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Wyatt JJ, McCallum HM, Maxwell RJ. Developing quality assurance tests for simultaneous Positron Emission Tomography - Magnetic Resonance imaging for radiotherapy planning. Phys Imaging Radiat Oncol 2022; 22:28-35. [PMID: 35493852 PMCID: PMC9048159 DOI: 10.1016/j.phro.2022.03.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 03/02/2022] [Accepted: 03/18/2022] [Indexed: 12/05/2022] Open
Abstract
Background and purpose Simultaneous Positron Emission Tomography - Magnetic Resonance (PET-MR) imaging can potentially improve radiotherapy by enabling more accurate tumour delineation and dose painting. The use of PET-MR imaging for radiotherapy planning requires a comprehensive Quality Assurance (QA) programme to be developed. This study aimed to develop the QA tests required and assess their repeatability and stability. Materials and methods QA tests were developed for: MR image quality, MR geometric accuracy, electromechanical accuracy, PET-MR alignment accuracy, Diffusion Weighted (DW)-MR Apparent Diffusion Coefficient (ADC) accuracy and PET Standard Uptake Value (SUV) accuracy. Each test used a dedicated phantom and was analysed automatically or semi-automatically, with in-house software. Repeatability was evaluated by three same-day measurements with independent phantom positions. Stability was assessed through 12 monthly measurements. Results The repeatability Standard Deviations (SDs) of distortion for the MR geometric accuracy test were ⩽ 0.7 mm . The repeatability SDs in ADC difference from reference were ⩽ 3 % for the DW-MR accuracy test. The PET SUV difference from reference repeatability SD was 0.3 % . The stability SDs agreed within 0.6 mm , 1 percentage point and 1.4 percentage points of the repeatability SDs for the geometric, ADC and SUV accuracy tests respectively. There were no monthly trends apparent. These results were representative of the other tests. Conclusions QA Tests for radiotherapy planning PET-MR have been developed. The tests appeared repeatable and stable over a 12-month period. The developed QA tests could form the basis of a QA programme that enables high-quality, robust PET-MR imaging for radiotherapy planning.
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Affiliation(s)
- Jonathan J. Wyatt
- Translational and Clinical Research Institute, Newcastle University, Newcastle, UK
- Northern Centre for Cancer Care, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle, UK
| | - Hazel M. McCallum
- Translational and Clinical Research Institute, Newcastle University, Newcastle, UK
- Northern Centre for Cancer Care, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle, UK
| | - Ross J. Maxwell
- Translational and Clinical Research Institute, Newcastle University, Newcastle, UK
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Liu C, Li M, Xiao H, Li T, Li W, Zhang J, Teng X, Cai J. Advances in MRI‐guided precision radiotherapy. PRECISION RADIATION ONCOLOGY 2022. [DOI: 10.1002/pro6.1143] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Affiliation(s)
- Chenyang Liu
- Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong SAR China
| | - Mao Li
- Department of Radiation Oncology Philips Healthcare Chengdu China
| | - Haonan Xiao
- Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong SAR China
| | - Tian Li
- Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong SAR China
| | - Wen Li
- Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong SAR China
| | - Jiang Zhang
- Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong SAR China
| | - Xinzhi Teng
- Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong SAR China
| | - Jing Cai
- Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong SAR China
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Finnegan RN, Reynolds HM, Ebert MA, Sun Y, Holloway L, Sykes JR, Dowling J, Mitchell C, Williams SG, Murphy DG, Haworth A. A statistical, voxelised model of prostate cancer for biologically optimised radiotherapy. Phys Imaging Radiat Oncol 2022; 21:136-145. [PMID: 35284663 PMCID: PMC8913349 DOI: 10.1016/j.phro.2022.02.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 02/16/2022] [Accepted: 02/17/2022] [Indexed: 11/04/2022] Open
Abstract
Background and purpose Radiation therapy (RT) is commonly indicated for treatment of prostate cancer (PC). Biologicallyoptimised RT for PC may improve disease-free survival. This requires accurate spatial localisation and characterisation of tumour lesions. We aimed to generate a statistical, voxelised biological model to complement in vivomultiparametric MRI data to facilitate biologically-optimised RT. Material and methods Ex vivo prostate MRI and histopathological imaging were acquired for 63 PC patients. These data were co-registered to derive three-dimensional distributions of graded tumour lesions and cell density. Novel registration processes were used to map these data to a common reference geometry. Voxelised statistical models of tumour probability and cell density were generated to create the PC biological atlas. Cell density models were analysed using the Kullback-Leibler divergence to compare normal vs. lognormal approximations to empirical data. Results A reference geometry was constructed using ex vivo MRI space, patient data were deformably registered using a novel anatomy-guided process. Substructure correspondence was maintained using peripheral zone definitions to address spatial variability in prostate anatomy between patients. Three distinct approaches to interpolation were designed to map contours, tumour annotations and cell density maps from histology into ex vivo MRI space. Analysis suggests a log-normal model provides a more consistent representation of cell density when compared to a linear-normal model. Conclusion A biological model has been created that combines spatial distributions of tumour characteristics from a population into three-dimensional, voxelised, statistical models. This tool will be used to aid the development of biologically-optimised RT for PC patients.
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Affiliation(s)
- Robert N Finnegan
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, New South Wales, Australia
- Liverpool Cancer Therapy Centre, South Western Sydney Local Health District, Liverpool, New South Wales, Australia
- InghamInstitute for Applied Medical Research, Liverpool, New South Wales, Australia
| | - Hayley M Reynolds
- Auckland Bioengineering Institute, University of Auckland, New Zealand
| | - Martin A Ebert
- Department of Radiation Oncology, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- School of Physics, Mathematics and Computing, University of Western Australia, Crawley, Western Australia, Australia
- 5D Clinics, Claremont, Western Australia, Australia
- Centre for Medical Radiation Physics, University of Wollongong, Wollongong, New South Wales, Australia
| | - Yu Sun
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, New South Wales, Australia
| | - Lois Holloway
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, New South Wales, Australia
- Liverpool Cancer Therapy Centre, South Western Sydney Local Health District, Liverpool, New South Wales, Australia
- InghamInstitute for Applied Medical Research, Liverpool, New South Wales, Australia
- Centre for Medical Radiation Physics, University of Wollongong, Wollongong, New South Wales, Australia
- South Western Sydney Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Jonathan R Sykes
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, New South Wales, Australia
- Department of Radiation Oncology, Sydney West Radiation Oncology Network, Blacktown Cancer & Haematology Centre, Blacktown, New South Wales, Australia
- Department of Radiation Oncology, Sydney West Radiation Oncology Network, Crown Princess Mary Cancer Centre, Westmead, New South Wales, Australia
| | - Jason Dowling
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, New South Wales, Australia
- School of Mathematical and Physical Sciences, University of Newcastle, Newcastle, New South Wales, Australia
- CSIRO Health and Biosecurity, The Australian e-Health and Research Centre, Herston, Queensland, Australia
| | - Catherine Mitchell
- Department of Pathology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Scott G Williams
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
- Division of Radiation Oncology and Cancer Imaging, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Declan G Murphy
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
- Division of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Annette Haworth
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, New South Wales, Australia
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O'Connor LM, Skehan K, Choi JH, Simpson J, Martin J, Warren-Forward H, Dowling J, Greer P. Optimisation and validation of an integrated magnetic resonance imaging-only radiotherapy planning solution. Phys Imaging Radiat Oncol 2021; 20:34-39. [PMID: 34901474 PMCID: PMC8640865 DOI: 10.1016/j.phro.2021.10.001] [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: 05/31/2021] [Revised: 10/05/2021] [Accepted: 10/10/2021] [Indexed: 11/19/2022] Open
Abstract
Background and purpose Magnetic resonance imaging (MRI)-only treatment planning is gaining in popularity in radiation oncology, with various methods available to generate a synthetic computed tomography (sCT) for this purpose. The aim of this study was to validate a sCT generation software for MRI-only radiotherapy planning of male and female pelvic cancers. The secondary aim of this study was to improve dose agreement by applying a derived relative electron and mass density (RED) curve to the sCT. Method and materials Computed tomography (CT) and MRI scans of forty patients with pelvic neoplasms were used in the study. Treatment plans were copied from the CT scan to the sCT scan for dose comparison. Dose difference at reference point, 3D gamma comparison and dose volume histogram analysis was used to validate the dose impact of the sCT. The RED values were optimised to improve dose agreement by using a linear plot. Results The average percentage dose difference at isocentre was 1.2% and the mean 3D gamma comparison with a criteria of 1%/1 mm was 84.0% ± 9.7%. The results indicate an inherent systematic difference in the dosimetry of the sCT plans, deriving from the tissue densities. With the adapted REDmod table, the average percentage dose difference was reduced to −0.1% and the mean 3D gamma analysis improved to 92.9% ± 5.7% at 1%/1 mm. Conclusions CT generation software is a viable solution for MRI-only radiotherapy planning. The option makes it relatively easy for departments to implement a MRI-only planning workflow for cancers of male and female pelvic anatomy.
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Affiliation(s)
- Laura M. O'Connor
- Department of Radiation Oncology, Calvary Mater Hospital, Newcastle, NSW, Australia
- School of Health Sciences, University of Newcastle, Newcastle, NSW, Australia
- Corresponding author at: Department of Radiation Oncology, Calvary Mater Hospital, Cnr Edith & Platt St, Waratah, Newcastle, NSW 2298, Australia.
| | - Kate Skehan
- Department of Radiation Oncology, Calvary Mater Hospital, Newcastle, NSW, Australia
| | - Jae H. Choi
- School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia
| | - John Simpson
- Department of Radiation Oncology, Calvary Mater Hospital, Newcastle, NSW, Australia
- School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia
| | - Jarad Martin
- Department of Radiation Oncology, Calvary Mater Hospital, Newcastle, NSW, Australia
- School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia
| | | | - Jason Dowling
- School of Mathematical and Physical Sciences, University of Newcastle, Newcastle, NSW, Australia
- Australian E-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Herston, QLD, Australia
| | - Peter Greer
- Department of Radiation Oncology, Calvary Mater Hospital, Newcastle, NSW, Australia
- School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia
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RESUME N: A flexible class of multi-parameter qMRI protocols. Phys Med 2021; 88:23-36. [PMID: 34171573 DOI: 10.1016/j.ejmp.2021.04.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 03/16/2021] [Accepted: 04/02/2021] [Indexed: 12/30/2022] Open
Abstract
PURPOSE To introduce a class of fast 3D quantitative MRI (qMRI) schemes (RESUMEN, for N=1,…,4) that allow for a thorough characterization of microstructural properties of brain tissues. METHODS An arbitrary multi-echo GRE acquisition optimized for quantitative susceptibility mapping (QSM) is complemented with an appropriate low flip-angle GRE sequence drawn from four possible choices. The acquired signals are processed to analytically derive the longitudinal relaxation (R1) and free induction decay (R2∗) rates, as well as the proton density (PD) and QSM. A comprehensive modeling of the excitation and B1- profiles and of the RF-spoiling is included in the acquisition and processing pipeline. RESULTS The RESUMEN maps appear homogeneous throughout the field-of-view and exhibit comparable values and high SNR across the considered range of N values. CONCLUSIONS The introduced schemes represent a class of robust and flexible strategies to derive a thorough and fast qMRI study, suitable for a whole-brain acquisition with isotropic voxel resolution of 700 μm in less than 15 min.
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Tyagi N, Zelefsky MJ, Wibmer A, Zakian K, Burleson S, Happersett L, Halkola A, Kadbi M, Hunt M. Clinical experience and workflow challenges with magnetic resonance-only radiation therapy simulation and planning for prostate cancer. Phys Imaging Radiat Oncol 2020; 16:43-49. [PMID: 33134566 PMCID: PMC7598055 DOI: 10.1016/j.phro.2020.09.009] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 08/24/2020] [Accepted: 09/25/2020] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND AND PURPOSE Magnetic Resonance (MR)-only planning has been implemented clinically for radiotherapy of prostate cancer. However, fewer studies exist regarding the overall success rate of MR-only workflows. We report on successes and challenges of implementing MR-only workflows for prostate. MATERIALS AND METHODS A total of 585 patients with prostate cancer underwent an MR-only simulation and planning between 06/2016-06/2018. MR simulation included images for contouring, synthetic-CT generation and fiducial identification. Workflow interruptions occurred that required a backup CT, a re-simulation or an update to our current quality assurance (QA) process. The challenges were prospectively evaluated and classified into syn-CT generation, motion/artifacts in the MRs, fiducial QA and bowel preparation guidelines. RESULTS MR-only simulation was successful in 544 (93.2 %) patients. . In seventeen patients (2.9%), reconstruction of synthetic-CT failed due to patient size, femur angulation, or failure to determine the body contour. Twenty-four patients (4.1%) underwent a repeat/backup CT scan because of artifacts on the MR such as image blur due to patient motion or biopsy/surgical artifacts that hampered identification of the implanted fiducial markers. In patients requiring large coverage due to nodal involvement, inhomogeneity artifacts were resolved by using a two-stack acquisition and adaptive inhomogeneity correction. Bowel preparation guidelines were modified to address frequent rectum/gas issues due to longer MR scan time. CONCLUSIONS MR-only simulation has been successfully implemented for a majority of patients in the clinic. However, MR-CT or CT-only pathway may still be needed for patients where MR-only solution fails or patients with MR contraindications.
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Affiliation(s)
- Neelam Tyagi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, NY, NY 10065, United States
| | - Michael J. Zelefsky
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, NY, NY 10065, United States
| | - Andreas Wibmer
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, NY, NY 10065, United States
| | - Kristen Zakian
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, NY, NY 10065, United States
| | - Sarah Burleson
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, NY, NY 10065, United States
| | - Laura Happersett
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, NY, NY 10065, United States
| | - Aleksi Halkola
- Philips Healthcare, 595 Milner Road, Cleveland, OH 44143, United States
| | - Mo Kadbi
- Philips Healthcare, 595 Milner Road, Cleveland, OH 44143, United States
| | - Margie Hunt
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, NY, NY 10065, United States
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Thorwarth D. Imaging science and development in modern high-precision radiotherapy. Phys Imaging Radiat Oncol 2019; 12:63-66. [PMID: 33458297 PMCID: PMC7807660 DOI: 10.1016/j.phro.2019.11.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Affiliation(s)
- Daniela Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Germany
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Jonsson J, Nyholm T, Söderkvist K. The rationale for MR-only treatment planning for external radiotherapy. Clin Transl Radiat Oncol 2019; 18:60-65. [PMID: 31341977 PMCID: PMC6630106 DOI: 10.1016/j.ctro.2019.03.005] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Revised: 03/28/2019] [Accepted: 03/29/2019] [Indexed: 12/12/2022] Open
Abstract
•MR-only treatment planning could improve the spatial accuracy of radiotherapy.•The benefit compared to a mixed MR-CT workflow will vary between patient groups.•Further development of QA tools is needed before the procedure will save resources.
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Affiliation(s)
| | - Tufve Nyholm
- Department of Radiation Sciences, Umeå University, 90187 Umeå, Sweden
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Grosu AL, van der Heide UA. Imaging for radiation treatment planning and monitoring in prostate Cancer: Precision, personalization, individualization of therapy. Phys Imaging Radiat Oncol 2019; 11:61-62. [PMID: 33458279 PMCID: PMC7807567 DOI: 10.1016/j.phro.2019.09.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Affiliation(s)
- Anca-Ligia Grosu
- Department of Radiation Oncology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site, Freiburg, Germany
| | - Uulke A van der Heide
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
- Department of Radiation Oncology, Leiden University Medical Center, Leiden, the Netherlands
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