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Finnegan RN, Quinn A, Booth J, Belous G, Hardcastle N, Stewart M, Griffiths B, Carroll S, Thwaites DI. Cardiac substructure delineation in radiation therapy - A state-of-the-art review. J Med Imaging Radiat Oncol 2024; 68:914-949. [PMID: 38757728 PMCID: PMC11686467 DOI: 10.1111/1754-9485.13668] [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: 01/24/2024] [Accepted: 04/29/2024] [Indexed: 05/18/2024]
Abstract
Delineation of cardiac substructures is crucial for a better understanding of radiation-related cardiotoxicities and to facilitate accurate and precise cardiac dose calculation for developing and applying risk models. This review examines recent advancements in cardiac substructure delineation in the radiation therapy (RT) context, aiming to provide a comprehensive overview of the current level of knowledge, challenges and future directions in this evolving field. Imaging used for RT planning presents challenges in reliably visualising cardiac anatomy. Although cardiac atlases and contouring guidelines aid in standardisation and reduction of variability, significant uncertainties remain in defining cardiac anatomy. Coupled with the inherent complexity of the heart, this necessitates auto-contouring for consistent large-scale data analysis and improved efficiency in prospective applications. Auto-contouring models, developed primarily for breast and lung cancer RT, have demonstrated performance comparable to manual contouring, marking a significant milestone in the evolution of cardiac delineation practices. Nevertheless, several key concerns require further investigation. There is an unmet need for expanding cardiac auto-contouring models to encompass a broader range of cancer sites. A shift in focus is needed from ensuring accuracy to enhancing the robustness and accessibility of auto-contouring models. Addressing these challenges is paramount for the integration of cardiac substructure delineation and associated risk models into routine clinical practice, thereby improving the safety of RT for future cancer patients.
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Affiliation(s)
- Robert N Finnegan
- Northern Sydney Cancer CentreRoyal North Shore HospitalSydneyNew South WalesAustralia
- Institute of Medical Physics, School of Physics, University of SydneySydneyNew South WalesAustralia
| | - Alexandra Quinn
- Northern Sydney Cancer CentreRoyal North Shore HospitalSydneyNew South WalesAustralia
| | - Jeremy Booth
- Northern Sydney Cancer CentreRoyal North Shore HospitalSydneyNew South WalesAustralia
- Institute of Medical Physics, School of Physics, University of SydneySydneyNew South WalesAustralia
| | - Gregg Belous
- Australian e‐Health Research CentreCommonwealth Scientific and Industrial Research OrganisationBrisbaneQueenslandAustralia
| | - Nicholas Hardcastle
- Department of Physical SciencesPeter MacCallum Cancer CentreMelbourneVictoriaAustralia
- Sir Peter MacCallum Department of OncologyUniversity of MelbourneMelbourneVictoriaAustralia
| | - Maegan Stewart
- Northern Sydney Cancer CentreRoyal North Shore HospitalSydneyNew South WalesAustralia
- School of Health Sciences, Faculty of Medicine and HealthUniversity of SydneySydneyNew South WalesAustralia
| | - Brooke Griffiths
- Northern Sydney Cancer CentreRoyal North Shore HospitalSydneyNew South WalesAustralia
| | - Susan Carroll
- Northern Sydney Cancer CentreRoyal North Shore HospitalSydneyNew South WalesAustralia
- School of Health Sciences, Faculty of Medicine and HealthUniversity of SydneySydneyNew South WalesAustralia
| | - David I Thwaites
- Institute of Medical Physics, School of Physics, University of SydneySydneyNew South WalesAustralia
- Radiotherapy Research GroupLeeds Institute of Medical Research, St James's Hospital and University of LeedsLeedsUK
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Whelan BM, Liu PZY, Shan S, Waddington DEJ, Dong B, Jameson MG, Keall PJ. Open-source hardware and software for the measurement, characterization, reporting, and correction of geometric distortion in MRI. Med Phys 2024; 51:8399-8410. [PMID: 39111826 DOI: 10.1002/mp.17342] [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: 11/22/2023] [Revised: 05/16/2024] [Accepted: 06/11/2024] [Indexed: 11/03/2024] Open
Abstract
BACKGROUND Geometric distortion is a serious problem in MRI, particularly in MRI guided therapy. A lack of affordable and adaptable tools in this area limits research progress and harmonized quality assurance. PURPOSE To develop and test a suite of open-source hardware and software tools for the measurement, characterization, reporting, and correction of geometric distortion in MRI. METHODS An open-source python library was developed, comprising modules for parametric phantom design, data processing, spherical harmonics, distortion correction, and interactive reporting. The code was used to design and manufacture a distortion phantom consisting of 618 oil filled markers covering a sphere of radius 150 mm. This phantom was imaged on a CT scanner and a novel split-bore 1.0 T MRI magnet. The CT images provide distortion-free dataset. These data were used to test all modules of the open-source software. RESULTS All markers were successfully extracted from all images. The distorted MRI markers were mapped to undistorted CT data using an iterative search approach. Spherical harmonics reconstructed the fitted gradient data to 1.0 ± 0.6% of the input data. High resolution data were reconstructed via spherical harmonics and used to generate an interactive report. Finally, distortion correction on an independent data set reduced distortion inside the DSV from 5.5 ± 3.1 to 1.6 ± 0.8 mm. CONCLUSION Open-source hardware and software for the measurement, characterization, reporting, and correction of geometric distortion in MRI have been developed. The utility of these tools has been demonstrated via their application on a novel 1.0 T split bore magnet.
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Affiliation(s)
- Brendan M Whelan
- Image-X Institute, School of Health Sciences, University of Sydney, Sydney, NSW, Australia
- Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia
| | - Paul Z Y Liu
- Image-X Institute, School of Health Sciences, University of Sydney, Sydney, NSW, Australia
- Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia
| | - Shanshan Shan
- Image-X Institute, School of Health Sciences, University of Sydney, Sydney, NSW, Australia
- Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia
| | - David E J Waddington
- Image-X Institute, School of Health Sciences, University of Sydney, Sydney, NSW, Australia
- Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia
| | - Bin Dong
- Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia
| | - Michael G Jameson
- GenesisCare, Sydney, NSW, Australia
- St Vincent's Clinical School, Faculty of Medicine, University NSW, Sydney, Australia
| | - Paul J Keall
- Image-X Institute, School of Health Sciences, University of Sydney, Sydney, NSW, Australia
- Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia
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McGee KP, Cao M, Das IJ, Yu V, Witte RJ, Kishan AU, Valle LF, Wiesinger F, De-Colle C, Cao Y, Breen WG, Traughber BJ. The Use of Magnetic Resonance Imaging in Radiation Therapy Treatment Simulation and Planning. J Magn Reson Imaging 2024; 60:1786-1805. [PMID: 38265188 DOI: 10.1002/jmri.29246] [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: 09/05/2023] [Revised: 01/08/2024] [Accepted: 01/08/2024] [Indexed: 01/25/2024] Open
Abstract
Ever since its introduction as a diagnostic imaging tool the potential of magnetic resonance imaging (MRI) in radiation therapy (RT) treatment simulation and planning has been recognized. Recent technical advances have addressed many of the impediments to use of this technology and as a result have resulted in rapid and growing adoption of MRI in RT. The purpose of this article is to provide a broad review of the multiple uses of MR in the RT treatment simulation and planning process, identify several of the most used clinical scenarios in which MR is integral to the simulation and planning process, highlight existing limitations and provide multiple unmet needs thereby highlighting opportunities for the diagnostic MR imaging community to contribute and collaborate with our oncology colleagues. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 5.
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Affiliation(s)
- Kiaran P McGee
- Department of Radiology, Mayo Clinic & Foundation, Rochester, Minnesota, USA
| | - Minsong Cao
- Department of Radiation Oncology, University of California, Los Angeles, California, USA
| | - Indra J Das
- Department of Radiation Oncology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Victoria Yu
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Robert J Witte
- Department of Radiology, Mayo Clinic & Foundation, Rochester, Minnesota, USA
| | - Amar U Kishan
- Department of Radiation Oncology, University of California, Los Angeles, California, USA
| | - Luca F Valle
- Department of Radiation Oncology, University of California, Los Angeles, California, USA
| | | | - Chiara De-Colle
- Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Yue Cao
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - William G Breen
- Department of Radiation Oncology, Mayo Clinic & Foundation, Rochester, Minnesota, USA
| | - Bryan J Traughber
- Department of Radiation Oncology, Mayo Clinic & Foundation, Rochester, Minnesota, USA
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4
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Chetty IJ, Cai B, Chuong MD, Dawes SL, Hall WA, Helms AR, Kirby S, Laugeman E, Mierzwa M, Pursley J, Ray X, Subashi E, Henke LE. Quality and Safety Considerations for Adaptive Radiation Therapy: An ASTRO White Paper. Int J Radiat Oncol Biol Phys 2024:S0360-3016(24)03474-6. [PMID: 39424080 DOI: 10.1016/j.ijrobp.2024.10.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2024] [Revised: 09/06/2024] [Accepted: 10/06/2024] [Indexed: 10/21/2024]
Abstract
PURPOSE Adaptive radiation therapy (ART) is the latest topic in a series of white papers published by the American Society for Radiation Oncology addressing quality processes and patient safety. ART widens the therapeutic index by improving the precision of radiation dose to targets, allowing for dose escalation and/or minimization of dose to normal tissue. ART is performed via offline or online methods; offline ART is the process of replanning a patient's treatment plan between fractions, whereas online ART involves plan adjustment with the patient on the treatment table. This is achieved with in-room imaging capable of assessing anatomic changes and the ability to reoptimize the treatment plan rapidly during the treatment session. Although ART has occurred in its simplest forms in clinical practice for decades, recent technological developments have enabled more clinical applications of ART. With increased clinical prevalence, compressed timelines, and the associated complexity of ART, quality and safety considerations are an important focus area. METHODS The American Society for Radiation Oncology convened an interdisciplinary task force to provide expert consensus on key workflows and processes for ART. Recommendations were created using a consensus-building methodology, and task force members indicated their level of agreement based on a 5-point Likert scale, from "strongly agree" to "strongly disagree." A prespecified threshold of ≥75% of raters selecting "strongly agree" or "agree" indicated consensus. Content not meeting this threshold was removed or revised. SUMMARY Establishing and maintaining an adaptive program requires a team-based approach, appropriately trained and credentialed specialists, significant resources, specialized technology, and implementation time. A comprehensive quality assurance program must be developed, using established guidance, to make sure all forms of ART are performed in a safe and effective manner. Patient safety when delivering ART is everyone's responsibility, and professional organizations, regulators, vendors, and end users must demonstrate a clear commitment to working together to deliver the highest levels of quality and safety.
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Affiliation(s)
- Indrin J Chetty
- Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, California
| | - Bin Cai
- Department of Radiation Oncology, University of Texas Southwestern, Dallas, Texas
| | - Michael D Chuong
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health South Florida, Miami, Florida
| | | | - William A Hall
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Amanda R Helms
- American Society for Radiation Oncology, Arlington, Virginia
| | - Suzanne Kirby
- Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia
| | - Eric Laugeman
- Department of Radiation Oncology, Washington University in St Louis, St Louis, Missouri
| | - Michelle Mierzwa
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Jennifer Pursley
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts
| | - Xenia Ray
- Department of Radiation Medicine & Applied Sciences, University of California, San Diego, California
| | - Ergys Subashi
- Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Lauren E Henke
- Department of Radiation Oncology, Case Western University Hospitals, Cleveland, Ohio
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Aliotta E, Paudyal R, Dresner A, Shukla-Dave A, Lee N, Cerviño L, Otazo R, Yu VY. Reduced-distortion diffusion weighted imaging for head and neck radiotherapy. Phys Imaging Radiat Oncol 2024; 32:100653. [PMID: 39399877 PMCID: PMC11466654 DOI: 10.1016/j.phro.2024.100653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Revised: 09/19/2024] [Accepted: 09/19/2024] [Indexed: 10/15/2024] Open
Abstract
Background and purpose Quantitative Diffusion Weighted Imaging (DWI) has potential value in guiding head and neck (HN) cancer radiotherapy. However, clinical translation has been hindered by severe distortions in standard single-shot Echo-Planar-Imaging (ssEPI) and prolonged scan time and low SNR in Turbo-Spin-Echo (ssTSE) sequences. In this study, we evaluate "multi-shot" (ms) msEPI and msTSE acquisitions in the context of HN radiotherapy. Materials and methods ssEPI, ssTSE, msEPI with 2 and 3 shots (2sEPI, 3sEPI), and msTSE DWI were acquired in a phantom, healthy volunteers (N=10), and patients with HN cancer (N=5) on a 3-Tesla wide-bore MRI in radiotherapy simulation RF coil setup, with matched spatial resolution (2x2x5mm) and b = 0, 200, 800 s/mm2.Geometric distortions measured with deformable vector field (DVF) and contour analysis, apparent diffusion coefficient (ADC) values, and signal-to-noise-ratio efficiency (SNReff) were quantified for all scans. Results All techniques significantly (P<1x10-3) reduced distortions compared with ssEPI (DVFmean = 3.1 ± 1.3 mm). Distortions were marginally lower for msTSE (DVFmean = 1.5 ± 0.6 mm) than ssTSE (1.8 ± 0.9 mm), but were slightly higher with 2sEPI and 3sEPI (2.6 ± 1.0 mm, 2.2 ± 1.0 mm). SNReff reduced with decreasing distortion with ssEPI=21.9 ± 7.9, 2sEPI=15.1 ± 5.0, 3sEPI=12.1 ± 4.5, ssTSE=6.0 ± 1.6, and msTSE=5.7 ± 1.9 for b = 0 images. Phantom ADC values were consistent across all protocols (errors ≤ 0.03x10-3mm2/s), but in vivo ADC values were ∼ 4 % lower with msEPI and ∼ 12 % lower with ssTSE/msTSE compared with ssEPI. Conclusions msEPI and TSE acquisitions exhibited improved geometric distortion at the cost of SNReff and scan time. While msTSE exhibited the least distortion, 3sEPI may offer an appealing middle-ground with improved geometric fidelity but superior efficiency and in vivo ADC quantification.
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Affiliation(s)
- Eric Aliotta
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Ramesh Paudyal
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | | | - Amita Shukla-Dave
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Nancy Lee
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Laura Cerviño
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Ricardo Otazo
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Victoria Y. Yu
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States
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6
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Knill C, Halford R, Sandhu R, Loughery B, Shamim S, Junn F, Lee K, Almahariq M, Seymour Z. Evaluating stereotactic accuracy with patient-specific MRI distortion corrections for frame-based radiosurgery. J Appl Clin Med Phys 2024; 25:e14472. [PMID: 39042450 PMCID: PMC11492306 DOI: 10.1002/acm2.14472] [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: 10/25/2023] [Revised: 04/15/2024] [Accepted: 06/15/2024] [Indexed: 07/24/2024] Open
Abstract
PURPOSE This study examines how MRI distortions affect frame-based SRS treatments and assesses the need for clinical distortion corrections. METHODS The study included 18 patients with 80 total brain targets treated using frame-based radiosurgery. Distortion within patients' MRIs were corrected using Cranial Distortion Correction (CDC) software, which utilizes the patient's CT to alter planning MRIs to reduce inherent intra-cranial distortion. Distortion was evaluated by comparing the original planning target volumes (PTVORIG) to targets contoured on corrected MRIs (PTVCORR). To provide an internal control, targets were also re-contoured on uncorrected (PTVRECON) MRIs. Additional analysis was done to assess if 1 mm expansions to PTVORIG targets would compensate for patient-specific distortions. Changes in target volumes, DICE and JACCARD similarity coefficients, minimum PTV dose (Dmin), dose to 95% of the PTV (D95%), and normal tissue receiving 12 Gy (V12Gy), 10 Gy (V10Gy), and 5 Gy (V5Gy) were calculated and evaluated. Student's t-tests were used to determine if changes in PTVCORR were significantly different than intra-contouring variability quantified by PTVRECON. RESULTS PTVRECON and PTVCORR relative changes in volume were 6.19% ± 10.95% and 1.48% ± 32.92%. PTVRECON and PTVCORR similarity coefficients were 0.90 ± 0.08 and 0.73 ± 0.16 for DICE and 0.82 ± 0.12 and 0.60 ± 0.18 for JACCARD. PTVRECON and PTVCORR changes in Dmin were -0.88% ± 8.77% and -12.9 ± 17.3%. PTVRECON and PTVCORR changes in D95% were -0.34% ± 5.89 and -8.68% ± 13.21%. The 1 mm expanded PTVORIG targets did not entirely cover 14 of the 80 PTVCORR targets. Normal tissue changes (V12Gy, V10Gy, V5Gy) calculated with PTVRECON were (-0.09% ± 7.39%, -0.38% ± 5.67%, -0.08% ± 2.04%) and PTVCORR were (-2.14% ± 7.34%, -1.42% ± 5.45%, -0.61% ± 1.93%). Except for V10Gy, all PTVCORR changes were significantly different (p < 0.05) than PTVRECON. CONCLUSION MRIs used for SRS target delineation exhibit notable geometric distortions that may compromise optimal dosimetric accuracy. A uniform 1 mm expansion may result in geometric misses; however, the CDC algorithm provides a feasible solution for rectifying distortions, thereby enhancing treatment precision.
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Affiliation(s)
- Cory Knill
- Department of Radiation OncologyCorewell Health William Beaumont University HospitalRoyal OakMichiganUSA
| | - Robert Halford
- Department of Radiation OncologyCorewell Health William Beaumont University HospitalRoyal OakMichiganUSA
| | - Raminder Sandhu
- Department of Radiation OncologyCorewell Health William Beaumont University HospitalRoyal OakMichiganUSA
| | - Brian Loughery
- Department of Radiation OncologyCorewell Health William Beaumont University HospitalRoyal OakMichiganUSA
| | - Sharjil Shamim
- William Beaumont School of MedicineOakland UniversityRochesterMichiganUSA
| | - Fred Junn
- Department of Radiation OncologyCorewell Health William Beaumont University HospitalRoyal OakMichiganUSA
| | - Kuei Lee
- Department of Radiation OncologyCorewell Health William Beaumont University HospitalRoyal OakMichiganUSA
| | - Muayad Almahariq
- Department of Radiation OncologyCorewell Health William Beaumont University HospitalRoyal OakMichiganUSA
| | - Zachary Seymour
- Department of Radiation OncologyCorewell Health William Beaumont University HospitalRoyal OakMichiganUSA
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Villegas F, Dal Bello R, Alvarez-Andres E, Dhont J, Janssen T, Milan L, Robert C, Salagean GAM, Tejedor N, Trnková P, Fusella M, Placidi L, Cusumano D. Challenges and opportunities in the development and clinical implementation of artificial intelligence based synthetic computed tomography for magnetic resonance only radiotherapy. Radiother Oncol 2024; 198:110387. [PMID: 38885905 DOI: 10.1016/j.radonc.2024.110387] [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: 10/29/2023] [Revised: 06/13/2024] [Accepted: 06/13/2024] [Indexed: 06/20/2024]
Abstract
Synthetic computed tomography (sCT) generated from magnetic resonance imaging (MRI) can serve as a substitute for planning CT in radiation therapy (RT), thereby removing registration uncertainties associated with multi-modality imaging pairing, reducing costs and patient radiation exposure. CE/FDA-approved sCT solutions are nowadays available for pelvis, brain, and head and neck, while more complex deep learning (DL) algorithms are under investigation for other anatomic sites. The main challenge in achieving a widespread clinical implementation of sCT lies in the absence of consensus on sCT commissioning and quality assurance (QA), resulting in variation of sCT approaches across different hospitals. To address this issue, a group of experts gathered at the ESTRO Physics Workshop 2022 to discuss the integration of sCT solutions into clinics and report the process and its outcomes. This position paper focuses on aspects of sCT development and commissioning, outlining key elements crucial for the safe implementation of an MRI-only RT workflow.
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Affiliation(s)
- Fernanda Villegas
- Department of Oncology-Pathology, Karolinska Institute, Solna, Sweden; Radiotherapy Physics and Engineering, Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Solna, Sweden
| | - Riccardo Dal Bello
- Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Emilie Alvarez-Andres
- OncoRay - National Center for Radiation Research in Oncology, Medical Faculty and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany; Faculty of Medicine Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany
| | - Jennifer Dhont
- Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B), Institut Jules Bordet, Department of Medical Physics, Brussels, Belgium; Université Libre De Bruxelles (ULB), Radiophysics and MRI Physics Laboratory, Brussels, Belgium
| | - Tomas Janssen
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Lisa Milan
- Medical Physics Unit, Imaging Institute of Southern Switzerland (IIMSI), Ente Ospedaliero Cantonale, Bellinzona, Switzerland
| | - Charlotte Robert
- UMR 1030 Molecular Radiotherapy and Therapeutic Innovations, ImmunoRadAI, Paris-Saclay University, Institut Gustave Roussy, Inserm, Villejuif, France; Department of Radiation Oncology, Gustave Roussy, Villejuif, France
| | - Ghizela-Ana-Maria Salagean
- Faculty of Physics, Babes-Bolyai University, Cluj-Napoca, Romania; Department of Radiation Oncology, TopMed Medical Centre, Targu Mures, Romania
| | - Natalia Tejedor
- Department of Medical Physics and Radiation Protection, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Petra Trnková
- Department of Radiation Oncology, Medical University of Vienna, Vienna, Austria
| | - Marco Fusella
- Department of Radiation Oncology, Abano Terme Hospital, Italy
| | - Lorenzo Placidi
- Fondazione Policlinico Universitario Agostino Gemelli, IRCCS, Department of Diagnostic Imaging, Oncological Radiotherapy and Hematology, Rome, Italy.
| | - Davide Cusumano
- Mater Olbia Hospital, Strada Statale Orientale Sarda 125, Olbia, Sassari, Italy
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8
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Chaknam K, Worapruekjaru L, Suphaphong S, Stansook N, Sodkokkruad P, Asavaphatiboon S. Impact Assessment of Systemic Geometric Distortion in 1.5T Magnetic Resonance Imaging Simulation through Three-dimensional Geometric Distortion Phantom on Dosimetric Accuracy for Magnetic Resonance Imaging-only Prostate Treatment Planning. J Med Phys 2024; 49:356-362. [PMID: 39526153 PMCID: PMC11548076 DOI: 10.4103/jmp.jmp_62_24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 04/09/2024] [Accepted: 04/24/2024] [Indexed: 11/16/2024] Open
Abstract
Aims Magnetic resonance imaging (MRI)-only radiotherapy has emerged as a solution to address registration errors that can lead to missed dose delivery. However, the presence of systemic geometric distortion (SGD) stemming from gradient nonlinearity (GNL) and inhomogeneity of the main magnetic field (B0) necessitates consideration. This study aimed to quantitatively assess residual SGD in 1.5T MRI simulation using a three-dimensional (3D) geometric distortion phantom and evaluate its impact on dosimetric accuracy for retrospective prostate cancer patients. Materials and Methods Ten retrospective cases of prostate cancer patients treated with volumetric modulated arc radiotherapy (VMAT) were randomly selected. A geometric distortion phantom was scanned on a 1.5T MRI simulation using a 3D T1 volumetric interpolated breath-hold examination sequence, varying bandwidth (BW), and two-phase-encoding directions. Distortion maps were generated and applied to the original computed tomography (oriCT) plan to create a distorted computed tomography plan (dCT), and a dice similarity coefficient (DSC) was observed. Dosimetric accuracy was evaluated by recalculating radiation dose for dCT plans using identical beam parameters as oriCT. Results The SGD increased with distance from the isocenter in all series. DSC exceeded 0.95 for all plans except the rectum. Regarding GNL's impact on dosimetric accuracy, most mean percentage errors for clinical target volume, planning target volume, and both femurs were under 2% in all plans, except for the bladder and rectum. Conclusion SGD pre-evaluation is crucial and should be incorporated into a quality assurance program to ensure effective MRI-simulation performance before MRI-only treatment planning for prostate cancer.
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Affiliation(s)
- Korawig Chaknam
- Division of Diagnostic Radiology, Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Ladawan Worapruekjaru
- Division of Radiation Oncology, Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Sithiphong Suphaphong
- Division of Radiation Oncology, Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Nualjun Stansook
- Division of Radiation Oncology, Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Prapa Sodkokkruad
- Division of Diagnostic Radiology, Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Sawwanee Asavaphatiboon
- Division of Diagnostic Radiology, Department of Diagnostic and Therapeutic Radiology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
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9
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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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10
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Pouymayou B, Perez-Haas Y, Allemann F, Saguner AM, Andratschke N, Guckenberger M, Tanadini-Lang S, Wilke L. Characterization of spatial integrity with active and passive implants in a low-field magnetic resonance linear accelerator scanner. Phys Imaging Radiat Oncol 2024; 30:100576. [PMID: 38644933 PMCID: PMC11031795 DOI: 10.1016/j.phro.2024.100576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 04/02/2024] [Accepted: 04/05/2024] [Indexed: 04/23/2024] Open
Abstract
Background and Purpose Standard imaging protocols can guarantee the spatial integrity of magnetic resonance (MR) images utilized in radiotherapy. However, the presence of metallic implants can significantly compromise this integrity. Our proposed method aims at characterizing the geometric distortions induced by both passive and active implants commonly encountered in planning images obtained from a low-field 0.35 T MR-linear accelerator (LINAC). Materials and Methods We designed a spatial integrity phantom defining 1276 control points and covering a field of view of 20x20x20 cm3. This phantom was scanned in a water tank with and without different implants used in hip and shoulder arthroplasty procedures as well as with active cardiac stimulators. The images were acquired with the clinical planning sequence (balanced steady-state free-precession, resolution 1.5x1.5x1.5 mm3). Spatial integrity was assessed by the Euclidian distance between the control point detected on the image and their theoretical locations. A first plane free of artefact (FPFA) was defined to evaluate the spatial integrity beyond the larger banding artefact. Results In the region extending up to 20 mm from the largest banding artefacts, the tested passive and active implants could cause distortions up to 2 mm and 3 mm, respectively. Beyond this region the spatial integrity was recovered and the image could be considered as unaffected by the implants. Conclusions We characterized the impact of common implants on a low field MR-LINAC planning sequence. These measurements could support the creation of extra margin while contouring organs at risk and target volumes in the vicinity of implants.
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Affiliation(s)
- Bertrand Pouymayou
- Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Yoel Perez-Haas
- Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Florin Allemann
- Department of Traumatology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Ardan M. Saguner
- Department of Cardiology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Nicolaus Andratschke
- Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Matthias Guckenberger
- Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Stephanie Tanadini-Lang
- Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Lotte Wilke
- Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
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11
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Marasini S, Cole M, Curcuru A, Dyke LM, Gach HM, Flores R, Kim T. Characterization of real-time cine MR imaging distortion on 0.35 T MRgRT with concentric cine imaging QA phantom. Phys Med Biol 2024; 69:065009. [PMID: 38408387 DOI: 10.1088/1361-6560/ad2d33] [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: 09/18/2023] [Accepted: 02/26/2024] [Indexed: 02/28/2024]
Abstract
Objective. Real-time MRgRT uses 2D-cine imaging for target tracking and motion evaluation. Rotation of gantry inducedB0off-resonance, resulting in image artifacts and imaging isocenter-shift precluding MR-guided arc therapy. Standard MRI phantoms designed for higher resolution images face challenges when low-resolution cine imaging is needed to achieve high frame rates. This work aimed to examine the spatial accuracy including geometric distortion and isocenter shift in real-time during gantry rotation on a 0.35 T MR-Linac using the concentric Cine imaging quality assurance (QA) phantom and its associated image analysis software.Approach. The Cine imaging QA phantom consists of two concentric shells of low-T1mineral oil and a central alignment structure. The phantom was scanned on three different MRI systems; 0.55 T Siemens Free.Max, 1.5 T Philips Ingenia, and 0.35 T ViewRay MRIdian MR-Linac using 2D balanced steady-state free precession (bSSFP) imaging sequence. In addition, bSSFP cine MRI with the banding artifact correction was tested on 0.35 T ViewRay MR-Linac. Images from the MR-Linac were acquired with the Linac gantry stationary and rotating from gantry 300°→ 0° and vice versa. Three orthogonal image planes were scanned excluding the 1.5 T Philips Ingenia, where only the axial plane was scanned. The image analysis software calculated the distortion values as well as the isocenter position for each cine frame.Main results. The geometric distortion of cine imaging on MRIs and MR-Linac at gantry stationary are within 1 mm while the substantial geometric distortion of 2 and 2.2 mm were observed on 0.35 T MR-Linac while rotating the gantry clockwise (300°→ 0°) and counterclockwise 0°→ 300° respectively. The average imaging isocenter shift was 0.1 mm for both MRIs and the static gantry and imaging isocenter shift of ≤1.5 mm was observed during the gantry rotation. The imaging isocenter shift decreased by 1 ± 0.2 mm clockwise and counterclockwise withB0compensation.Significance. The concentric Cine imaging QA phantom and its associated software effectively demonstrate the image distortion on real-time cine imaging on regular MRIs and 0.35 T MR-Linac. The results of significant geometric distortion with a rotating gantry in the MR-Linac system require further investigation to alleviate the extent of the image distortion.
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Affiliation(s)
- Shanti Marasini
- Departments of Radiation Oncology, Washington University School of Medicine, St. Louis, MO,United States of America
| | | | - Austen Curcuru
- Departments of Radiation Oncology, Washington University School of Medicine, St. Louis, MO,United States of America
| | - Lara M Dyke
- Departments of Radiation Oncology, Washington University School of Medicine, St. Louis, MO,United States of America
| | - H Michael Gach
- Departments of Radiation Oncology, Washington University School of Medicine, St. Louis, MO,United States of America
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, United States of America
- Departments of Biomedical Engineering, Washington University in St. Louis, MO, United States of America
| | | | - Taeho Kim
- Departments of Radiation Oncology, Washington University School of Medicine, St. Louis, MO,United States of America
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12
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Grigo J, Szkitsak J, Höfler D, Fietkau R, Putz F, Bert C. "sCT-Feasibility" - a feasibility study for deep learning-based MRI-only brain radiotherapy. Radiat Oncol 2024; 19:33. [PMID: 38459584 PMCID: PMC10924348 DOI: 10.1186/s13014-024-02428-3] [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: 10/31/2023] [Accepted: 02/29/2024] [Indexed: 03/10/2024] Open
Abstract
BACKGROUND Radiotherapy (RT) is an important treatment modality for patients with brain malignancies. Traditionally, computed tomography (CT) images are used for RT treatment planning whereas magnetic resonance imaging (MRI) images are used for tumor delineation. Therefore, MRI and CT need to be registered, which is an error prone process. The purpose of this clinical study is to investigate the clinical feasibility of a deep learning-based MRI-only workflow for brain radiotherapy, that eliminates the registration uncertainty through calculation of a synthetic CT (sCT) from MRI data. METHODS A total of 54 patients with an indication for radiation treatment of the brain and stereotactic mask immobilization will be recruited. All study patients will receive standard therapy and imaging including both CT and MRI. All patients will receive dedicated RT-MRI scans in treatment position. An sCT will be reconstructed from an acquired MRI DIXON-sequence using a commercially available deep learning solution on which subsequent radiotherapy planning will be performed. Through multiple quality assurance (QA) measures and reviews during the course of the study, the feasibility of an MRI-only workflow and comparative parameters between sCT and standard CT workflow will be investigated holistically. These QA measures include feasibility and quality of image guidance (IGRT) at the linear accelerator using sCT derived digitally reconstructed radiographs in addition to potential dosimetric deviations between the CT and sCT plan. The aim of this clinical study is to establish a brain MRI-only workflow as well as to identify risks and QA mechanisms to ensure a safe integration of deep learning-based sCT into radiotherapy planning and delivery. DISCUSSION Compared to CT, MRI offers a superior soft tissue contrast without additional radiation dose to the patients. However, up to now, even though the dosimetrical equivalence of CT and sCT has been shown in several retrospective studies, MRI-only workflows have still not been widely adopted. The present study aims to determine feasibility and safety of deep learning-based MRI-only radiotherapy in a holistic manner incorporating the whole radiotherapy workflow. TRIAL REGISTRATION NCT06106997.
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Affiliation(s)
- Johanna Grigo
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Universitätsstraße 27, DE- 91054, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Erlangen, Germany
| | - Juliane Szkitsak
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Universitätsstraße 27, DE- 91054, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Erlangen, Germany
| | - Daniel Höfler
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Universitätsstraße 27, DE- 91054, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Erlangen, Germany
| | - Rainer Fietkau
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Universitätsstraße 27, DE- 91054, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Erlangen, Germany
| | - Florian Putz
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Universitätsstraße 27, DE- 91054, Erlangen, Germany
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Erlangen, Germany
| | - Christoph Bert
- Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Universitätsstraße 27, DE- 91054, Erlangen, Germany.
- Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Erlangen, Germany.
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13
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Tseng CL, Zeng KL, Mellon EA, Soltys SG, Ruschin M, Lau AZ, Lutsik NS, Chan RW, Detsky J, Stewart J, Maralani PJ, Sahgal A. Evolving concepts in margin strategies and adaptive radiotherapy for glioblastoma: A new future is on the horizon. Neuro Oncol 2024; 26:S3-S16. [PMID: 38437669 PMCID: PMC10911794 DOI: 10.1093/neuonc/noad258] [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] [Indexed: 03/06/2024] Open
Abstract
Chemoradiotherapy is the standard treatment after maximal safe resection for glioblastoma (GBM). Despite advances in molecular profiling, surgical techniques, and neuro-imaging, there have been no major breakthroughs in radiotherapy (RT) volumes in decades. Although the majority of recurrences occur within the original gross tumor volume (GTV), treatment of a clinical target volume (CTV) ranging from 1.5 to 3.0 cm beyond the GTV remains the standard of care. Over the past 15 years, the incorporation of standard and functional MRI sequences into the treatment workflow has become a routine practice with increasing adoption of MR simulators, and new integrated MR-Linac technologies allowing for daily pre-, intra- and post-treatment MR imaging. There is now unprecedented ability to understand the tumor dynamics and biology of GBM during RT, and safe CTV margin reduction is being investigated with the goal of improving the therapeutic ratio. The purpose of this review is to discuss margin strategies and the potential for adaptive RT for GBM, with a focus on the challenges and opportunities associated with both online and offline adaptive workflows. Lastly, opportunities to biologically guide adaptive RT using non-invasive imaging biomarkers and the potential to define appropriate volumes for dose modification will be discussed.
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Affiliation(s)
- Chia-Lin Tseng
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - K Liang Zeng
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
- Department of Radiation Oncology, Simcoe Muskoka Regional Cancer Program, Royal Victoria Regional Health Centre, University of Toronto, Toronto, Ontario, Canada
| | - Eric A Mellon
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, Florida, USA
| | - Scott G Soltys
- Department of Radiation Oncology, Stanford University, Stanford, California, USA
| | - Mark Ruschin
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Angus Z Lau
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Natalia S Lutsik
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, Florida, USA
| | - Rachel W Chan
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Jay Detsky
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - James Stewart
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Pejman J Maralani
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Arjun Sahgal
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
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Poulin E, Lacroix F, Archambault L, Jutras JD. Commissioning and implementing a Quality Assurance program for dedicated radiation oncology MRI scanners. J Appl Clin Med Phys 2024; 25:e14185. [PMID: 38332556 DOI: 10.1002/acm2.14185] [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: 01/20/2023] [Revised: 09/20/2023] [Accepted: 10/05/2023] [Indexed: 02/10/2024] Open
Abstract
PURPOSE ACR and AAPM task group's guidelines addressing commissioning for dedicated MR simulators were recently published. The goal of the current paper is to present the authors' 2-year experience regarding the commissioning and introduction of a QA program based on these guidelines and an associated automated workflow. METHODS All mandatory commissioning tests suggested by AAPM report 284 were performed and results are reported for two MRI scanners (MAGNETOM Sola and Aera). Visual inspection, vendor clinical or service platform, third-party software, or in-house python-based code were used. Automated QA and data analysis was performed via vendor, in-house or third-party software. QATrack+ was used for QA data logging and storage. 3D geometric distortion, B0 inhomogeneity, EPI, and parallel imaging performance were evaluated. RESULTS Contrasting with AAPM report 284 recommendations, homogeneity and RF tests were performed monthly. The QA program allowed us to detect major failures over time (shimming, gradient calibration and RF interference). Automated QA, data analysis, and logging allowed fast ACR analysis daily and monthly QA to be performed in 3 h. On the Sola, the average distortion is 1 mm for imaging radii of 250 mm or less. For radii of up to 200 mm, the maximum, average (standard deviation) distortion is 1.2 and 0.4 mm (0.3 mm). Aera values are roughly double the Sola for radii up to 200 mm. EPI geometric distortion, ghosting ratio, and long-term stability were found to be under the maximum recommended values. Parallel imaging SNR ratio was stable and close to the theoretical value (ideal g-factor). No major failures were detected during commissioning. CONCLUSION An automated workflow and enhanced QA program allowed to automatically track machine and environmental changes over time and to detect periodic failures and errors that might otherwise have gone unnoticed. The Sola is more geometrically accurate, with a more homogenous B0 field than the Aera.
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Affiliation(s)
- Eric Poulin
- Département de physique, de génie physique et d'optique et Centre de recherche sur le cancer de l'Université Laval, Université Laval, Québec, Canada
- Département de radio-oncologie et Axe Oncologie du Centre de recherche du CHU de Québec, CHU de Québec-Université Laval, Québec, Canada
| | - Frederic Lacroix
- Département de physique, de génie physique et d'optique et Centre de recherche sur le cancer de l'Université Laval, Université Laval, Québec, Canada
- Département de radio-oncologie et Axe Oncologie du Centre de recherche du CHU de Québec, CHU de Québec-Université Laval, Québec, Canada
| | - Louis Archambault
- Département de physique, de génie physique et d'optique et Centre de recherche sur le cancer de l'Université Laval, Université Laval, Québec, Canada
- Département de radio-oncologie et Axe Oncologie du Centre de recherche du CHU de Québec, CHU de Québec-Université Laval, Québec, Canada
| | - Jean-David Jutras
- Département de physique, de génie physique et d'optique et Centre de recherche sur le cancer de l'Université Laval, Université Laval, Québec, Canada
- Département de radio-oncologie et Axe Oncologie du Centre de recherche du CHU de Québec, CHU de Québec-Université Laval, Québec, Canada
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15
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Law MWK, Tse MY, Ho LCC, Lau KK, Wong OL, Yuan J, Cheung KY, Yu SK. A study of Bayesian deep network uncertainty and its application to synthetic CT generation for MR-only radiotherapy treatment planning. Med Phys 2024; 51:1244-1262. [PMID: 37665783 DOI: 10.1002/mp.16666] [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: 08/19/2022] [Revised: 06/05/2023] [Accepted: 07/20/2023] [Indexed: 09/06/2023] Open
Abstract
BACKGROUND The use of synthetic computed tomography (CT) for radiotherapy treatment planning has received considerable attention because of the absence of ionizing radiation and close spatial correspondence to source magnetic resonance (MR) images, which have excellent tissue contrast. However, in an MR-only environment, little effort has been made to examine the quality of synthetic CT images without using the original CT images. PURPOSE To estimate synthetic CT quality without referring to original CT images, this study established the relationship between synthetic CT uncertainty and Bayesian uncertainty, and proposed a new Bayesian deep network for generating synthetic CT images and estimating synthetic CT uncertainty for MR-only radiotherapy treatment planning. METHODS AND MATERIALS A novel deep Bayesian network was formulated using probabilistic network weights. Two mathematical expressions were proposed to quantify the Bayesian uncertainty of the network and synthetic CT uncertainty, which was closely related to the mean absolute error (MAE) in Hounsfield Unit (HU) of synthetic CT. These uncertainties were examined to demonstrate the accuracy of representing the synthetic CT uncertainty using a Bayesian counterpart. We developed a hybrid Bayesian architecture and a new data normalization scheme, enabling the Bayesian network to generate both accurate synthetic CT and reliable uncertainty information when probabilistic weights were applied. The proposed method was evaluated in 59 patients (13/12/32/2 for training/validation/testing/uncertainty visualization) diagnosed with prostate cancer, who underwent same-day pelvic CT- and MR-acquisitions. To assess the relationship between Bayesian and synthetic CT uncertainties, linear and non-linear correlation coefficients were calculated on per-voxel, per-tissue, and per-patient bases. For accessing the accuracy of the CT number and dosimetric accuracy, the proposed method was compared with a commercially available atlas-based method (MRCAT) and a U-Net conditional-generative adversarial network (UcGAN). RESULTS The proposed model exhibited 44.33 MAE, outperforming UcGAN 52.51 and MRCAT 54.87. The gamma rate (2%/2 mm dose difference/distance to agreement) of the proposed model was 98.68%, comparable to that of UcGAN (98.60%) and MRCAT (98.56%). The per-patient and per-tissue linear correlation coefficients between the Bayesian and synthetic CT uncertainties ranged from 0.53 to 0.83, implying a moderate to strong linear correlation. Per-voxel correlation coefficients varied from -0.13 to 0.67 depending on the regions-of-interest evaluated, indicating tissue-dependent correlation. The R2 value for estimating MAE solely using Bayesian uncertainty was 0.98, suggesting that the uncertainty of the proposed model was an ideal candidate for predicting synthetic CT error, without referring to the original CT. CONCLUSION This study established a relationship between the Bayesian model uncertainty and synthetic CT uncertainty. A novel Bayesian deep network was proposed to generate a synthetic CT and estimate its uncertainty. Various metrics were used to thoroughly examine the relationship between the uncertainties of the proposed Bayesian model and the generated synthetic CT. Compared with existing approaches, the proposed model showed comparable CT number and dosimetric accuracies. The experiments showed that the proposed Bayesian model was capable of producing accurate synthetic CT, and was an effective indicator of the uncertainty and error associated with synthetic CT in MR-only workflows.
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Affiliation(s)
- Max Wai-Kong Law
- Medical Physics Department, Hong Kong Sanatorium and Hospital, Hong Kong SAR, China
| | - Mei-Yan Tse
- Medical Physics Department, Hong Kong Sanatorium and Hospital, Hong Kong SAR, China
| | - Leon Chin-Chak Ho
- Medical Physics Department, Hong Kong Sanatorium and Hospital, Hong Kong SAR, China
| | - Ka-Ki Lau
- Medical Physics Department, Hong Kong Sanatorium and Hospital, Hong Kong SAR, China
| | - Oi Lei Wong
- Research Department, Hong Kong Sanatorium and Hospital, Hong Kong SAR, China
| | - Jing Yuan
- Research Department, Hong Kong Sanatorium and Hospital, Hong Kong SAR, China
| | - Kin Yin Cheung
- Medical Physics Department, Hong Kong Sanatorium and Hospital, Hong Kong SAR, China
| | - Siu Ki Yu
- Medical Physics Department, Hong Kong Sanatorium and Hospital, Hong Kong SAR, China
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16
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Courtney PT, Valle LF, Raldow AC, Steinberg ML. MRI-Guided Radiation Therapy-An Emerging and Disruptive Process of Care: Healthcare Economic and Policy Considerations. Semin Radiat Oncol 2024; 34:4-13. [PMID: 38105092 DOI: 10.1016/j.semradonc.2023.10.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
MRI-guided radiation therapy (MRgRT) is an emerging, innovative technology that provides opportunities to transform and improve the current clinical care process in radiation oncology. As with many new technologies in radiation oncology, careful evaluation from a healthcare economic and policy perspective is required for its successful implementation. In this review article, we describe the current evidence surrounding MRgRT, framing it within the context of value within the healthcare system. Additionally, we highlight areas in which MRgRT may disrupt the current process of care, and discuss the evidence thresholds and timeline required for the widespread adoption of this promising technology.
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Affiliation(s)
- P Travis Courtney
- Department of Radiation Oncology, University of California, Los Angeles, CA
| | - Luca F Valle
- Department of Radiation Oncology, University of California, Los Angeles, CA
| | - Ann C Raldow
- Department of Radiation Oncology, University of California, Los Angeles, CA
| | - Michael L Steinberg
- Department of Radiation Oncology, University of California, Los Angeles, CA.
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17
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Crop F, Robert C, Viard R, Dumont J, Kawalko M, Makala P, Liem X, El Aoud I, Ben Miled A, Chaton V, Patin L, Pasquier D, Guillaud O, Vandendorpe B, Mirabel X, Ceugnart L, Decoene C, Lacornerie T. Efficiency and Accuracy Evaluation of Multiple Diffusion-Weighted MRI Techniques Across Different Scanners. J Magn Reson Imaging 2024; 59:311-322. [PMID: 37335079 DOI: 10.1002/jmri.28869] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 05/23/2023] [Accepted: 05/23/2023] [Indexed: 06/21/2023] Open
Abstract
BACKGROUND The choice between different diffusion-weighted imaging (DWI) techniques is difficult as each comes with tradeoffs for efficient clinical routine imaging and apparent diffusion coefficient (ADC) accuracy. PURPOSE To quantify signal-to-noise-ratio (SNR) efficiency, ADC accuracy, artifacts, and distortions for different DWI acquisition techniques, coils, and scanners. STUDY TYPE Phantom, in vivo intraindividual biomarker accuracy between DWI techniques and independent ratings. POPULATION/PHANTOMS NIST diffusion phantom. 51 Patients: 40 with prostate cancer and 11 with head-and-neck cancer at 1.5 T FIELD STRENGTH/SEQUENCE: Echo planar imaging (EPI): 1.5 T and 3 T Siemens; 3 T Philips. Distortion-reducing: RESOLVE (1.5 and 3 T Siemens); Turbo Spin Echo (TSE)-SPLICE (3 T Philips). Small field-of-view (FOV): ZoomitPro (1.5 T Siemens); IRIS (3 T Philips). Head-and-neck and flexible coils. ASSESSMENT SNR Efficiency, geometrical distortions, and susceptibility artifacts were quantified for different b-values in a phantom. ADC accuracy/agreement was quantified in phantom and for 51 patients. In vivo image quality was independently rated by four experts. STATISTICAL TESTS QIBA methodology for accuracy: trueness, repeatability, reproducibility, Bland-Altman 95% Limits-of-Agreement (LOA) for ADC. Wilcoxon Signed-Rank and student tests on P < 0.05 level. RESULTS The ZoomitPro small FOV sequence improved b-image efficiency by 8%-14%, reduced artifacts and observer scoring for most raters at the cost of smaller FOV compared to EPI. The TSE-SPLICE technique reduced artifacts almost completely at a 24% efficiency cost compared to EPI for b-values ≤500 sec/mm2 . Phantom ADC 95% LOA trueness were within ±0.03 × 10-3 mm2 /sec except for small FOV IRIS. The in vivo ADC agreement between techniques, however, resulted in 95% LOAs in the order of ±0.3 × 10-3 mm2 /sec with up to 0.2 × 10-3 mm2 /sec of bias. DATA CONCLUSION ZoomitPro for Siemens and TSE SPLICE for Philips resulted in a trade-off between efficiency and artifacts. Phantom ADC quality control largely underestimated in vivo accuracy: significant ADC bias and variability was found between techniques in vivo. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Frederik Crop
- Department of Medical Physics, Centre Oscar Lambret, Lille, France
- University of Lille, IEMN, Lille, France
| | - Clémence Robert
- Department of Medical Physics, Centre Oscar Lambret, Lille, France
| | - Romain Viard
- University of Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, PLBS UAR 2014-US 41, Lille, France
- University of Lille, Inserm, CHU Lille, U1172-LilNCog-Lille Neuroscience & Cognition, Lille, France
| | - Julien Dumont
- University of Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, PLBS UAR 2014-US 41, Lille, France
| | - Marine Kawalko
- Department of Radiology, Centre Oscar Lambret, Lille, France
| | - Pauline Makala
- Academic Department of Radiotherapy, Centre Oscar Lambret, Lille, France
| | - Xavier Liem
- Academic Department of Radiotherapy, Centre Oscar Lambret, Lille, France
| | - Imen El Aoud
- Department of Radiology, Centre Oscar Lambret, Lille, France
| | - Aicha Ben Miled
- Department of Radiology, Centre Oscar Lambret, Lille, France
| | - Victor Chaton
- Department of Radiology, Centre Oscar Lambret, Lille, France
| | - Lucas Patin
- Department of Radiology, Centre Oscar Lambret, Lille, France
| | - David Pasquier
- Academic Department of Radiotherapy, Centre Oscar Lambret, Lille, France
- University of Lille, Centre de recherche en informatique, Signal et automatique de Lille, Lille, France
| | | | | | - Xavier Mirabel
- Academic Department of Radiotherapy, Centre Oscar Lambret, Lille, France
| | - Luc Ceugnart
- Department of Radiology, Centre Oscar Lambret, Lille, France
| | - Camille Decoene
- Department of Medical Physics, Centre Oscar Lambret, Lille, France
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18
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Olsson LE, Af Wetterstedt S, Scherman J, Gunnlaugsson A, Persson E, Jamtheim Gustafsson C. Evaluation of a deep learning magnetic resonance imaging reconstruction method for synthetic computed tomography generation in prostate radiotherapy. Phys Imaging Radiat Oncol 2024; 29:100557. [PMID: 38414521 PMCID: PMC10897922 DOI: 10.1016/j.phro.2024.100557] [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: 05/26/2023] [Revised: 02/07/2024] [Accepted: 02/08/2024] [Indexed: 02/29/2024] Open
Abstract
Background and Purpose In magnetic resonance imaging (MRI) only radiotherapy computed tomography (CT) is excluded. The method relies entirely on synthetic CT images generated from MRI. This study evaluates the compatibility of a commercial synthetic CT (sCT) with an accelerated commercial deep learning reconstruction (DLR) in MRI-only prostate radiotherapy. Materials and Methods For a group of 24 patients (cohort 1) the effects of DLR were studied in isolation. MRI data were reconstructed conventionally and with DLR from identical k-space data, and sCTs were generated for both reconstructions. The sCT quality, Hounsfield Unit (HU) and dosimetric impact were investigated. In another group of 15 patients (cohort 2) effects on sCT generation using accelerated MRI acquisition (40 % time reduction) reconstructed with DLR were investigated. Results sCT images from both cohorts, generated from DLR MRI data, were of clinically expected image quality. The mean dose differences for targets and organs at risks in cohort 1 were <0.06 Gy, corresponding to a 0.1 % prescribed dose difference. Similar dose differences were observed in cohort 2. Gamma pass rates for cohort 1 were 100 % for criteria 3 %/3mm, 2 %/2mm and 1 %/1mm for all dose levels. Mean error and mean absolute error inside the body, between sCTs, averaged over all cohort 1 subjects, were -1.1 ± 0.6 [-2.4 0.2] and 2.9 ± 0.4 [2.3 3.9] HU, respectively. Conclusions DLR was suitable for sCT generation with clinically negligible differences in HU and calculated dose compared to the conventional MRI reconstruction method. For sCT generation DLR enables scan time reduction, without compromised sCT quality.
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Affiliation(s)
- Lars E Olsson
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, Lund 221 85, Sweden
- Department of Translational Medicine, Medical Radiation Physics, Lund University, Carl Bertil Laurells gata 9, Malmö 205 02, Sweden
| | - Sacha Af Wetterstedt
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, Lund 221 85, Sweden
| | - Jonas Scherman
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, Lund 221 85, Sweden
| | - Adalsteinn Gunnlaugsson
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, Lund 221 85, Sweden
| | - Emilia Persson
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, Lund 221 85, Sweden
- Department of Translational Medicine, Medical Radiation Physics, Lund University, Carl Bertil Laurells gata 9, Malmö 205 02, Sweden
| | - Christian Jamtheim Gustafsson
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, Lund 221 85, Sweden
- Department of Translational Medicine, Medical Radiation Physics, Lund University, Carl Bertil Laurells gata 9, Malmö 205 02, Sweden
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19
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Riis HL, Chick J, Dunlop A, Tilly D. The Quality Assurance of a 1.5 T MR-Linac. Semin Radiat Oncol 2024; 34:120-128. [PMID: 38105086 DOI: 10.1016/j.semradonc.2023.10.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
The recent introduction of a commercial 1.5 T MR-linac system has considerably improved the image quality of the patient acquired in the treatment unit as well as enabling online adaptive radiation therapy (oART) treatment strategies. Quality Assurance (QA) of this new technology requires new methodology that allows for the high field MR in a linac environment. The presence of the magnetic field requires special attention to the phantoms, detectors, and tools to perform QA. Due to the design of the system, the integrated megavoltage imager (MVI) is essential for radiation beam calibrations and QA. Additionally, the alignment between the MR image system and the radiation isocenter must be checked. The MR-linac system has vendor-supplied phantoms for calibration and QA tests. However, users have developed their own routine QA systems to independently check that the machine is performing as required, as to ensure we are able to deliver the intended dose with sufficient certainty. The aim of this work is therefore to review the MR-linac specific QA procedures reported in the literature.
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Affiliation(s)
- Hans Lynggaard Riis
- Department of Oncology, Odense University Hospital, Odense, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
| | - Joan Chick
- The Joint Department of Physics, The Royal Marsden Hospital and the Institute of Cancer Research, London, UK
| | - Alex Dunlop
- The Joint Department of Physics, The Royal Marsden Hospital and the Institute of Cancer Research, London, UK
| | - David Tilly
- Department of Immunology, Genetics and Pathology, Medical Radiation Physics, Uppsala University, Uppsala, Sweden; Medical Physics, Uppsala University Hospital, Uppsala, Sweden
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20
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Putz F, Bock M, Schmitt D, Bert C, Blanck O, Ruge MI, Hattingen E, Karger CP, Fietkau R, Grigo J, Schmidt MA, Bäuerle T, Wittig A. Quality requirements for MRI simulation in cranial stereotactic radiotherapy: a guideline from the German Taskforce "Imaging in Stereotactic Radiotherapy". Strahlenther Onkol 2024; 200:1-18. [PMID: 38163834 PMCID: PMC10784363 DOI: 10.1007/s00066-023-02183-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 11/06/2023] [Indexed: 01/03/2024]
Abstract
Accurate Magnetic Resonance Imaging (MRI) simulation is fundamental for high-precision stereotactic radiosurgery and fractionated stereotactic radiotherapy, collectively referred to as stereotactic radiotherapy (SRT), to deliver doses of high biological effectiveness to well-defined cranial targets. Multiple MRI hardware related factors as well as scanner configuration and sequence protocol parameters can affect the imaging accuracy and need to be optimized for the special purpose of radiotherapy treatment planning. MRI simulation for SRT is possible for different organizational environments including patient referral for imaging as well as dedicated MRI simulation in the radiotherapy department but require radiotherapy-optimized MRI protocols and defined quality standards to ensure geometrically accurate images that form an impeccable foundation for treatment planning. For this guideline, an interdisciplinary panel including experts from the working group for radiosurgery and stereotactic radiotherapy of the German Society for Radiation Oncology (DEGRO), the working group for physics and technology in stereotactic radiotherapy of the German Society for Medical Physics (DGMP), the German Society of Neurosurgery (DGNC), the German Society of Neuroradiology (DGNR) and the German Chapter of the International Society for Magnetic Resonance in Medicine (DS-ISMRM) have defined minimum MRI quality requirements as well as advanced MRI simulation options for cranial SRT.
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Affiliation(s)
- Florian Putz
- Strahlenklinik, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
| | - Michael Bock
- Klinik für Radiologie-Medizinphysik, Universitätsklinikum Freiburg, Freiburg, Germany
| | - Daniela Schmitt
- Klinik für Strahlentherapie und Radioonkologie, Universitätsmedizin Göttingen, Göttingen, Germany
| | - Christoph Bert
- Strahlenklinik, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Oliver Blanck
- Klinik für Strahlentherapie, Universitätsklinikum Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Maximilian I Ruge
- Klinik für Stereotaxie und funktionelle Neurochirurgie, Zentrum für Neurochirurgie, Universitätsklinikum Köln, Cologne, Germany
| | - Elke Hattingen
- Institut für Neuroradiologie, Universitätsklinikum Frankfurt, Frankfurt am Main, Germany
| | - Christian P Karger
- Abteilung Medizinische Physik in der Strahlentherapie, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany
- Nationales Zentrum für Strahlenforschung in der Onkologie (NCRO), Heidelberger Institut für Radioonkologie (HIRO), Heidelberg, Germany
| | - Rainer Fietkau
- Strahlenklinik, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Johanna Grigo
- Strahlenklinik, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Manuel A Schmidt
- Neuroradiologisches Institut, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Tobias Bäuerle
- Radiologisches Institut, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Andrea Wittig
- Klinik und Poliklinik für Strahlentherapie und Radioonkologie, Universitätsklinikum Würzburg, Würzburg, Germany
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21
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Cahill K, Rienecker S, O'Connor P, Denham M, Gibbons F, Willis D, Vignarajah D, Buddle N, Min M. Implementation of a retrofit MRI simulator for radiation therapy planning. J Med Radiat Sci 2023; 70:498-508. [PMID: 37315100 PMCID: PMC10715355 DOI: 10.1002/jmrs.693] [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: 12/18/2022] [Accepted: 05/23/2023] [Indexed: 06/16/2023] Open
Abstract
Magnetic resonance imaging (MRI) is being integrated into routine radiation therapy (RT) planning workflows. To reap the benefits of this imaging modality, patient positioning, image acquisition parameters and a quality assurance programme must be considered for accurate use. This paper will report on the implementation of a retrofit MRI Simulator for RT planning, demonstrating an economical, resource efficient solution to improve the accuracy of MRI in this setting.
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Affiliation(s)
- Katelyn Cahill
- Adem Crosby Centre – Radiation OncologySunshine Coast University HospitalBirtinyaQueenslandAustralia
- Sunshine Coast Mind and Neuroscience – Thompson InstituteUniversity of the Sunshine CoastBirtinyaQueenslandAustralia
- University of the Sunshine CoastSippy DownsQueenslandAustralia
| | - Shermiyah Rienecker
- Biomedical Technology ServicesRoyal Brisbane and Women's HospitalHerstonQueenslandAustralia
| | - Patrick O'Connor
- Adem Crosby Centre – Radiation OncologySunshine Coast University HospitalBirtinyaQueenslandAustralia
- University of QueenslandSt LuciaQueenslandAustralia
| | - Mark Denham
- Department of Medical ImagingSunshine Coast University HospitalBirtinyaQueenslandAustralia
| | - Francis Gibbons
- Adem Crosby Centre – Radiation OncologySunshine Coast University HospitalBirtinyaQueenslandAustralia
| | - David Willis
- Adem Crosby Centre – Radiation OncologySunshine Coast University HospitalBirtinyaQueenslandAustralia
| | - Dinesh Vignarajah
- Adem Crosby Centre – Radiation OncologySunshine Coast University HospitalBirtinyaQueenslandAustralia
- Griffith UniversityBrisbaneQueenslandAustralia
| | - Nicole Buddle
- Adem Crosby Centre – Radiation OncologySunshine Coast University HospitalBirtinyaQueenslandAustralia
| | - Myo Min
- Adem Crosby Centre – Radiation OncologySunshine Coast University HospitalBirtinyaQueenslandAustralia
- University of the Sunshine CoastSippy DownsQueenslandAustralia
- Griffith UniversityBrisbaneQueenslandAustralia
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22
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Hasler SW, Kallehauge JF, Hansen RH, Samsøe E, Arp DT, Nissen HD, Edmund JM, Bernchou U, Mahmood F. Geometric distortions in clinical MRI sequences for radiotherapy: insights gained from a multicenter investigation. Acta Oncol 2023; 62:1551-1560. [PMID: 37815867 DOI: 10.1080/0284186x.2023.2266560] [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: 05/23/2023] [Accepted: 09/28/2023] [Indexed: 10/12/2023]
Abstract
BACKGROUND As magnetic resonance imaging (MRI) becomes increasingly integrated into radiotherapy (RT) for enhanced treatment planning and adaptation, the inherent geometric distortion in acquired MR images pose a potential challenge to treatment accuracy. This study aimed to evaluate the geometric distortion levels in the clinical MRI protocols used across Danish RT centers and discuss influence of specific sequence parameters. Based on the variety in geometric performance across centers, we assess if harmonization of MRI sequences is a relevant measure. MATERIALS AND METHODS Nine centers participated with 12 MRI scanners and MRI-Linacs (MRL). Using a travelling phantom approach, a reference MRI sequence was used to assess variation in baseline distortion level between scanners. The phantom was also scanned with local clinical MRI sequences for brain, head/neck (H/N), abdomen, and pelvis. The influence of echo time, receiver bandwidth, image weighting, and 2D/3D acquisition was investigated. RESULTS We found a large variation in geometric accuracy across 93 clinical sequences examined, exceeding the baseline variation found between MRI scanners (σ = 0.22 mm), except for abdominal sequences where the variation was lower. Brain and abdominal sequences showed lowest distortion levels ([0.22, 2.26] mm), and a large variation in performance was found for H/N and pelvic sequences ([0.19, 4.07] mm). Post hoc analyses revealed that distortion levels decreased with increasing bandwidth and a less clear increase in distortion levels with increasing echo time. 3D MRI sequences had lower distortion levels than 2D (median of 1.10 and 2.10 mm, respectively), and in DWI sequences, the echo-planar imaging read-out resulted in highest distortion levels. CONCLUSION There is a large variation in the geometric distortion levels of clinical MRI sequences across Danish RT centers, and between anatomical sites. The large variation observed makes harmonization of MRI sequences across institutions and adoption of practices from well-performing anatomical sites, a relevant measure within RT.
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Affiliation(s)
- Signe Winther Hasler
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Odense, Denmark
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Jesper Folsted Kallehauge
- Danish Centre for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Rasmus Hvass Hansen
- Section for Radiation Therapy, Department of Oncology, Center for Cancer and Organ Diseases, Copenhagen University Hospital, Copenhagen, Denmark
| | - Eva Samsøe
- Department of Clinical Oncology, Zealand University Hospital, Naestved, Denmark
| | - Dennis Tideman Arp
- Department of Medical Physics, Department of Oncology, Aalborg University Hospital, Aalborg, Denmark
| | - Henrik Dahl Nissen
- Department of Medical Physics, Vejle Hospital, University Hospital of Southern Denmark, Vejle, Denmark
| | - Jens M Edmund
- Radiotherapy Research Unit, Department of Oncology, Herlev and Gentofte Hospital, Herlev, Denmark
- Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
| | - Uffe Bernchou
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Odense, Denmark
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Faisal Mahmood
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Odense, Denmark
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
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23
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Marasini S, Zhang H, Dyke L, Cole M, Quinn B, Curcuru A, Gu B, Flores R, Kim T. Comprehensive MR imaging QA of 0.35 T MR-Linac using a multi-purpose large FOV phantom: A single-institution experience. J Appl Clin Med Phys 2023; 24:e14066. [PMID: 37307238 PMCID: PMC10562018 DOI: 10.1002/acm2.14066] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 04/27/2023] [Accepted: 05/31/2023] [Indexed: 06/14/2023] Open
Abstract
PURPOSE Magnetic resonance-guided radiotherapy (MRgRT) is desired for the treatment of diseases in the abdominothoracic region, which has a broad imaging area and continuous motion. To ensure accurate treatment delivery, an effective image quality assurance (QA) program, with a phantom that covers the field of view (FOV) similar to a human torso, is required. However, routine image QA for a large FOV is not readily available at many MRgRT centers. In this work, we present the clinical experience of the large FOV MRgRT Insight phantom for periodic daily and monthly comprehensive magnetic resonance imaging (MRI)-QA and its feasibility compared to the existing institutional routine MRI-QA procedures in 0.35 T MRgRT. METHODS Three phantoms; ViewRay cylindrical water phantom, Fluke 76-907 uniformity and linearity phantom, and Modus QA large FOV MRgRT Insight phantom, were imaged on the 0.35 T MR-Linac. The measurements were made in MRI mode with the true fast imaging with steady-state free precession (TRUFI) sequence. The ViewRay cylindrical water phantom was imaged in a single-position setup whereas the Fluke phantom and Insight phantom were imaged in three different orientations: axial, sagittal, and coronal. Additionally, the phased array coil QA was performed using the horizontal base plate of the Insight phantom by placing the desired coil around the base section which was compared to an in-house built Polyurethane foam phantom for reference. RESULT The Insight phantom captured image artifacts across the entire planar field of view, up to 400 mm, in a single image acquisition, which is beyond the FOV of the conventional phantoms. The geometric distortion test showed a similar distortion of 0.45 ± 0.01 and 0.41 ± 0.01 mm near the isocenter, that is, within 300 mm lengths for Fluke and Insight phantoms, respectively, but showed higher geometric distortion of 0.8 ± 0.4 mm in the peripheral region between 300 and 400 mm of the imaging slice for the Insight phantom. The Insight phantom with multiple image quality features and its accompanying software utilized the modulation transform function (MTF) to evaluate the image spatial resolution. The average MTF values were 0.35 ± 0.01, 0.35 ± 0.01, and 0.34 ± 0.03 for axial, coronal, and sagittal images, respectively. The plane alignment and spatial accuracy of the ViewRay water phantom were measured manually. The phased array coil test for both the Insight phantom and the Polyurethane foam phantoms ensured the proper functionality of each coil element. CONCLUSION The multifunctional large FOV Insight phantom helps in tracking MR imaging quality of the system to a larger extent compared to the routine daily and monthly QA phantoms currently used in our institute. Also, the Insight phantom is found to be more feasible for routine QA with easy setup.
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Affiliation(s)
- Shanti Marasini
- Department of Radiation OncologyWashington University School of MedicineSt. LouisUSA
| | - Hailei Zhang
- Department of Radiation OncologyWashington University School of MedicineSt. LouisUSA
| | - Lara Dyke
- Department of Radiation OncologyWashington University School of MedicineSt. LouisUSA
| | | | | | - Austen Curcuru
- Department of Biomedical EngineeringWashington University School of MedicineSt. LouisUSA
| | - Bruce Gu
- Department of Radiation OncologyWashington University School of MedicineSt. LouisUSA
| | | | - Taeho Kim
- Department of Radiation OncologyWashington University School of MedicineSt. LouisUSA
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24
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Feng L. Live-view 4D GRASP MRI: A framework for robust real-time respiratory motion tracking with a sub-second imaging latency. Magn Reson Med 2023; 90:1053-1068. [PMID: 37203314 PMCID: PMC10330383 DOI: 10.1002/mrm.29700] [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: 10/13/2022] [Revised: 04/21/2023] [Accepted: 04/21/2023] [Indexed: 05/20/2023]
Abstract
PURPOSE To propose a framework called live-view golden-angle radial sparse parallel (GRASP) MRI for low-latency and high-fidelity real-time volumetric MRI. METHODS Live-view GRASP MRI has two stages. The first one is called an off-view stage and the second one is called a live-view stage. In the off-view stage, 3D k-space data and 2D navigators are acquired alternatively using a new navi-stack-of-stars sampling scheme. A 4D motion database is then generated that contains time-resolved MR images at a sub-second temporal resolution, and each image is linked to a 2D navigator. In the live-view stage, only 2D navigators are acquired. At each time point, a live-view 2D navigator is matched to all the off-view 2D navigators. A 3D image that is linked to the best-matched off-view 2D navigator is then selected for this time point. This framework places the typical acquisition and reconstruction burden of MRI in the off-view stage, enabling low-latency real-time 3D imaging in the live-view stage. The accuracy of live-view GRASP MRI and the robustness of 2D navigators for characterizing respiratory variations and/or body movements were assessed. RESULTS Live-view GRASP MRI can efficiently generate real-time volumetric images that match well with the ground-truth references, with an imaging latency below 500 ms. Compared to 1D navigators, 2D navigators enable more reliable characterization of respiratory variations and/or body movements that may occur throughout the two imaging stages. CONCLUSION Live-view GRASP MRI represents a novel, accurate, and robust framework for real-time volumetric imaging, which can potentially be applied for motion adaptive radiotherapy on MRI-Linac.
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Affiliation(s)
- Li Feng
- Center for Advanced Imaging Innovation and Research (CAI2R), New York University Grossman School of Medicine, New York, New York, USA
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, New York, USA
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25
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Amjad A, Xu J, Thill D, Zhang Y, Ding J, Paulson E, Hall W, Erickson BA, Li XA. Deep learning auto-segmentation on multi-sequence magnetic resonance images for upper abdominal organs. Front Oncol 2023; 13:1209558. [PMID: 37483486 PMCID: PMC10358771 DOI: 10.3389/fonc.2023.1209558] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 06/19/2023] [Indexed: 07/25/2023] Open
Abstract
Introduction Multi-sequence multi-parameter MRIs are often used to define targets and/or organs at risk (OAR) in radiation therapy (RT) planning. Deep learning has so far focused on developing auto-segmentation models based on a single MRI sequence. The purpose of this work is to develop a multi-sequence deep learning based auto-segmentation (mS-DLAS) based on multi-sequence abdominal MRIs. Materials and methods Using a previously developed 3DResUnet network, a mS-DLAS model using 4 T1 and T2 weighted MRI acquired during routine RT simulation for 71 cases with abdominal tumors was trained and tested. Strategies including data pre-processing, Z-normalization approach, and data augmentation were employed. Additional 2 sequence specific T1 weighted (T1-M) and T2 weighted (T2-M) models were trained to evaluate performance of sequence-specific DLAS. Performance of all models was quantitatively evaluated using 6 surface and volumetric accuracy metrics. Results The developed DLAS models were able to generate reasonable contours of 12 upper abdomen organs within 21 seconds for each testing case. The 3D average values of dice similarity coefficient (DSC), mean distance to agreement (MDA mm), 95 percentile Hausdorff distance (HD95% mm), percent volume difference (PVD), surface DSC (sDSC), and relative added path length (rAPL mm/cc) over all organs were 0.87, 1.79, 7.43, -8.95, 0.82, and 12.25, respectively, for mS-DLAS model. Collectively, 71% of the auto-segmented contours by the three models had relatively high quality. Additionally, the obtained mS-DLAS successfully segmented 9 out of 16 MRI sequences that were not used in the model training. Conclusion We have developed an MRI-based mS-DLAS model for auto-segmenting of upper abdominal organs on MRI. Multi-sequence segmentation is desirable in routine clinical practice of RT for accurate organ and target delineation, particularly for abdominal tumors. Our work will act as a stepping stone for acquiring fast and accurate segmentation on multi-contrast MRI and make way for MR only guided radiation therapy.
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Affiliation(s)
- Asma Amjad
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, United States
| | | | - Dan Thill
- Elekta Inc., ST. Charles, MO, United States
| | - Ying Zhang
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Jie Ding
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Eric Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - William Hall
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Beth A. Erickson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - X. Allen Li
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, United States
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Chick J, Alexander S, Herbert T, Huddart R, Ingle M, Mitchell A, Nill S, Oelfke U, Dunlop A, Hafeez S. Evaluation of non-vendor magnetic resonance imaging sequences for use in bladder cancer magnetic resonance image guided radiotherapy. Phys Imaging Radiat Oncol 2023; 27:100481. [PMID: 37655122 PMCID: PMC10465927 DOI: 10.1016/j.phro.2023.100481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 08/07/2023] [Accepted: 08/11/2023] [Indexed: 09/02/2023] Open
Abstract
Hybrid systems that combine Magnetic Resonance Imaging (MRI) and linear accelerators are available clinically to guide and adapt radiotherapy. Vendor-approved MRI sequences are provided, however alternative sequences may offer advantages. The aim of this study was to develop a systematic approach for non-vendor sequence evaluation, to determine safety, accuracy and overall clinical application of two potential sequences for bladder cancer MRI guided radiotherapy. Non-vendor sequences underwent and passed clinical image qualitative review, phantom quality assurance, and radiotherapy planning assessments. Volunteer workflow tests showed the potential for one sequence to reduce workflow time by 27% compared to the standard vendor sequence.
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Affiliation(s)
- Joan Chick
- The Joint Department of Physics at The Institute of Cancer Research & The Royal Marsden NHS Foundation Trust, Downs Road, Sutton SM2 5PT, UK
| | - Sophie Alexander
- The Institute of Cancer Research & The Royal Marsden NHS Foundation Trust, Downs Road, Sutton SM2 5PT, UK
| | - Trina Herbert
- The Royal Marsden NHS Foundation Trust, Downs Road, Sutton SM2 5PT, UK
| | - Robert Huddart
- The Institute of Cancer Research & The Royal Marsden NHS Foundation Trust, Downs Road, Sutton SM2 5PT, UK
| | - Manasi Ingle
- The Institute of Cancer Research & The Royal Marsden NHS Foundation Trust, Downs Road, Sutton SM2 5PT, UK
| | - Adam Mitchell
- The Joint Department of Physics at The Institute of Cancer Research & The Royal Marsden NHS Foundation Trust, Downs Road, Sutton SM2 5PT, UK
| | - Simeon Nill
- The Joint Department of Physics at The Institute of Cancer Research & The Royal Marsden NHS Foundation Trust, Downs Road, Sutton SM2 5PT, UK
| | - Uwe Oelfke
- The Joint Department of Physics at The Institute of Cancer Research & The Royal Marsden NHS Foundation Trust, Downs Road, Sutton SM2 5PT, UK
| | - Alex Dunlop
- The Joint Department of Physics at The Institute of Cancer Research & The Royal Marsden NHS Foundation Trust, Downs Road, Sutton SM2 5PT, UK
| | - Shaista Hafeez
- The Institute of Cancer Research & The Royal Marsden NHS Foundation Trust, Downs Road, Sutton SM2 5PT, UK
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Sohn JJ, Lim S, Das IJ, Yadav P. An integrated and fast imaging quality assurance phantom for a 0.35 T magnetic resonance imaging linear accelerator. Phys Imaging Radiat Oncol 2023; 27:100462. [PMID: 37449023 PMCID: PMC10338140 DOI: 10.1016/j.phro.2023.100462] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 06/17/2023] [Accepted: 06/20/2023] [Indexed: 07/18/2023] Open
Abstract
Purpose Periodic imaging quality assurance (QA) of magnetic resonance imaging linear accelerator (MRL) is critical. The feasibility of a new MRL imaging phantom used for QA in the low field was evaluated with automated image analysis of various parameters for accuracy and reproducibility. Methods and materials The new MRL imaging phantom was scanned across every 30 degrees of the gantry, having the on/off state of the linac in a low-field MRL system using three magnetic resonance imaging sequences: true fast imaging with steady-state precession (TrueFISP), T1 weighted (T1W), and T2 weighted (T2W). The DICOM files were used to calculate the imaging parameters: geometric distortion, uniformity, resolution, signal-to-noise ratio (SNR), and laser alignment. The point spread function (PSF) and edge spread function (ESF) were also calculated for resolution analysis. Results The phantom data showed a small standard deviation - and high consistency for each imaging parameter. The highest variability in data was observed with the true fast imaging sequence at the calibration angle, which was expected because of low resolution and short scan time (25 sec). The mean magnitude of the largest distortion measured within 200 mm diameter with TrueFISP was 0.31 ± 0.05 mm. The PSF, ESF, signal uniformity, and SNR measurements remained consistent. Laser alignment traditional offsets and angular deviation remained consistent. Conclusions The new MRL imaging phantom is reliable, reproducible, time effective, and easy to use for a 0.35 T MRL system. The results promise a more streamlined, time-saving, and error-free QA process for low-field MRL adapted in our clinical setting.
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Affiliation(s)
| | | | | | - Poonam Yadav
- Corresponding author at: Department of Radiation Oncology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.
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Dorsch S, Paul K, Beyer C, Karger CP, Jäkel O, Debus J, Klüter S. Quality assurance and temporal stability of a 1.5 T MRI scanner for MR-guided Photon and Particle Therapy. Z Med Phys 2023:S0939-3889(23)00046-6. [PMID: 37150727 DOI: 10.1016/j.zemedi.2023.04.004] [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: 08/26/2022] [Revised: 03/12/2023] [Accepted: 04/04/2023] [Indexed: 05/09/2023]
Abstract
PURPOSE To describe performance measurements, adaptations and time stability over 20 months of a diagnostic MR scanner for integration into MR-guided photon and particle radiotherapy. MATERIAL AND METHODS For realization of MR-guided photon and particle therapy (MRgRT/MRgPT), a 1.5 T MR scanner was installed at the Heidelberg Ion Beam Therapy Center. To integrate MRI into the treatment process, a flat tabletop and dedicated coil holders for flex coils were used, which prevent deformation of the patient external contour and allow for the use of immobilization tools for reproducible positioning. The signal-to-noise ratio (SNR) was compared for the diagnostic and therapy-specific setup using the flat couch top and flexible coils for the a) head & neck and b) abdominal region as well as for different bandwidths and clinical pulse sequences. Additionally, a quality assurance (QA) protocol with monthly measurements of the ACR phantom and measurement of geometric distortions for a large field-of-view (FOV) was implemented to assess the imaging quality parameters of the device over the course of 20 months. RESULTS The SNR measurements showed a decreased SNR for the RT-specific as compared to the diagnostic setup of (a) 26% to 34% and (b) 11% to 33%. No significant bandwidth dependency for this ratio was found. The longitudinal assessment of the image quality parameters with the ACR and distortion phantom confirmed the long-term stability of the MRI device. CONCLUSION A diagnostic MRI was commissioned for use in MR-guided particle therapy. Using a radiotherapy specific setup, a high geometric accuracy and signal homogeneity was obtained after some adaptions and the measured parameters were shown to be stable over a period of 20 months.
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Affiliation(s)
- Stefan Dorsch
- Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), INF 280, 69120 Heidelberg, Germany; National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany; Department of Radiation Oncology, University Hospital Heidelberg, INF 400, 69120 Heidelberg, Germany.
| | - Katharina Paul
- National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany; Department of Radiation Oncology, University Hospital Heidelberg, INF 400, 69120 Heidelberg, Germany
| | - Cedric Beyer
- National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany; Department of Radiation Oncology, University Hospital Heidelberg, INF 400, 69120 Heidelberg, Germany
| | - Christian P Karger
- Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), INF 280, 69120 Heidelberg, Germany; National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany
| | - Oliver Jäkel
- Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), INF 280, 69120 Heidelberg, Germany; National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany; Heidelberg Ion-Beam Therapy Center (HIT), Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Jürgen Debus
- National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany; Department of Radiation Oncology, University Hospital Heidelberg, INF 400, 69120 Heidelberg, Germany; Heidelberg Ion-Beam Therapy Center (HIT), Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany; Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Core center Heidelberg, German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Sebastian Klüter
- National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany; Department of Radiation Oncology, University Hospital Heidelberg, INF 400, 69120 Heidelberg, Germany.
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Aliotta E, Hu YC, Zhang P, Lichtenwalner P, Caringi A, Allgood N, Tsai CJ, Zakeri K, Lee N, Zhang P, Cerviño L, Aristophanous M. Automated tracking of morphologic changes in weekly magnetic resonance imaging during head and neck radiotherapy. J Appl Clin Med Phys 2023:e13959. [PMID: 37147912 DOI: 10.1002/acm2.13959] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 12/15/2022] [Accepted: 02/20/2023] [Indexed: 05/07/2023] Open
Abstract
BACKGROUND AND PURPOSE Anatomic changes during head and neck radiotherapy can impact dose delivery, necessitate adaptive replanning, and indicate patient-specific response to treatment. We have developed an automated system to track these changes through longitudinal MRI scans to aid identification and clinical intervention. The purpose of this article is to describe this tracking system and present results from an initial cohort of patients. MATERIALS AND METHODS The Automated Watchdog in Adaptive Radiotherapy Environment (AWARE) was developed to process longitudinal MRI data for radiotherapy patients. AWARE automatically identifies and collects weekly scans, propagates radiotherapy planning structures, computes structure changes over time, and reports important trends to the clinical team. AWARE also incorporates manual structure review and revision from clinical experts and dynamically updates tracking statistics when necessary. AWARE was applied to patients receiving weekly T2-weighted MRI scans during head and neck radiotherapy. Changes in nodal gross tumor volume (GTV) and parotid gland delineations were tracked over time to assess changes during treatment and identify early indicators of treatment response. RESULTS N = 91 patients were tracked and analyzed in this study. Nodal GTVs and parotids both shrunk considerably throughout treatment (-9.7 ± 7.7% and -3.7 ± 3.3% per week, respectively). Ipsilateral parotids shrunk significantly faster than contralateral (-4.3 ± 3.1% vs. -2.9 ± 3.3% per week, p = 0.005) and increased in distance from GTVs over time (+2.7 ± 7.2% per week, p < 1 × 10-5 ). Automatic structure propagations agreed well with manual revisions (Dice = 0.88 ± 0.09 for parotids and 0.80 ± 0.15 for GTVs), but for GTVs the agreement degraded 4-5 weeks after the start of treatment. Changes in GTV volume observed by AWARE as early as one week into treatment were predictive of large changes later in the course (AUC = 0.79). CONCLUSION AWARE automatically identified longitudinal changes in GTV and parotid volumes during radiotherapy. Results suggest that this system may be useful for identifying rapidly responding patients as early as one week into treatment.
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Affiliation(s)
- Eric Aliotta
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Yu-Chi Hu
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Peng Zhang
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Phillip Lichtenwalner
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Amanda Caringi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Natasha Allgood
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - C Jillian Tsai
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Kaveh Zakeri
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Nancy Lee
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Pengpeng Zhang
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Laura Cerviño
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Michalis Aristophanous
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
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Delaby N, Barateau A, Chiavassa S, Biston MC, Chartier P, Graulières E, Guinement L, Huger S, Lacornerie T, Millardet-Martin C, Sottiaux A, Caron J, Gensanne D, Pointreau Y, Coutte A, Biau J, Serre AA, Castelli J, Tomsej M, Garcia R, Khamphan C, Badey A. Practical and technical key challenges in head and neck adaptive radiotherapy: The GORTEC point of view. Phys Med 2023; 109:102568. [PMID: 37015168 DOI: 10.1016/j.ejmp.2023.102568] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 02/15/2023] [Accepted: 03/18/2023] [Indexed: 04/05/2023] Open
Abstract
Anatomical variations occur during head and neck (H&N) radiotherapy (RT) treatment. These variations may result in underdosage to the target volume or overdosage to the organ at risk. Replanning during the treatment course can be triggered to overcome this issue. Due to technological, methodological and clinical evolutions, tools for adaptive RT (ART) are becoming increasingly sophisticated. The aim of this paper is to give an overview of the key steps of an H&N ART workflow and tools from the point of view of a group of French-speaking medical physicists and physicians (from GORTEC). Focuses are made on image registration, segmentation, estimation of the delivered dose of the day, workflow and quality assurance for an implementation of H&N offline and online ART. Practical recommendations are given to assist physicians and medical physicists in a clinical workflow.
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Tanadini-Lang S, Budgell G, Bohoudi O, Corradini S, Cusumano D, Güngör G, Kerkmeijer LGW, Mahmood F, Nill S, Palacios MA, Reiner M, Thorwarth D, Wilke L, Wolthaus J. An ESTRO-ACROP guideline on quality assurance and medical physics commissioning of online MRI guided radiotherapy systems based on a consensus expert opinion. Radiother Oncol 2023; 181:109504. [PMID: 36736592 DOI: 10.1016/j.radonc.2023.109504] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 01/25/2023] [Indexed: 02/05/2023]
Abstract
OBJECTIVE The goal of this consensus expert opinion was to define quality assurance (QA) tests for online magnetic resonance image (MRI) guided radiotherapy (oMRgRT) systems and to define the important medical physics aspects for installation and commissioning of an oMRgRT system. MATERIALS AND METHODS Ten medical physicists and two radiation oncologists experienced in oMRgRT participated in the survey. In the first round of the consensus expert opinion, ideas on QA and commissioning were collected. Only tests and aspects different from commissioning of a CT guided radiotherapy (RT) system were considered. In the following two rounds all twelve participants voted on the importance of the QA tests, their recommended frequency and their suitability for the two oMRgRT systems approved for clinical use as well as on the importance of the aspects to consider during medical physics commissioning. RESULTS Twenty-four QA tests were identified which are potentially important during commissioning and routine QA on oMRgRT systems compared to online CT guided RT systems. An additional eleven tasks and aspects related to construction, workflow development and training were collected. Consensus was found for most tests on their importance, their recommended frequency and their suitability for the two approved systems. In addition, eight aspects mostly related to the definition of workflows were also found to be important during commissioning. CONCLUSIONS A program for QA and commissioning of oMRgRT systems was developed to support medical physicists to prepare for safe handling of such systems.
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Affiliation(s)
- Stephanie Tanadini-Lang
- Department of Radiation Oncology, University Hospital Zurich, University of Zurich, 8091 Zurich, Switzerland.
| | - Geoff Budgell
- Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Wilmslow Road, Manchester iM20 4BX, UK
| | - Omar Bohoudi
- Amsterdam UMC, Vrije Universiteit Medical Centre, Dept. of Radiation Oncology, de Boelelaan 1117, 1081 HV Amsterdam, the Netherlands
| | - Stefanie Corradini
- Department of Radiation Oncology, University Hospital, LMU Munich, 81377 Munich, Germany
| | - Davide Cusumano
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy; Mater Olbia Hospital, Olbia, SS, Italy
| | - Görkem Güngör
- Department of Medical Physics, Graduade School of Health Sciences, Istanbul Medipol University, Istanbul, Turkey
| | - Linda G W Kerkmeijer
- Department of Radiation Oncology, Radboud University Medical Center Nijmegen, the Netherlands
| | - Faisal Mahmood
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Odense, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Simeon Nill
- The Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Miguel A Palacios
- Amsterdam UMC, Vrije Universiteit Medical Centre, Dept. of Radiation Oncology, de Boelelaan 1117, 1081 HV Amsterdam, the Netherlands
| | - Michael Reiner
- Department of Radiation Oncology, University Hospital, LMU Munich, 81377 Munich, Germany
| | - Daniela Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Lotte Wilke
- Department of Radiation Oncology, University Hospital Zurich, University of Zurich, 8091 Zurich, Switzerland
| | - Jochem Wolthaus
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands
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Liu X, Li Z, Yin Y. Clinical application of MR-Linac in tumor radiotherapy: a systematic review. Radiat Oncol 2023; 18:52. [PMID: 36918884 PMCID: PMC10015924 DOI: 10.1186/s13014-023-02221-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 02/01/2023] [Indexed: 03/15/2023] Open
Abstract
Recent years have seen both a fresh knowledge of cancer and impressive advancements in its treatment. However, the clinical treatment paradigm of cancer is still difficult to implement in the twenty-first century due to the rise in its prevalence. Radiotherapy (RT) is a crucial component of cancer treatment that is helpful for almost all cancer types. The accuracy of RT dosage delivery is increasing as a result of the quick development of computer and imaging technology. The use of image-guided radiation (IGRT) has improved cancer outcomes and decreased toxicity. Online adaptive radiotherapy will be made possible by magnetic resonance imaging-guided radiotherapy (MRgRT) using a magnetic resonance linear accelerator (MR-Linac), which will enhance the visibility of malignancies. This review's objectives are to examine the benefits of MR-Linac as a treatment approach from the perspective of various cancer patients' prognoses and to suggest prospective development areas for additional study.
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Affiliation(s)
- Xin Liu
- Department of Oncology, Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China.,Department of Radiation Physics, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117, China
| | - Zhenjiang Li
- Department of Radiation Physics, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117, China.
| | - Yong Yin
- Department of Oncology, Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China. .,Department of Radiation Physics, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, 250117, China.
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Cook N, Shelton N, Gibson S, Barnes P, Alinaghi-Zadeh R, Jameson MG. ACPSEM position paper: the safety of magnetic resonance imaging linear accelerators. Phys Eng Sci Med 2023; 46:19-43. [PMID: 36847966 PMCID: PMC10030425 DOI: 10.1007/s13246-023-01224-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/19/2023] [Indexed: 03/01/2023]
Abstract
Magnetic Resonance Imaging linear-accelerator (MRI-linac) equipment has recently been introduced to multiple centres in Australia and New Zealand. MRI equipment creates hazards for staff, patients and others in the MR environment; these hazards must be well understood, and risks managed by a system of environmental controls, written procedures and a trained workforce. While MRI-linac hazards are similar to the diagnostic paradigm, the equipment, workforce and environment are sufficiently different that additional safety guidance is warranted. In 2019 the Australasian College of Physical Scientists and Engineers in Medicine (ACPSEM) formed the Magnetic Resonance Imaging Linear-Accelerator Working Group (MRILWG) to support the safe clinical introduction and optimal use of MR-guided radiation therapy treatment units. This Position Paper is intended to provide safety guidance and education for Medical Physicists and others planning for and working with MRI-linac technology. This document summarises MRI-linac hazards and describes particular effects which arise from the combination of strong magnetic fields with an external radiation treatment beam. This document also provides guidance on safety governance and training, and recommends a system of hazard management tailored to the MRI-linac environment, ancillary equipment, and workforce.
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Affiliation(s)
- Nick Cook
- Christchurch Hospital, Christchurch, New Zealand
| | - Nikki Shelton
- Olivia Newton-John Cancer Wellness and Research Centre, Heidelberg, VIC Australia
| | | | | | - Reza Alinaghi-Zadeh
- Olivia Newton-John Cancer Wellness and Research Centre, Heidelberg, VIC Australia
| | - Michael G. Jameson
- GenesisCare, Sydney, NSW Australia
- University of New South Wales, Sydney, Australia
| | - on behalf of the ACPSEM Magnetic Resonance Imaging Linac Working Group (MRILWG)
- Christchurch Hospital, Christchurch, New Zealand
- Olivia Newton-John Cancer Wellness and Research Centre, Heidelberg, VIC Australia
- Townsville Cancer Centre, Douglas, QLD Australia
- Austin Health, Heidelberg, VIC Australia
- GenesisCare, Sydney, NSW Australia
- University of New South Wales, Sydney, Australia
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Quality and Safety Considerations in Image Guided Radiation Therapy: An ASTRO Safety White Paper Update. Pract Radiat Oncol 2023; 13:97-111. [PMID: 36585312 DOI: 10.1016/j.prro.2022.09.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 09/07/2022] [Accepted: 09/08/2022] [Indexed: 12/30/2022]
Abstract
PURPOSE This updated report on image guided radiation therapy (IGRT) is part of a series of consensus-based white papers previously published by the American Society for Radiation Oncology addressing patient safety. Since the first white papers were published, IGRT technology and procedures have progressed significantly such that these procedures are now more commonly used. The use of IGRT has now extended beyond high-precision treatments, such as stereotactic radiosurgery and stereotactic body radiation therapy, and into routine clinical practice for many treatment techniques and anatomic sites. Therefore, quality and patient safety considerations for these techniques remain an important area of focus. METHODS AND MATERIALS The American Society for Radiation Oncology convened an interdisciplinary task force to assess the original IGRT white paper and update content where appropriate. Recommendations were created using a consensus-building methodology, and task force members indicated their level of agreement based on a 5-point Likert scale from "strongly agree" to "strongly disagree." A prespecified threshold of ≥75% of raters who selected "strongly agree" or "agree" indicated consensus. SUMMARY This IGRT white paper builds on the previous version and uses other guidance documents to primarily focus on processes related to quality and safety. IGRT requires an interdisciplinary team-based approach, staffed by appropriately trained specialists, as well as significant personnel resources, specialized technology, and implementation time. A thorough feasibility analysis of resources is required to achieve the clinical and technical goals and should be discussed with all personnel before undertaking new imaging techniques. A comprehensive quality-assurance program must be developed, using established guidance, to ensure IGRT is performed in a safe and effective manner. As IGRT technologies continue to improve or emerge, existing practice guidelines should be reviewed or updated regularly according to the latest American Association of Physicists in Medicine Task Group reports or guidelines. Patient safety in the application of IGRT is everyone's responsibility, and professional organizations, regulators, vendors, and end-users must demonstrate a clear commitment to working together to ensure the highest levels of safety.
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Olberg S, Choi BS, Park I, Liang X, Kim JS, Deng J, Yan Y, Jiang S, Park JC. Ensemble learning and personalized training for the improvement of unsupervised deep learning-based synthetic CT reconstruction. Med Phys 2023; 50:1436-1449. [PMID: 36336718 DOI: 10.1002/mp.16087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 08/22/2022] [Accepted: 10/19/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND The growing adoption of magnetic resonance imaging (MRI)-guided radiation therapy (RT) platforms and a focus on MRI-only RT workflows have brought the technical challenge of synthetic computed tomography (sCT) reconstruction to the forefront. Unpaired-data deep learning-based approaches to the problem offer the attractive characteristic of not requiring paired training data, but the gap between paired- and unpaired-data results can be limiting. PURPOSE We present two distinct approaches aimed at improving unpaired-data sCT reconstruction results: a cascade ensemble that combines multiple models and a personalized training strategy originally designed for the paired-data setting. METHODS Comparisons are made between the following models: (1) the paired-data fully convolutional DenseNet (FCDN), (2) the FCDN with the Intentional Deep Overfit Learning (IDOL) personalized training strategy, (3) the unpaired-data CycleGAN, (4) the CycleGAN with the IDOL training strategy, and (5) the CycleGAN as an intermediate model in a cascade ensemble approach. Evaluation of the various models over 25 total patients is carried out using a five-fold cross-validation scheme, with the patient-specific IDOL models being trained for the five patients of fold 3, chosen at random. RESULTS In both the paired- and unpaired-data settings, adopting the IDOL training strategy led to improvements in the mean absolute error (MAE) between true CT images and sCT outputs within the body contour (mean improvement, paired- and unpaired-data approaches, respectively: 38%, 9%) and in regions of bone (52%, 5%), the peak signal-to-noise ratio (PSNR; 15%, 7%), and the structural similarity index (SSIM; 6%, <1%). The ensemble approach offered additional benefits over the IDOL approach in all three metrics (mean improvement over unpaired-data approach in fold 3; MAE: 20%; bone MAE: 16%; PSNR: 10%; SSIM: 2%), and differences in body MAE between the ensemble approach and the paired-data approach are statistically insignificant. CONCLUSIONS We have demonstrated that both a cascade ensemble approach and a personalized training strategy designed initially for the paired-data setting offer significant improvements in image quality metrics for the unpaired-data sCT reconstruction task. Closing the gap between paired- and unpaired-data approaches is a step toward fully enabling these powerful and attractive unpaired-data frameworks.
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Affiliation(s)
- Sven Olberg
- Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Byong Su Choi
- Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Medical Physics and Biomedical Engineering Lab (MPBEL), Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea
| | - Inkyung Park
- Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Medical Physics and Biomedical Engineering Lab (MPBEL), Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea
| | - Xiao Liang
- Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Jin Sung Kim
- Medical Physics and Biomedical Engineering Lab (MPBEL), Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea
- Oncosoft Inc., Seoul, South Korea
| | - Jie Deng
- Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Yulong Yan
- Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Steve Jiang
- Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Justin C Park
- Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Medical Physics and Biomedical Engineering Lab (MPBEL), Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea
- Department of Radiation Oncology, Mayo Clinic, Jacksonville, Florida, USA
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Snyder KC, Mao W, Kim JP, Cunningham J, Chetty IJ, Siddiqui SM, Parikh P, Dolan J. Commissioning, clinical implementation, and initial experience with a new brain tumor treatment package on a low‐field MR‐linac. J Appl Clin Med Phys 2023. [DOI: 10.1002/acm2.13919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/20/2023] Open
Affiliation(s)
- Karen Chin Snyder
- Department of Radiation Oncology Henry Ford Health Detroit Michigan USA
| | - Weihua Mao
- Department of Radiation Oncology Henry Ford Health Detroit Michigan USA
| | - Joshua P. Kim
- Department of Radiation Oncology Henry Ford Health Detroit Michigan USA
| | | | - Indrin J. Chetty
- Department of Radiation Oncology Henry Ford Health Detroit Michigan USA
| | - Salim M. Siddiqui
- Department of Radiation Oncology Henry Ford Health Detroit Michigan USA
| | - Parag Parikh
- Department of Radiation Oncology Henry Ford Health Detroit Michigan USA
| | - Jennifer Dolan
- Department of Radiation Oncology Henry Ford Health Detroit Michigan USA
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Moore-Palhares D, Ho L, Lu L, Chugh B, Vesprini D, Karam I, Soliman H, Symons S, Leung E, Loblaw A, Myrehaug S, Stanisz G, Sahgal A, Czarnota GJ. Clinical implementation of magnetic resonance imaging simulation for radiation oncology planning: 5 year experience. Radiat Oncol 2023; 18:27. [PMID: 36750891 PMCID: PMC9903411 DOI: 10.1186/s13014-023-02209-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Accepted: 01/16/2023] [Indexed: 02/09/2023] Open
Abstract
PURPOSE Integrating magnetic resonance (MR) into radiotherapy planning has several advantages. This report details the clinical implementation of an MR simulation (MR-planning) program for external beam radiotherapy (EBRT) in one of North America's largest radiotherapy programs. METHODS AND MATERIALS An MR radiotherapy planning program was developed and implemented at Sunnybrook Health Sciences Center in 2016 with two dedicated wide-bore MR platforms (1.5 and 3.0 Tesla). Planning MR was sequentially implemented every 3 months for separate treatment sites, including the central nervous system (CNS), gynecologic (GYN), head and neck (HN), genitourinary (GU), gastrointestinal (GI), breast, and brachial plexus. Essential protocols and processes were detailed in this report, including clinical workflow, optimized MR-image acquisition protocols, MR-adapted patient setup, strategies to overcome risks and challenges, and an MR-planning quality assurance program. This study retrospectively reviewed simulation site data for all MR-planning sessions performed for EBRT over the past 5 years. RESULTS From July 2016 to December 2021, 8798 MR-planning sessions were carried out, which corresponds to 25% of all computer tomography (CT) simulations (CT-planning) performed during the same period at our institution. There was a progressive rise from 80 MR-planning sessions in 2016 to 1126 in 2017, 1492 in 2018, 1824 in 2019, 2040 in 2020, and 2236 in 2021. As a result, the relative number of planning MR/CT increased from 3% of all planning sessions in 2016 to 36% in 2021. The most common site of MR-planning was CNS (49%), HN (13%), GYN (12%), GU (12%), and others (8%). CONCLUSION Detailed clinical processes and protocols of our MR-planning program were presented, which have been improved over more than 5 years of robust experience. Strategies to overcome risks and challenges in the implementation process are highlighted. Our work provides details that can be used by institutions interested in implementing an MR-planning program.
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Affiliation(s)
- Daniel Moore-Palhares
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada ,grid.17063.330000 0001 2157 2938Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
| | - Ling Ho
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada
| | - Lin Lu
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada
| | - Brige Chugh
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada ,grid.17063.330000 0001 2157 2938Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
| | - Danny Vesprini
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Irene Karam
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Hany Soliman
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Sean Symons
- grid.17063.330000 0001 2157 2938Physical Sciences, Sunnybrook Research Institute, Toronto, Canada ,grid.413104.30000 0000 9743 1587Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Eric Leung
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Andrew Loblaw
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Sten Myrehaug
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Greg Stanisz
- grid.17063.330000 0001 2157 2938Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
| | - Arjun Sahgal
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Gregory J. Czarnota
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada ,grid.17063.330000 0001 2157 2938Physical Sciences, Sunnybrook Research Institute, Toronto, Canada ,grid.17063.330000 0001 2157 2938Department of Medical Biophysics, University of Toronto, Toronto, Canada
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Liu PZY, Shan S, Waddington D, Whelan B, Dong B, Liney G, Keall P. Rapid distortion correction enables accurate magnetic resonance imaging-guided real-time adaptive radiotherapy. Phys Imaging Radiat Oncol 2023; 25:100414. [PMID: 36713071 PMCID: PMC9880240 DOI: 10.1016/j.phro.2023.100414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 01/11/2023] [Accepted: 01/17/2023] [Indexed: 01/22/2023] Open
Abstract
Background and purpose Magnetic resonance imaging (MRI)-Linac systems combine simultaneous MRI with radiation delivery, allowing treatments to be guided by anatomically detailed, real-time images. However, MRI can be degraded by geometric distortions that cause uncertainty between imaged and actual anatomy. In this work, we develop and integrate a real-time distortion correction method that enables accurate real-time adaptive radiotherapy. Materials and methods The method was based on the pre-treatment calculation of distortion and the rapid correction of intrafraction images. A motion phantom was set up in an MRI-Linac at isocentre (P0 ), the edge (P 1) and just outside (P 2) the imaging volume. The target was irradiated and tracked during real-time adaptive radiotherapy with and without the distortion correction. The geometric tracking error and latency were derived from the measurements of the beam and target positions in the EPID images. Results Without distortion correction, the mean geometric tracking error was 1.3 mm at P 1 and 3.1 mm at P 2. When distortion correction was applied, the error was reduced to 1.0 mm at P 1 and 1.1 mm at P 2. The corrected error was similar to an error of 0.9 mm at P0 where the target was unaffected by distortion indicating that this method has accurately accounted for distortion during tracking. The latency was 319 ± 12 ms without distortion correction and 335 ± 34 ms with distortion correction. Conclusions We have demonstrated a real-time distortion correction method that maintains accurate radiation delivery to the target, even at treatment locations with large distortion.
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Affiliation(s)
- Paul Z. Y Liu
- Image X Institute, University of Sydney Central Clinical School, Sydney, NSW, Australia
- Department of Medical Physics, Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia
| | - Shanshan Shan
- Image X Institute, University of Sydney Central Clinical School, Sydney, NSW, Australia
- Department of Medical Physics, Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia
| | - David Waddington
- Image X Institute, University of Sydney Central Clinical School, Sydney, NSW, Australia
- Department of Medical Physics, Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia
| | - Brendan Whelan
- Image X Institute, University of Sydney Central Clinical School, Sydney, NSW, Australia
- Department of Medical Physics, Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia
| | - Bin Dong
- Department of Medical Physics, Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia
| | - Gary Liney
- Department of Medical Physics, Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia
- School of Medicine, University of New South Wales, Sydney, NSW, Australia
- Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW, Australia
| | - Paul Keall
- Image X Institute, University of Sydney Central Clinical School, Sydney, NSW, Australia
- Department of Medical Physics, Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia
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Goodburn RJ, Philippens MEP, Lefebvre TL, Khalifa A, Bruijnen T, Freedman JN, Waddington DEJ, Younus E, Aliotta E, Meliadò G, Stanescu T, Bano W, Fatemi‐Ardekani A, Wetscherek A, Oelfke U, van den Berg N, Mason RP, van Houdt PJ, Balter JM, Gurney‐Champion OJ. The future of MRI in radiation therapy: Challenges and opportunities for the MR community. Magn Reson Med 2022; 88:2592-2608. [PMID: 36128894 PMCID: PMC9529952 DOI: 10.1002/mrm.29450] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 08/17/2022] [Accepted: 08/22/2022] [Indexed: 01/11/2023]
Abstract
Radiation therapy is a major component of cancer treatment pathways worldwide. The main aim of this treatment is to achieve tumor control through the delivery of ionizing radiation while preserving healthy tissues for minimal radiation toxicity. Because radiation therapy relies on accurate localization of the target and surrounding tissues, imaging plays a crucial role throughout the treatment chain. In the treatment planning phase, radiological images are essential for defining target volumes and organs-at-risk, as well as providing elemental composition (e.g., electron density) information for radiation dose calculations. At treatment, onboard imaging informs patient setup and could be used to guide radiation dose placement for sites affected by motion. Imaging is also an important tool for treatment response assessment and treatment plan adaptation. MRI, with its excellent soft tissue contrast and capacity to probe functional tissue properties, holds great untapped potential for transforming treatment paradigms in radiation therapy. The MR in Radiation Therapy ISMRM Study Group was established to provide a forum within the MR community to discuss the unmet needs and fuel opportunities for further advancement of MRI for radiation therapy applications. During the summer of 2021, the study group organized its first virtual workshop, attended by a diverse international group of clinicians, scientists, and clinical physicists, to explore our predictions for the future of MRI in radiation therapy for the next 25 years. This article reviews the main findings from the event and considers the opportunities and challenges of reaching our vision for the future in this expanding field.
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Affiliation(s)
- Rosie J. Goodburn
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | | | - Thierry L. Lefebvre
- Department of PhysicsUniversity of CambridgeCambridgeUnited Kingdom
- Cancer Research UK Cambridge Research InstituteUniversity of CambridgeCambridgeUnited Kingdom
| | - Aly Khalifa
- Department of Medical BiophysicsUniversity of TorontoTorontoOntarioCanada
| | - Tom Bruijnen
- Department of RadiotherapyUniversity Medical Center UtrechtUtrechtNetherlands
| | | | - David E. J. Waddington
- Faculty of Medicine and Health, Sydney School of Health Sciences, ACRF Image X InstituteThe University of SydneySydneyNew South WalesAustralia
| | - Eyesha Younus
- Department of Medical Physics, Odette Cancer CentreSunnybrook Health Sciences CentreTorontoOntarioCanada
| | - Eric Aliotta
- Department of Medical PhysicsMemorial Sloan Kettering Cancer CenterNew YorkNew YorkUSA
| | - Gabriele Meliadò
- Unità Operativa Complessa di Fisica SanitariaAzienda Ospedaliera Universitaria Integrata VeronaVeronaItaly
| | - Teo Stanescu
- Department of Radiation Oncology, University of Toronto and Medical Physics, Princess Margaret Cancer CentreUniversity Health NetworkTorontoOntarioCanada
| | - Wajiha Bano
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | - Ali Fatemi‐Ardekani
- Department of PhysicsJackson State University (JSU)JacksonMississippiUSA
- SpinTecxJacksonMississippiUSA
- Department of Radiation OncologyCommunity Health Systems (CHS) Cancer NetworkJacksonMississippiUSA
| | - Andreas Wetscherek
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | - Uwe Oelfke
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | - Nico van den Berg
- Department of RadiotherapyUniversity Medical Center UtrechtUtrechtNetherlands
| | - Ralph P. Mason
- Department of RadiologyUniversity of Texas Southwestern Medical CenterDallasTexasUSA
| | - Petra J. van Houdt
- Department of Radiation OncologyNetherlands Cancer InstituteAmsterdamNetherlands
| | - James M. Balter
- Department of Radiation OncologyUniversity of MichiganAnn ArborMichiganUSA
| | - Oliver J. Gurney‐Champion
- Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam UMCUniversity of AmsterdamAmsterdamNetherlands
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Lu L, Yang X, Raterman B, Jiang X, Meineke M, Grecula J, Blakaj D, Palmer J, Raval R, Thomas E, Hintenlang D, Gupta N. Assessment of MRI image distortion based on 6 consecutive years of annual QAs and measurements on 14 MRI scanners used for radiation therapy. J Appl Clin Med Phys 2022; 24:e13843. [PMID: 36385457 PMCID: PMC9859981 DOI: 10.1002/acm2.13843] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 09/30/2022] [Accepted: 10/21/2022] [Indexed: 11/18/2022] Open
Abstract
PURPOSE To determine the magnitude of MRI image distortion based on 6 consecutive years of annual quality assurances/measurements on 14 MRI scanners used for radiation therapy and to provide evidence for the inclusion of additional margin for treatment planning. METHODS AND MATERIALS We used commercial MRI image phantoms to quantitatively study the MRI image distortion over period of 6 years for up to 14 1.5 and 3 T MRI scanners that could potentially be used to provide MRI images for treatment planning. With the phantom images collected from 2016 to 2022, we investigated the MRI image distortion, the dependence of distortion on the distance from the imaging isocenter, and the possible causes of large distortion discovered. RESULTS MRI image distortion increases with the distance from the imaging isocenter. For a region of interest (ROI) with a radius of 100 mm centered at the isocenter, the mean magnitude of distortion for all MRI scanners is 0.44 ± 0.18 mm $0.44 \pm 0.18\;{\rm{mm}}$ , and the maximum distortion varies from 0.52 to 1.31 mm $0.52\;{\rm{to}}\;1.31\;{\rm{mm}}$ depending on MRI scanners. For an ROI with a radius of 200 mm centered at the isocenter, the mean magnitude of distortion increases to 0.84 ± 0.45 mm $0.84 \pm 0.45\;{\rm{mm}}$ , and the range of the maximum distortion increases to 1.92 - 5.03 mm $1.92 - 5.03\;{\rm{mm}}$ depending on MRI scanners. The distortion could reach 2 mm at 150 mm from the isocenter. CONCLUSION An additional margin to accommodate image distortion should be considered for treatment planning. Imaging with proper patient alignment to the isocenter is vital to reducing image distortion. We recommend performing image distortion checks annually and after major upgrade on MRI scanners.
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Affiliation(s)
- Lanchun Lu
- Department of Radiation OncologyThe Ohio State UniversityColumbusOhioUSA
| | - Xiangyu Yang
- Department of RadiologyThe Ohio State UniversityColumbusOhioUSA
| | - Brian Raterman
- Department of RadiologyThe Ohio State UniversityColumbusOhioUSA
| | - Xia Jiang
- Department of RadiologyThe Ohio State UniversityColumbusOhioUSA
| | - Matthew Meineke
- Department of Radiation OncologyThe Ohio State UniversityColumbusOhioUSA
| | - John Grecula
- Department of Radiation OncologyThe Ohio State UniversityColumbusOhioUSA
| | - Dukagjin Blakaj
- Department of Radiation OncologyThe Ohio State UniversityColumbusOhioUSA
| | - Joshua Palmer
- Department of Radiation OncologyThe Ohio State UniversityColumbusOhioUSA
| | - Raju Raval
- Department of Radiation OncologyThe Ohio State UniversityColumbusOhioUSA
| | - Evan Thomas
- Department of Radiation OncologyThe Ohio State UniversityColumbusOhioUSA
| | | | - Nilendu Gupta
- Department of Radiation OncologyThe Ohio State UniversityColumbusOhioUSA
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Kaza E, Guenette JP, Guthier CV, Hatch S, Marques A, Singer L, Schoenfeld JD. Image quality comparisons of coil setups in 3T MRI for brain and head and neck radiotherapy simulations. J Appl Clin Med Phys 2022; 23:e13794. [PMID: 36285814 PMCID: PMC9797171 DOI: 10.1002/acm2.13794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 07/11/2022] [Accepted: 09/06/2022] [Indexed: 01/01/2023] Open
Abstract
PURPOSE MRI is increasingly used for brain and head and neck radiotherapy treatment planning due to its superior soft tissue contrast. Flexible array coils can be arranged to encompass treatment immobilization devices, which do not fit in diagnostic head/neck coils. Selecting a flexible coil arrangement to replace a diagnostic coil should rely on image quality characteristics and patient comfort. We compared image quality obtained with a custom UltraFlexLarge18 (UFL18) coil setup against a commercial FlexLarge4 (FL4) coil arrangement, relative to a diagnostic Head/Neck20 (HN20) coil at 3T. METHODS The large American College of Radiology (ACR) MRI phantom was scanned monthly in the UFL18, FL4, and HN20 coil setup over 2 years, using the ACR series and three clinical sequences. High-contrast spatial resolution (HCSR), image intensity uniformity (IIU), percent-signal ghosting (PSG), low-contrast object detectability (LCOD), signal-to-noise ratio (SNR), and geometric accuracy were calculated according to ACR recommendations for each series and coil arrangement. Five healthy volunteers were scanned with the clinical sequences in all three coil setups. SNR, contrast-to-noise ratio (CNR) and artifact size were extracted from regions-of-interest along the head for each sequence and coil setup. For both experiments, ratios of image quality parameters obtained with UFL18 or FL4 over those from HN20 were formed for each coil setup, grouping the ACR and clinical sequences. RESULTS Wilcoxon rank-sum tests revealed significantly higher (p < 0.001) LCOD, IIU and SNR, and lower PSG ratios with UFL18 than FL4 on the phantom for the clinical sequences, with opposite PSG and SNR trends for the ACR series. Similar statistical tests on volunteer data corroborated that SNR ratios with UFL18 (0.58 ± 0.19) were significantly higher (p < 0.001) than with FL4 (0.51 ± 0.18) relative to HN20. CONCLUSIONS The custom UFL18 coil setup was selected for clinical application in MR simulations due to the superior image quality demonstrated on a phantom and volunteers for clinical sequences and increased volunteer comfort.
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Affiliation(s)
- Evangelia Kaza
- Radiation Oncology, Brigham and Women's HospitalDana‐Farber Cancer Institute, Harvard Medical SchoolBostonMassachusettsUSA
| | - Jeffrey P. Guenette
- Division of Neuroradiology, Brigham and Women's HospitalDana‐Farber Cancer Institute, Harvard Medical SchoolBostonMassachusettsUSA
| | - Christian V. Guthier
- Radiation Oncology, Brigham and Women's HospitalDana‐Farber Cancer Institute, Harvard Medical SchoolBostonMassachusettsUSA
| | - Steven Hatch
- Radiation Oncology, Brigham and Women's HospitalDana‐Farber Cancer Institute, Harvard Medical SchoolBostonMassachusettsUSA
| | - Alexander Marques
- Radiation Oncology, Brigham and Women's HospitalDana‐Farber Cancer Institute, Harvard Medical SchoolBostonMassachusettsUSA
| | - Lisa Singer
- Radiation Oncology, Brigham and Women's HospitalDana‐Farber Cancer Institute, Harvard Medical SchoolBostonMassachusettsUSA,Radiation OncologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Jonathan D. Schoenfeld
- Radiation Oncology, Brigham and Women's HospitalDana‐Farber Cancer Institute, Harvard Medical SchoolBostonMassachusettsUSA
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McGee KP, Campeau NG, Witte RJ, Rossman PJ, Christopherson JA, Tryggestad EJ, Brinkmann DH, Ma DJ, Park SS, Rettmann DW, Robb FJ. Evaluation of a New, Highly Flexible Radiofrequency Coil for MR Simulation of Patients Undergoing External Beam Radiation Therapy. J Clin Med 2022; 11:5984. [PMID: 36294304 PMCID: PMC9604708 DOI: 10.3390/jcm11205984] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 09/30/2022] [Accepted: 10/08/2022] [Indexed: 04/20/2024] Open
Abstract
PURPOSE To evaluate the performance of a new, highly flexible radiofrequency (RF) coil system for imaging patients undergoing MR simulation. METHODS Volumetric phantom and in vivo images were acquired with a commercially available and prototype RF coil set. Phantom evaluation was performed using a silicone-filled humanoid phantom of the head and shoulders. In vivo assessment was performed in five healthy and six patient subjects. Phantom data included T1-weighted volumetric imaging, while in vivo acquisitions included both T1- and T2-weighted volumetric imaging. Signal to noise ratio (SNR) and uniformity metrics were calculated in the phantom data, while SNR values were calculated in vivo. Statistical significance was tested by means of a non-parametric analysis of variance test. RESULTS At a threshold of p = 0.05, differences in measured SNR distributions within the entire phantom volume were statistically different in two of the three paired coil set comparisons. Differences in per slice average SNR between the two coil sets were all statistically significant, as well as differences in per slice image uniformity. For patients, SNRs within the entire imaging volume were statistically significantly different in four of the nine comparisons and seven of the nine comparisons performed on the per slice average SNR values. For healthy subjects, SNRs within the entire imaging volume were statistically significantly different in seven of the nine comparisons and eight of the nine comparisons when per slice average SNR was tested. CONCLUSIONS Phantom and in vivo results demonstrate that image quality obtained from the novel flexible RF coil set was similar or improved over the conventional coil system. The results also demonstrate that image quality is impacted by the specific coil configurations used for imaging and should be matched appropriately to the anatomic site imaged to ensure optimal and reproducible image quality.
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Affiliation(s)
- Kiaran P. McGee
- Department of Radiology, Mayo Clinic and Foundation, Rochester, MN 55905, USA
| | - Norbert G. Campeau
- Department of Radiology, Mayo Clinic and Foundation, Rochester, MN 55905, USA
| | - Robert J. Witte
- Department of Radiology, Mayo Clinic and Foundation, Rochester, MN 55905, USA
| | - Philip J. Rossman
- Department of Radiology, Mayo Clinic and Foundation, Rochester, MN 55905, USA
| | | | - Erik J. Tryggestad
- Department of Radiation Oncology, Mayo Clinic and Foundation, Rochester, MN 55905, USA
| | - Debra H. Brinkmann
- Department of Radiation Oncology, Mayo Clinic and Foundation, Rochester, MN 55905, USA
| | - Daniel J. Ma
- Department of Radiation Oncology, Mayo Clinic and Foundation, Rochester, MN 55905, USA
| | - Sean S. Park
- Department of Radiation Oncology, Mayo Clinic and Foundation, Rochester, MN 55905, USA
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Walker A, Chlap P, Causer T, Mahmood F, Buckley J, Holloway L. Development of a vendor neutral MRI distortion quality assurance workflow. J Appl Clin Med Phys 2022; 23:e13735. [PMID: 35880651 PMCID: PMC9588272 DOI: 10.1002/acm2.13735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Revised: 05/17/2022] [Accepted: 07/07/2022] [Indexed: 12/04/2022] Open
Abstract
With the utilization of magnetic resonance (MR) imaging in radiotherapy increasing, routine quality assurance (QA) of these systems is necessary. The assessment of geometric distortion in images used for radiotherapy treatment planning needs to be quantified and monitored over time. This work presents an adaptable methodology for performing routine QA for systematic MRI geometric distortion. A software tool and compatible protocol (designed to work with any CT and MR compatible phantom on any scanner) were developed to quantify geometric distortion via deformable image registration. The MR image is deformed to the CT, generating a deformation field, which is sampled, quantifying geometric distortion as a function of distance from scanner isocenter. Configurability of the QA tool was tested, and results compared to those provided from commercial solutions. Registration accuracy was investigated by repeating the deformable registration step on the initial deformed MR image to define regions with residual distortions. The geometric distortion of four clinical systems was quantified using the customisable QA method presented. Maximum measured distortions varied from 2.2 to 19.4 mm (image parameter and sampling volume dependent). The workflow was successfully customized for different phantom configurations and volunteer imaging studies. Comparison to a vendor supplied solution showed good agreement in regions where the two procedures were sampling the same imaging volume. On a large field of view phantom across various scanners, the QA tool accurately quantified geometric distortions within 17–22 cm from scanner isocenter. Beyond these regions, the geometric integrity of images in clinical applications should be considered with a higher degree of uncertainty due to increased gradient nonlinearity and B0 inhomogeneity. This tool has been successfully integrated into routine QA of the MRI scanner utilized for radiotherapy within our department. It enables any low susceptibility MR‐CT compatible phantom to quantify the geometric distortion on any MRI scanner with a configurable, user friendly interface for ease of use and consistency in data collection and analysis.
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Affiliation(s)
- Amy Walker
- Liverpool and Macarthur Cancer Therapy Centres, Sydney, Australia.,Ingham Institute of Applied Medical Research, Sydney, Australia.,Centre for Medical Radiation Physics, University of Wollongong, Wollongong, Australia.,South Western Clinical School, University of New South Wales, Sydney, Australia
| | - Phillip Chlap
- Liverpool and Macarthur Cancer Therapy Centres, Sydney, Australia.,Ingham Institute of Applied Medical Research, Sydney, Australia.,South Western Clinical School, University of New South Wales, Sydney, Australia
| | - Trent Causer
- Centre for Medical Radiation Physics, University of Wollongong, Wollongong, Australia.,Illawarra Cancer Care Centre, Wollongong, Australia
| | - Faisal Mahmood
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Odense, Denmark.,Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Jarryd Buckley
- Liverpool and Macarthur Cancer Therapy Centres, Sydney, Australia.,Ingham Institute of Applied Medical Research, Sydney, Australia.,Centre for Medical Radiation Physics, University of Wollongong, Wollongong, Australia.,Illawarra Cancer Care Centre, Wollongong, Australia
| | - Lois Holloway
- Liverpool and Macarthur Cancer Therapy Centres, Sydney, Australia.,Ingham Institute of Applied Medical Research, Sydney, Australia.,Centre for Medical Radiation Physics, University of Wollongong, Wollongong, Australia.,South Western Clinical School, University of New South Wales, Sydney, Australia.,Institute of Medical Physics, University of Sydney, Sydney, Australia
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44
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Buatti JS, Gallagher KJ, Bailey I, Griglock T, Heard M. An evaluation of quality assurance guidelines comparing the American College of Radiology and American Association of Physicists in Medicine task group 284 for magnetic resonance simulation. J Appl Clin Med Phys 2022; 23:e13730. [PMID: 35851720 PMCID: PMC9359023 DOI: 10.1002/acm2.13730] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 07/04/2022] [Indexed: 11/08/2022] Open
Affiliation(s)
- Jacob S. Buatti
- Department of Radiation Medicine Oregon Health and Science University Portland Oregon USA
| | - Kyle J. Gallagher
- Department of Radiation Medicine Oregon Health and Science University Portland Oregon USA
| | - Isaac Bailey
- Department of Diagnostic Radiology Oregon Health and Science University Portland Oregon USA
| | - Thomas Griglock
- Department of Diagnostic Radiology Oregon Health and Science University Portland Oregon USA
| | - Malcolm Heard
- Department of Radiation Medicine Oregon Health and Science University Portland Oregon USA
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Crop F, Guillaud O, Ben Haj Amor M, Gaignierre A, Barre C, Fayard C, Vandendorpe B, Lodyga K, Mouttet-Audouard R, Mirabel X. Comparison of compressed sensing and controlled aliasing in parallel imaging acceleration for 3D magnetic resonance imaging for radiotherapy preparation. Phys Imaging Radiat Oncol 2022; 23:44-47. [PMID: 35789969 PMCID: PMC9249804 DOI: 10.1016/j.phro.2022.06.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 06/09/2022] [Accepted: 06/20/2022] [Indexed: 11/28/2022] Open
Abstract
Magnetic resonance imaging (MRI) for radiotherapy is often based on 3D acquisitions, but suffers from low signal-to-noise ratio due to immobilization device and flexible coil use. The aim of this study was to investigate if Compressed Sensing (CS) improves image quality for 3D Turbo Spin Echo acquisitions compared with Controlled Aliasing k-space-based parallel imaging in equivalent acquisition time for intracranial T1, T2-Fluid-Attenuated Inversion Recovery (FLAIR) and pelvic T2 imaging. Qualitative ratings suffered from large inter-rater variability. CS-T1 brain MRI was superior numerically and qualitatively. CS-T2-FLAIR brain MRI was numerically superior, but rater equivalent. CS-T2 pelvic MRI was equivalent without gain.
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Affiliation(s)
- Frederik Crop
- Medical Physics, Centre Oscar Lambret, Lille, 3 Rue Frédéric Combemale, 59000 Lille, France
| | - Ophélie Guillaud
- Radiology, Centre Oscar Lambret, Lille, 3 Rue Frédéric Combemale, 59000 Lille, France
| | - Mariem Ben Haj Amor
- Radiology, Centre Oscar Lambret, Lille, 3 Rue Frédéric Combemale, 59000 Lille, France
| | - Alexandre Gaignierre
- Radiology, Centre Oscar Lambret, Lille, 3 Rue Frédéric Combemale, 59000 Lille, France
| | - Carole Barre
- Academic Department of Radiotherapy, Centre Oscar Lambret, Lille, 3 Rue Frédéric Combemale, 59000 Lille, France
| | - Cindy Fayard
- Radiology, Centre Oscar Lambret, Lille, 3 Rue Frédéric Combemale, 59000 Lille, France
| | - Benjamin Vandendorpe
- Academic Department of Radiotherapy, Centre Oscar Lambret, Lille, 3 Rue Frédéric Combemale, 59000 Lille, France
| | - Kaoutar Lodyga
- Academic Department of Radiotherapy, Centre Oscar Lambret, Lille, 3 Rue Frédéric Combemale, 59000 Lille, France
| | - Raphaëlle Mouttet-Audouard
- Academic Department of Radiotherapy, Centre Oscar Lambret, Lille, 3 Rue Frédéric Combemale, 59000 Lille, France
| | - Xavier Mirabel
- Radiology, Centre Oscar Lambret, Lille, 3 Rue Frédéric Combemale, 59000 Lille, France
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46
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Keall PJ, Brighi C, Glide-Hurst C, Liney G, Liu PZY, Lydiard S, Paganelli C, Pham T, Shan S, Tree AC, van der Heide UA, Waddington DEJ, Whelan B. Integrated MRI-guided radiotherapy - opportunities and challenges. Nat Rev Clin Oncol 2022; 19:458-470. [PMID: 35440773 DOI: 10.1038/s41571-022-00631-3] [Citation(s) in RCA: 63] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/31/2022] [Indexed: 12/25/2022]
Abstract
MRI can help to categorize tissues as malignant or non-malignant both anatomically and functionally, with a high level of spatial and temporal resolution. This non-invasive imaging modality has been integrated with radiotherapy in devices that can differentially target the most aggressive and resistant regions of tumours. The past decade has seen the clinical deployment of treatment devices that combine imaging with targeted irradiation, making the aspiration of integrated MRI-guided radiotherapy (MRIgRT) a reality. The two main clinical drivers for the adoption of MRIgRT are the ability to image anatomical changes that occur before and during treatment in order to adapt the treatment approach, and to image and target the biological features of each tumour. Using motion management and biological targeting, the radiation dose delivered to the tumour can be adjusted during treatment to improve the probability of tumour control, while simultaneously reducing the radiation delivered to non-malignant tissues, thereby reducing the risk of treatment-related toxicities. The benefits of this approach are expected to increase survival and quality of life. In this Review, we describe the current state of MRIgRT, and the opportunities and challenges of this new radiotherapy approach.
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Affiliation(s)
- Paul J Keall
- ACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia.
| | - Caterina Brighi
- ACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia
| | - Carri Glide-Hurst
- Department of Human Oncology, University of Wisconsin, Madison, WI, USA
| | - Gary Liney
- Ingham Institute of Applied Medical Research, Sydney, New South Wales, Australia
| | - Paul Z Y Liu
- ACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia
| | - Suzanne Lydiard
- ACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia
| | - Chiara Paganelli
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy
| | - Trang Pham
- Faculty of Medicine and Health, The University of New South Wales, Sydney, New South Wales, Australia
| | - Shanshan Shan
- ACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia
| | - Alison C Tree
- The Royal Marsden NHS Foundation Trust and the Institute of Cancer Research, London, UK
| | - Uulke A van der Heide
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - David E J Waddington
- ACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia
| | - Brendan Whelan
- ACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia
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47
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Damyanovich AZ, Tadic T, Foltz WD, Jelveh S, Bissonnette JP. Time-course assessment of 3D-image distortion on the 1.5 T Marlin/Elekta Unity MR-LINAC. Phys Med 2022; 100:90-98. [PMID: 35777256 DOI: 10.1016/j.ejmp.2022.05.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 04/04/2022] [Accepted: 05/25/2022] [Indexed: 11/29/2022] Open
Abstract
PURPOSE The efficacy of MR-guided radiotherapy on a MR-LINAC (MR-L) is dependent on the geometric accuracy of its MR images over clinically relevant Fields-of-View (FOVs). Our objectives were to: evaluate gradient non-linearity (GNL) on the Elekta Unity MR-L across time via 76 weekly measurements of 3D-distortion over concentrically larger diameter spherical volumes (DSVs); quantify distortion measurement error; and assess the temporal stability of spatial distortion using statistical process control (SPC). METHODS MR-image distortion was assessed using a large-FOV 3D-phantom containing 1932 markers embedded in seven parallel plates, spaced 25 mm × 25 mm in- and 55 mm through-plane. Automatically analyzed T1 images yielded distortions in 200, 300, 400 and 500 mm concentric DSVs. Distortion measurement error was evaluated using median absolute difference analysis of imaging repeatability tests. RESULTS Over the measurement period absolute time-averaged distortion varied between: dr = 0.30 - 0.49 mm, 0.53 - 0.80 mm, 1.0 - 1.4 mm and 2.28 - 2.37 mm, for DSVs 200, 300, 400 and 500 mm at the 98th percentile level. Repeatability tests showed that imaging/repositioning introduces negligible error: mean ≤ 0.02 mm (max ≤ 0.3 mm). SPC analysis showed image distortion was stable across all DSVs; however, noticeable changes in GNL were observed following servicing at the one-year mark. CONCLUSIONS Image distortion on the MR-L is in the sub-millimeter range for DSVs ≤ 300 mm and stable across time, with SPC analysis indicating all measurements remain within control for each DSV.
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Affiliation(s)
- Andrei Z Damyanovich
- Department of Medical Physics, Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada; Techna Institute, Toronto, Ontario, Canada.
| | - Tony Tadic
- Department of Medical Physics, Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada; Techna Institute, Toronto, Ontario, Canada
| | - Warren D Foltz
- Department of Medical Physics, Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada; Techna Institute, Toronto, Ontario, Canada
| | - Salomeh Jelveh
- Department of Medical Physics, Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, Canada
| | - Jean-Pierre Bissonnette
- Department of Medical Physics, Princess Margaret Cancer Center, University Health Network, Toronto, Ontario, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada; Techna Institute, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
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48
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Tang S, Rai R, Vinod SK, Elwadia D, Forstner D, Moretti D, Tran T, Do V, King O, Lim K, Liney G, Goozee G, Holloway L. Rates of MRI simulator utilisation in a tertiary cancer therapy centre. J Med Imaging Radiat Oncol 2022; 66:717-723. [PMID: 35687525 DOI: 10.1111/1754-9485.13422] [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: 10/06/2021] [Accepted: 04/27/2022] [Indexed: 11/28/2022]
Abstract
Magnetic resonance imaging (MRI) is increasingly being integrated into the radiation oncology workflow, due to its improved soft tissue contrast without additional exposure to ionising radiation. A review of MRI utilisation according to evidence based departmental guidelines was performed. Guideline utilisation rates were calculated to be 50% (true utilisation rate was 46%) of all new cancer patients treated with adjuvant or curative intent, excluding simple skin and breast cancer patients. Guideline utilisation rates were highest in the lower gastrointestinal and gynaecological subsites, with the lowest being in the upper gastrointestinal and thorax subsites. Head and neck (38% vs 45%) and CNS (46% vs 67%) cancers had the largest discrepancy between true and guideline utilisation rates due to unnamed reasons and non-contemporaneous diagnostic imaging respectively. This report outlines approximate MRI utilisation rates in a tertiary radiation oncology service and may help guide planning for future departments contemplating installation of an MRI simulator.
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Affiliation(s)
- Simon Tang
- Central West Cancer, Gosford, New South Wales, Australia.,Ingham Institute of Applied Medical Research, Liverpool, New South Wales, Australia
| | - Robba Rai
- Ingham Institute of Applied Medical Research, Liverpool, New South Wales, Australia.,Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia.,South Western Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Shalini K Vinod
- Ingham Institute of Applied Medical Research, Liverpool, New South Wales, Australia.,Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia.,South Western Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Doaa Elwadia
- Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia
| | - Dion Forstner
- Genesis Care, St Vincent's Clinic, Darlinghust, New South Wales, Australia
| | - Daniel Moretti
- Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia
| | - Thomas Tran
- Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia
| | - Viet Do
- Ingham Institute of Applied Medical Research, Liverpool, New South Wales, Australia.,Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia.,South Western Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Odette King
- Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia
| | - Karen Lim
- Ingham Institute of Applied Medical Research, Liverpool, New South Wales, Australia.,Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia.,South Western Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Gary Liney
- Ingham Institute of Applied Medical Research, Liverpool, New South Wales, Australia.,Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia.,South Western Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Gary Goozee
- Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia
| | - Lois Holloway
- Ingham Institute of Applied Medical Research, Liverpool, New South Wales, Australia.,Liverpool and Macarthur Cancer Therapy Centres, Liverpool, New South Wales, Australia.,South Western Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia.,University of Sydney, Sydney, New South Wales, Australia.,University of Wollongong, Wollongong, New South Wales, Australia
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49
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Prisciandaro J, Zoberi JE, Cohen G, Kim Y, Johnson P, Paulson E, Song W, Hwang KP, Erickson B, Beriwal S, Kirisits C, Mourtada F. AAPM Task Group Report 303 endorsed by the ABS: MRI Implementation in HDR Brachytherapy-Considerations from Simulation to Treatment. Med Phys 2022; 49:e983-e1023. [PMID: 35662032 DOI: 10.1002/mp.15713] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 04/11/2022] [Accepted: 05/05/2022] [Indexed: 11/05/2022] Open
Abstract
The Task Group (TG) on Magnetic Resonance Imaging (MRI) Implementation in High Dose Rate (HDR) Brachytherapy - Considerations from Simulation to Treatment, TG 303, was constituted by the American Association of Physicists in Medicine's (AAPM's) Science Council under the direction of the Therapy Physics Committee, the Brachytherapy Subcommittee, and the Working Group on Brachytherapy Clinical Applications. The TG was charged with developing recommendations for commissioning, clinical implementation, and on-going quality assurance (QA). Additionally, the TG was charged with describing HDR brachytherapy (BT) workflows and evaluating practical consideration that arise when implementing MR imaging. For brevity, the report is focused on the treatment of gynecologic and prostate cancer. The TG report provides an introduction and rationale for MRI implementation in BT, a review of previous publications on topics including available applicators, clinical trials, previously published BT related TG reports, and new image guided recommendations beyond CT based practices. The report describes MRI protocols and methodologies, including recommendations for the clinical implementation and logical considerations for MR imaging for HDR BT. Given the evolution from prescriptive to risk-based QA,1 an example of a risk-based analysis using MRI-based, prostate HDR BT is presented. In summary, the TG report is intended to provide clear and comprehensive guidelines and recommendations for commissioning, clinical implementation, and QA for MRI-based HDR BT that may be utilized by the medical physics community to streamline this process. This report is endorsed by the American Brachytherapy Society (ABS). This article is protected by copyright. All rights reserved.
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Affiliation(s)
| | | | - Gil'ad Cohen
- Memorial Sloan-Kettering Cancer Center, New York, NY
| | | | - Perry Johnson
- University of Florida Health Proton Therapy Institute, Jacksonville, FL
| | | | | | - Ken-Pin Hwang
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Sushil Beriwal
- Allegheny Health Network Cancer Institute, Pittsburgh, PA
| | | | - Firas Mourtada
- Sidney Kimmel Cancer Center at Thomas Jefferson University Hospital, Philadelphia, Pennsylvania
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50
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Nousiainen K, Mäkelä T, Peltonen JI. Characterizing geometric distortions of 3D sequences in clinical head MRI. MAGNETIC RESONANCE MATERIALS IN PHYSICS, BIOLOGY AND MEDICINE 2022; 35:983-995. [PMID: 35657535 PMCID: PMC9596562 DOI: 10.1007/s10334-022-01020-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 04/20/2022] [Accepted: 05/12/2022] [Indexed: 11/25/2022]
Abstract
Objective Phantoms are often used to estimate the geometric accuracy in magnetic resonance imaging (MRI). However, the distortions may differ between anatomical and phantom images. This study aimed to investigate the applicability of a phantom-based and a test-subject-based method in evaluating geometric distortion present in clinical head-imaging sequences. Materials and methods We imaged a 3D-printed phantom and test subjects with two MRI scanners using two clinical head-imaging 3D sequences with varying patient-table positions and receiver bandwidths. The geometric distortions were evaluated through nonrigid registrations: the displaced acquisitions were compared against the ideal isocenter positioning, and the varied bandwidth volumes against the volume with the highest bandwidth. The phantom acquisitions were also registered to a computed tomography scan. Results Geometric distortion magnitudes increased with larger table displacements and were in good agreement between the phantom and test-subject acquisitions. The effect of increased distortions with decreasing receiver bandwidth was more prominent for test-subject acquisitions. Conclusion Presented results emphasize the sensitivity of the geometric accuracy to positioning and imaging parameters. Phantom limitations may become an issue with some sequence types, encouraging the use of anatomical images for evaluating the geometric accuracy.
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Affiliation(s)
- Katri Nousiainen
- HUS Medical Imaging Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.
- Department of Physics, University of Helsinki, Helsinki, Finland.
| | - Teemu Mäkelä
- HUS Medical Imaging Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
- Department of Physics, University of Helsinki, Helsinki, Finland
| | - Juha I Peltonen
- HUS Medical Imaging Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
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