 30322, USA
| | - Daniel Yeung
- Saudi Proton Therapy Center, King Fahad Medical City, Riyadh, Riyadh Province, 11525, Saudi Arabia
| | - X Ronald Zhu
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
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18
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Giacometti V, Hounsell AR, McGarry CK. A review of dose calculation approaches with cone beam CT in photon and proton therapy. Phys Med 2020; 76:243-276. [DOI: 10.1016/j.ejmp.2020.06.017] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 06/04/2020] [Accepted: 06/22/2020] [Indexed: 01/12/2023] Open
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19
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Thummerer A, Zaffino P, Meijers A, Marmitt GG, Seco J, Steenbakkers RJHM, Langendijk JA, Both S, Spadea MF, Knopf AC. Comparison of CBCT based synthetic CT methods suitable for proton dose calculations in adaptive proton therapy. Phys Med Biol 2020; 65:095002. [PMID: 32143207 DOI: 10.1088/1361-6560/ab7d54] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
In-room imaging is a prerequisite for adaptive proton therapy. The use of onboard cone-beam computed tomography (CBCT) imaging, which is routinely acquired for patient position verification, can enable daily dose reconstructions and plan adaptation decisions. Image quality deficiencies though, hamper dose calculation accuracy and make corrections of CBCTs a necessity. This study compared three methods to correct CBCTs and create synthetic CTs that are suitable for proton dose calculations. CBCTs, planning CTs and repeated CTs (rCT) from 33 H&N cancer patients were used to compare a deep convolutional neural network (DCNN), deformable image registration (DIR) and an analytical image-based correction method (AIC) for synthetic CT (sCT) generation. Image quality of sCTs was evaluated by comparison with a same-day rCT, using mean absolute error (MAE), mean error (ME), Dice similarity coefficient (DSC), structural non-uniformity (SNU) and signal/contrast-to-noise ratios (SNR/CNR) as metrics. Dosimetric accuracy was investigated in an intracranial setting by performing gamma analysis and calculating range shifts. Neural network-based sCTs resulted in the lowest MAE and ME (37/2 HU) and the highest DSC (0.96). While DIR and AIC generated images with a MAE of 44/77 HU, a ME of -8/1 HU and a DSC of 0.94/0.90. Gamma and range shift analysis showed almost no dosimetric difference between DCNN and DIR based sCTs. The lower image quality of AIC based sCTs affected dosimetric accuracy and resulted in lower pass ratios and higher range shifts. Patient-specific differences highlighted the advantages and disadvantages of each method. For the set of patients, the DCNN created synthetic CTs with the highest image quality. Accurate proton dose calculations were achieved by both DCNN and DIR based sCTs. The AIC method resulted in lower image quality and dose calculation accuracy was reduced compared to the other methods.
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Affiliation(s)
- Adrian Thummerer
- Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
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Tyyger M, Nix M, Al-Qaisieh B, Teo MT, Speight R. Identification and separation of rigid image registration error sources, demonstrated for MRI-only image guided radiotherapy. Biomed Phys Eng Express 2020; 6:035032. [PMID: 33438677 DOI: 10.1088/2057-1976/ab81ad] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
PURPOSE Rigid image registration (RIR) accuracy is crucial for image guided radiotherapy (IGRT). However, existing clinical image registration assessment methods cannot separate and quantify RIR error sources. Herein, we develop an extension of the 'full circle method' for RIR consistency. Paired registration circuits are used to isolate sources of RIR error caused by reference dataset substitution, from those inherent to the underlying RIR. This approach was demonstrated in the context of MRI-only IGRT, assessing substitution of MRI-derived synthetic-CT (sCT) for conventional CT, in a cohort of rectal cancer patients. MATERIALS AND METHODS Planning CT, MRI-derived sCT, and two CBCTs from seven rectal cancer patients were retrospectively registered with global and soft tissue clipbox based RIR. Paired registration circuits were constructed using two moving (cone beam CT) images and two reference images (CT and sCT), per patient. Differences between inconsistencies in registration circuits containing CT and sCT were used to determine changes in registration accuracy due to substitution of sCT for CT. RESULTS sCT was found to be equivalent to CT under global RIR, with median differences of 0.05 mm and 0.01°. Soft tissue clipbox based RIR with sCT exhibited gross misregistration (>5 mm or 3°) for 3 patients. Registration consistency was degraded compared to CT across the cohort, with median differences of 0.54 mm and 0.15°. CONCLUSION A paired registration circuit methodology for assessing RIR accuracy without ground truth information was developed and demonstrated for MRI-only IGRT in rectal cancer. This highlighted a reduction in clipbox based RIR consistency when sCT was substituted for conventional CT. The developed method enabled separation of degraded registration accuracy, from other error sources within the overall registration inconsistency. This novel methodology is applicable to any RIR scenario and enables analysis of the change in RIR performance on modification of image data or process.
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Affiliation(s)
- M Tyyger
- Leeds Cancer Centre, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
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21
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Yuan Z, Rong Y, Benedict SH, Daly ME, Qiu J, Yamamoto T. "Dose of the day" based on cone beam computed tomography and deformable image registration for lung cancer radiotherapy. J Appl Clin Med Phys 2019; 21:88-94. [PMID: 31816170 PMCID: PMC6964750 DOI: 10.1002/acm2.12793] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Revised: 02/04/2019] [Accepted: 11/17/2019] [Indexed: 12/25/2022] Open
Abstract
Purpose Adaptive radiotherapy (ART) has potential to reduce toxicity and facilitate safe dose escalation. Dose calculations with the planning CT deformed to cone beam CT (CBCT) have shown promise for estimating the “dose of the day”. The purpose of this study is to investigate the “dose of the day” calculation accuracy based on CBCT and deformable image registration (DIR) for lung cancer radiotherapy. Methods A total of 12 lung cancer patients were identified, for which daily CBCT imaging was performed for treatment positioning. A re‐planning CT (rCT) was acquired after 20 Gy for all patients. A virtual CT (vCT) was created by deforming initial planning CT (pCT) to the simulated CBCT that was generated from deforming CBCT to rCT acquired on the same day. Treatment beams from the initial plan were copied to the vCT and rCT for dose calculation. Dosimetric agreement between vCT‐based and rCT‐based accumulated doses was evaluated using the Bland‐Altman analysis. Results Mean differences in dose‐volume metrics between vCT and rCT were smaller than 1.5%, and most discrepancies fell within the range of ± 5% for the target volume, lung, esophagus, and heart. For spinal cord Dmax, a large mean difference of −5.55% was observed, which was largely attributed to very limited CBCT image quality (e.g., truncation artifacts). Conclusion This study demonstrated a reasonable agreement in dose‐volume metrics between dose accumulation based on vCT and rCT, with the exception for cases with poor CBCT image quality. These findings suggest potential utility of vCT for providing a reasonable estimate of the “dose of the day”, and thus facilitating the process of ART for lung cancer.
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Affiliation(s)
- Zilong Yuan
- Department of Radiation Oncology, University of California Davis Comprehensive Cancer Center, Sacramento, CA, USA.,Department of Radiology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Rong
- Department of Radiation Oncology, University of California Davis Comprehensive Cancer Center, Sacramento, CA, USA
| | - Stanley H Benedict
- Department of Radiation Oncology, University of California Davis Comprehensive Cancer Center, Sacramento, CA, USA
| | - Megan E Daly
- Department of Radiation Oncology, University of California Davis Comprehensive Cancer Center, Sacramento, CA, USA
| | - Jianfeng Qiu
- Medical Engineering and Technology Research Center, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Tokihiro Yamamoto
- Department of Radiation Oncology, University of California Davis Comprehensive Cancer Center, Sacramento, CA, USA
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22
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Nomura Y, Xu Q, Peng H, Takao S, Shimizu S, Xing L, Shirato H. Modified fast adaptive scatter kernel superposition (mfASKS) correction and its dosimetric impact on CBCT‐based proton therapy dose calculation. Med Phys 2019; 47:190-200. [DOI: 10.1002/mp.13878] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2019] [Revised: 10/11/2019] [Accepted: 10/12/2019] [Indexed: 12/27/2022] Open
Affiliation(s)
- Yusuke Nomura
- Department of Radiation Oncology Graduate School of Medicine Hokkaido University Sapporo 060‐8638 Japan
| | - Qiong Xu
- Global Station for Quantum Medical Science and Engineering Global Institution for Collaborative Research and Education (GI‐CoRE) Hokkaido University Sapporo 060‐8648 Japan
| | - Hao Peng
- Global Station for Quantum Medical Science and Engineering Global Institution for Collaborative Research and Education (GI‐CoRE) Hokkaido University Sapporo 060‐8648 Japan
- Department of Radiation Oncology Stanford University Stanford CA 94305‐5847 USA
| | - Seishin Takao
- Global Station for Quantum Medical Science and Engineering Global Institution for Collaborative Research and Education (GI‐CoRE) Hokkaido University Sapporo 060‐8648 Japan
- Department of Radiation Oncology Hokkaido University Hospital Sapporo 060‐8648 Japan
| | - Shinichi Shimizu
- Global Station for Quantum Medical Science and Engineering Global Institution for Collaborative Research and Education (GI‐CoRE) Hokkaido University Sapporo 060‐8648 Japan
- Department of Radiation Medical Science and Engineering Faculty of Medicine and Graduate School of Medicine Hokkaido University Sapporo 060‐8638 Japan
| | - Lei Xing
- Global Station for Quantum Medical Science and Engineering Global Institution for Collaborative Research and Education (GI‐CoRE) Hokkaido University Sapporo 060‐8648 Japan
- Department of Radiation Oncology Stanford University Stanford CA 94305‐5847 USA
| | - Hiroki Shirato
- Global Station for Quantum Medical Science and Engineering Global Institution for Collaborative Research and Education (GI‐CoRE) Hokkaido University Sapporo 060‐8648 Japan
- Department of Proton Beam Therapy Research Center for Cooperative Projects Faculty of Medicine Hokkaido University Sapporo 060‐8638 Japan
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Kurz C, Maspero M, Savenije MHF, Landry G, Kamp F, Pinto M, Li M, Parodi K, Belka C, van den Berg CAT. CBCT correction using a cycle-consistent generative adversarial network and unpaired training to enable photon and proton dose calculation. Phys Med Biol 2019; 64:225004. [PMID: 31610527 DOI: 10.1088/1361-6560/ab4d8c] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
In presence of inter-fractional anatomical changes, clinical benefits are anticipated from image-guided adaptive radiotherapy. Nowadays, cone-beam CT (CBCT) imaging is mostly utilized during pre-treatment imaging for position verification. Due to various artifacts, image quality is typically not sufficient for photon or proton dose calculation, thus demanding accurate CBCT correction, as potentially provided by deep learning techniques. This work aimed at investigating the feasibility of utilizing a cycle-consistent generative adversarial network (cycleGAN) for prostate CBCT correction using unpaired training. Thirty-three patients were included. The network was trained to translate uncorrected, original CBCT images (CBCTorg) into planning CT equivalent images (CBCTcycleGAN). HU accuracy was determined by comparison to a previously validated CBCT correction technique (CBCTcor). Dosimetric accuracy was inferred for volumetric-modulated arc photon therapy (VMAT) and opposing single-field uniform dose (OSFUD) proton plans, optimized on CBCTcor and recalculated on CBCTcycleGAN. Single-sided SFUD proton plans were utilized to assess proton range accuracy. The mean HU error of CBCTcycleGAN with respect to CBCTcor decreased from 24 HU for CBCTorg to -6 HU. Dose calculation accuracy was high for VMAT, with average pass-rates of 100%/89% for a 2%/1% dose difference criterion. For proton OSFUD plans, the average pass-rate for a 2% dose difference criterion was 80%. Using a (2%, 2 mm) gamma criterion, the pass-rate was 96%. 93% of all analyzed SFUD profiles had a range agreement better than 3 mm. CBCT correction time was reduced from 6-10 min for CBCTcor to 10 s for CBCTcycleGAN. Our study demonstrated the feasibility of utilizing a cycleGAN for CBCT correction, achieving high dose calculation accuracy for VMAT. For proton therapy, further improvements may be required. Due to unpaired training, the approach does not rely on anatomically consistent training data or potentially inaccurate deformable image registration. The substantial speed-up for CBCT correction renders the method particularly interesting for adaptive radiotherapy.
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Affiliation(s)
- Christopher Kurz
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany. Department of Radiotherapy, Center for Image Sciences, Universitair Medisch Centrum Utrecht, Utrecht, the Netherlands. Department of Medical Physics, Fakultät für Physik, Ludwig-Maximilians-Universität München (LMU Munich), Garching, Germany. Author to whom correspondence should be addressed
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Wu RY, Liu AY, Williamson TD, Yang J, Wisdom PG, Zhu XR, Frank SJ, Fuller CD, Gunn GB, Gao S. Quantifying the accuracy of deformable image registration for cone-beam computed tomography with a physical phantom. J Appl Clin Med Phys 2019; 20:92-100. [PMID: 31541526 PMCID: PMC6806467 DOI: 10.1002/acm2.12717] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 08/16/2019] [Accepted: 08/21/2019] [Indexed: 01/31/2023] Open
Abstract
PURPOSE Kilo-voltage cone-beam computed tomography (CBCT) is widely used for patient alignment, contour propagation, and adaptive treatment planning in radiation therapy. In this study, we evaluated the accuracy of deformable image registration (DIR) for CBCT under various imaging protocols with different noise and patient dose levels. METHODS A physical phantom previously developed to facilitate end-to-end testing of the DIR accuracy was used with Varian Velocity v4.0 software to evaluate the performance of image registration from CT to CT, CBCT to CT, and CBCT to CBCT. The phantom is acrylic and includes several inserts that simulate different tissue shapes and properties. Deformations and anatomic changes were simulated by changing the rotations of both the phantom and the inserts. CT images (from a head and neck protocol) and CBCT images (from pelvis, head and "Image Gently" protocols) were obtained with different image noise and dose levels. Large inserts were filled with Mobil DTE oil to simulate soft tissue, and small inserts were filled with bone materials. All inserts were contoured before the DIR process to provide a ground truth contour size and shape for comparison. After the DIR process, all deformed contours were compared with the originals using Dice similarity coefficient (DSC) and mean distance to agreement (MDA). Both large and small volume of interests (VOIs) for DIR volume selection were tested by simulating a DIR process that included whole patient image volume and clinical target volumes (CTV) only (for CTVs propagation). RESULTS For cross-modality DIR registration (CT to CBCT), the DSC were >0.8 and the MDA were <3 mm for CBCT pelvis, and CBCT head protocols. For CBCT to CBCT and CT to CT, the DIR accuracy was improved relative to the cross-modality tests. For smaller VOIs, the DSC were >0.8 and MDA <2 mm for all modalities. CONCLUSIONS The accuracy of DIR depends on the quality of the CBCT image at different dose and noise levels.
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Affiliation(s)
- Richard Y. Wu
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Amy Y. Liu
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Tyler D. Williamson
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Jinzhong Yang
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Paul G. Wisdom
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Xiaorong R. Zhu
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Steven J. Frank
- Department of Radiation OncologyThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Clifton D. Fuller
- Department of Radiation OncologyThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Gary B. Gunn
- Department of Radiation OncologyThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
| | - Song Gao
- Department of Radiation PhysicsThe University of Texas MD Anderson Cancer CenterHoustonTXUSA
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Niepel K, Kamp F, Kurz C, Hansen D, Rit S, Neppl S, Hofmaier J, Bondesson D, Thieke C, Dinkel J, Belka C, Parodi K, Landry G. Feasibility of 4DCBCT-based proton dose calculation: An ex vivo porcine lung phantom study. Z Med Phys 2019; 29:249-261. [DOI: 10.1016/j.zemedi.2018.10.005] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2018] [Revised: 09/06/2018] [Accepted: 10/22/2018] [Indexed: 12/25/2022]
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Landry G, Hansen D, Kamp F, Li M, Hoyle B, Weller J, Parodi K, Belka C, Kurz C. Comparing Unet training with three different datasets to correct CBCT images for prostate radiotherapy dose calculations. Phys Med Biol 2019; 64:035011. [PMID: 30523998 DOI: 10.1088/1361-6560/aaf496] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Image intensity correction is crucial to enable cone beam computed tomography (CBCT) based radiotherapy dose calculations. This study evaluated three different deep learning based correction methods using a U-shaped convolutional neural network architecture (Unet) in terms of their photon and proton dose calculation accuracy. CT and CBCT imaging data of 42 prostate cancer patients were included. For target ground truth data generation, a CBCT correction method based on CT to CBCT deformable image registration (DIR) was used. The method yields a deformed CT called (i) virtual CT (vCT) which is used to generate (ii) corrected CBCT projections allowing the reconstruction of (iii) a final corrected CBCT image. The single Unet architecture was trained using these three different datasets: (Unet1) raw and corrected CBCT projections, (Unet2) raw CBCT and vCT image slices and (Unet3) raw and reference corrected CBCT image slices. Volumetric arc therapy (VMAT) and proton pencil beam scanning (PBS) single field uniform dose (SFUD) plans were optimized on the reference corrected image and recalculated on the obtained Unet-corrected CBCT images. The mean error (ME) and mean absolute error (MAE) for Unet1/2/3 were [Formula: see text] Hounsfield units (HU) and [Formula: see text] HU. The 1% dose difference pass rates were better than 98.4% for VMAT for 8 test patients not seen during training, with little difference between Unets. Gamma evaluation results were even better. For protons a gamma evaluation was employed to account for small range shifts, and [Formula: see text] mm pass rates for Unet1/2/3 were better than [Formula: see text] and 91%. A 3 mm range difference threshold was established. Only for Unet3 the 5th and 95th percentiles of the range difference distributions over all fields, test patients and dose profiles were within this threshold. A single Unet architecture was successfully trained using both CBCT projections and CBCT image slices. Since the results of the other Unets were poorer than Unet3, we conclude that training using corrected CBCT image slices as target data is optimal for PBS SFUD proton dose calculations, while for VMAT all Unets provided sufficient accuracy.
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Affiliation(s)
- Guillaume Landry
- Department of Medical Physics, Fakultät für Physik, Ludwig-Maximilians-Universität München (LMU Munich), Garching, Germany
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Landry G, Hua CH. Current state and future applications of radiological image guidance for particle therapy. Med Phys 2018; 45:e1086-e1095. [PMID: 30421805 DOI: 10.1002/mp.12744] [Citation(s) in RCA: 67] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2017] [Revised: 10/25/2017] [Accepted: 11/30/2017] [Indexed: 12/27/2022] Open
Abstract
In this review paper, we first give a short overview of radiological image guidance in photon radiotherapy, placing emphasis on the fact that linac based radiotherapy has outpaced particle therapy in the adoption of volumetric image guidance. While cone beam computed tomography (CBCT) has been an established technique in linac treatment rooms for almost two decades, the widespread adoption of volumetric image guidance in particle therapy, whether by means of CBCT or in-room CT imaging, is recent. This lag may be attributable to the bespoke nature and lower number of particle therapy installations, as well as the differences in geometry between those installations and linac treatment rooms. In addition, for particle therapy the so called shift invariance of the dose distribution rarely applies. An overview of the different volumetric image guidance solutions found at modern particle therapy facilities is provided, covering gantry, nozzle, C-arm, and couch-mounted CBCT as well different in-room CT configurations. A summary of the use of in-room volumetric imaging data beyond anatomy-based positioning is also presented as well as the necessary corrections to CBCT images for accurate water equivalent thickness calculation. Finally, the use of non-ionizing imaging modalities is discussed.
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Affiliation(s)
- Guillaume Landry
- Faculty of Physics, Department of Medical Physics, Ludwig-Maximilians-Universität München (LMU Munich), 85748, Garching b. München, Germany
| | - Chia-Ho Hua
- Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
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Sun B, Yang D, Lam D, Zhang T, Dvergsten T, Bradley J, Mutic S, Zhao T. Toward adaptive proton therapy guided with a mobile helical CT scanner. Radiother Oncol 2018; 129:479-485. [PMID: 30314717 DOI: 10.1016/j.radonc.2018.08.021] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Revised: 08/21/2018] [Accepted: 08/26/2018] [Indexed: 10/28/2022]
Abstract
PURPOSE To evaluate the feasibility of image-guided adaptive proton therapy (IGAPT) with a mobile helical-CT without rails. METHOD CT images were acquired with a 32-slice mobile CT (mCT) scanning through a 6 degree-of-freedom robotic couch rotated isocentrically 90 degrees from an initial setup position. The relationship between the treatment isocenter and the mCT imaging isocenter was established by a stereotactic reference frame attached to the treatment couch. Imaging quality, geometric integrity and localization accuracy were evaluated according to AAPM TG-66. Accuracy of relative stopping power ratio (RSPR) was evaluated by comparing water equivalent distance (WED) and dose calculations on anthropomorphic phantoms to that of planning CT (pCT). Feasibility of image-guided adaptive proton therapy was demonstrated on fractional images acquired with the mCT scanner. RESULTS mCT images showed slightly lower spatial resolution and a higher contrast-to-noise ratio compared to pCT images from the standard helical CT scanner. The geometric accuracy of the mCT was <1 mm. Localization accuracy was <0.4 mm and <0.3° with respect to 2DkV/kV matching. WED differences between mCT and pCT images were negligible, with discrepancies of 0.8 ± 0.6 mm and 1.3 ± 0.9 mm for brain and lung phantoms respectively. 3D gamma analysis (3% and 3 mm) passing rate was >95% on dose computed on mCT, with respect to dose calculation on pCT. CONCLUSION Our study has demonstrated that the geometric integrity, image quality and RSPR accuracy of the mCT are sufficient for IGAPT.
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Affiliation(s)
- Baozhou Sun
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, United States.
| | - Deshan Yang
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, United States
| | - Dao Lam
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, United States
| | - Tiezhi Zhang
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, United States
| | - Thomas Dvergsten
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, United States
| | - Jeffrey Bradley
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, United States
| | - Sasa Mutic
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, United States
| | - Tianyu Zhao
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, United States
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The technological basis for adaptive ion beam therapy at MedAustron: Status and outlook. Z Med Phys 2018; 28:196-210. [DOI: 10.1016/j.zemedi.2017.09.007] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Revised: 09/02/2017] [Accepted: 09/18/2017] [Indexed: 11/22/2022]
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Oliver JA, Zeidan O, Meeks SL, Shah AP, Pukala J, Kelly P, Ramakrishna NR, Willoughby TR. Commissioning an in-room mobile CT for adaptive proton therapy with a compact proton system. J Appl Clin Med Phys 2018; 19:149-158. [PMID: 29682879 PMCID: PMC5978963 DOI: 10.1002/acm2.12319] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2017] [Revised: 11/20/2017] [Accepted: 02/06/2018] [Indexed: 11/16/2022] Open
Abstract
Purpose To describe the commissioning of AIRO mobile CT system (AIRO) for adaptive proton therapy on a compact double scattering proton therapy system. Methods A Gammex phantom was scanned with varying plug patterns, table heights, and mAs on a CT simulator (CT Sim) and on the AIRO. AIRO‐specific CT‐stopping power ratio (SPR) curves were created with a commonly used stoichiometric method using the Gammex phantom. A RANDO anthropomorphic thorax, pelvis, and head phantom, and a CIRS thorax and head phantom were scanned on the CT Sim and AIRO. Clinically realistic treatment plans and nonclinical plans were generated on the CT Sim images and subsequently copied onto the AIRO CT scans for dose recalculation and comparison for various AIRO SPR curves. Gamma analysis was used to evaluate dosimetric deviation between both plans. Results AIRO CT values skewed toward solid water when plugs were scanned surrounded by other plugs in phantom. Low‐density materials demonstrated largest differences. Dose calculated on AIRO CT scans with stoichiometric‐based SPR curves produced over‐ranged proton beams when large volumes of low‐density material were in the path of the beam. To create equivalent dose distributions on both data sets, the AIRO SPR curve's low‐density data points were iteratively adjusted to yield better proton beam range agreement based on isodose lines. Comparison of the stoichiometric‐based AIRO SPR curve and the “dose‐adjusted” SPR curve showed slight improvement on gamma analysis between the treatment plan and the AIRO plan for single‐field plans at the 1%, 1 mm level, but did not affect clinical plans indicating that HU number differences between the CT Sim and AIRO did not affect dose calculations for robust clinical beam arrangements. Conclusion Based on this study, we believe the AIRO can be used offline for adaptive proton therapy on a compact double scattering proton therapy system.
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Affiliation(s)
| | - Omar Zeidan
- Orlando Health UF Health Cancer Center, Orlando, FL, USA
| | | | - Amish P Shah
- Orlando Health UF Health Cancer Center, Orlando, FL, USA
| | - Jason Pukala
- Orlando Health UF Health Cancer Center, Orlando, FL, USA
| | - Patrick Kelly
- Orlando Health UF Health Cancer Center, Orlando, FL, USA
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Yao W, Krasin MJ, Farr JB, Merchant TE. Feasibility study of range-based registration using daily cone beam CT for intensity-modulated proton therapy. Med Phys 2018; 45:1191-1203. [PMID: 29360157 DOI: 10.1002/mp.12760] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Revised: 12/13/2017] [Accepted: 12/14/2017] [Indexed: 12/15/2022] Open
Abstract
PURPOSE Proton dose coverage is sensitive to proton beam range. The current practice of CT number-based registration for patient positioning focuses on matching the target and is not sufficient for proton therapy because the proton range depends on the medium traversed by the beam. Patient body deformations and anatomical changes result in range deviation in the target. We propose proton range-based registration to minimize the range deviation. METHODS The range was calculated from cone beam-computed tomography (CBCT) of the patient on couch, and the range deviation was the difference of the calculated range from that on the initial (day 1) CBCT. In the investigated prostate cases in which the main cause of range deviation was the rotation of femur bones, and in the investigated abdomen cases in which the main cause of range deviation was body growth and anatomic change, our range-based registration was used to obtain the optimal beam angle by minimizing the range deviation. The new angle was limited to be ±5° from that planned to prevent potentially increased dose to the organs at risk. To demonstrate the benefit of range-based registration, we investigated the range at the voxels on the surface of the target volume. The calculation error of range deviation due to CBCT scatter was investigated by using solid water phantoms with different thicknesses. Range-based registration using both CBCTs and CTs was performed in cases of two patients with pelvic rhabdomyosarcoma and one patient with upper abdominal tumor. The range was represented by the water-equivalent thickness to shorten the computation for online application purposes. RESULTS In the phantom study, the calculation error of range deviation due to CBCT scatter was within 2 mm for a 1-cm thickness change (the mean range deviation was 0.8 mm). In the CT study of the prostate cases, the range deviation (mean ± root-mean-square deviation) on the contour in each slice was efficiently reduced from 3.6 ± 2.8 mm to 2.1 ± 1.4 mm, with most slices being within 3 mm; in the CT study of the abdomen cases, the range deviation of the whole set was reduced from 4.4 ± 1.9 mm to 3.5 ± 2.1 mm. Both the mean and root-mean-square deviation of the range deviation on each treatment day were decreased. The dose coverage on the target was improved and the dose on the OARs was only slightly changed. CONCLUSION Range-based registration can efficiently mitigate range deviation due to patient positioning and anatomical changes. It can shorten patient positioning time and reduce the patient's dose from CBCT.
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Affiliation(s)
- Weiguang Yao
- Department of Radiation Oncology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA
| | - Matthew J Krasin
- Department of Radiation Oncology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA
| | - Jonathan B Farr
- Department of Radiation Oncology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA
| | - Thomas E Merchant
- Department of Radiation Oncology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA
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Dedes G, De Angelis L, Rit S, Hansen D, Belka C, Bashkirov V, Johnson RP, Coutrakon G, Schubert KE, Schulte RW, Parodi K, Landry G. Application of fluence field modulation to proton computed tomography for proton therapy imaging. ACTA ACUST UNITED AC 2017; 62:6026-6043. [DOI: 10.1088/1361-6560/aa7734] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Zöllner C, Rit S, Kurz C, Vilches-Freixas G, Kamp F, Dedes G, Belka C, Parodi K, Landry G. Decomposing a prior-CT-based cone-beam CT projection correction algorithm into scatter and beam hardening components. PHYSICS & IMAGING IN RADIATION ONCOLOGY 2017. [DOI: 10.1016/j.phro.2017.09.002] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Teske H, Bartelheimer K, Meis J, Bendl R, Stoiber EM, Giske K. Construction of a biomechanical head and neck motion model as a guide to evaluation of deformable image registration. Phys Med Biol 2017; 62:N271-N284. [PMID: 28350540 DOI: 10.1088/1361-6560/aa69b6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
The use of deformable image registration methods in the context of adaptive radiotherapy leads to uncertainties in the simulation of the administered dose distributions during the treatment course. Evaluation of these methods is a prerequisite to decide if a plan adaptation will improve the individual treatment. Current approaches using manual references limit the validity of evaluation, especially for low-contrast regions. In particular, for the head and neck region, the highly flexible anatomy and low soft tissue contrast in control images pose a challenge to image registration and its evaluation. Biomechanical models promise to overcome this issue by providing anthropomorphic motion modelling of the patient. We introduce a novel biomechanical motion model for the generation and sampling of different postures of the head and neck anatomy. Motion propagation behaviour of the individual bones is defined by an underlying kinematic model. This model interconnects the bones by joints and thus is capable of providing a wide range of motion. Triggered by the motion of the individual bones, soft tissue deformation is described by an extended heterogeneous tissue model based on the chainmail approach. This extension, for the first time, allows the propagation of decaying rotations within soft tissue without the necessity for explicit tissue segmentation. Overall motion simulation and sampling of deformed CT scans including a basic noise model is achieved within 30 s. The proposed biomechanical motion model for the head and neck site generates displacement vector fields on a voxel basis, approximating arbitrary anthropomorphic postures of the patient. It was developed with the intention of providing input data for the evaluation of deformable image registration.
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Affiliation(s)
- Hendrik Teske
- Division of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany. National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany
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Veiga C, Janssens G, Baudier T, Hotoiu L, Brousmiche S, McClelland J, Teng CL, Yin L, Royle G, Teo BKK. A comprehensive evaluation of the accuracy of CBCT and deformable registration based dose calculation in lung proton therapy. Biomed Phys Eng Express 2017. [DOI: 10.1088/2057-1976/3/1/015003] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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Kurz C, Kamp F, Park YK, Zöllner C, Rit S, Hansen D, Podesta M, Sharp GC, Li M, Reiner M, Hofmaier J, Neppl S, Thieke C, Nijhuis R, Ganswindt U, Belka C, Winey BA, Parodi K, Landry G. Investigating deformable image registration and scatter correction for CBCT-based dose calculation in adaptive IMPT. Med Phys 2016; 43:5635. [DOI: 10.1118/1.4962933] [Citation(s) in RCA: 70] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
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Hauler F, Furtado H, Jurisic M, Polanec SH, Spick C, Laprie A, Nestle U, Sabatini U, Birkfellner W. Automatic quantification of multi-modal rigid registration accuracy using feature detectors. Phys Med Biol 2016; 61:5198-214. [DOI: 10.1088/0031-9155/61/14/5198] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Yeom YS, Kim HS, Nguyen TT, Choi C, Han MC, Kim CH, Lee JK, Zankl M, Petoussi-Henss N, Bolch WE, Lee C, Chung BS. New small-intestine modeling method for surface-based computational human phantoms. JOURNAL OF RADIOLOGICAL PROTECTION : OFFICIAL JOURNAL OF THE SOCIETY FOR RADIOLOGICAL PROTECTION 2016; 36:230-245. [PMID: 27007802 DOI: 10.1088/0952-4746/36/2/230] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
When converting voxel phantoms to a surface format, the small intestine (SI), which is usually not accurately represented in a voxel phantom due to its complex and irregular shape on one hand and the limited voxel resolutions on the other, cannot be directly converted to a high-quality surface model. Currently, stylized pipe models are used instead, but they are strongly influenced by developer's subjectivity, resulting in unacceptable geometric and dosimetric inconsistencies. In this paper, we propose a new method for the construction of SI models based on the Monte Carlo approach. In the present study, the proposed method was tested by constructing the SI model for the polygon-mesh version of the ICRP reference male phantom currently under development. We believe that the new SI model is anatomically more realistic than the stylized SI models. Furthermore, our simulation results show that the new SI model, for both external and internal photon exposures, leads to dose values that are more similar to those of the original ICRP male voxel phantom than does the previously constructed stylized SI model.
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Affiliation(s)
- Yeon Soo Yeom
- Department of Nuclear Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 133-791, Korea
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Landry G, Nijhuis R, Dedes G, Handrack J, Thieke C, Janssens G, Orban de Xivry J, Reiner M, Kamp F, Wilkens JJ, Paganelli C, Riboldi M, Baroni G, Ganswindt U, Belka C, Parodi K. Investigating CT to CBCT image registration for head and neck proton therapy as a tool for daily dose recalculation. Med Phys 2016; 42:1354-66. [PMID: 25735290 DOI: 10.1118/1.4908223] [Citation(s) in RCA: 103] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
PURPOSE Intensity modulated proton therapy (IMPT) of head and neck (H&N) cancer patients may be improved by plan adaptation. The decision to adapt the treatment plan based on a dose recalculation on the current anatomy requires a diagnostic quality computed tomography (CT) scan of the patient. As gantry-mounted cone beam CT (CBCT) scanners are currently being offered by vendors, they may offer daily or weekly updates of patient anatomy. CBCT image quality may not be sufficient for accurate proton dose calculation and it is likely necessary to perform CBCT CT number correction. In this work, the authors investigated deformable image registration (DIR) of the planning CT (pCT) to the CBCT to generate a virtual CT (vCT) to be used for proton dose recalculation. METHODS Datasets of six H&N cancer patients undergoing photon intensity modulated radiation therapy were used in this study to validate the vCT approach. Each dataset contained a CBCT acquired within 3 days of a replanning CT (rpCT), in addition to a pCT. The pCT and rpCT were delineated by a physician. A Morphons algorithm was employed in this work to perform DIR of the pCT to CBCT following a rigid registration of the two images. The contours from the pCT were deformed using the vector field resulting from DIR to yield a contoured vCT. The DIR accuracy was evaluated with a scale invariant feature transform (SIFT) algorithm comparing automatically identified matching features between vCT and CBCT. The rpCT was used as reference for evaluation of the vCT. The vCT and rpCT CT numbers were converted to stopping power ratio and the water equivalent thickness (WET) was calculated. IMPT dose distributions from treatment plans optimized on the pCT were recalculated with a Monte Carlo algorithm on the rpCT and vCT for comparison in terms of gamma index, dose volume histogram (DVH) statistics as well as proton range. The DIR generated contours on the vCT were compared to physician-drawn contours on the rpCT. RESULTS The DIR accuracy was better than 1.4 mm according to the SIFT evaluation. The mean WET differences between vCT (pCT) and rpCT were below 1 mm (2.6 mm). The amount of voxels passing 3%/3 mm gamma criteria were above 95% for the vCT vs rpCT. When using the rpCT contour set to derive DVH statistics from dose distributions calculated on the rpCT and vCT the differences, expressed in terms of 30 fractions of 2 Gy, were within [-4, 2 Gy] for parotid glands (D(mean)), spinal cord (D(2%)), brainstem (D(2%)), and CTV (D(95%)). When using DIR generated contours for the vCT, those differences ranged within [-8, 11 Gy]. CONCLUSIONS In this work, the authors generated CBCT based stopping power distributions using DIR of the pCT to a CBCT scan. DIR accuracy was below 1.4 mm as evaluated by the SIFT algorithm. Dose distributions calculated on the vCT agreed well to those calculated on the rpCT when using gamma index evaluation as well as DVH statistics based on the same contours. The use of DIR generated contours introduced variability in DVH statistics.
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Affiliation(s)
- Guillaume Landry
- Department of Medical Physics, Ludwig-Maximilians-University, Munich D85748, Germany and Department of Radiation Oncology, Ludwig-Maximilians-University, Munich D81377, Germany
| | - Reinoud Nijhuis
- Department of Radiation Oncology, Ludwig-Maximilians-University, Munich D81377, Germany
| | - George Dedes
- Department of Medical Physics, Ludwig-Maximilians-University, Munich D85748, Germany
| | - Josefine Handrack
- Department of Medical Physics, Ludwig-Maximilians-University, Munich D85748, Germany
| | - Christian Thieke
- Department of Radiation Oncology, Ludwig-Maximilians-University, Munich D81377, Germany
| | - Guillaume Janssens
- ICTEAM, Université Catholique de Louvain, Louvain-La-Neuve B1348, Belgium
| | | | - Michael Reiner
- Department of Radiation Oncology, Ludwig-Maximilians-University, Munich D81377, Germany
| | - Florian Kamp
- Department of Radiation Oncology, Technische Universität München, Klinikum rechts der Isar, Munich D81675, Germany and Physik-Department, Technische Universität München, Garching D85748, Germany
| | - Jan J Wilkens
- Department of Radiation Oncology, Technische Universität München, Klinikum rechts der Isar, Munich D81675, Germany and Physik-Department, Technische Universität München, Garching D85748, Germany
| | - Chiara Paganelli
- Dipartimento di Elettronica Informazione e Bioingegneria, Politecnico di Milano, Milan 20133, Italy
| | - Marco Riboldi
- Dipartimento di Elettronica Informazione e Bioingegneria, Politecnico di Milano, Milan 20133, Italy
| | - Guido Baroni
- Dipartimento di Elettronica Informazione e Bioingegneria, Politecnico di Milano, Milan 20133, Italy
| | - Ute Ganswindt
- Department of Radiation Oncology, Ludwig-Maximilians-University, Munich D81377, Germany
| | - Claus Belka
- Department of Radiation Oncology, Ludwig-Maximilians-University, Munich D81377, Germany
| | - Katia Parodi
- Department of Medical Physics, Ludwig-Maximilians-University, Munich D85748, Germany
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Park YK, Sharp GC, Phillips J, Winey BA. Proton dose calculation on scatter-corrected CBCT image: Feasibility study for adaptive proton therapy. Med Phys 2016; 42:4449-59. [PMID: 26233175 DOI: 10.1118/1.4923179] [Citation(s) in RCA: 95] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE To demonstrate the feasibility of proton dose calculation on scatter-corrected cone-beam computed tomographic (CBCT) images for the purpose of adaptive proton therapy. METHODS CBCT projection images were acquired from anthropomorphic phantoms and a prostate patient using an on-board imaging system of an Elekta infinity linear accelerator. Two previously introduced techniques were used to correct the scattered x-rays in the raw projection images: uniform scatter correction (CBCTus) and a priori CT-based scatter correction (CBCTap). CBCT images were reconstructed using a standard FDK algorithm and GPU-based reconstruction toolkit. Soft tissue ROI-based HU shifting was used to improve HU accuracy of the uncorrected CBCT images and CBCTus, while no HU change was applied to the CBCTap. The degree of equivalence of the corrected CBCT images with respect to the reference CT image (CTref) was evaluated by using angular profiles of water equivalent path length (WEPL) and passively scattered proton treatment plans. The CBCTap was further evaluated in more realistic scenarios such as rectal filling and weight loss to assess the effect of mismatched prior information on the corrected images. RESULTS The uncorrected CBCT and CBCTus images demonstrated substantial WEPL discrepancies (7.3 ± 5.3 mm and 11.1 ± 6.6 mm, respectively) with respect to the CTref, while the CBCTap images showed substantially reduced WEPL errors (2.4 ± 2.0 mm). Similarly, the CBCTap-based treatment plans demonstrated a high pass rate (96.0% ± 2.5% in 2 mm/2% criteria) in a 3D gamma analysis. CONCLUSIONS A priori CT-based scatter correction technique was shown to be promising for adaptive proton therapy, as it achieved equivalent proton dose distributions and water equivalent path lengths compared to those of a reference CT in a selection of anthropomorphic phantoms.
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Affiliation(s)
- Yang-Kyun Park
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114
| | - Justin Phillips
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114
| | - Brian A Winey
- Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114
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Veiga C, Janssens G, Teng CL, Baudier T, Hotoiu L, McClelland JR, Royle G, Lin L, Yin L, Metz J, Solberg TD, Tochner Z, Simone CB, McDonough J, Kevin Teo BK. First Clinical Investigation of Cone Beam Computed Tomography and Deformable Registration for Adaptive Proton Therapy for Lung Cancer. Int J Radiat Oncol Biol Phys 2016; 95:549-559. [DOI: 10.1016/j.ijrobp.2016.01.055] [Citation(s) in RCA: 135] [Impact Index Per Article: 16.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2015] [Revised: 01/26/2016] [Accepted: 01/28/2016] [Indexed: 12/25/2022]
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Kurz C, Nijhuis R, Reiner M, Ganswindt U, Thieke C, Belka C, Parodi K, Landry G. Feasibility of automated proton therapy plan adaptation for head and neck tumors using cone beam CT images. Radiat Oncol 2016; 11:64. [PMID: 27129305 PMCID: PMC4851791 DOI: 10.1186/s13014-016-0641-7] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2015] [Accepted: 04/27/2016] [Indexed: 11/10/2022] Open
Abstract
Background Intensity modulated proton therapy (IMPT) of head and neck (H&N) tumors may benefit from plan adaptation to correct for the dose perturbations caused by weight loss and tumor volume changes observed in these patients. As cone beam CT (CBCT) is increasingly considered in proton therapy, it may be possible to use available CBCT images following intensity correction for plan adaptation. This is the first study exploring IMPT plan adaptation on CBCT images corrected and delineated by deformable image registration of the planning CT (pCT) to the CBCT, yielding a virtual CT (vCT). Methods A Morphons algorithm was used to deform the pCTs and corresponding delineations of 9 H&N cancer patients to a weekly CBCT acquired within ±3 days of a control replanning CT scan (rpCT). The IMPT treatment plans were adapted using the vCT and the adapted and original plans were recalculated on the rpCT for dose/volume parameter evaluation of the impact of adaptation. Results On the rpCT, the adapted plans were equivalent to the original plans in terms of target volumes D95 and V95, but showed a significant reduction of D2 in these volumes. OAR doses were mostly equivalent or reduced. In particular, the adapted plans did not reduce parotid gland Dmean, but the dose to the optical system. For three patients the spinal cord or brain stem received higher, though well below tolerance, maximum dose. Subsequent tightening of the treatment planning constraints for these OARs on new vCT-adapted plans did not degrade target coverage and yielded pCT equivalent plans on the vCT. Conclusions An offline automated procedure to generate an adapted IMPT plan on CBCT images was developed and investigated. When evaluating the adapted plan on a control rpCT we observed reduced D2 in target volumes as major improvement. OAR sparing was only partially improved by the procedure. Despite potential limitations in the accuracy of the vCT approach, an improved quality of the adapted plans could be achieved. Electronic supplementary material The online version of this article (doi:10.1186/s13014-016-0641-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Christopher Kurz
- Department of Radiation Oncology, LMU Munich, Munich, Germany.,Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Reinoud Nijhuis
- Department of Radiation Oncology, LMU Munich, Munich, Germany
| | - Michael Reiner
- Department of Radiation Oncology, LMU Munich, Munich, Germany
| | - Ute Ganswindt
- Department of Radiation Oncology, LMU Munich, Munich, Germany
| | | | - Claus Belka
- Department of Radiation Oncology, LMU Munich, Munich, Germany
| | - Katia Parodi
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Guillaume Landry
- Department of Radiation Oncology, LMU Munich, Munich, Germany. .,Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Munich, Germany.
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Hudobivnik N, Schwarz F, Johnson T, Agolli L, Dedes G, Tessonnier T, Verhaegen F, Thieke C, Belka C, Sommer WH, Parodi K, Landry G. Comparison of proton therapy treatment planning for head tumors with a pencil beam algorithm on dual and single energy CT images. Med Phys 2016; 43:495. [DOI: 10.1118/1.4939106] [Citation(s) in RCA: 73] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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Veiga C, Alshaikhi J, Amos R, Lourenço AM, Modat M, Ourselin S, Royle G, McClelland JR. Cone-Beam Computed Tomography and Deformable Registration-Based “Dose of the Day” Calculations for Adaptive Proton Therapy. Int J Part Ther 2015. [DOI: 10.14338/ijpt-14-00024.1] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Affiliation(s)
- Catarina Veiga
- Radiation Physics Group, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK
| | - Jailan Alshaikhi
- Radiation Physics Group, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK
- Department of Radiotherapy Physics, University College London Hospital, London NW1 2PG, UK
| | - Richard Amos
- Department of Radiotherapy Physics, University College London Hospital, London NW1 2PG, UK
| | - Ana Mónica Lourenço
- Radiation Physics Group, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK
- Ionizing Radiation Team, National Physical Laboratory, Teddington TW11 0LW, UK
| | - Marc Modat
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK
| | - Sebastien Ourselin
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK
| | - Gary Royle
- Radiation Physics Group, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK
| | - Jamie R. McClelland
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK
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Kurz C, Dedes G, Resch A, Reiner M, Ganswindt U, Nijhuis R, Thieke C, Belka C, Parodi K, Landry G. Comparing cone-beam CT intensity correction methods for dose recalculation in adaptive intensity-modulated photon and proton therapy for head and neck cancer. Acta Oncol 2015. [PMID: 26198654 DOI: 10.3109/0284186x.2015.1061206] [Citation(s) in RCA: 77] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
BACKGROUND Adaptive intensity-modulated photon and proton radiotherapy (IMRT and IMPT) of head and neck (H&N) cancer requires frequent three-dimensional (3D) dose calculation. We compared two approaches for dose recalculation on the basis of intensity-corrected cone-beam (CB) x-ray computed tomography (CT) images. MATERIAL AND METHODS For nine H&N tumor patients, virtual CTs (vCT) were generated by deformable image registration of the planning CT (pCT) to the CBCT. The second intensity correction approach used population-based lookup tables for scaling CBCT intensities to the pCT HU range (CBCTLUT). IMRT and IMPT plans were generated with a commercial treatment planning system. Dose recalculations on vCT and CBCTLUT were analyzed using a (3%, 3 mm) gamma-index analysis and comparison of normal tissue and tumor dose/volume parameters. A replanning CT (rpCT) acquired within three days of the CBCT served as reference. Single field uniform dose (SFUD) proton plans were created and recalculated on vCT and CBCTLUT for proton range comparison. RESULTS Dose/volume parameters showed minor differences between rpCT, vCT and CBCTLUT in IMRT, but clinically relevant deviations between CBCTLUT and rpCT in the spinal cord for IMPT. Gamma-index pass-rates were found increased for vCT with respect to CBCTLUT in IMPT (by up to 21 percentage points) and IMRT (by up to 9 percentage points) for most cases. The SFUD-based proton range assessment showed improved agreement of vCT and rpCT, with 88-99% of the depth dose profiles in beam's eye view agreeing within 3 mm. For CBCTLUT, only 80-94% of the profiles fulfilled this criterion. CONCLUSION vCT and CBCTLUT are suitable options for dose recalculation in adaptive IMRT. In the scope of IMPT, the vCT approach is preferable.
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Affiliation(s)
- Christopher Kurz
- a Department of Radiation Oncology , Ludwig-Maximilians-University , Munich , Germany
- b Department of Medical Physics , Ludwig-Maximilians-University , Munich , Germany
| | - George Dedes
- b Department of Medical Physics , Ludwig-Maximilians-University , Munich , Germany
| | - Andreas Resch
- b Department of Medical Physics , Ludwig-Maximilians-University , Munich , Germany
| | - Michael Reiner
- a Department of Radiation Oncology , Ludwig-Maximilians-University , Munich , Germany
| | - Ute Ganswindt
- a Department of Radiation Oncology , Ludwig-Maximilians-University , Munich , Germany
| | - Reinoud Nijhuis
- a Department of Radiation Oncology , Ludwig-Maximilians-University , Munich , Germany
| | - Christian Thieke
- a Department of Radiation Oncology , Ludwig-Maximilians-University , Munich , Germany
| | - Claus Belka
- a Department of Radiation Oncology , Ludwig-Maximilians-University , Munich , Germany
| | - Katia Parodi
- b Department of Medical Physics , Ludwig-Maximilians-University , Munich , Germany
| | - Guillaume Landry
- a Department of Radiation Oncology , Ludwig-Maximilians-University , Munich , Germany
- b Department of Medical Physics , Ludwig-Maximilians-University , Munich , Germany
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