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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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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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Singhrao K, Dugan CL, Calvin C, Pelayo L, Yom SS, Chan JW, Scholey JE, Singer L. Evaluating the Hounsfield unit assignment and dose differences between CT-based standard and deep learning-based synthetic CT images for MRI-only radiation therapy of the head and neck. J Appl Clin Med Phys 2024; 25:e14239. [PMID: 38128040 PMCID: PMC10795453 DOI: 10.1002/acm2.14239] [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: 08/16/2023] [Revised: 11/22/2023] [Accepted: 11/29/2023] [Indexed: 12/23/2023] Open
Abstract
BACKGROUND Magnetic resonance image only (MRI-only) simulation for head and neck (H&N) radiotherapy (RT) could allow for single-image modality planning with excellent soft tissue contrast. In the MRI-only simulation workflow, synthetic computed tomography (sCT) is generated from MRI to provide electron density information for dose calculation. Bone/air regions produce little MRI signal which could lead to electron density misclassification in sCT. Establishing the dosimetric impact of this error could inform quality assurance (QA) procedures using MRI-only RT planning or compensatory methods for accurate dosimetric calculation. PURPOSE The aim of this study was to investigate if Hounsfield unit (HU) voxel misassignments from sCT images result in dosimetric errors in clinical treatment plans. METHODS Fourteen H&N cancer patients undergoing same-day CT and 3T MRI simulation were retrospectively identified. MRI was deformed to the CT using multimodal deformable image registration. sCTs were generated from T1w DIXON MRIs using a commercially available deep learning-based generator (MRIplanner, Spectronic Medical AB, Helsingborg, Sweden). Tissue voxel assignment was quantified by creating a CT-derived HU threshold contour. CT/sCT HU differences for anatomical/target contours and tissue classification regions including air (<250 HU), adipose tissue (-250 HU to -51 HU), soft tissue (-50 HU to 199 HU), spongy (200 HU to 499 HU) and cortical bone (>500 HU) were quantified. t-test was used to determine if sCT/CT HU differences were significant. The frequency of structures that had a HU difference > 80 HU (the CT window-width setting for intra-cranial structures) was computed to establish structure classification accuracy. Clinical intensity modulated radiation therapy (IMRT) treatment plans created on CT were retrospectively recalculated on sCT images and compared using the gamma metric. RESULTS The mean ratio of sCT HUs relative to CT for air, adipose tissue, soft tissue, spongy and cortical bone were 1.7 ± 0.3, 1.1 ± 0.1, 1.0 ± 0.1, 0.9 ± 0.1 and 0.8 ± 0.1 (value of 1 indicates perfect agreement). T-tests (significance set at t = 0.05) identified differences in HU values for air, spongy and cortical bone in sCT images compared to CT. The structures with sCT/CT HU differences > 80 HU of note were the left and right (L/R) cochlea and mandible (>79% of the tested cohort), the oral cavity (for 57% of the tested cohort), the epiglottis (for 43% of the tested cohort) and the L/R TM joints (occurring > 29% of the cohort). In the case of the cochlea and TM joints, these structures contain dense bone/air interfaces. In the case of the oral cavity and mandible, these structures suffer the additional challenge of being positionally altered in CT versus MRI simulation (due to a non-MR safe immobilizing bite block requiring absence of bite block in MR). Finally, the epiglottis HU assignment suffers from its small size and unstable positionality. Plans recalculated on sCT yielded global/local gamma pass rates of 95.5% ± 2% (3 mm, 3%) and 92.7% ± 2.1% (2 mm, 2%). The largest mean differences in D95, Dmean , D50 dose volume histogram (DVH) metrics for organ-at-risk (OAR) and planning tumor volumes (PTVs) were 2.3% ± 3.0% and 0.7% ± 1.9% respectively. CONCLUSIONS In this cohort, HU differences of CT and sCT were observed but did not translate into a reduction in gamma pass rates or differences in average PTV/OAR dose metrics greater than 3%. For sites such as the H&N where there are many tissue interfaces we did not observe large scale dose deviations but further studies using larger retrospective cohorts are merited to establish the variation in sCT dosimetric accuracy which could help to inform QA limits on clinical sCT usage.
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Affiliation(s)
- Kamal Singhrao
- Department of Radiation OncologyBrigham and Women's Hospital, Dana‐Farber Cancer Institute, Harvard Medical SchoolBostonMassachusettsUSA
| | - Catherine Lu Dugan
- Department of Radiation OncologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Christina Calvin
- Department of Radiation OncologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Luis Pelayo
- Department of Radiation OncologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Sue Sun Yom
- Department of Radiation OncologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Jason Wing‐Hong Chan
- Department of Radiation OncologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | | | - Lisa Singer
- Department of Radiation OncologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
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Singhrao K, Zubair M, Nano T, Scholey JE, Descovich M. End-to-end validation of fiducial tracking accuracy in robotic radiosurgery using MRI-only simulation imaging. Med Phys 2024; 51:31-41. [PMID: 38055419 DOI: 10.1002/mp.16857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 10/13/2023] [Accepted: 11/05/2023] [Indexed: 12/08/2023] Open
Abstract
BACKGROUND Image-guided radiation-therapy (IGRT)-based robotic radiosurgery using magnetic resonance imaging (MRI)-only simulation could allow for improved target definition with highly conformal radiotherapy treatments. Fiducial marker (FM)-based alignment is used with robotic radiosurgery treatments of sites such as the prostate because it aids in accurate target localization. Synthetic CT (sCT) images are generated in the MRI-only workflow but FMs used for IGRT appear as signal voids in MRIs and do not appear in MR-generated sCTs, hindering the ability to use sCTs for fiducial-based IGRT. PURPOSE In this study we evaluate the fiducial tracking accuracy for a novel artificial fiducial insertion method in sCT images that allows for fiducial marker tracking in robotic radiosurgery, using MRI-only simulation imaging (MRI-only workflow). METHODS Artificial fiducial markers were inserted into sCT images at the site of the real marker implantation as visible in MRI. Two phantoms were used in this study. A custom anthropomorphic pelvis phantom was designed to validate the tracking accuracy for a variety of artificial fiducials in an MRI-only workflow. A head phantom containing a hidden target and orthogonal film pair inserts was used to perform end-to-end tests of artificial fiducial configurations inserted in sCT images. The setup and end-to-end targeting accuracy of the MRI-only workflow were compared to the computed tomography (CT)-based standard. Each phantom had six FMs implanted with a minimum spacing of 2 cm. For each phantom a bulk-density sCT was generated, and artificial FMs were inserted at the implantation location. Several methods of FM insertion were tested including: (1) replacing HU with a fixed value (10000HU) (voxel-burned); (2) using a representative fiducial image derived from a linear combination of fiducial templates (composite-fiducial); (3) computationally simulating FM signal voids using a digital phantom containing FMs and inserting the corresponding signal void into sCT images (simulated-fiducial). All tests were performed on a CyberKnife system (Accuray, Sunnyvale, CA). Treatment plans and digital-reconstructed-radiographs were generated from the original CT and sCTs with embedded fiducials and used to align the phantom on the treatment couch. Differences in the initial phantom alignment (3D translations/rotations) and tracking parameters between CT-based plans and sCT-based plans were analyzed. End-to-end plans for both scenarios were generated and analyzed following our clinical protocol. RESULTS For all plans, the fiducial tracking algorithm was able to identify the fiducial locations. The mean FM-extraction uncertainty for the composite and simulated FMs was below 48% for fiducials in both the anthropomorphic pelvis and end-to-end phantoms, which is below the 70% treatment uncertainty threshold. The total targeting error was within tolerance (<0.95 mm) for end-to-end tests of sCT images with the composite and head-on simulated FMs (0.26, 0.44, and 0.35 mm for the composite fiducial in sCT, head-on simulated fiducial in sCT, and fiducials in original CT, respectively. CONCLUSIONS MRI-only simulation for robotic radiosurgery could potentially improve treatment accuracy and reduce planning margins. Our study has shown that using a composite-derived or simulated FM in conjunction with sCT images, MRI-only workflow can provide clinically acceptable setup accuracy in line with CT-based standards for FM-based robotic radiosurgery.
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Affiliation(s)
- Kamal Singhrao
- Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA
| | - Muhammad Zubair
- Department of Radiation Oncology, University of California, San Francisco, California, USA
| | - Tomi Nano
- Department of Radiation Oncology, University of California, San Francisco, California, USA
| | - Jessica E Scholey
- Department of Radiation Oncology, University of California, San Francisco, California, USA
| | - Martina Descovich
- Department of Radiation Oncology, University of California, San Francisco, California, USA
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Young T, Dowling J, Rai R, Liney G, Greer P, Thwaites D, Holloway L. Clinical validation of MR imaging time reduction for substitute/synthetic CT generation for prostate MRI-only treatment planning. Phys Eng Sci Med 2023; 46:1015-1021. [PMID: 37219797 PMCID: PMC10480277 DOI: 10.1007/s13246-023-01268-x] [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: 10/31/2022] [Accepted: 04/26/2023] [Indexed: 05/24/2023]
Abstract
Radiotherapy treatment planning based only on magnetic resonance imaging (MRI) has become clinically achievable. Though computed tomography (CT) is the gold standard for radiotherapy imaging, directly providing the electron density values needed for planning calculations, MRI has superior soft tissue visualisation to guide treatment planning decisions and optimisation. MRI-only planning removes the need for the CT scan, but requires generation of a substitute/synthetic/pseudo CT (sCT) for electron density information. Shortening the MRI imaging time would improve patient comfort and reduce the likelihood of motion artefacts. A volunteer study was previously carried out to investigate and optimise faster MRI sequences for a hybrid atlas-voxel conversion to sCT for prostate treatment planning. The aim of this follow-on study was to clinically validate the performance of the new optimised sequence for sCT generation in a treated MRI-only prostate patient cohort. 10 patients undergoing MRI-only treatment were scanned on a Siemens Skyra 3T MRI as part of the MRI-only sub-study of the NINJA clinical trial (ACTRN12618001806257). Two sequences were used, the standard 3D T2-weighted SPACE sequence used for sCT conversion which has been previously validated against CT, and a modified fast SPACE sequence, selected based on the volunteer study. Both were used to generate sCT scans. These were then compared to evaluate the fast sequence conversion for anatomical and dosimetric accuracy against the clinically approved treatment plans. The average Mean Absolute Error (MAE) for the body was 14.98 ± 2.35 HU, and for bone was 40.77 ± 5.51 HU. The external volume contour comparison produced a Dice Similarity Coefficient (DSC) of at least 0.976, and an average of 0.985 ± 0.004, and the bony anatomy contour comparison a DSC of at least 0.907, and an average of 0.950 ± 0.018. The fast SPACE sCT agreed with the gold standard sCT within an isocentre dose of -0.28% ± 0.16% and an average gamma pass rate of 99.66% ± 0.41% for a 1%/1 mm gamma tolerance. In this clinical validation study, the fast sequence, which reduced the required imaging time by approximately a factor of 4, produced an sCT with similar clinical dosimetric results compared to the standard sCT, demonstrating its potential for clinical use for treatment planning.
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Affiliation(s)
- Tony Young
- Liverpool and Macarthur Cancer Therapy Centres and Ingham Institute, Sydney, Australia
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, Australia
| | - Jason Dowling
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, Australia
- CSIRO Health and Biosecurity, The Australian e-Health & Research Centre, Brisbane, QLD Australia
- South Western Sydney Clinical School, University of New South Wales, Sydney, NSW Australia
- School of Mathematical and Physical Sciences, University of Newcastle, Callaghan, NSW Australia
- Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW Australia
| | - Robba Rai
- Liverpool and Macarthur Cancer Therapy Centres and Ingham Institute, Sydney, Australia
- South Western Sydney Clinical School, University of New South Wales, Sydney, NSW Australia
| | - Gary Liney
- Liverpool and Macarthur Cancer Therapy Centres and Ingham Institute, Sydney, Australia
- South Western Sydney Clinical School, University of New South Wales, Sydney, NSW Australia
- Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW Australia
| | - Peter Greer
- School of Mathematical and Physical Sciences, University of Newcastle, Callaghan, NSW Australia
- Calvary Mater Newcastle Hospital, Newcastle, NSW Australia
| | - David Thwaites
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, Australia
| | - Lois Holloway
- Liverpool and Macarthur Cancer Therapy Centres and Ingham Institute, Sydney, Australia
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, Australia
- South Western Sydney Clinical School, University of New South Wales, Sydney, NSW Australia
- Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW Australia
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Wegener E, Samuels J, Sidhom M, Trada Y, Sridharan S, Dickson S, McLeod N, Martin JM. Virtual HDR Boost for Prostate Cancer: Rebooting a Classic Treatment Using Modern Tech. Cancers (Basel) 2023; 15:cancers15072018. [PMID: 37046680 PMCID: PMC10093761 DOI: 10.3390/cancers15072018] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 03/23/2023] [Accepted: 03/27/2023] [Indexed: 03/31/2023] Open
Abstract
Prostate cancer (PC) is the most common malignancy in men. Internal radiotherapy (brachytherapy) has been used to treat PC successfully for over a century. In particular, there is level-one evidence of the benefits of using brachytherapy to escalate the dose of radiotherapy compared with standard external beam radiotherapy approaches. However, the use of PC brachytherapy is declining, despite strong evidence for its improved cancer outcomes. A method using external beam radiotherapy known as virtual high-dose-rate brachytherapy boost (vHDRB) aims to noninvasively mimic a brachytherapy boost radiation dose plan. In this review, we consider the evidence supporting brachytherapy boosts for PC and the continuing evolution of vHDRB approaches, culminating in the current generation of clinical trials, which will help define the role of this emerging modality.
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Affiliation(s)
- Eric Wegener
- School of Medicine and Public Health, The University of Newcastle, Callaghan, NSW 2308, Australia
- Department of Radiation Oncology, Calvary Mater Newcastle Hospital, Waratah, NSW 2298, Australia
- GenesisCare, Maitland, NSW 2323, Australia
- GenesisCare, Gateshead, NSW 2290, Australia
- Correspondence:
| | - Justin Samuels
- Department of Radiation Oncology, Calvary Mater Newcastle Hospital, Waratah, NSW 2298, Australia
| | - Mark Sidhom
- Department of Radiation Oncology, Liverpool Hospital, Liverpool, NSW 2170, Australia
| | - Yuvnik Trada
- Department of Radiation Oncology, Calvary Mater Newcastle Hospital, Waratah, NSW 2298, Australia
| | - Swetha Sridharan
- Department of Radiation Oncology, Calvary Mater Newcastle Hospital, Waratah, NSW 2298, Australia
- GenesisCare, Gateshead, NSW 2290, Australia
| | - Samuel Dickson
- Department of Radiation Oncology, Calvary Mater Newcastle Hospital, Waratah, NSW 2298, Australia
| | - Nicholas McLeod
- Department of Urology, John Hunter Hospital, Newcastle, NSW 2305, Australia
| | - Jarad M. Martin
- School of Medicine and Public Health, The University of Newcastle, Callaghan, NSW 2308, Australia
- Department of Radiation Oncology, Calvary Mater Newcastle Hospital, Waratah, NSW 2298, Australia
- GenesisCare, Maitland, NSW 2323, Australia
- GenesisCare, Gateshead, NSW 2290, Australia
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Hyuk Choi J, Asadi B, Simpson J, Dowling JA, Chalup S, Welsh J, Greer P. Investigation of a water equivalent depth method for dosimetric accuracy evaluation of synthetic CT. Phys Med 2023; 105:102507. [PMID: 36535236 DOI: 10.1016/j.ejmp.2022.11.011] [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: 05/18/2022] [Revised: 11/24/2022] [Accepted: 11/26/2022] [Indexed: 12/23/2022] Open
Abstract
PURPOSE To provide a metric that reflects the dosimetric utility of the synthetic CT (sCT) and can be rapidly determined. METHODS Retrospective CT and atlas-based sCT of 62 (53 IMRT and 9 VMAT) prostate cancer patients were used. For image similarity measurements, the sCT and reference CT (rCT) were aligned using clinical registration parameters. Conventional image similarity metrics including the mean absolute error (MAE) and mean error (ME) were calculated. The water equivalent depth (WED) was automatically determined for each patient on the rCT and sCT as the distance from the skin surface to the treatment plan isocentre at 36 equidistant gantry angles, and the mean WED difference (ΔWED¯) between the two scans was calculated. Doses were calculated on each scan pair for the clinical plan in the treatment planning system. The image similarity measurements and ΔWED¯ were then compared to the isocentre dose difference (ΔDiso) between the two scans. RESULTS While no particular relationship to dose was observed for the other image similarity metrics, the ME results showed a linear trend against ΔDiso with R2 = 0.6, and the 95 % prediction interval for ΔDiso between -1.2 and 1 %. The ΔWED¯ results showed an improved linear trend (R2 = 0.8) with a narrower 95 % prediction interval from -0.8 % to 0.8 %. CONCLUSION ΔWED¯ highly correlates with ΔDiso for the reference and synthetic CT scans. This is easy to calculate automatically and does not require time-consuming dose calculations. Therefore, it can facilitate the process of developing and evaluating new sCT generation algorithms.
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Affiliation(s)
- Jae Hyuk Choi
- School of Information and Physical Sciences, University of Newcastle, Newcastle, New South Wales, Australia.
| | - Behzad Asadi
- Department of Radiation Oncology, Calvary Mater Hospital, Newcastle, New South Wales, Australia
| | - John Simpson
- Department of Radiation Oncology, Calvary Mater Hospital, Newcastle, New South Wales, Australia
| | - Jason A Dowling
- School of Information and Physical Sciences, University of Newcastle, Newcastle, New South Wales, Australia; Commonwealth Scientific and Industrial Research Organisation, Australian E-Health Research Centre, Herston, Queensland, Australia
| | - Stephan Chalup
- School of Information and Physical Sciences, University of Newcastle, Newcastle, New South Wales, Australia
| | - James Welsh
- School of Engineering, University of Newcastle, Newcastle, New South Wales, Australia
| | - Peter Greer
- School of Information and Physical Sciences, University of Newcastle, Newcastle, New South Wales, Australia; Department of Radiation Oncology, Calvary Mater Hospital, Newcastle, New South Wales, Australia
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Persson E, Svanberg N, Scherman J, Jamtheim Gustafsson C, Fridhammar A, Hjalte F, Bäck S, Nilsson P, Gunnlaugsson A, Olsson LE. MRI-only radiotherapy from an economic perspective: Can new techniques in prostate cancer treatment be cost saving? Clin Transl Radiat Oncol 2022; 38:183-187. [DOI: 10.1016/j.ctro.2022.11.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 10/16/2022] [Accepted: 11/19/2022] [Indexed: 11/23/2022] Open
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Chourak H, Barateau A, Tahri S, Cadin C, Lafond C, Nunes JC, Boue-Rafle A, Perazzi M, Greer PB, Dowling J, de Crevoisier R, Acosta O. Quality assurance for MRI-only radiation therapy: A voxel-wise population-based methodology for image and dose assessment of synthetic CT generation methods. Front Oncol 2022; 12:968689. [PMID: 36300084 PMCID: PMC9589295 DOI: 10.3389/fonc.2022.968689] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 09/20/2022] [Indexed: 11/13/2022] Open
Abstract
The quality assurance of synthetic CT (sCT) is crucial for safe clinical transfer to an MRI-only radiotherapy planning workflow. The aim of this work is to propose a population-based process assessing local errors in the generation of sCTs and their impact on dose distribution. For the analysis to be anatomically meaningful, a customized interpatient registration method brought the population data to the same coordinate system. Then, the voxel-based process was applied on two sCT generation methods: a bulk-density method and a generative adversarial network. The CT and MRI pairs of 39 patients treated by radiotherapy for prostate cancer were used for sCT generation, and 26 of them with delineated structures were selected for analysis. Voxel-wise errors in sCT compared to CT were assessed for image intensities and dose calculation, and a population-based statistical test was applied to identify the regions where discrepancies were significant. The cumulative histograms of the mean absolute dose error per volume of tissue were computed to give a quantitative indication of the error for each generation method. Accurate interpatient registration was achieved, with mean Dice scores higher than 0.91 for all organs. The proposed method produces three-dimensional maps that precisely show the location of the major discrepancies for both sCT generation methods, highlighting the heterogeneity of image and dose errors for sCT generation methods from MRI across the pelvic anatomy. Hence, this method provides additional information that will assist with both sCT development and quality control for MRI-based planning radiotherapy.
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Affiliation(s)
- Hilda Chourak
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
- The Australian eHealth Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Health and Biosecurity, Brisbane, QLD, Australia
- *Correspondence: Hilda Chourak, ; Jason Dowling,
| | - Anaïs Barateau
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
| | - Safaa Tahri
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
| | - Capucine Cadin
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
| | - Caroline Lafond
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
| | - Jean-Claude Nunes
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
| | - Adrien Boue-Rafle
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
| | - Mathias Perazzi
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
| | - Peter B. Greer
- School of Mathematical and Physical Sciences, University of Newcastle, Newcastle, NSW, Australia
- Radiation Oncology, Calvary Mater Newcastle Hospital, Newcastle, NSW, Australia
| | - Jason Dowling
- The Australian eHealth Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Health and Biosecurity, Brisbane, QLD, Australia
- *Correspondence: Hilda Chourak, ; Jason Dowling,
| | - Renaud de Crevoisier
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
| | - Oscar Acosta
- University of Rennes, CLCC Eugène Marquis, INSERM, LTSI - UMR 1099, Rennes, France
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10
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Amarell K, Jaysing A, Mendez C, Haas JA, Blacksburg SR, Katz AE, Sanchez A, Tong A, Carpenter T, Witten M, Collins SP, Lischalk JW. Safety of stereotactic body radiation therapy for localized prostate cancer without treatment planning MRI. Radiat Oncol 2022; 17:66. [PMID: 35366926 PMCID: PMC8977039 DOI: 10.1186/s13014-022-02026-1] [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: 08/20/2021] [Accepted: 03/09/2022] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
The use of treatment planning prostate MRI for Stereotactic Body Radiation Therapy (SBRT) is largely a standard, yet not all patients can receive MRI for a variety of clinical reasons. Thus, we aim to investigate the safety of patients who received CT alone based SBRT planning for the definitive treatment of localized prostate cancer.
Methods
Our study analyzed 3410 patients with localized prostate cancer who were treated with SBRT at a single academic institution between 2006 and 2020. Acute and late toxicity was evaluated using the Common Terminology Criteria for Adverse Events version 5.0. Expanded Prostate Cancer Index Composite (EPIC) questionnaires evaluated QOL and PSA nadir was evaluated to detect biochemical failures.
Results
A total of 162 patients (4.75%) received CT alone for treatment planning. The CT alone group was older relative to the MRI group (69.9 vs 67.2, p < 0.001) and had higher risk and grade disease (p < 0.001). Additionally, the CT group exhibited a trend in larger CTVs (82.56 cc vs 76.90 cc; p = 0.055), lower total radiation doses (p = 0.048), and more frequent pelvic nodal radiation versus the MRI group (p < 0.001). There were only two reported cases of Grade 3 + toxicity within the CT alone group. Quality of life data within the CT alone group revealed declines in urinary and bowel scores at one month with return to baseline at subsequent follow up. Early biochemical failure data at median time of 2.3 years revealed five failures by Phoenix definition.
Conclusions
While clinical differences existed between the MRI and CT alone group, we observed tolerable toxicity profiles in the CT alone cohort, which was further supported by EPIC questionnaire data. The overall clinical outcomes appear comparable in patients unable to receive MRI for their SBRT treatment plan with early clinical follow up.
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11
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MRI-Based Radiotherapy Planning to Reduce Rectal Dose in Excess of Tolerance. Prostate Cancer 2022; 2022:7930744. [PMID: 35154830 PMCID: PMC8831048 DOI: 10.1155/2022/7930744] [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: 07/18/2021] [Revised: 12/15/2021] [Accepted: 12/28/2021] [Indexed: 11/18/2022] Open
Abstract
Materials and Methods This prospective single-arm study enrolled 15 men treated with IG-IMRT for localized prostate cancer. All participants received a dedicated 3 Tesla MRI examination of the prostate in addition to a pelvic CT examination for treatment planning. Two volumetric modulated arc therapy (VMAT) plans with a prescription dose of 79.2 Gy were designed using identical constraints based on CT- and MRI-defined consensus volumes. The volume of rectum exposed to 70 Gy or more was compared using the Wilcoxon paired signed rank test. Results For CT-based treatment plans, the median volume of rectum receiving 70 Gy or more was 9.3 cubic centimeters (cc) (IQR 7.0 to 10.2) compared with 4.9 cc (IQR 4.1 to 7.8) for MRI-based plans. This resulted in a median volume reduction of 2.1 cc (IQR 0.5 to 5.3, P < .001). Conclusions Using MRI to plan prostate IG-IMRT to a dose of 79.2 Gy reduces the volume of rectum receiving radiation dose in excess of tolerance (70 Gy or more) and should be considered in men who are at high risk for late rectal toxicity and are not good candidates for other rectal sparing techniques such as hydrogel spacer. This trial is registered with NCT02470910.
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12
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Lerner M, Medin J, Jamtheim Gustafsson C, Alkner S, Olsson LE. Prospective Clinical Feasibility Study for MRI-Only Brain Radiotherapy. Front Oncol 2022; 11:812643. [PMID: 35083159 PMCID: PMC8784680 DOI: 10.3389/fonc.2021.812643] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 12/20/2021] [Indexed: 11/14/2022] Open
Abstract
OBJECTIVES MRI-only radiotherapy (RT) provides a workflow to decrease the geometric uncertainty introduced by the image registration process between MRI and CT data and to streamline the RT planning. Despite the recent availability of validated synthetic CT (sCT) methods for the head region, there are no clinical implementations reported for brain tumors. Based on a preceding validation study of sCT, this study aims to investigate MRI-only brain RT through a prospective clinical feasibility study with endpoints for dosimetry and patient setup. MATERIAL AND METHODS Twenty-one glioma patients were included. MRI Dixon images were used to generate sCT images using a CE-marked deep learning-based software. RT treatment plans were generated based on MRI delineated anatomical structures and sCT for absorbed dose calculations. CT scans were acquired but strictly used for sCT quality assurance (QA). Prospective QA was performed prior to MRI-only treatment approval, comparing sCT and CT image characteristics and calculated dose distributions. Additional retrospective analysis of patient positioning and dose distribution gamma evaluation was performed. RESULTS Twenty out of 21 patients were treated using the MRI-only workflow. A single patient was excluded due to an MRI artifact caused by a hemostatic substance injected near the target during surgery preceding radiotherapy. All other patients fulfilled the acceptance criteria. Dose deviations in target were within ±1% for all patients in the prospective analysis. Retrospective analysis yielded gamma pass rates (2%, 2 mm) above 99%. Patient positioning using CBCT images was within ± 1 mm for registrations with sCT compared to CT. CONCLUSION We report a successful clinical study of MRI-only brain radiotherapy, conducted using both prospective and retrospective analysis. Synthetic CT images generated using the CE-marked deep learning-based software were clinically robust based on endpoints for dosimetry and patient positioning.
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Affiliation(s)
- Minna Lerner
- Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Department of Translational Medicine, Medical Radiation Physics, Lund University, Malmö, Sweden
| | - Joakim Medin
- Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Department of Medical Radiation Physics, Clinical Sciences, Lund, Lund University, Lund, Sweden
| | - Christian Jamtheim Gustafsson
- Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Department of Translational Medicine, Medical Radiation Physics, Lund University, Malmö, Sweden
| | - Sara Alkner
- Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Department of Clinical Sciences Lund, Oncology and Pathology, Lund University, Lund, Sweden
| | - Lars E. Olsson
- Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Lund, Sweden
- Department of Translational Medicine, Medical Radiation Physics, Lund University, Malmö, Sweden
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13
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Richardson M, Skehan K, Wilton L, Sams J, Samuels J, Goodwin J, Greer P, Sridharan S, Martin J. Visualising the urethra for prostate radiotherapy planning. J Med Radiat Sci 2021; 68:282-288. [PMID: 34028976 PMCID: PMC8424315 DOI: 10.1002/jmrs.485] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 05/01/2021] [Indexed: 12/26/2022] Open
Abstract
INTRODUCTION The prostatic urethra is an organ at risk for prostate radiotherapy with genitourinary toxicities a common side effect. Many external beam radiation therapy protocols call for urethral sparing, and with modulated radiotherapy techniques, the radiation dose distribution can be controlled so that maximum doses do not fall within the prostatic urethral volume. Whilst traditional diagnostic MRI sequences provide excellent delineation of the prostate, uncertainty often remains as to the true path of the urethra within the gland. This study aims to assess if a high-resolution isotropic 3D T2 MRI series can reduce inter-observer variability in urethral delineation for radiotherapy planning. METHODS Five independent observers contoured the prostatic urethra for ten patients on three data sets; a 2 mm axial CT, a diagnostic 3 mm axial T2 TSE MRI and a 0.9 mm isotropic 3D T2 SPACE MRI. The observers were blinded from each other's contours. A Dice Similarity Coefficient (DSC) score was calculated using the intersection and union of the five observer contours vs an expert reference contour for each data set. RESULTS The mean DSC of the observer vs reference contours was 0.47 for CT, 0.62 for T2 TSE and 0.78 for T2 SPACE (P < 0.001). CONCLUSIONS The introduction of a 0.9 mm isotropic 3D T2 SPACE MRI for treatment planning provides improved urethral visualisation and can lead to a significant reduction in inter-observer variation in prostatic urethral contouring.
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Affiliation(s)
- Matthew Richardson
- Department of Radiation OncologyCalvary Mater NewcastleWaratahNew South WalesAustralia
| | - Kate Skehan
- Department of Radiation OncologyCalvary Mater NewcastleWaratahNew South WalesAustralia
| | - Lee Wilton
- Department of Radiation OncologyCalvary Mater NewcastleWaratahNew South WalesAustralia
| | - Joshua Sams
- Department of Radiation OncologyCalvary Mater NewcastleWaratahNew South WalesAustralia
| | - Justin Samuels
- Department of Radiation OncologyCalvary Mater NewcastleWaratahNew South WalesAustralia
| | - Jonathan Goodwin
- Department of Radiation OncologyCalvary Mater NewcastleWaratahNew South WalesAustralia
- School of Mathematical and Physical ScienceUniversity of NewcastleCallaghanNew South WalesAustralia
| | - Peter Greer
- Department of Radiation OncologyCalvary Mater NewcastleWaratahNew South WalesAustralia
- School of Mathematical and Physical ScienceUniversity of NewcastleCallaghanNew South WalesAustralia
| | - Swetha Sridharan
- Department of Radiation OncologyCalvary Mater NewcastleWaratahNew South WalesAustralia
| | - Jarad Martin
- Department of Radiation OncologyCalvary Mater NewcastleWaratahNew South WalesAustralia
- School of Medicine and Public HealthUniversity of NewcastleCallaghanNew South WalesAustralia
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14
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Spadea MF, Maspero M, Zaffino P, Seco J. Deep learning based synthetic-CT generation in radiotherapy and PET: A review. Med Phys 2021; 48:6537-6566. [PMID: 34407209 DOI: 10.1002/mp.15150] [Citation(s) in RCA: 82] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 06/06/2021] [Accepted: 07/13/2021] [Indexed: 01/22/2023] Open
Abstract
Recently,deep learning (DL)-based methods for the generation of synthetic computed tomography (sCT) have received significant research attention as an alternative to classical ones. We present here a systematic review of these methods by grouping them into three categories, according to their clinical applications: (i) to replace computed tomography in magnetic resonance (MR) based treatment planning, (ii) facilitate cone-beam computed tomography based image-guided adaptive radiotherapy, and (iii) derive attenuation maps for the correction of positron emission tomography. Appropriate database searching was performed on journal articles published between January 2014 and December 2020. The DL methods' key characteristics were extracted from each eligible study, and a comprehensive comparison among network architectures and metrics was reported. A detailed review of each category was given, highlighting essential contributions, identifying specific challenges, and summarizing the achievements. Lastly, the statistics of all the cited works from various aspects were analyzed, revealing the popularity and future trends and the potential of DL-based sCT generation. The current status of DL-based sCT generation was evaluated, assessing the clinical readiness of the presented methods.
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Affiliation(s)
- Maria Francesca Spadea
- Department Experimental and Clinical Medicine, University "Magna Graecia" of Catanzaro, Catanzaro, 88100, Italy
| | - Matteo Maspero
- Division of Imaging & Oncology, Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan, Utrecht, The Netherlands.,Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Heidelberglaan, Utrecht, The Netherlands
| | - Paolo Zaffino
- Department Experimental and Clinical Medicine, University "Magna Graecia" of Catanzaro, Catanzaro, 88100, Italy
| | - Joao Seco
- Division of Biomedical Physics in Radiation Oncology, DKFZ German Cancer Research Center, Heidelberg, Germany.,Department of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
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15
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Persson E, Emin S, Scherman J, Jamtheim Gustafsson C, Brynolfsson P, Ceberg S, Gunnlaugsson A, Olsson LE. Investigation of the clinical inter-observer bias in prostate fiducial marker image registration between CT and MR images. Radiat Oncol 2021; 16:150. [PMID: 34399806 PMCID: PMC8365967 DOI: 10.1186/s13014-021-01865-8] [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: 01/12/2021] [Accepted: 07/17/2021] [Indexed: 01/17/2023] Open
Abstract
Background and purpose Inter-modality image registration between computed tomography (CT) and magnetic resonance (MR) images is associated with systematic uncertainties and the magnitude of these uncertainties is not well documented.
The purpose of this study was to investigate the potential uncertainty of gold fiducial marker (GFM) registration for localized prostate cancer and to estimate the inter-observer bias in a clinical setting. Methods
Four experienced observers registered CT and MR images for 42 prostate cancer patients. Manual GFM identification was followed by a landmark-based registration. The absolute difference between observers in GFM identification and the displacement of the clinical target volume (CTV) was investigated. The CTV center of mass (CoM) vector displacements, DICE-index and Hausdorff distances for the observer registrations were compared against a clinical baseline registration. The time allocated for the manual registrations was compared. Results Absolute difference in GFM identification between observers ranged from 0.0 to 3.0 mm. The maximum CTV CoM displacement from the clinical baseline was 3.1 mm. Displacements larger than or equal to 1 mm, 2 mm and 3 mm were 46%, 18% and 4%, respectively. No statistically significant difference was detected between observers in terms of CTV displacement. Median DICE-index and Hausdorff distance for the CTV, with their respective ranges were 0.94 [0.70–1.00] and 2.5 mm [0.7–8.7]. Conclusions Registration of CT and MR images using GFMs for localized prostate cancer patients was subject to inter-observer bias on an individual patient level. A CTV displacement as large as 3 mm occurred for individual patients. These results show that GFM registration in a clinical setting is associated with uncertainties, which motivates the removal of inter-modality registrations in the radiotherapy workflow and a transition to an MRI-only workflow for localized prostate cancer.
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Affiliation(s)
- Emilia Persson
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics , Skåne University Hospital, Klinikgatan 5, 221 85, Lund, Sweden. .,Department of Translational Medicine, Medical Radiation Physics, Lund University, Carl Bertil Laurellsgata 9, 205 02, Malmö, Sweden.
| | - Sevgi Emin
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics , Skåne University Hospital, Klinikgatan 5, 221 85, Lund, Sweden
| | - Jonas Scherman
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics , Skåne University Hospital, Klinikgatan 5, 221 85, Lund, Sweden
| | - Christian Jamtheim Gustafsson
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics , Skåne University Hospital, Klinikgatan 5, 221 85, Lund, Sweden.,Department of Translational Medicine, Medical Radiation Physics, Lund University, Carl Bertil Laurellsgata 9, 205 02, Malmö, Sweden
| | - Patrik Brynolfsson
- Department of Translational Medicine, Medical Radiation Physics, Lund University, Carl Bertil Laurellsgata 9, 205 02, Malmö, Sweden
| | - Sofie Ceberg
- Department of Medical Radiation Physics, Lund University, Barngatan 4, 222 85, Lund, Sweden
| | - Adalsteinn Gunnlaugsson
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics , Skåne University Hospital, Klinikgatan 5, 221 85, Lund, Sweden
| | - Lars E Olsson
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics , Skåne University Hospital, Klinikgatan 5, 221 85, Lund, Sweden.,Department of Translational Medicine, Medical Radiation Physics, Lund University, Carl Bertil Laurellsgata 9, 205 02, Malmö, Sweden
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16
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Young T, Dowling J, Rai R, Liney G, Greer P, Thwaites D, Holloway L. Effects of MR imaging time reduction on substitute CT generation for prostate MRI-only treatment planning. Phys Eng Sci Med 2021; 44:799-807. [PMID: 34228255 DOI: 10.1007/s13246-021-01031-0] [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: 11/19/2020] [Accepted: 06/24/2021] [Indexed: 11/25/2022]
Abstract
The introduction of MRI linear accelerators (MR-linacs) and the increased use of MR imaging in radiotherapy, requires improved approaches to MRI-only radiotherapy. MRI provides excellent soft tissue visualisation but does not provide any electron density information required for radiotherapy dose calculation, instead MRI is registered to CT images to enable dose calculations. MRI-only radiotherapy eliminates registration errors and reduces patient discomfort, workload and cost. Electron density requirements may be addressed in different ways, from manually applying bulk density corrections, to more computationally intensive methods to produce substitute CT datasets (sCT), requiring additional sequences, increasing overall imaging time. Reducing MR imaging time would reduce potential artefacts from intrafraction motion and patient discomfort. The aim of this study was to assess the impact of reducing MR imaging time on a hybrid atlas-voxel sCT conversion for prostate MRI-only treatment planning, considering both anatomical and dosimetric parameters. 10 volunteers were scanned on a Siemens Skyra 3T MRI. Sequences included the 3D T2-weighted (T2-w) SPACE sequence used for sCT conversion as previously validated against CT, along with variations to this sequence in repetition time (TR), turbo factor, and combinations of these to reduce the imaging time. All scans were converted to sCT and were compared to the sCT from the original SPACE sequence, evaluating for anatomical changes and dosimetric differences for a standard prostate VMAT plan. Compared to the previously validated T2-w SPACE sequence, scan times were reduced by up to 80%. The external volume and bony anatomy were compared, with all but one sequence meeting a DICE coefficient of 0.9 or better, with the largest variations occurring at the edges of the external body volume. The generated sCT agreed with the gold standard sCT within an isocentre dose of 1% and a gamma pass rate of 99% for a 1%/1 mm gamma tolerance for all but one sequence. This study demonstrates that the MR imaging sequence time was able to be reduced by approximately 80% with similar dosimetric results.
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Affiliation(s)
- Tony Young
- Liverpool and Macarthur Cancer Therapy Centres and Ingham Institute, Sydney, NSW, Australia. .,Institute of Medical Physics, School of Physics, University of Sydney, Sydney, NSW, Australia.
| | - Jason Dowling
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, NSW, Australia.,CSIRO Health and Biosecurity, The Australian e-Health & Research Centre, Brisbane, QLD, Australia.,South Western Sydney Clinical School, University of New South Wales, Sydney, NSW, Australia.,School of Mathematical and Physical Sciences, University of Newcastle, Callaghan, NSW, Australia.,Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW, Australia
| | - Robba Rai
- Liverpool and Macarthur Cancer Therapy Centres and Ingham Institute, Sydney, NSW, Australia.,South Western Sydney Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - Gary Liney
- Liverpool and Macarthur Cancer Therapy Centres and Ingham Institute, Sydney, NSW, Australia.,South Western Sydney Clinical School, University of New South Wales, Sydney, NSW, Australia.,Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW, Australia
| | - Peter Greer
- School of Mathematical and Physical Sciences, University of Newcastle, Callaghan, NSW, Australia.,Calvary Mater Newcastle Hospital, Newcastle, NSW, Australia
| | - David Thwaites
- Institute of Medical Physics, School of Physics, University of Sydney, Sydney, NSW, Australia
| | - Lois Holloway
- Liverpool and Macarthur Cancer Therapy Centres and Ingham Institute, Sydney, NSW, Australia.,Institute of Medical Physics, School of Physics, University of Sydney, Sydney, NSW, Australia.,South Western Sydney Clinical School, University of New South Wales, Sydney, NSW, Australia.,Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW, Australia
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17
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Nosrati R, Lam WW, Paudel M, Pejović-Milić A, Morton G, Stanisz GJ. Feasibility of using a single MRI acquisition for fiducial marker localization and synthetic CT generation towards MRI-only prostate radiation therapy treatment planning. Biomed Phys Eng Express 2021; 7. [PMID: 34034242 DOI: 10.1088/2057-1976/ac0501] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 05/25/2021] [Indexed: 11/12/2022]
Abstract
Purpose.To investigate the feasibility of using a single MRI acquisition for fiducial marker identification and synthetic CT (sCT) generation towards MRI-only treatment planning for prostate external beam radiation therapy (EBRT).Methods.Seven prostate cancer patients undergoing EBRT, each with three implanted gold fiducial markers, participated in this study. In addition to the planning CT scan, all patients were scanned on a 3 T MR scanner with a 3D double-echo gradient echo (GRE) sequence. Quantitative susceptibility mapping (QSM) was performed for marker localization. QSM-derived marker positions were compared to those from CT. The bulk density assignment technique for sCT generation was adopted. The magnitude GRE images were segmented into muscle, bone, fat, and air using a combination of unsupervised intensity-based classification of soft tissue and convolutional neural networks (CNN) for bone segmentation.Results.All implanted markers were visualized and accurately identified (average error: 0.7 ± 0.5 mm). QSM generated distinctive contrast for hemorrhage, calcifications, and gold fiducial markers. The estimated susceptibility/HU values on QSM/CT for gold and calcifications were 31.5 ± 2.9 ppm/1220 ± 100 HU and 14.6 ± 0.9 ppm/440 ± 100 HU, respectively. The intensity-based soft tissue classification resulted in an average Dice score of 0.97 ± 0.02; bone segmentation using CNN resulted in an average Dice score of 0.93 ± 0.03.Conclusion.This work indicates the feasibility of simultaneous fiducial marker identification and sCT generation using a single MRI acquisition. Future works includes evaluation of the proposed method in a large cohort of patients with optimized acquisition parameters as well as dosimetric evaluations.
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Affiliation(s)
- R Nosrati
- Harvard Medical School, Boston, MA, United States of America.,Boston Children's Hospital, Boston, MA, United States of America
| | - W W Lam
- Sunnybrook Health Sciences Centre, ON, Canada
| | - M Paudel
- Sunnybrook Health Sciences Centre, ON, Canada.,University of Toronto, Toronto, ON, Canada
| | | | - G Morton
- Sunnybrook Health Sciences Centre, ON, Canada.,University of Toronto, Toronto, ON, Canada
| | - G J Stanisz
- Sunnybrook Health Sciences Centre, ON, Canada.,University of Toronto, Toronto, ON, Canada
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18
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Edmund JM, Andreasen D, Van Leemput K. Cone beam computed tomography based image guidance and quality assessment of prostate cancer for magnetic resonance imaging-only radiotherapy in the pelvis. PHYSICS & IMAGING IN RADIATION ONCOLOGY 2021; 18:55-60. [PMID: 34258409 PMCID: PMC8254192 DOI: 10.1016/j.phro.2021.05.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 04/23/2021] [Accepted: 05/04/2021] [Indexed: 12/22/2022]
Abstract
MRI-only IGRT accuracy is ≤2 mm as compared to CT but significant differences were observed. MRI-only CBCT-based IGRT seems feasible but caution is advised. The median absolute error (MeAE) for independent verification on the sCT quality is proposed. A MeAE around 0.1 in mass density could call for sCT quality inspection.
Background and purpose Radiotherapy (RT) based on magentic resonance imaging (MRI) only is currently used clinically in the pelvis. A synthetic computed tomography (sCT) is needed for dose planning. Here, we investigate the accuracy of cone beam CT (CBCT) based MRI-only image guided RT (IGRT) and sCT image quality. Materials and methods CT, MRI and CBCT scans of ten prostate cancer patients were included. The MRI was converted to a sCT using a multi-atlas approach. The sCT, CT and MR images were auto-matched with the CBCT on the bony anatomy. Paired sCT-CT and sCT-CBCT data were created. CT numbers were converted to relative electron (RED) and mass densities (DES) using a standard calibration curve for the CT and sCT. For the CBCT RED/DES conversion, a phantom and paired CT-CBCT population based calibration curve was used. For the latter, the CBCT numbers were averaged in 100 HU bins and the known RED/DES of the CT were assigned. The paired sCT-CT and sCT-CBCT data were averaged in bins of 10 HU or 0.01 RED/DES. The median absolute error (MeAE) between the sCT-CT and sCT-CBCT bins was calculated. Wilcoxon rank-sum tests were carried out for the IGRT and MeAE study. Results The mean sCT or MR IGRT difference from CT was ≤ 2 mm but significant differences were observed. A CBCT HU or phantom-based RED/DES MeAE did not estimate the sCT quality similar to a CT based MeAE but the CBCT population-based RED/DES MeAE did. Conclusions MRI-only CBCT-based IGRT seems feasible but caution is advised. A MeAE around 0.1 DES could call for sCT quality inspection.
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Affiliation(s)
- Jens M Edmund
- Radiotherapy Research Unit, Department of Oncology, Gentofte and Herlev Hospital, University of Copenhagen, 2730 Herlev, Denmark.,Niels Bohr Institute, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Daniel Andreasen
- Department of Health Technology, Technical University of Denmark, 2800 Lyngby, Denmark
| | - Koen Van Leemput
- Department of Health Technology, Technical University of Denmark, 2800 Lyngby, Denmark.,Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
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Bourbonne V, Jaouen V, Hognon C, Boussion N, Lucia F, Pradier O, Bert J, Visvikis D, Schick U. Dosimetric Validation of a GAN-Based Pseudo-CT Generation for MRI-Only Stereotactic Brain Radiotherapy. Cancers (Basel) 2021; 13:1082. [PMID: 33802499 PMCID: PMC7959466 DOI: 10.3390/cancers13051082] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Revised: 02/23/2021] [Accepted: 02/24/2021] [Indexed: 12/15/2022] Open
Abstract
PURPOSE Stereotactic radiotherapy (SRT) has become widely accepted as a treatment of choice for patients with a small number of brain metastases that are of an acceptable size, allowing for better target dose conformity, resulting in high local control rates and better sparing of organs at risk. An MRI-only workflow could reduce the risk of misalignment between magnetic resonance imaging (MRI) brain studies and computed tomography (CT) scanning for SRT planning, while shortening delays in planning. Given the absence of a calibrated electronic density in MRI, we aimed to assess the equivalence of synthetic CTs generated by a generative adversarial network (GAN) for planning in the brain SRT setting. METHODS All patients with available MRIs and treated with intra-cranial SRT for brain metastases from 2014 to 2018 in our institution were included. After co-registration between the diagnostic MRI and the planning CT, a synthetic CT was generated using a 2D-GAN (2D U-Net). Using the initial treatment plan (Pinnacle v9.10, Philips Healthcare), dosimetric comparison was performed using main dose-volume histogram (DVH) endpoints in respect to ICRU 91 guidelines (Dmax, Dmean, D2%, D50%, D98%) as well as local and global gamma analysis with 1%/1 mm, 2%/1 mm and 2%/2 mm criteria and a 10% threshold to the maximum dose. t-test analysis was used for comparison between the two cohorts (initial and synthetic dose maps). RESULTS 184 patients were included, with 290 treated brain metastases. The mean number of treated lesions per patient was 1 (range 1-6) and the median planning target volume (PTV) was 6.44 cc (range 0.12-45.41). Local and global gamma passing rates (2%/2 mm) were 99.1 CI95% (98.1-99.4) and 99.7 CI95% (99.6-99.7) respectively (CI: confidence interval). DVHs were comparable, with no significant statistical differences regarding ICRU 91's endpoints. CONCLUSIONS Our study is the first to compare GAN-generated CT scans from diagnostic brain MRIs with initial CT scans for the planning of brain stereotactic radiotherapy. We found high similarity between the planning CT and the synthetic CT for both the organs at risk and the target volumes. Prospective validation is under investigation at our institution.
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Affiliation(s)
- Vincent Bourbonne
- Radiation Oncology Department, CHRU Brest, 2 Avenue Foch, 29200 Brest, France; (N.B.); (F.L.); (O.P.); (U.S.)
- Laboratoire de Traitement de l’Information Médicale, Unité Mixte de Recherche 1101, Institut National de la Santé et de la Recherche, Université de Bretagne Occidentale, 29200 Brest, France; (V.J.); (C.H.); (J.B.); (D.V.)
| | - Vincent Jaouen
- Laboratoire de Traitement de l’Information Médicale, Unité Mixte de Recherche 1101, Institut National de la Santé et de la Recherche, Université de Bretagne Occidentale, 29200 Brest, France; (V.J.); (C.H.); (J.B.); (D.V.)
- Institut Mines-Télécom Atlantique, 29200 Brest, France
| | - Clément Hognon
- Laboratoire de Traitement de l’Information Médicale, Unité Mixte de Recherche 1101, Institut National de la Santé et de la Recherche, Université de Bretagne Occidentale, 29200 Brest, France; (V.J.); (C.H.); (J.B.); (D.V.)
| | - Nicolas Boussion
- Radiation Oncology Department, CHRU Brest, 2 Avenue Foch, 29200 Brest, France; (N.B.); (F.L.); (O.P.); (U.S.)
- Laboratoire de Traitement de l’Information Médicale, Unité Mixte de Recherche 1101, Institut National de la Santé et de la Recherche, Université de Bretagne Occidentale, 29200 Brest, France; (V.J.); (C.H.); (J.B.); (D.V.)
| | - François Lucia
- Radiation Oncology Department, CHRU Brest, 2 Avenue Foch, 29200 Brest, France; (N.B.); (F.L.); (O.P.); (U.S.)
- Laboratoire de Traitement de l’Information Médicale, Unité Mixte de Recherche 1101, Institut National de la Santé et de la Recherche, Université de Bretagne Occidentale, 29200 Brest, France; (V.J.); (C.H.); (J.B.); (D.V.)
| | - Olivier Pradier
- Radiation Oncology Department, CHRU Brest, 2 Avenue Foch, 29200 Brest, France; (N.B.); (F.L.); (O.P.); (U.S.)
- Laboratoire de Traitement de l’Information Médicale, Unité Mixte de Recherche 1101, Institut National de la Santé et de la Recherche, Université de Bretagne Occidentale, 29200 Brest, France; (V.J.); (C.H.); (J.B.); (D.V.)
| | - Julien Bert
- Laboratoire de Traitement de l’Information Médicale, Unité Mixte de Recherche 1101, Institut National de la Santé et de la Recherche, Université de Bretagne Occidentale, 29200 Brest, France; (V.J.); (C.H.); (J.B.); (D.V.)
| | - Dimitris Visvikis
- Laboratoire de Traitement de l’Information Médicale, Unité Mixte de Recherche 1101, Institut National de la Santé et de la Recherche, Université de Bretagne Occidentale, 29200 Brest, France; (V.J.); (C.H.); (J.B.); (D.V.)
| | - Ulrike Schick
- Radiation Oncology Department, CHRU Brest, 2 Avenue Foch, 29200 Brest, France; (N.B.); (F.L.); (O.P.); (U.S.)
- Laboratoire de Traitement de l’Information Médicale, Unité Mixte de Recherche 1101, Institut National de la Santé et de la Recherche, Université de Bretagne Occidentale, 29200 Brest, France; (V.J.); (C.H.); (J.B.); (D.V.)
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Gustafsson CJ, Swärd J, Adalbjörnsson SI, Jakobsson A, Olsson LE. Development and evaluation of a deep learning based artificial intelligence for automatic identification of gold fiducial markers in an MRI-only prostate radiotherapy workflow. Phys Med Biol 2020; 65:225011. [PMID: 33179610 DOI: 10.1088/1361-6560/abb0f9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Identification of prostate gold fiducial markers in magnetic resonance imaging (MRI) images is challenging when CT images are not available, due to misclassifications from intra-prostatic calcifications. It is also a time consuming task and automated identification methods have been suggested as an improvement for both objectives. Multi-echo gradient echo (MEGRE) images have been utilized for manual fiducial identification with 100% detection accuracy. The aim is therefore to develop an automatic deep learning based method for fiducial identification in MRI images intended for MRI-only prostate radiotherapy. MEGRE images from 326 prostate cancer patients with fiducials were acquired on a 3T MRI, post-processed with N4 bias correction, and the fiducial center of mass (CoM) was identified. A 9 mm radius sphere was created around the CoM as ground truth. A deep learning HighRes3DNet model for semantic segmentation was trained using image augmentation. The model was applied to 39 MRI-only patients and 3D probability maps for fiducial location and segmentation were produced and spatially smoothed. In each of the three largest probability peaks, a 9 mm radius sphere was defined. Detection sensitivity and geometric accuracy was assessed. To raise awareness of potential false findings a 'BeAware' score was developed, calculated from the total number and quality of the probability peaks. All datasets, annotations and source code used were made publicly available. The detection sensitivity for all fiducials were 97.4%. Thirty-six out of thirty-nine patients had all fiducial markers correctly identified. All three failed patients generated a user notification using the BeAware score. The mean absolute difference between the detected fiducial and ground truth CoM was 0.7 ± 0.9 [0 3.1] mm. A deep learning method for automatic fiducial identification in MRI images was developed and evaluated with state-of-the-art results. The BeAware score has the potential to notify the user regarding patients where the proposed method is uncertain.
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Affiliation(s)
- Christian Jamtheim Gustafsson
- Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, Lund, Sweden. Department of Translational Sciences, Medical Radiation Physics, Lund University, Malmö, Sweden
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Singhrao K, Fu J, Parikh NR, Mikaeilian AG, Ruan D, Kishan AU, Lewis JH. A generative adversarial network‐based (GAN‐based) architecture for automatic fiducial marker detection in prostate MRI‐only radiotherapy simulation images. Med Phys 2020; 47:6405-6413. [DOI: 10.1002/mp.14498] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 08/02/2020] [Accepted: 09/07/2020] [Indexed: 12/22/2022] Open
Affiliation(s)
- Kamal Singhrao
- Department of Radiation Oncology University of California, Los Angeles Los Angeles CA 90095 USA
| | - Jie Fu
- Department of Radiation Oncology University of California, Los Angeles Los Angeles CA 90095 USA
| | - Neil R. Parikh
- Department of Radiation Oncology University of California, Los Angeles Los Angeles CA 90095 USA
| | - Argin G. Mikaeilian
- Department of Radiation Oncology University of California, Los Angeles Los Angeles CA 90095 USA
| | - Dan Ruan
- Department of Radiation Oncology University of California, Los Angeles Los Angeles CA 90095 USA
| | - Amar U. Kishan
- Department of Radiation Oncology University of California, Los Angeles Los Angeles CA 90095 USA
| | - John H. Lewis
- Department of Radiation Oncology Cedars‐Sinai Medical Center Los Angeles CA 90048 USA
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Persson E, Jamtheim Gustafsson C, Ambolt P, Engelholm S, Ceberg S, Bäck S, Olsson LE, Gunnlaugsson A. MR-PROTECT: Clinical feasibility of a prostate MRI-only radiotherapy treatment workflow and investigation of acceptance criteria. Radiat Oncol 2020; 15:77. [PMID: 32272943 PMCID: PMC7147064 DOI: 10.1186/s13014-020-01513-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Accepted: 03/13/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Retrospective studies on MRI-only radiotherapy have been presented. Widespread clinical implementations of MRI-only workflows are however limited by the absence of guidelines. The MR-PROTECT trial presents an MRI-only radiotherapy workflow for prostate cancer using a new single sequence strategy. The workflow incorporated the commercial synthetic CT (sCT) generation software MriPlanner™ (Spectronic Medical, Helsingborg, Sweden). Feasibility of the workflow and limits for acceptance criteria were investigated for the suggested workflow with the aim to facilitate future clinical implementations. METHODS An MRI-only workflow including imaging, post imaging tasks, treatment plan creation, quality assurance and treatment delivery was created with questionnaires. All tasks were performed in a single MR-sequence geometry, eliminating image registrations. Prospective CT-quality assurance (QA) was performed prior treatment comparing the PTV mean dose between sCT and CT dose-distributions. Retrospective analysis of the MRI-only gold fiducial marker (GFM) identification, DVH- analysis, gamma evaluation and patient set-up verification using GFMs and cone beam CT were performed. RESULTS An MRI-only treatment was delivered to 39 out of 40 patients. The excluded patient was too large for the predefined imaging field-of-view. All tasks could successfully be performed for the treated patients. There was a maximum deviation of 1.2% in PTV mean dose was seen in the prospective CT-QA. Retrospective analysis showed a maximum deviation below 2% in the DVH-analysis after correction for rectal gas and gamma pass-rates above 98%. MRI-only patient set-up deviation was below 2 mm for all but one investigated case and a maximum of 2.2 mm deviation in the GFM-identification compared to CT. CONCLUSIONS The MR-PROTECT trial shows the feasibility of an MRI-only prostate radiotherapy workflow. A major advantage with the presented workflow is the incorporation of a sCT-generation method with multi-vendor capability. The presented single sequence approach are easily adapted by other clinics and the general implementation procedure can be replicated. The dose deviation and the gamma pass-rate acceptance criteria earlier suggested was achievable, and these limits can thereby be confirmed. GFM-identification acceptance criteria are depending on the choice of identification method and slice thickness. Patient positioning strategies needs further investigations to establish acceptance criteria.
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Affiliation(s)
- Emilia Persson
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, 221 85, Lund, Sweden.
- Department of Translational Medicine, Medical Radiation Physics, Lund University, Inga-Marie Nilssons gata 49, 205 02, Malmö, Sweden.
| | - Christian Jamtheim Gustafsson
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, 221 85, Lund, Sweden
- Department of Translational Medicine, Medical Radiation Physics, Lund University, Inga-Marie Nilssons gata 49, 205 02, Malmö, Sweden
| | - Petra Ambolt
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, 221 85, Lund, Sweden
| | - Silke Engelholm
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, 221 85, Lund, Sweden
| | - Sofie Ceberg
- Department of Medical Radiation Physics, Lund University, Barngatan 4, 222 85, Lund, Sweden
| | - Sven Bäck
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, 221 85, Lund, Sweden
| | - Lars E Olsson
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, 221 85, Lund, Sweden
- Department of Translational Medicine, Medical Radiation Physics, Lund University, Inga-Marie Nilssons gata 49, 205 02, Malmö, Sweden
| | - Adalsteinn Gunnlaugsson
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, 221 85, Lund, Sweden
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