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Hobson MA, Hu Y, Caldwell B, Cohen GN, Glide-Hurst C, Huang L, Jackson PD, Jang S, Langner U, Lee HJ, Levesque IR, Narayanan S, Park JC, Steffen J, Wu QJ, Zhou Y. AAPM Task Group 334: A guidance document to using radiotherapy immobilization devices and accessories in an MR environment. Med Phys 2024; 51:3822-3849. [PMID: 38648857 PMCID: PMC11330642 DOI: 10.1002/mp.17061] [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: 07/10/2023] [Revised: 11/13/2023] [Accepted: 03/28/2024] [Indexed: 04/25/2024] Open
Abstract
Use of magnetic resonance (MR) imaging in radiation therapy has increased substantially in recent years as more radiotherapy centers are having MR simulators installed, requesting more time on clinical diagnostic MR systems, or even treating with combination MR linear accelerator (MR-linac) systems. With this increased use, to ensure the most accurate integration of images into radiotherapy (RT), RT immobilization devices and accessories must be able to be used safely in the MR environment and produce minimal perturbations. The determination of the safety profile and considerations often falls to the medical physicist or other support staff members who at a minimum should be a Level 2 personnel as per the ACR. The purpose of this guidance document will be to help guide the user in making determinations on MR Safety labeling (i.e., MR Safe, Conditional, or Unsafe) including standard testing, and verification of image quality, when using RT immobilization devices and accessories in an MR environment.
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Affiliation(s)
- Maritza A Hobson
- Department of Radiation Oncology, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Yanle Hu
- Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA
| | - Barrett Caldwell
- School of Industrial Engineering, Purdue University, West Lafayette, Indiana, USA
- School of Aeronautics and Astronautics, Purdue University, West Lafayette, Indiana, USA
| | - Gil'ad N Cohen
- Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York, USA
| | - Carri Glide-Hurst
- Department of Human Oncology, University of Wisconsin--Madison, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin--Madison, Madison, Wisconsin, USA
| | - Long Huang
- Department of Radiation Oncology, University of Utah, Salt Lake City, Utah, USA
| | - Paul D Jackson
- Department of Radiation Oncology, Henry Ford Health System, Detroit, Michigan, USA
| | - Sunyoung Jang
- Department of Radiation Oncology, Penn State College of Medicine, Hershey, Pennsylvania, USA
| | - Ulrich Langner
- Department of Radiation Oncology, Rhode Island Hospital, Providence, Rhode Island, USA
| | - Hannah J Lee
- Corewell Health William Beaumont University Hospital, Royal Oak, Michigan, USA
| | - Ives R Levesque
- Gerald Bronfman Department of Oncology and Medical Physics Unit, McGill University, Montreal, QC, Canada
- Department of Medical Physics, McGill University Health Centre, Cedars Cancer Centre, Montreal, QC, Canada
| | - Sreeram Narayanan
- Department of Radiation Oncology, Virginia Mason Cancer Institute, Seattle, Washington, USA
| | - Justin C Park
- Division of Medical Physics, Department of Radiation Oncology, Mayo Clinic, Jacksonville, Florida, USA
| | | | - Q Jackie Wu
- Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina, USA
| | - Yong Zhou
- Department of Radiology Services, Corewell Health, Grand Rapids, Michigan, USA
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Glide-Hurst CK, Paulson ES, McGee K, Tyagi N, Hu Y, Balter J, Bayouth J. Task group 284 report: magnetic resonance imaging simulation in radiotherapy: considerations for clinical implementation, optimization, and quality assurance. Med Phys 2021; 48:e636-e670. [PMID: 33386620 DOI: 10.1002/mp.14695] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 12/12/2020] [Accepted: 12/16/2020] [Indexed: 12/18/2022] Open
Abstract
The use of dedicated magnetic resonance simulation (MR-SIM) platforms in Radiation Oncology has expanded rapidly, introducing new equipment and functionality with the overall goal of improving the accuracy of radiation treatment planning. However, this emerging technology presents a new set of challenges that need to be addressed for safe and effective MR-SIM implementation. The major objectives of this report are to provide recommendations for commercially available MR simulators, including initial equipment selection, siting, acceptance testing, quality assurance, optimization of dedicated radiation therapy specific MR-SIM workflows, patient-specific considerations, safety, and staffing. Major contributions include guidance on motion and distortion management as well as MRI coil configurations to accommodate patients immobilized in the treatment position. Examples of optimized protocols and checklists for QA programs are provided. While the recommendations provided here are minimum requirements, emerging areas and unmet needs are also highlighted for future development.
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Affiliation(s)
- Carri K Glide-Hurst
- Department of Human Oncology, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | - Eric S Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Kiaran McGee
- Department of Diagnostic Radiology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Neelam Tyagi
- Medical Physics Department, Memorial Sloan-Kettering Cancer Center, New York, NY, 10065, USA
| | - Yanle Hu
- Department of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, 85054, USA
| | - James Balter
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - John Bayouth
- Department of Human Oncology, University of Wisconsin-Madison, Madison, WI, 53792, USA
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Speight R, Dubec M, Eccles CL, George B, Henry A, Herbert T, Johnstone RI, Liney GP, McCallum H, Schmidt MA. IPEM topical report: guidance on the use of MRI for external beam radiotherapy treatment planning . Phys Med Biol 2021; 66:055025. [PMID: 33450742 DOI: 10.1088/1361-6560/abdc30] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 01/15/2021] [Indexed: 12/18/2022]
Abstract
This document gives guidance for multidisciplinary teams within institutions setting up and using an MRI-guided radiotherapy (RT) treatment planning service. It has been written by a multidisciplinary working group from the Institute of Physics and Engineering in Medicine (IPEM). Guidance has come from the experience of the institutions represented in the IPEM working group, in consultation with other institutions, and where appropriate references are given for any relevant legislation, other guidance documentation and information in the literature. Guidance is only given for MRI acquired for external beam RT treatment planning in a CT-based workflow, i.e. when MRI is acquired and registered to CT with the purpose of aiding delineation of target or organ at risk volumes. MRI use for treatment response assessment, MRI-only RT and other RT treatment types such as brachytherapy and gamma radiosurgery are not considered within the scope of this document. The aim was to produce guidance that will be useful for institutions who are setting up and using a dedicated MR scanner for RT (referred to as an MR-sim) and those who will have limited time on an MR scanner potentially managed outside of the RT department, often by radiology. Although not specifically covered in this document, there is an increase in the use of hybrid MRI-linac systems worldwide and brief comments are included to highlight any crossover with the early implementation of this technology. In this document, advice is given on introducing a RT workload onto a non-RT-dedicated MR scanner, as well as planning for installation of an MR scanner dedicated for RT. Next, practical guidance is given on the following, in the context of RT planning: training and education for all staff working in and around an MR scanner; RT patient set-up on an MR scanner; MRI sequence optimisation for RT purposes; commissioning and quality assurance (QA) to be performed on an MR scanner; and MRI to CT registration, including commissioning and QA.
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Affiliation(s)
- Richard Speight
- Leeds Cancer Centre, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom
| | - Michael Dubec
- The Christie NHS Foundation Trust and the University of Manchester, Manchester, United Kingdom
| | - Cynthia L Eccles
- The Christie NHS Foundation Trust and the University of Manchester, Manchester, United Kingdom
| | - Ben George
- University of Oxford and GenesisCare, Oxford, United Kingdom
| | - Ann Henry
- Leeds Cancer Centre, Leeds Teaching Hospitals NHS Trust and University of Leeds, Leeds, United Kingdom
| | - Trina Herbert
- Royal Marsden NHS Foundation Trust, London, United Kingdom
| | | | - Gary P Liney
- Ingham Institute for Applied Medical Research and Liverpool Cancer Therapy Centre, Liverpool, Sydney, NSW 2170, Australia
| | - Hazel McCallum
- Translational and Clinical Research Institute, Newcastle University and Northern Centre for Cancer Care, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, United Kingdom
| | - Maria A Schmidt
- Royal Marsden NHS Foundation Trust and Institute of Cancer Research, London, United Kingdom
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4
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Zimmermann L, Buschmann M, Herrmann H, Heilemann G, Kuess P, Goldner G, Nyholm T, Georg D, Nesvacil N. An MR-only acquisition and artificial intelligence based image-processing protocol for photon and proton therapy using a low field MR. Z Med Phys 2021; 31:78-88. [PMID: 33455822 DOI: 10.1016/j.zemedi.2020.10.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 09/14/2020] [Accepted: 10/27/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVE Recent developments on synthetically generated CTs (sCT), hybrid MRI linacs and MR-only simulations underlined the clinical feasibility and acceptance of MR guided radiation therapy. However, considering clinical application of open and low field MR with a limited field of view can result in truncation of the patient's anatomy which further affects the MR to sCT conversion. In this study an acquisition protocol and subsequent MR image stitching is proposed to overcome the limited field of view restriction of open MR scanners, for MR-only photon and proton therapy. MATERIAL AND METHODS 12 prostate cancer patients scanned with an open 0.35T scanner were included. To obtain the full body contour an enhanced imaging protocol including two repeated scans after bilateral table movement was introduced. All required structures (patient contour, target and organ at risk) were delineated on a post-processed combined transversal image set (stitched MRI). The postprocessed MR was converted into a sCT by a pretrained neural network generator. Inversely planned photon and proton plans (VMAT and SFUD) were designed using the sCT and recalculated for rigidly and deformably registered CT images and compared based on D2%, D50%, V70Gy for organs at risk and based on D2%, D50%, D98% for the CTV and PTV. The stitched MRI and the untruncated MRI were compared to the CT, and the maximum surface distance was calculated. The sCT was evaluated with respect to delineation accuracy by comparing on stitched MRI and sCT using the DICE coefficient for femoral bones and the whole body. RESULTS Maximum surface distance analysis revealed uncertainties in lateral direction of 1-3mm on average. DICE coefficient analysis confirms good performance of the sCT conversion, i.e. 92%, 93%, and 100% were obtained for femoral bone left and right and whole body. Dose comparison resulted in uncertainties below 1% between deformed CT and sCT and below 2% between rigidly registered CT and sCT in the CTV for photon and proton treatment plans. DISCUSSION A newly developed acquisition protocol for open MR scanners and subsequent Sct generation revealed good acceptance for photon and proton therapy. Moreover, this protocol tackles the restriction of the limited FOVs and expands the capacities towards MR guided proton therapy with horizontal beam lines.
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Affiliation(s)
- Lukas Zimmermann
- Division of Medical Radiation Physics, Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria.
| | - Martin Buschmann
- Division of Medical Radiation Physics, Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria
| | - Harald Herrmann
- Division of Medical Radiation Physics, Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria
| | - Gerd Heilemann
- Division of Medical Radiation Physics, Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria
| | - Peter Kuess
- Division of Medical Radiation Physics, Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria
| | - Gregor Goldner
- Division of Medical Radiation Physics, Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria
| | - Tufve Nyholm
- Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | - Dietmar Georg
- Division of Medical Radiation Physics, Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria
| | - Nicole Nesvacil
- Division of Medical Radiation Physics, Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria
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5
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Hu Q, Yu VY, Yang Y, Hu P, Sheng K, Lee PP, Kishan AU, Raldow AC, O'Connell DP, Woods KE, Cao M. Practical Safety Considerations for Integration of Magnetic Resonance Imaging in Radiation Therapy. Pract Radiat Oncol 2020; 10:443-453. [PMID: 32781246 DOI: 10.1016/j.prro.2020.07.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 07/16/2020] [Accepted: 07/28/2020] [Indexed: 12/29/2022]
Abstract
Interest in integrating magnetic resonance imaging (MRI) in radiation therapy (RT) practice has increased dramatically in recent years owing to its unique advantages such as excellent soft tissue contrast and capability of measuring biological properties. Continuous real-time imaging for intrafractional motion tracking without ionizing radiation serves as a particularly attractive feature for applications in RT. Despite its many advantages, the integration of MRI in RT workflows is not straightforward, with many unmet needs. MR safety remains one of the key challenges and concerns in the clinical implementation of MR simulators and MR-guided radiation therapy systems in radiation oncology. Most RT staff are not accustomed to working in an environment with a strong magnetic field. There are specific requirements in RT that are different from diagnostic applications. A large variety of implants and devices used in routine RT practice do not have clear MR safety labels. RT-specific imaging pulse sequences focusing on fast acquisition, high spatial integrity, and continuous, real-time acquisition require additional MR safety testing and evaluation. This article provides an overview of MR safety tailored toward RT staff, followed by discussions on specific requirements and challenges associated with MR safety in the RT environment. Strategies and techniques for developing an MR safety program specific to RT are presented and discussed.
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Affiliation(s)
- Qiongge Hu
- Department of Radiation Oncology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Victoria Y Yu
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Yingli Yang
- Department of Radiation Oncology, University of California, Los Angeles, California
| | - Peng Hu
- Department of Radiology, University of California, Los Angeles, California
| | - Ke Sheng
- Department of Radiation Oncology, University of California, Los Angeles, California
| | - Percy P Lee
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Amar U Kishan
- Department of Radiation Oncology, University of California, Los Angeles, California
| | - Ann C Raldow
- Department of Radiation Oncology, University of California, Los Angeles, California
| | - Dylan P O'Connell
- Department of Radiation Oncology, University of California, Los Angeles, California
| | - Kaley E Woods
- Department of Radiation Oncology, University of California, Los Angeles, California
| | - Minsong Cao
- Department of Radiation Oncology, University of California, Los Angeles, California.
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Li M, Shan S, Chandra SS, Liu F, Crozier S. Fast geometric distortion correction using a deep neural network: Implementation for the 1 Tesla MRI‐Linac system. Med Phys 2020; 47:4303-4315. [DOI: 10.1002/mp.14382] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 06/18/2020] [Accepted: 07/04/2020] [Indexed: 11/08/2022] Open
Affiliation(s)
- Mao Li
- School of Information Technology and Electrical Engineering University of Queensland Brisbane QLD 4067 Australia
| | - Shanshan Shan
- School of Information Technology and Electrical Engineering University of Queensland Brisbane QLD 4067 Australia
| | - Shekhar S. Chandra
- School of Information Technology and Electrical Engineering University of Queensland Brisbane QLD 4067 Australia
| | - Feng Liu
- School of Information Technology and Electrical Engineering University of Queensland Brisbane QLD 4067 Australia
| | - Stuart Crozier
- School of Information Technology and Electrical Engineering University of Queensland Brisbane QLD 4067 Australia
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7
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Abstract
Modern radiation therapy treatment planning and delivery is a complex process that relies on advanced imaging and computing technology as well as expertise from the medical team. The process begins with simulation imaging, in which three-dimensional computed tomography images (or magnetic resonance images in some cases) are used to characterize the patient anatomy. From there, the radiation oncologist delineates the relevant target/tumor volumes and normal tissue and communicates the goals for treatment planning. The planning process attempts to generate a radiation therapy treatment plan that will deliver a therapeutic dose of radiation to the tumor while sparing nearby normal tissue.
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8
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Eccles CL, Campbell M. Keeping Up with the Hybrid Magnetic Resonance Linear Accelerators: How Do Radiation Therapists Stay Current in the Era of Hybrid Technologies? J Med Imaging Radiat Sci 2019; 50:195-198. [PMID: 31064719 DOI: 10.1016/j.jmir.2019.04.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Revised: 03/30/2019] [Accepted: 04/01/2019] [Indexed: 01/09/2023]
Abstract
The benefits of integrating magnetic resonance imaging (MRI) into radiotherapy planning have long been extolled, first appearing in the literature as early as 1986. Most often described as a tool to be used when registered to a planning computed tomography to improve target and organ at risk delineation, the use of MRI for on-board image guidance and as a sole imaging modality throughout the entire radiotherapy pathway is quickly becoming a reality for appropriately selected patient populations in academic centres throughout the world. With the commercialization of these integrated magnetic resonance - radiotherapy delivery systems, an MRI-only workflow will prove beneficial, with MRI being used for treatment planning, localization, and on-treatment plan adaptation. Despite these technological advancements, recent surveys indicate uptake of MRI in radiotherapy as a routine practice has proven challenging. Reasons cited for this slow uptake were primarily related to health economics and/or accessibility. Furthermore, these surveys, like much of the academic literature, shy away from focusing on safe, sustainable staffing models enabled by comprehensive and appropriate education and training. In stark contrast to conebeam computed tomography guided therapy, magnetic resonance - radiotherapy systems are currently being operated by teams of physicians, radiographers, and physicists because of the diverse and complex tasks required to deliver treatment. The pace of innovation in RT remains high and unfortunately the window of opportunity to implement appropriate education continues to narrow. It is vital that we establish a framework to future-proof our profession. In the era of magnetic resonance-guided radiotherapy, we have yet to address the question of how to devise a consensus on the requisite knowledge, skills, and competence for radiation therapists and therapy radiographers using and/or operating MRI that provides guidance, without becoming prohibitively costly or time consuming.
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Affiliation(s)
- Cynthia L Eccles
- Department of Radiotherapy, The Christie NHS Foundation Trust and Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.
| | - Mikki Campbell
- Radiation Treatment Program, Odette Cancer Centre at Sunnybrook Health Sciences Centre, Toronto, Canada
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Tijssen RHN, Philippens MEP, Paulson ES, Glitzner M, Chugh B, Wetscherek A, Dubec M, Wang J, van der Heide UA. MRI commissioning of 1.5T MR-linac systems - a multi-institutional study. Radiother Oncol 2018; 132:114-120. [PMID: 30825959 DOI: 10.1016/j.radonc.2018.12.011] [Citation(s) in RCA: 100] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Revised: 11/14/2018] [Accepted: 12/11/2018] [Indexed: 10/27/2022]
Abstract
BACKGROUND Magnetic Resonance linear accelerator (MR-linac) systems represent a new type of technology that allows for online MR-guidance for high precision radiotherapy (RT). Currently, the first MR-linac installations are being introduced clinically. Since the imaging performance of these integrated MR-linac systems is critical for their application, a thorough commissioning of the MRI performance is essential. However, guidelines on the commissioning of MR-guided RT systems are not yet defined and data on the performance of MR-linacs are not yet available. MATERIALS & METHODS Here we describe a comprehensive commissioning protocol, which contains standard MRI performance measurements as well as dedicated hybrid tests that specifically assess the interactions between the Linac and the MRI system. The commissioning results of four MR-linac systems are presented in a multi-center study. RESULTS Although the four systems showed similar performance in all the standard MRI performance tests, some differences were observed relating to the hybrid character of the systems. Field homogeneity measurements identified differences in the gantry shim configuration, which was later confirmed by the vendor. CONCLUSION Our results highlight the importance of dedicated hybrid commissioning tests and the ability to compare the machines between institutes at this very early stage of clinical introduction. Until formal guidelines and tolerances are defined the tests described in this study may be used as a practical guideline. Moreover, the multi-center results provide initial bench mark data for future MR-linac installations.
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Affiliation(s)
- Rob H N Tijssen
- Department of Radiotherapy, University Medical Center Utrecht, the Netherlands.
| | | | - Eric S Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, United States
| | - Markus Glitzner
- Department of Radiotherapy, University Medical Center Utrecht, the Netherlands
| | - Brige Chugh
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Andreas Wetscherek
- Joint Department of Physics, the Institute of Cancer Research and the Royal Marsden Hospital NHS Foundation Trust, London, UK
| | - Michael Dubec
- The Christie NHS Foundation Trust and the University of Manchester, UK
| | - Jihong Wang
- Department of Radiation Physics, the University of Texas MD Anderson Cancer Center, Houston, United States
| | - Uulke A van der Heide
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
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10
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Das IJ, McGee KP, Tyagi N, Wang H. Role and future of MRI in radiation oncology. Br J Radiol 2018; 92:20180505. [PMID: 30383454 DOI: 10.1259/bjr.20180505] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Technical innovations and developments in areas such as disease localization, dose calculation algorithms, motion management and dose delivery technologies have revolutionized radiation therapy resulting in improved patient care with superior outcomes. A consequence of the ability to design and accurately deliver complex radiation fields is the need for improved target visualization through imaging. While CT imaging has been the standard of care for more than three decades, the superior soft tissue contrast afforded by MR has resulted in the adoption of this technology in radiation therapy. With the development of real time MR imaging techniques, the problem of real time motion management is enticing. Currently, the integration of an MR imaging and megavoltage radiation therapy treatment delivery system (MR-linac or MRL) is a reality that has the potential to provide improved target localization and real time motion management during treatment. Higher magnetic field strengths provide improved image quality potentially providing the backbone for future work related to image texture analysis-a field known as Radiomics-thereby providing meaningful information on the selection of future patients for radiation dose escalation, motion-managed treatment techniques and ultimately better patient care. On-going advances in MRL technologies promise improved real time soft tissue visualization, treatment margin reductions, beam optimization, inhomogeneity corrected dose calculation, fast multileaf collimators and volumetric arc radiation therapy. This review article provides rationale, advantages and disadvantages as well as ideas for future research in MRI related to radiation therapy mainly in adoption of MRL.
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Affiliation(s)
- Indra J Das
- 1 Department of Radiation Oncology, NYU Langone Medical Center , New York, NY , USA
| | - Kiaran P McGee
- 2 Department of Radiology, Mayo Clinic , Rochester, MN , USA
| | - Neelam Tyagi
- 3 Department of Medical Physics, Memorial Sloan-Kettering Cancer Center , New York, NY , USA
| | - Hesheng Wang
- 1 Department of Radiation Oncology, NYU Langone Medical Center , New York, NY , USA
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11
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Abstract
Over the past decade, the application of magnetic resonance imaging (MRI) has increased, and there is growing evidence to suggest that improvements in the accuracy of target delineation in MRI-guided radiation therapy may improve clinical outcomes in a variety of cancer types. However, some considerations should be recognized including patient motion during image acquisition and geometric accuracy of images. Moreover, MR-compatible immobilization devices need to be used when acquiring images in the treatment position while minimizing patient motion during the scan time. Finally, synthetic CT images (i.e. electron density maps) and digitally reconstructed radiograph images should be generated from MRI images for dose calculation and image guidance prior to treatment. A short review of the concepts and techniques that have been developed for implementation of MRI-only workflows in radiation therapy is provided in this document.
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Affiliation(s)
- Amir M. Owrangi
- Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, Texas
| | - Peter B. Greer
- School of Mathematical and Physical Sciences, University of Newcastle, Newcastle, NSW, 2308, Australia
- Department of Radiation Oncology, Calvary Mater Hospital, Newcastle, NSW, 2298, Australia
| | - Carri K. Glide-Hurst
- Department of Radiation Oncology, Henry Ford Health System, Detroit, Michigan
- Department of Radiation Oncology, Wayne State University School of Medicine, Detroit, Michigan
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12
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Wang H, Du K, Qu J, Chandarana H, Das IJ. Dosimetric evaluation of magnetic resonance-generated synthetic CT for radiation treatment of rectal cancer. PLoS One 2018; 13:e0190883. [PMID: 29304105 PMCID: PMC5755922 DOI: 10.1371/journal.pone.0190883] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2017] [Accepted: 12/21/2017] [Indexed: 12/20/2022] Open
Abstract
Purpose The purpose of this study was to assess the dosimetric equivalence of magnetic resonance (MR)-generated synthetic CT (synCT) and simulation CT for treatment planning in radiotherapy of rectal cancer. Methods This study was conducted on eleven patients who underwent whole-body PET/MR and PET/CT examination in a prospective IRB-approved study. For each patient synCT was generated from Dixon MR using a model-based method. Standard treatment planning directives were used to create a four-field box (4F), an oblique four-field (O4F) and a volumetric modulated arc therapy (VMAT) plan on synCT for treatment of rectal cancer. The plans were recalculated on CT with the same monitor units (MUs) as that of synCT. Dose-volume metrics of planning target volume (PTV) and organs at risk (OARs) as well as gamma analysis of dose distributions were evaluated to quantify the difference between synCT and CT plans. All plans were calculated using the analytical anisotropic algorithm (AAA). The VMAT plans on synCT and CT were also calculated using the Acuros XB algorithm for comparison with the AAA calculation. Results Medians of absolute differences in PTV metrics between synCT and CT plans were 0.2%, 0.2% and 0.3% for 4F, O4F and VMAT respectively. No significant differences were observed in OAR dose metrics including bladder V40Gy, mean dose in bladder, bowel V45Gy and femoral head V30Gy in any techniques. Gamma analysis with 2%/2mm dose difference/distance to agreement criteria showed median passing rates of 99.8% (range: 98.5 to 100%), 99.9% (97.2 to 100%), and 99.9% (99.4 to 100%) for 4F, O4F and VMAT, respectively. Using Acuros XB dose calculation, 2%/2mm gamma analysis generated a passing rate of 99.2% (97.7 to 99.9%) for VMAT plans. Conclusion SynCT enabled dose calculation equivalent to conventional CT for treatment planning of 3D conformal treatment as well as VMAT of rectal cancer. The dosimetric agreement between synCT and CT calculated doses demonstrated the potential of MR-only treatment planning for rectal cancer using MR generated synCT.
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Affiliation(s)
- Hesheng Wang
- Department of Radiation Oncology, New York University School of Medicine, New York, NY, United States of America
- * E-mail:
| | - Kevin Du
- Department of Radiation Oncology, New York University School of Medicine, New York, NY, United States of America
| | - Juliet Qu
- Department of Radiation Oncology, New York University School of Medicine, New York, NY, United States of America
| | - Hersh Chandarana
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, United States of America
| | - Indra J. Das
- Department of Radiation Oncology, New York University School of Medicine, New York, NY, United States of America
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13
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Paulson ES, Crijns SPM, Keller BM, Wang J, Schmidt MA, Coutts G, van der Heide UA. Consensus opinion on MRI simulation for external beam radiation treatment planning. Radiother Oncol 2016; 121:187-192. [PMID: 27838146 DOI: 10.1016/j.radonc.2016.09.018] [Citation(s) in RCA: 59] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2016] [Revised: 09/08/2016] [Accepted: 09/09/2016] [Indexed: 11/26/2022]
Abstract
AIM To determine the levels at which consensus could be reached regarding general and site-specific principles of MRI simulation for offline MRI-aided external beam radiation treatment planning. METHODS A process inspired by the Delphi method was employed to determine levels of consensus using a series of questionnaires interspersed with controlled opinion feedback. RESULTS In general, full consensus was reached regarding general principles of MRI simulation. However, the level of consensus decreased when site-specific principles of MRI simulation were considered. CONCLUSIONS These results indicate variability in MRI simulation approaches that are largely explained by the use of MRI in combination with CT.
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Affiliation(s)
| | | | | | - Jihong Wang
- MD Anderson Cancer Center, Houston, United States
| | - Maria A Schmidt
- The Royal Marsden NHS Foundation Trust and Institute of Cancer Research, Sutton, United Kingdom
| | - Glyn Coutts
- The Christie NHS Foundation Trust, Manchester, United Kingdom
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Walker A, Metcalfe P, Liney G, Batumalai V, Dundas K, Glide‐Hurst C, Delaney GP, Boxer M, Yap ML, Dowling J, Rivest‐Henault D, Pogson E, Holloway L. MRI geometric distortion: Impact on tangential whole-breast IMRT. J Appl Clin Med Phys 2016; 17:7-19. [PMID: 28297426 PMCID: PMC5495026 DOI: 10.1120/jacmp.v17i5.6242] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2015] [Accepted: 03/21/2016] [Indexed: 12/04/2022] Open
Abstract
The purpose of this study was to determine the impact of magnetic resonance imaging (MRI) geometric distortions when using MRI for target delineation and planning for whole-breast, intensity-modulated radiotherapy (IMRT). Residual system distortions and combined systematic and patient-induced distortions are considered. This retrospective study investigated 18 patients who underwent whole-breast external beam radiotherapy, where both CT and MRIs were acquired for treatment planning. Distortion phantoms were imaged on two MRI systems, dedicated to radiotherapy planning (a wide, closed-bore 3T and an open-bore 1T). Patient scans were acquired on the 3T system. To simulate MRI-based planning, distortion maps representing residual system distortions were generated via deformable registration between phantom CT and MRIs. Patient CT images and structures were altered to match the residual system distortion measured by the phantoms on each scanner. The patient CTs were also registered to the corresponding patient MRI scans, to assess patient and residual system effects. Tangential IMRT plans were generated and optimized on each resulting CT dataset, then propagated to the original patient CT space. The resulting dose distributions were then evaluated with respect to the standard clinically acceptable DVH and visual assessment criteria. Maximum residual systematic distortion was measured to be 7.9 mm (95%<4.7mm) and 11.9 mm (95%<4.6mm) for the 3T and 1T scanners, respectively, which did not result in clinically unacceptable plans. Eight of the plans accounting for patient and systematic distortions were deemed clinically unacceptable when assessed on the original CT. For these plans, the mean difference in PTV V95 (volume receiving 95% prescription dose) was 0.13±2.51% and -0.73±1.93% for right- and left-sided patients, respectively. Residual system distortions alone had minimal impact on the dosimetry for the two scanners investigated. The combination of MRI systematic and patient-related distortions can result in unacceptable dosimetry for whole-breast IMRT, a potential issue when considering MRI-only radiotherapy treatment planning. PACS number(s): 87.61.-c, 87.57.cp, 87.57.nj, 87.55.D.
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Affiliation(s)
- Amy Walker
- Centre for Medical Radiation Physics, University of WollongongWollongongNSWAustralia
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- Ingham Institute for Applied Medical Research, Liverpool HospitalSydneyNSWAustralia
| | - Peter Metcalfe
- Centre for Medical Radiation Physics, University of WollongongWollongongNSWAustralia
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- Ingham Institute for Applied Medical Research, Liverpool HospitalSydneyNSWAustralia
| | - Gary Liney
- Centre for Medical Radiation Physics, University of WollongongWollongongNSWAustralia
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- Ingham Institute for Applied Medical Research, Liverpool HospitalSydneyNSWAustralia
- Institute of Medical Physics, School of Physics, University of SydneySydneyNSWAustralia
| | - Vikneswary Batumalai
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- Ingham Institute for Applied Medical Research, Liverpool HospitalSydneyNSWAustralia
- South Western Clinical School, University of New South WalesSydneyNSWAustralia
| | - Kylie Dundas
- Centre for Medical Radiation Physics, University of WollongongWollongongNSWAustralia
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- Ingham Institute for Applied Medical Research, Liverpool HospitalSydneyNSWAustralia
| | - Carri Glide‐Hurst
- Department of Radiation OncologyHenry Ford Health SystemDetroitMIUSA
| | - Geoff P Delaney
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- South Western Clinical School, University of New South WalesSydneyNSWAustralia
- Collaboration for Cancer Outcomes Research and Evaluation, Liverpool HospitalLiverpoolNSWAustralia
- School of Medicine, University of Western SydneySydneyNSWAustralia
| | - Miriam Boxer
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- South Western Clinical School, University of New South WalesSydneyNSWAustralia
| | - Mei Ling Yap
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- Ingham Institute for Applied Medical Research, Liverpool HospitalSydneyNSWAustralia
- South Western Clinical School, University of New South WalesSydneyNSWAustralia
- Collaboration for Cancer Outcomes Research and Evaluation, Liverpool HospitalLiverpoolNSWAustralia
- School of Medicine, University of Western SydneySydneyNSWAustralia
| | - Jason Dowling
- Commonwealth Scientific and Industrial Research Organisation Computational Informatics, Australian E‐Health Research CentreBrisbaneAustralia
| | - David Rivest‐Henault
- Commonwealth Scientific and Industrial Research Organisation Computational Informatics, Australian E‐Health Research CentreBrisbaneAustralia
| | - Elise Pogson
- Centre for Medical Radiation Physics, University of WollongongWollongongNSWAustralia
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- Ingham Institute for Applied Medical Research, Liverpool HospitalSydneyNSWAustralia
| | - Lois Holloway
- Centre for Medical Radiation Physics, University of WollongongWollongongNSWAustralia
- Liverpool and Macarthur Cancer Therapy CentresNSWAustralia
- Ingham Institute for Applied Medical Research, Liverpool HospitalSydneyNSWAustralia
- South Western Clinical School, University of New South WalesSydneyNSWAustralia
- Institute of Medical Physics, School of Physics, University of SydneySydneyNSWAustralia
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Price RG, Kadbi M, Kim J, Balter J, Chetty IJ, Glide-Hurst CK. Technical Note: Characterization and correction of gradient nonlinearity induced distortion on a 1.0 T open bore MR-SIM. Med Phys 2016; 42:5955-60. [PMID: 26429270 DOI: 10.1118/1.4930245] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Distortions in magnetic resonance imaging (MRI) compromise spatial fidelity, potentially impacting delineation and dose calculation. We characterized 2D and 3D large field of view (FOV), sequence-independent distortion at various positions in a 1.0 T high-field open MR simulator (MR-SIM) to implement correction maps for MRI treatment planning. METHODS A 36 × 43 × 2 cm(3) phantom with 255 known landmarks (∼1 mm(3)) was scanned using 1.0 T high-field open MR-SIM at isocenter in the transverse, sagittal, and coronal axes, and a 465 × 350 × 168 mm(3) 3D phantom was scanned by stepping in the superior-inferior direction in three overlapping positions to achieve a total 465 × 350 × 400 mm(3) sampled FOV yielding >13 800 landmarks (3D Gradient-Echo, TE/TR/α = 5.54 ms/30 ms/28°, voxel size = 1 × 1 × 2 mm(3)). A binary template (reference) was generated from a phantom schematic. An automated program converted MR images to binary via masking, thresholding, and testing for connectivity to identify landmarks. Distortion maps were generated by centroid mapping. Images were corrected via warping with inverse distortion maps, and temporal stability was assessed. RESULTS Over the sampled FOV, non-negligible residual gradient distortions existed as close as 9.5 cm from isocenter, with a maximum distortion of 7.4 mm as close as 23 cm from isocenter. Over six months, average gradient distortions were -0.07 ± 1.10 mm and 0.10 ± 1.10 mm in the x and y directions for the transverse plane, 0.03 ± 0.64 and -0.09 ± 0.70 mm in the sagittal plane, and 0.4 ± 1.16 and 0.04 ± 0.40 mm in the coronal plane. After implementing 3D correction maps, distortions were reduced to <1 pixel width (1 mm) for all voxels up to 25 cm from magnet isocenter. CONCLUSIONS Inherent distortion due to gradient nonlinearity was found to be non-negligible even with vendor corrections applied, and further corrections are required to obtain 1 mm accuracy for large FOVs. Statistical analysis of temporal stability shows that sequence independent distortion maps are consistent within six months of characterization.
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Affiliation(s)
- Ryan G Price
- Department of Radiation Oncology, Henry Ford Health System, Detroit, Michigan 48202 and Department of Radiation Oncology, Wayne State University School of Medicine, Detroit, Michigan 48201
| | - Mo Kadbi
- Philips Healthcare, Cleveland, Ohio 44143
| | - Joshua Kim
- Department of Radiation Oncology, Henry Ford Health System, Detroit, Michigan 48202
| | - James Balter
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan 48109
| | - Indrin J Chetty
- Department of Radiation Oncology, Henry Ford Health System, Detroit, Michigan 48202 and Department of Radiation Oncology, Wayne State University School of Medicine, Detroit, Michigan 48201
| | - Carri K Glide-Hurst
- Department of Radiation Oncology, Henry Ford Health System, Detroit, Michigan 48202 and Department of Radiation Oncology, Wayne State University School of Medicine, Detroit, Michigan 48201
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Xing A, Holloway L, Arumugam S. Commissioning and quality control of a dedicated wide bore 3T MRI simulator for radiotherapy planning. INTERNATIONAL JOURNAL OF CANCER THERAPY AND ONCOLOGY 2016. [DOI: 10.14319/ijcto.42.1] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
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To DT, Kim JP, Price RG, Chetty IJ, Glide-Hurst CK. Impact of incorporating visual biofeedback in 4D MRI. J Appl Clin Med Phys 2016; 17:128-137. [PMID: 27167270 PMCID: PMC5690930 DOI: 10.1120/jacmp.v17i3.6017] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2015] [Revised: 02/15/2016] [Accepted: 12/17/2015] [Indexed: 12/25/2022] Open
Abstract
Precise radiation therapy (RT) for abdominal lesions is complicated by respiratory motion and suboptimal soft tissue contrast in 4D CT. 4D MRI offers improved con-trast although long scan times and irregular breathing patterns can be limiting. To address this, visual biofeedback (VBF) was introduced into 4D MRI. Ten volunteers were consented to an IRB-approved protocol. Prospective respiratory-triggered, T2-weighted, coronal 4D MRIs were acquired on an open 1.0T MR-SIM. VBF was integrated using an MR-compatible interactive breath-hold control system. Subjects visually monitored their breathing patterns to stay within predetermined tolerances. 4D MRIs were acquired with and without VBF for 2- and 8-phase acquisitions. Normalized respiratory waveforms were evaluated for scan time, duty cycle (programmed/acquisition time), breathing period, and breathing regularity (end-inhale coefficient of variation, EI-COV). Three reviewers performed image quality assessment to compare artifacts with and without VBF. Respiration-induced liver motion was calculated via centroid difference analysis of end-exhale (EE) and EI liver contours. Incorporating VBF reduced 2-phase acquisition time (4.7 ± 1.0 and 5.4 ± 1.5 min with and without VBF, respectively) while reducing EI-COV by 43.8% ± 16.6%. For 8-phase acquisitions, VBF reduced acquisition time by 1.9 ± 1.6 min and EI-COVs by 38.8% ± 25.7% despite breathing rate remaining similar (11.1 ± 3.8 breaths/min with vs. 10.5 ± 2.9 without). Using VBF yielded higher duty cycles than unguided free breathing (34.4% ± 5.8% vs. 28.1% ± 6.6%, respectively). Image grading showed that out of 40 paired evaluations, 20 cases had equivalent and 17 had improved image quality scores with VBF, particularly for mid-exhale and EI. Increased liver excursion was observed with VBF, where superior-inferior, anterior-posterior, and left-right EE-EI displacements were 14.1± 5.8, 4.9 ± 2.1, and 1.5 ± 1.0 mm, respectively, with VBF compared to 11.9 ± 4.5, 3.7 ± 2.1, and 1.2 ± 1.4 mm without. Incorporating VBF into 4D MRI substantially reduced acquisition time, breathing irregularity, and image artifacts. However, differences in excursion were observed, thus implementation will be required throughout the RT workflow.
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Zheng W, Kim JP, Kadbi M, Movsas B, Chetty IJ, Glide-Hurst CK. Magnetic Resonance–Based Automatic Air Segmentation for Generation of Synthetic Computed Tomography Scans in the Head Region. Int J Radiat Oncol Biol Phys 2015; 93:497-506. [DOI: 10.1016/j.ijrobp.2015.07.001] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2015] [Revised: 05/09/2015] [Accepted: 07/01/2015] [Indexed: 12/30/2022]
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19
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Dowling JA, Sun J, Pichler P, Rivest-Hénault D, Ghose S, Richardson H, Wratten C, Martin J, Arm J, Best L, Chandra SS, Fripp J, Menk FW, Greer PB. Automatic Substitute Computed Tomography Generation and Contouring for Magnetic Resonance Imaging (MRI)-Alone External Beam Radiation Therapy From Standard MRI Sequences. Int J Radiat Oncol Biol Phys 2015; 93:1144-53. [PMID: 26581150 DOI: 10.1016/j.ijrobp.2015.08.045] [Citation(s) in RCA: 119] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2015] [Revised: 08/05/2015] [Accepted: 08/25/2015] [Indexed: 11/28/2022]
Abstract
PURPOSE To validate automatic substitute computed tomography CT (sCT) scans generated from standard T2-weighted (T2w) magnetic resonance (MR) pelvic scans for MR-Sim prostate treatment planning. PATIENTS AND METHODS A Siemens Skyra 3T MR imaging (MRI) scanner with laser bridge, flat couch, and pelvic coil mounts was used to scan 39 patients scheduled for external beam radiation therapy for localized prostate cancer. For sCT generation a whole-pelvis MRI scan (1.6 mm 3-dimensional isotropic T2w SPACE [Sampling Perfection with Application optimized Contrasts using different flip angle Evolution] sequence) was acquired. Three additional small field of view scans were acquired: T2w, T2*w, and T1w flip angle 80° for gold fiducials. Patients received a routine planning CT scan. Manual contouring of the prostate, rectum, bladder, and bones was performed independently on the CT and MR scans. Three experienced observers contoured each organ on MRI, allowing interobserver quantification. To generate a training database, each patient CT scan was coregistered to their whole-pelvis T2w using symmetric rigid registration and structure-guided deformable registration. A new multi-atlas local weighted voting method was used to generate automatic contours and sCT results. RESULTS The mean error in Hounsfield units between the sCT and corresponding patient CT (within the body contour) was 0.6 ± 14.7 (mean ± 1 SD), with a mean absolute error of 40.5 ± 8.2 Hounsfield units. Automatic contouring results were very close to the expert interobserver level (Dice similarity coefficient): prostate 0.80 ± 0.08, bladder 0.86 ± 0.12, rectum 0.84 ± 0.06, bones 0.91 ± 0.03, and body 1.00 ± 0.003. The change in monitor units between the sCT-based plans relative to the gold standard CT plan for the same dose prescription was found to be 0.3% ± 0.8%. The 3-dimensional γ pass rate was 1.00 ± 0.00 (2 mm/2%). CONCLUSIONS The MR-Sim setup and automatic sCT generation methods using standard MR sequences generates realistic contours and electron densities for prostate cancer radiation therapy dose planning and digitally reconstructed radiograph generation.
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Affiliation(s)
- Jason A Dowling
- CSIRO Australian e-Health Research Centre, Herston, Queensland, Australia; University of Newcastle, Callaghan, New South Wales, Australia.
| | - Jidi Sun
- University of Newcastle, Callaghan, New South Wales, Australia
| | - Peter Pichler
- Calvary Mater Newcastle Hospital, Waratah, New South Wales, Australia
| | | | - Soumya Ghose
- CSIRO Australian e-Health Research Centre, Herston, Queensland, Australia
| | - Haylea Richardson
- Calvary Mater Newcastle Hospital, Waratah, New South Wales, Australia
| | - Chris Wratten
- University of Newcastle, Callaghan, New South Wales, Australia; Calvary Mater Newcastle Hospital, Waratah, New South Wales, Australia
| | - Jarad Martin
- University of Newcastle, Callaghan, New South Wales, Australia; Calvary Mater Newcastle Hospital, Waratah, New South Wales, Australia
| | - Jameen Arm
- Calvary Mater Newcastle Hospital, Waratah, New South Wales, Australia
| | - Leah Best
- Department of Radiology, Hunter New England Health, New Lambton, New South Wales, Australia
| | - Shekhar S Chandra
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Queensland, Australia
| | - Jurgen Fripp
- CSIRO Australian e-Health Research Centre, Herston, Queensland, Australia
| | | | - Peter B Greer
- University of Newcastle, Callaghan, New South Wales, Australia; Calvary Mater Newcastle Hospital, Waratah, New South Wales, Australia
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