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Li Y, Gong Z, Liu M, Li H, Gao H, Guo C, Yu L, Zhu C, Sun Z, Sun L, Xu H, He X. 3D-US and CBCT Dual-guided Radiotherapy for Postoperative Uterine Malignancy: A Primary Workflow Set-up. Technol Cancer Res Treat 2023; 22:15330338231212082. [PMID: 37993995 PMCID: PMC10666818 DOI: 10.1177/15330338231212082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 09/09/2023] [Accepted: 09/26/2023] [Indexed: 11/24/2023] Open
Abstract
Introduction: The consistency of clinical target volume is essential to guiding radiotherapy with precision for postoperative uterine malignancy patients. By introducing a three-dimensional ultrasound system (3D-US) into image-guided radiation therapy (IGRT), this study was designed to investigate the initial workflow set-up, the therapeutic potential, and the adverse events of 3D-US and cone-beam computed tomography (CBCT) dual-guided radiotherapy in postoperative uterine malignancy treatment. Methods: From April 2021 to December 2021, postoperative uterine malignancy patients were instructed to follow the previously standard protocol of daily radiation treatment, particularly a 3D-US (Clarity system) guiding was involved before CBCT. Soft-tissue-based displacements resulting from the additional US-IGRT were acquired in the LT (left)/RT (right), ANT (anterior)/POST (posterior), and SUP (superior)/INF(inferior) directions of the patient before fractional treatment. Displacement distributions before and after treatment either from 3D-US or from CBCT were also estimated and compared subsequently, and the urinary and rectal toxicity was further evaluated. Results: All the patients completed radiation treatment as planned. The assessment of 170 scans resulted in a mean displacement of (0.17 ± 0.24) cm, (0.19 ± 0.23) cm, (0.22 ± 0.26) cm for bladder in LT/RT, ANT/POST, and SUP/INF directions. A mean deviation of (0.26 ± 0.22) cm, (0.58 ± 0.5) cm, and (0.3 ± 0.23) cm was also observed for the bladder centroid between the CBCT and computed tomography -simulation images in three directions. Paired comparison between these two guidance shows that the variations from 3D-US are much smaller than those from CBCT in three directions, especially in ANT/POST and SUP/INF directions with significance (P = 0.000, 0.001, respectively). During treatment, and 0, 3, 6, 9, and 12 months after treatment, there was no severe urinary and rectal toxicity happened. Conclusion: A primary workflow of 3D-US and CBCT dual-guided radiotherapy has been established, which showed great therapeutic potential with mild to moderate urinary and rectal toxicity for postoperative uterine malignancy patients. But the clinical outcomes of this non-invasive technique need to be investigated further.
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Affiliation(s)
- Yang Li
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, China
| | - Zhen Gong
- Department of Gynecology, Women's Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, China
| | - Mengyu Liu
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, China
| | - Huixin Li
- Department of Gynecology, Women's Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing, China
| | - Han Gao
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, China
| | - Chang Guo
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, China
| | - Le Yu
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, China
| | - Chenjing Zhu
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, China
| | - Zhihua Sun
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, China
| | - Li Sun
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, China
| | - Hanzi Xu
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, China
| | - Xia He
- Department of Radiation Oncology, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Nanjing, China
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Dellmann MFW, Jerg KI, Stratemeier J, Heiman R, Hesser JW, Aschenbrenner KP, Blessing M. Noise-robust breathing-phase estimation on marker-free, ultra low dose X-ray projections for real-time tumor localization via surrogate structures. Z Med Phys 2021; 31:355-364. [PMID: 34088565 DOI: 10.1016/j.zemedi.2021.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 11/11/2020] [Accepted: 04/08/2021] [Indexed: 11/25/2022]
Abstract
PURPOSE This paper presents a novel strategy for feature-based breathing-phase estimation on ultra low-dose X-ray projections for tumor motion control in radiation therapy. METHODS Coarse-scaled Curvelet coefficients are identified as motion sensitive but noise-robust features for this purpose. For feature-based breathing-phase estimation, an ensemble strategy with two classifiers is used. This consensus-based estimation substantially increases tracking reliability by rejection of false positives. The algorithm is evaluated on both synthetic and measured phantom data: Monte Carlo simulated ultra low dose projections for a C-arm X-ray and on the basis of 4D-chest-CTs of eight patients on one hand side and real measurements based on a motion phantom. RESULTS To achieve an accuracy of breathing-phase estimation of more than 95% a fluence between 20 and 400 photons per pixel (open field) is required depending on the patient. Furthermore, the algorithm is evaluated on real ultra low dose projections from an XVI R5.0 system (Elekta AB, Stockholm, Sweden) using an additional lead filter to reduce fluence. The classifiers-consensus-based-gating method estimated the correct position of the test projections in all test cases at a fluence of ∼180 photons per pixel and 92% at a fluence of ∼40 photons per pixel. The deposited dose to patient per image is in the range of nGy. CONCLUSIONS A novel method is presented for estimation of breathing-phases for real-time tumor localization at ultra low dose both on a simulation and a phantom basis. Its accuracy is comparable to state of the art X-ray based algorithms while the released dose to patients is reduced by two to three orders of magnitude compared to conventional template-based approaches. This allows for continuous motion control during irradiation without the need of external markers.
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Affiliation(s)
- Max F W Dellmann
- Department of Data Analysis and Modeling in Medicine, Mannheim Institute for Intelligent Systems in Medicine (MIISM), Medical Faculty of Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany.
| | - Katharina I Jerg
- Department of Data Analysis and Modeling in Medicine, Mannheim Institute for Intelligent Systems in Medicine (MIISM), Medical Faculty of Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Johanna Stratemeier
- Department of Data Analysis and Modeling in Medicine, Mannheim Institute for Intelligent Systems in Medicine (MIISM), Medical Faculty of Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Ron Heiman
- Department of Data Analysis and Modeling in Medicine, Mannheim Institute for Intelligent Systems in Medicine (MIISM), Medical Faculty of Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
| | - Jürgen W Hesser
- Department of Data Analysis and Modeling in Medicine, Mannheim Institute for Intelligent Systems in Medicine (MIISM), Medical Faculty of Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany; Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany; Central Institute for Computer Engineering (ZITI), Heidelberg University, Im Neuenheimer Feld 368, 69120 Heidelberg, Germany
| | - Katharina P Aschenbrenner
- Department of Data Analysis and Modeling in Medicine, Mannheim Institute for Intelligent Systems in Medicine (MIISM), Medical Faculty of Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany; Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Manuel Blessing
- Department of Data Analysis and Modeling in Medicine, Mannheim Institute for Intelligent Systems in Medicine (MIISM), Medical Faculty of Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany
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Krieger M, Giger A, Jud C, Duetschler A, Salomir R, Bieri O, Bauman G, Nguyen D, Cattin PC, Weber DC, Lomax AJ, Zhang Y. Liver-ultrasound-guided lung tumour tracking for scanned proton therapy: a feasibility study. Phys Med Biol 2021; 66:035011. [PMID: 33238246 DOI: 10.1088/1361-6560/abcde6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Pencil beam scanned (PBS) proton therapy of lung tumours is hampered by respiratory motion and the motion-induced density changes along the beam path. In this simulation study, we aim to investigate the effectiveness of proton beam tracking for lung tumours both under ideal conditions and in conjunction with a respiratory motion model guided by real-time ultrasound imaging of the liver. Multiple-breathing-cycle 4DMRIs of the thorax and abdominal 2D ultrasound images were acquired simultaneously for five volunteers. Deformation vector fields extracted from the 4DMRI, referred to as ground truth motion, were used to generate 4DCT(MRI) data sets of two lung cancer patients, resulting in 10 data sets with variable motion patterns. Given the 4DCT(MRI) and the corresponding ultrasound images as surrogate data, a patient-specific motion model was built. The model consists of an autoregressive model and Gaussian process regression for the temporal and spatial prediction, respectively. Two-field PBS plans were optimised on the reference CTs, and 4D dose calculations (4DDC) were used to simulate dose delivery for (a) unmitigated motion, (b) ideal 2D and 3D tracking (both beam adaption and 4DDC based on ground truth motion), and (c) realistic 2D and 3D tracking (beam adaption based on motion predictions, 4DDC on ground truth motion). Model-guided tracking retrieved clinically acceptable target dose homogeneity, as seen in a substantial reduction of the D5%-D95% compared to the non-mitigated simulation. Tracking in 2D and 3D resulted in a similar improvement of the dose homogeneity, as did ideal and realistic tracking simulations. In some cases, however, the tracked deliveries resulted in a shift towards higher or lower dose levels, leading to unacceptable target over- or under-coverage. The presented motion modelling framework was shown to be an accurate motion prediction tool for the use in proton beam tracking. Tracking alone, however, may not always effectively mitigate motion effects, making it necessary to combine it with other techniques such as rescanning.
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Affiliation(s)
- Miriam Krieger
- Center for Proton Therapy, Paul Scherrer Institute (PSI), Villigen PSI, Switzerland. Department of Physics, ETH Zurich, Zurich, Switzerland
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Alina G, Krieger M, Jud C, Duetschler A, Salomir R, Bieri O, Bauman G, Nguyen D, Weber DC, Lomax AJ, Zhang Y, Cattin PC. Liver-ultrasound based motion modelling to estimate 4D dose distributions for lung tumours in scanned proton therapy. ACTA ACUST UNITED AC 2020; 65:235050. [DOI: 10.1088/1361-6560/abaa26] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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Tsai P, Yan G, Liu C, Hung Y, Kahler DL, Park J, Potter N, Li JG, Lu B. Tumor phase recognition using cone‐beam computed tomography projections and external surrogate information. Med Phys 2020; 47:5077-5089. [DOI: 10.1002/mp.14298] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Revised: 05/10/2020] [Accepted: 05/18/2020] [Indexed: 12/25/2022] Open
Affiliation(s)
- Pingfang Tsai
- Department of Radiation Oncology College of Medicine University of Florida Gainesville Fl32610‐0385 USA
| | - Guanghua Yan
- Department of Radiation Oncology College of Medicine University of Florida Gainesville Fl32610‐0385 USA
| | - Chihray Liu
- Department of Radiation Oncology College of Medicine University of Florida Gainesville Fl32610‐0385 USA
| | - Ying‐Chao Hung
- Department of Statistics National Chengchi University Taipei11604 Taiwan
| | - Darren L. Kahler
- Department of Radiation Oncology College of Medicine University of Florida Gainesville Fl32610‐0385 USA
| | - Ji‐Yeon Park
- Department of Radiation Oncology College of Medicine University of Florida Gainesville Fl32610‐0385 USA
| | - Nick Potter
- Department of Radiation Oncology College of Medicine University of Florida Gainesville Fl32610‐0385 USA
| | - Jonathan G. Li
- Department of Radiation Oncology College of Medicine University of Florida Gainesville Fl32610‐0385 USA
| | - Bo Lu
- Department of Radiation Oncology College of Medicine University of Florida Gainesville Fl32610‐0385 USA
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Ferguson D, Harris T, Shi M, Jacobson M, Myronakis M, Lehmann M, Huber P, Morf D, Fueglistaller R, Baturin P, Valencia Lozano I, Williams C, Berbeco R. Automated MV markerless tumor tracking for VMAT. Phys Med Biol 2020; 65:125011. [PMID: 32330918 DOI: 10.1088/1361-6560/ab8cd3] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Tumor tracking during radiotherapy treatment can improve dose accuracy, conformity and sparing of healthy tissue. Many methods have been introduced to tackle this challenge utilizing multiple imaging modalities, including a template matching based approach using the megavoltage (MV) on-board portal imager demonstrated on 3D conformal treatments. However, the complexity of treatments is evolving with the introduction of VMAT and IMRT, and successful motion management is becoming more important due to a trend towards hypofractionation. We have developed a markerless lung tumor tracking algorithm, utilizing the electronic portal imager (EPID) of the treatment machine. The algorithm has been specifically adapted to track during complex treatment deliveries with gantry and MLC motion. The core of the algorithm is an adaptive template matching method that relies on template stability metrics and local relative orientations to perform multiple feature tracking simultaneously. Only a single image is required to initialize the algorithm and features are automatically added, modified or removed in response to the input images. This algorithm was evaluated against images collected during VMAT arcs of a dynamic thorax phantom. Dynamic phantom images were collected during radiation delivery for multiple lung SBRT breathing traces and an example patient data set. The tracking error was 1.34 mm for the phantom data and 0.68 mm for the patient data. A multi-region, markerless tracking algorithm has been developed, capable of tracking multiple features simultaneously without requiring any other a priori information. This novel approach delivers robust target localization during complex treatment delivery. The reported tracking error is similar to previous reports for 3D conformal treatments.
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Affiliation(s)
- D Ferguson
- Brigham and Women's Hospital, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, MA, United States of America
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Bertholet J, Knopf A, Eiben B, McClelland J, Grimwood A, Harris E, Menten M, Poulsen P, Nguyen DT, Keall P, Oelfke U. Real-time intrafraction motion monitoring in external beam radiotherapy. Phys Med Biol 2019; 64:15TR01. [PMID: 31226704 PMCID: PMC7655120 DOI: 10.1088/1361-6560/ab2ba8] [Citation(s) in RCA: 131] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Revised: 05/10/2019] [Accepted: 06/21/2019] [Indexed: 12/25/2022]
Abstract
Radiotherapy (RT) aims to deliver a spatially conformal dose of radiation to tumours while maximizing the dose sparing to healthy tissues. However, the internal patient anatomy is constantly moving due to respiratory, cardiac, gastrointestinal and urinary activity. The long term goal of the RT community to 'see what we treat, as we treat' and to act on this information instantaneously has resulted in rapid technological innovation. Specialized treatment machines, such as robotic or gimbal-steered linear accelerators (linac) with in-room imaging suites, have been developed specifically for real-time treatment adaptation. Additional equipment, such as stereoscopic kilovoltage (kV) imaging, ultrasound transducers and electromagnetic transponders, has been developed for intrafraction motion monitoring on conventional linacs. Magnetic resonance imaging (MRI) has been integrated with cobalt treatment units and more recently with linacs. In addition to hardware innovation, software development has played a substantial role in the development of motion monitoring methods based on respiratory motion surrogates and planar kV or Megavoltage (MV) imaging that is available on standard equipped linacs. In this paper, we review and compare the different intrafraction motion monitoring methods proposed in the literature and demonstrated in real-time on clinical data as well as their possible future developments. We then discuss general considerations on validation and quality assurance for clinical implementation. Besides photon RT, particle therapy is increasingly used to treat moving targets. However, transferring motion monitoring technologies from linacs to particle beam lines presents substantial challenges. Lessons learned from the implementation of real-time intrafraction monitoring for photon RT will be used as a basis to discuss the implementation of these methods for particle RT.
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Affiliation(s)
- Jenny Bertholet
- Joint Department of Physics, Institute of Cancer Research and Royal Marsden NHS
Foundation Trust, London, United
Kingdom
- Author to whom any correspondence should be
addressed
| | - Antje Knopf
- Department of Radiation Oncology,
University Medical Center
Groningen, University of Groningen, The
Netherlands
| | - Björn Eiben
- Department of Medical Physics and Biomedical
Engineering, Centre for Medical Image Computing, University College London, London,
United Kingdom
| | - Jamie McClelland
- Department of Medical Physics and Biomedical
Engineering, Centre for Medical Image Computing, University College London, London,
United Kingdom
| | - Alexander Grimwood
- Joint Department of Physics, Institute of Cancer Research and Royal Marsden NHS
Foundation Trust, London, United
Kingdom
| | - Emma Harris
- Joint Department of Physics, Institute of Cancer Research and Royal Marsden NHS
Foundation Trust, London, United
Kingdom
| | - Martin Menten
- Joint Department of Physics, Institute of Cancer Research and Royal Marsden NHS
Foundation Trust, London, United
Kingdom
| | - Per Poulsen
- Department of Oncology, Aarhus University Hospital, Aarhus,
Denmark
| | - Doan Trang Nguyen
- ACRF Image X Institute, University of Sydney, Sydney,
Australia
- School of Biomedical Engineering,
University of Technology
Sydney, Sydney, Australia
| | - Paul Keall
- ACRF Image X Institute, University of Sydney, Sydney,
Australia
| | - Uwe Oelfke
- Joint Department of Physics, Institute of Cancer Research and Royal Marsden NHS
Foundation Trust, London, United
Kingdom
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Inter-fractional Respiratory Motion Modelling from Abdominal Ultrasound: A Feasibility Study. PREDICTIVE INTELLIGENCE IN MEDICINE 2019. [DOI: 10.1007/978-3-030-32281-6_2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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Trnková P, Knäusl B, Actis O, Bert C, Biegun AK, Boehlen TT, Furtado H, McClelland J, Mori S, Rinaldi I, Rucinski A, Knopf AC. Clinical implementations of 4D pencil beam scanned particle therapy: Report on the 4D treatment planning workshop 2016 and 2017. Phys Med 2018; 54:121-130. [PMID: 30337001 DOI: 10.1016/j.ejmp.2018.10.002] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2018] [Revised: 09/18/2018] [Accepted: 10/02/2018] [Indexed: 12/14/2022] Open
Abstract
In 2016 and 2017, the 8th and 9th 4D treatment planning workshop took place in Groningen (the Netherlands) and Vienna (Austria), respectively. This annual workshop brings together international experts to discuss research, advances in clinical implementation as well as problems and challenges in 4D treatment planning, mainly in spot scanned proton therapy. In the last two years several aspects like treatment planning, beam delivery, Monte Carlo simulations, motion modeling and monitoring, QA phantoms as well as 4D imaging were thoroughly discussed. This report provides an overview of discussed topics, recent findings and literature review from the last two years. Its main focus is to highlight translation of 4D research into clinical practice and to discuss remaining challenges and pitfalls that still need to be addressed and to be overcome.
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Affiliation(s)
- Petra Trnková
- HollandPTC, P.O. Box 5046, 2600 GA Delft, the Netherlands; Erasmus MC, P.O. Box 5201, 3008 AE Rotterdam, the Netherlands
| | - Barbara Knäusl
- Department of Radiation Oncology, Division of Medical Radiation Physics, Christian Doppler Laboratory for Medical Radiation Research for Radiation Oncology, Medical University of Vienna/AKH Vienna, Austria
| | - Oxana Actis
- Paul Scherrer Institute (PSI), 5232 Villigen, Switzerland
| | - Christoph Bert
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
| | - Aleksandra K Biegun
- KVI-Center for Advanced Radiation Technology, University of Groningen, Groningen, the Netherlands
| | - Till T Boehlen
- Paul Scherrer Institute (PSI), 5232 Villigen, Switzerland
| | - Hugo Furtado
- Department of Radiation Oncology, Division of Medical Radiation Physics, Christian Doppler Laboratory for Medical Radiation Research for Radiation Oncology, Medical University of Vienna/AKH Vienna, Austria
| | - Jamie McClelland
- Centre for Medical Image Computing, Dept. Medical Physics and Biomedical, University College London, London, UK
| | - Shinichiro Mori
- National Institute of Radiological Sciences for Charged Particle Therapy, Chiba, Japan
| | - Ilaria Rinaldi
- Lyon 1 University and CNRS/IN2P3, UMR 5822, 69622 Villeurbanne, France; MAASTRO Clinic, P.O. Box 3035, 6202 NA Maastricht, the Netherlands
| | | | - Antje C Knopf
- University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, Groningen, the Netherlands.
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