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Mein S, Wuyckens S, Li X, Both S, Carabe A, Vera MC, Engwall E, Francesco F, Graeff C, Gu W, Hong L, Inaniwa T, Janssens G, de Jong B, Li T, Liang X, Liu G, Lomax A, Mackie T, Mairani A, Mazal A, Nesteruk KP, Paganetti H, Pérez Moreno JM, Schreuder N, Soukup M, Tanaka S, Tessonnier T, Volz L, Zhao L, Ding X. Particle arc therapy: Status and potential. Radiother Oncol 2024; 199:110434. [PMID: 39009306 DOI: 10.1016/j.radonc.2024.110434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Revised: 06/23/2024] [Accepted: 07/10/2024] [Indexed: 07/17/2024]
Abstract
There is a rising interest in developing and utilizing arc delivery techniques with charged particle beams, e.g., proton, carbon or other ions, for clinical implementation. In this work, perspectives from the European Society for Radiotherapy and Oncology (ESTRO) 2022 physics workshop on particle arc therapy are reported. This outlook provides an outline and prospective vision for the path forward to clinically deliverable proton, carbon, and other ion arc treatments. Through the collaboration among industry, academic, and clinical research and development, the scientific landscape and outlook for particle arc therapy are presented here to help our community understand the physics, radiobiology, and clinical principles. The work is presented in three main sections: (i) treatment planning, (ii) treatment delivery, and (iii) clinical outlook.
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Affiliation(s)
- Stewart Mein
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA, USA; Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany; Division of Molecular and Translational Radiation Oncology, National Center for Tumor Diseases (NCT), Heidelberg University Hospital, Heidelberg, Germany; Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Sophie Wuyckens
- UCLouvain, Molecular Imaging, Radiotherapy and Oncology (MIRO), Brussels, Belgium
| | - Xiaoqiang Li
- Department of Radiation Oncology, Corewell Health, William Beaumont University Hospital, Proton Therapy Center, Royal Oak, MI, USA
| | - Stefan Both
- Department of Radiation Oncology, University Medical Center Groningen, Groningen, The Netherlands
| | | | - Macarena Chocan Vera
- UCLouvain, Molecular Imaging, Radiotherapy and Oncology (MIRO), Brussels, Belgium
| | | | | | - Christian Graeff
- GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt, Germany; Technische Universität Darmstadt, Institut für Physik Kondensierter Materie, Darmstadt, Germany
| | - Wenbo Gu
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA, USA
| | - Liu Hong
- Ion Beam Applications SA, Louvain-la-Neuve, Belgium
| | - Taku Inaniwa
- Department of Accelerator and Medical Physics, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba, Japan; Department of Medical Physics and Engineering, Graduate School of Medicine, Division of Health Sciences, Osaka University, Osaka, Japan
| | | | - Bas de Jong
- Department of Radiation Oncology, University Medical Center Groningen, Groningen, The Netherlands
| | - Taoran Li
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA, USA
| | - Xiaoying Liang
- Department of Radiation Oncology, Mayo Clinic Jacksonville, Jacksonville, FL, USA
| | - Gang Liu
- Department of Radiation Oncology, Corewell Health, William Beaumont University Hospital, Proton Therapy Center, Royal Oak, MI, USA; Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Antony Lomax
- Centre for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland; ETH, Department of Physics, Zürich, Switzerland
| | - Thomas Mackie
- Department of Human Oncology, University of Wisconsin School of Medicine, Madison, WI, USA
| | - Andrea Mairani
- Heidelberg Ion-Beam Therapy Center (HIT), Heidelberg, Germany; National Centre of Oncological Hadrontherapy (CNAO), Medical Physics, Pavia, Italy
| | | | - Konrad P Nesteruk
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, USA; Harvard Medical School, Boston, USA
| | - Harald Paganetti
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, USA; Harvard Medical School, Boston, USA
| | | | | | | | - Sodai Tanaka
- Department of Accelerator and Medical Physics, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba, Japan
| | | | - Lennart Volz
- GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt, Germany; Technische Universität Darmstadt, Institut für Physik Kondensierter Materie, Darmstadt, Germany
| | - Lewei Zhao
- Department of Radiation Oncology, Stanford University, Stanford, CA, USA
| | - Xuanfeng Ding
- Department of Radiation Oncology, Corewell Health, William Beaumont University Hospital, Proton Therapy Center, Royal Oak, MI, USA.
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Wuyckens S, Wase V, Marthin O, Sundström J, Janssens G, Borderias-Villarroel E, Souris K, Sterpin E, Engwall E, Lee JA. Efficient proton arc optimization and delivery through energy layer pre-selection and post-filtering. Med Phys 2024; 51:4982-4995. [PMID: 38742774 DOI: 10.1002/mp.17127] [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: 12/08/2023] [Revised: 04/16/2024] [Accepted: 04/30/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Proton arc therapy (PAT) has emerged as a promising approach for improving dose distribution, but also enabling simpler and faster treatment delivery in comparison to conventional proton treatments. However, the delivery speed achievable in proton arc relies on dedicated algorithms, which currently do not generate plans with a clear speed-up and sometimes even result in increased delivery time. PURPOSE This study aims to address the challenge of minimizing delivery time through a hybrid method combining a fast geometry-based energy layer (EL) pre-selection with a dose-based EL filtering, and comparing its performance to a baseline approach without filtering. METHODS Three methods of EL filtering were developed: unrestricted, switch-up (SU), and switch-up gap (SU gap) filtering. The unrestricted method filters the lowest weighted EL while the SU gap filtering removes the EL around a new SU to minimize the gantry rotation braking. The SU filtering removes the lowest weighted group of EL that includes a SU. These filters were combined with the RayStation dynamic proton arc optimization framework energy layer selection and spot assignment (ELSA). Four bilateral oropharyngeal and four lung cancer patients' data were used for evaluation. Objective function values, target coverage robustness, organ-at-risk doses and normal tissue complication probability evaluations, as well as comparisons to intensity-modulated proton therapy (IMPT) plans, were used to assess plan quality. RESULTS The SU gap filtering algorithm performed best in five out of the eight cases, maintaining plan quality within tolerance while reducing beam delivery time, in particular for the oropharyngeal cohort. It achieved up to approximately 22% and 15% reduction in delivery time for oropharyngeal and lung treatment sites, respectively. The unrestricted filtering algorithm followed closely. In contrast, the SU filtering showed limited improvement, suppressing one or two SU without substantial delivery time shortening. Robust target coverage was kept within 1% of variation compared to the PAT baseline plan while organs-at-risk doses slightly decreased or kept about the same for all patients. CONCLUSIONS This study provides insights to accelerate PAT delivery without compromising plan quality. These advancements could enhance treatment efficiency and patient throughput.
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Affiliation(s)
- Sophie Wuyckens
- UCLouvain, Institut de recherche expérimentale et clinique, Molecular Imaging and Radiation Oncology Laboratory, Brussels, Belgium
| | | | | | | | - Guillaume Janssens
- UCLouvain, Institute of Information and Communication Technologies, Louvain-La-Neuve, Belgium
- Ion Beam Applications SA, Louvain-La-Neuve, Belgium
| | - Elena Borderias-Villarroel
- UCLouvain, Institut de recherche expérimentale et clinique, Molecular Imaging and Radiation Oncology Laboratory, Brussels, Belgium
| | - Kevin Souris
- UCLouvain, Institut de recherche expérimentale et clinique, Molecular Imaging and Radiation Oncology Laboratory, Brussels, Belgium
- Ion Beam Applications SA, Louvain-La-Neuve, Belgium
| | - Edmond Sterpin
- UCLouvain, Institut de recherche expérimentale et clinique, Molecular Imaging and Radiation Oncology Laboratory, Brussels, Belgium
- KULeuven, Department of Oncology, Laboratory of experimental radiotherapy, Leuven, Belgium
- Particle Therapy Interuniversity Center Leuven - PARTICLE, Leuven, Belgium
| | | | - John A Lee
- UCLouvain, Institut de recherche expérimentale et clinique, Molecular Imaging and Radiation Oncology Laboratory, Brussels, Belgium
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Wase V, Marthin O, Fredriksson A, Finnson A. Optimizing the traversal time for gantry trajectories for proton arc therapy treatment plans. Phys Med Biol 2024; 69:065007. [PMID: 38359454 DOI: 10.1088/1361-6560/ad29b7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 02/15/2024] [Indexed: 02/17/2024]
Abstract
Background.Proton arc therapy (PAT) is an emerging radiation therapy technique where either the gantry or the patient continuously rotates during the irradiation treatment. One of the perceived advantages of PAT is the reduced treatment time, but it is still unclear exactly how long these treatment times will be, given that no machine capable of its delivery is available on the market at the time of writing.Objective.We introduce the algorithm arc trajectory optimization method (ATOM), which aims to determine an efficient velocity profile for the gantry for rapid delivery of a given proton arc treatment plan. This algorithm could be used to minimize the delivery time of a proton arc plan without changing the plan or updating the machine.Approach.ATOM computes the trajectory with the shortest delivery time while ensuring there is enough time to deliver all spots in each energy layer and switch energy between layers. The feasibility of the dynamic gantry movement was assured by enforcing maximum and minimum limits for velocity, acceleration, and jerk. This was achieved by discretizing the gantry velocity and combining theA* algorithm with the open-source motion generation library Ruckig. The algorithm was tested on a synthetic data set as well as a liver case, a prostate case and a head and neck case.Main results.Arc trajectories for plans with 360 energy layers were calculated in under a second using 256 discrete velocities. The delivery time of the liver case, the prostate case and the head and neck case were 284 s, 288 s and 309 s respectively, for 180 energy layers.Significance.ATOM is an open-source C++ library with a Python interface that rapidly generates velocity profiles, making it a highly efficient tool for determining proton arc delivery times, which could be integrated into the treatment planning process.
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Affiliation(s)
- V Wase
- RaySearch Laboratories AB, Stockholm, Sweden
| | - O Marthin
- RaySearch Laboratories AB, Stockholm, Sweden
| | | | - A Finnson
- RaySearch Laboratories AB, Stockholm, Sweden
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Qian Y, Fan Q, Dao R, Li X, Yang Z, Zhang S, Yang K, Quan H, Tu B, Ding X, Liu G. A novel planning framework for efficient spot-scanning proton arc therapy via particle swarm optimization (SPArc- particle swarm). Phys Med Biol 2023; 69:015004. [PMID: 38041874 DOI: 10.1088/1361-6560/ad11a4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 12/01/2023] [Indexed: 12/04/2023]
Abstract
Objective.Delivery efficiency is the bottleneck of spot-scanning proton arc therapy (SPArc) because of the numerous energy layers (ELs) ascending switches. This study aims to develop a new algorithm to mitigate the need for EL ascending via water equivalent thickness (WET) sector selection followed by particle swarm optimization (SPArc-particle swarm).Approach.SPArc-particle swarmdivided the full arc trajectory into the optimal sectors based on K-means clustering analysis of the relative mean WET. Within the sector, particle swarm optimization was used to minimize the total energy switch time, optimizing the energy selection integrated with the EL delivery sequence and relationship. This novel planning framework was implemented on the open-source platform matRad (Department of Medical Physics in Radiation Oncology, German Cancer Research Center-DKFZ). Three representative cases (brain, liver, and prostate cancer) were selected for testing purposes. Two kinds of plans were generated: SPArc_seq and SPArc-particle swarm. The plan quality and delivery efficiency were evaluated.Main results. With a similar plan quality, the delivery efficiency was significantly improved using SPArc-particle swarmcompared to SPArc_seq. More specifically, it reduces the number of ELs ascending switching compared to the SPArc_seq (from 21 to 7 in the brain, from 21 to 5 in the prostate, from 21 to 6 in the liver), leading to a 16%-26% reduction of the beam delivery time (BDT) in the SPArc treatment.Significance. A novel planning framework, SPArc-particle swarm, could significantly improve the delivery efficiency, which paves the roadmap towards routine clinical implementation.
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Affiliation(s)
- Yujia Qian
- Wuhan University, School of Physics and Technology, Wuhan, People's Republic of China
| | - Qingkun Fan
- Wuhan University, School of Mathematics and Statistics, Wuhan, People's Republic of China
| | - Riao Dao
- Wuhan University, School of Physics and Technology, Wuhan, People's Republic of China
| | - Xiaoqiang Li
- Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, MI, United States of America
| | - Zhijian Yang
- Wuhan University, School of Mathematics and Statistics, Wuhan, People's Republic of China
| | - Sheng Zhang
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China
- Hubei Key Laboratory of Precision Radiation Oncology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China
- Institute of Radiation Oncology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan,430022, People's Republic of China
| | - Kunyu Yang
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China
- Hubei Key Laboratory of Precision Radiation Oncology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China
- Institute of Radiation Oncology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan,430022, People's Republic of China
| | - Hong Quan
- Wuhan University, School of Physics and Technology, Wuhan, People's Republic of China
| | - Biao Tu
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China
- Hubei Key Laboratory of Precision Radiation Oncology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China
- Institute of Radiation Oncology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan,430022, People's Republic of China
| | - Xuanfeng Ding
- Department of Radiation Oncology, Corewell Health William Beaumont University Hospital, Royal Oak, MI, United States of America
| | - Gang Liu
- Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China
- Hubei Key Laboratory of Precision Radiation Oncology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, People's Republic of China
- Institute of Radiation Oncology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan,430022, People's Republic of China
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