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Emin S, Rossi E, Myrvold Rooth E, Dorniok T, Hedman M, Gagliardi G, Villegas F. Clinical implementation of a commercial synthetic computed tomography solution for radiotherapy treatment of glioblastoma. Phys Imaging Radiat Oncol 2024; 30:100589. [PMID: 38818305 PMCID: PMC11137592 DOI: 10.1016/j.phro.2024.100589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 05/12/2024] [Accepted: 05/13/2024] [Indexed: 06/01/2024] Open
Abstract
Background and Purpose Magnetic resonance (MR)-only radiotherapy (RT) workflow eliminates uncertainties due to computed tomography (CT)-MR image registration, by using synthetic CT (sCT) images generated from MR. This study describes the clinical implementation process, from retrospective commissioning to prospective validation stage of a commercial artificial intelligence (AI)-based sCT product. Evaluation of the dosimetric performance of the sCT is presented, with emphasis on the impact of voxel size differences between image modalities. Materials and methods sCT performance was assessed in glioblastoma RT planning. Dose differences for 30 patients in both commissioning and validation cohorts were calculated at various dose-volume-histogram (DVH) points for target and organs-at-risk (OAR). A gamma analysis was conducted on regridded image plans. Quality assurance (QA) guidelines were established based on commissioning phase results. Results Mean dose difference to target structures was found to be within ± 0.7 % regardless of image resolution and cohort. OARs' mean dose differences were within ± 1.3 % for plans calculated on regridded images for both cohorts, while differences were higher for plans with original voxel size, reaching up to -4.2 % for chiasma D2% in the commissioning cohort. Gamma passing rates for the brain structure using the criteria 1 %/1mm, 2 %/2mm and 3 %/3mm were 93.6 %/99.8 %/100 % and 96.6 %/99.9 %/100 % for commissioning and validation cohorts, respectively. Conclusions Dosimetric outcomes in both commissioning and validation stages confirmed sCT's equivalence to CT. The large patient cohort in this study aided in establishing a robust QA program for the MR-only workflow, now applied in glioblastoma RT at our center.
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Affiliation(s)
- Sevgi Emin
- Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, 171 76 Stockholm, Sweden
| | - Elia Rossi
- Department of Radiation Oncology, Karolinska University Hospital, 171 76 Stockholm, Sweden
| | | | - Torsten Dorniok
- Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, 171 76 Stockholm, Sweden
| | - Mattias Hedman
- Department of Radiation Oncology, Karolinska University Hospital, 171 76 Stockholm, Sweden
- Department of Oncology-Pathology, Karolinska Institute, 171 77 Stockholm, Sweden
| | - Giovanna Gagliardi
- Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, 171 76 Stockholm, Sweden
- Department of Oncology-Pathology, Karolinska Institute, 171 77 Stockholm, Sweden
| | - Fernanda Villegas
- Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, 171 76 Stockholm, Sweden
- Department of Oncology-Pathology, Karolinska Institute, 171 77 Stockholm, Sweden
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Samanci Y, Askeroglu MO, Düzkalir AH, Peker S. Assessing the impact of distortion correction on Gamma Knife radiosurgery for multiple metastasis: Volumetric and dosimetric analysis. BRAIN & SPINE 2024; 4:102791. [PMID: 38584868 PMCID: PMC10995810 DOI: 10.1016/j.bas.2024.102791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 03/11/2024] [Accepted: 03/19/2024] [Indexed: 04/09/2024]
Abstract
Introduction Magnetic resonance imaging (MRI) is a robust neuroimaging technique and is the preferred method for stereotactic radiosurgery (SRS) planning. However, MRI data always contain distortions caused by hardware and patient factors. Research question Can these distortions potentially compromise the effectiveness and safety of SRS treatments? Material and methods Twenty-six MR datasets with multiple metastatic brain tumors (METs) used for Gamma Knife radiosurgery (GKRS) were retrospectively evaluated. A commercially available software was used for distortion correction. Geometrical agreement between corrected and uncorrected tumor volumes was evaluated using MacDonald criteria, Euclidian distance, and Dice similarity coefficient (DSC). SRS plans were generated using uncorrected tumor volumes, which were assessed to determine their coverage of the corrected tumor volumes. Results The median target volume was 0.38 cm3 (range,0.01-12.38 cm3). A maximum displacement of METs of up to 2.87 mm and a median displacement of 0.55 mm (range,0.1-2.87 mm) were noted. The median DSC between uncorrected and corrected MRI was 0.92, and the most concerning case had a DSC of 0.46. Although all plans met the optimization criterion of at least 98% of the uncorrected tumor volume (median 99.55%, range 98.1-100%) receiving at least 100% of the prescription dose, the percent of the corrected tumor volume receiving the total prescription dose was a median of 95.45% (range,23.1-99.5%). Discussion and conclusion MRI distortion, though visually subtle, has significant implications for SRS planning. Regular utilization of corrected MRI is recommended for SRS planning as distortion is sometimes enough to cause a volumetric miss of SRS targets.
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Affiliation(s)
- Yavuz Samanci
- Department of Neurosurgery, Koc University School of Medicine, Istanbul, Turkey
- Gamma Knife Center, Department of Neurosurgery, Koc University Hospital, Istanbul, Turkey
| | - M. Orbay Askeroglu
- Gamma Knife Center, Department of Neurosurgery, Koc University Hospital, Istanbul, Turkey
| | - Ali Haluk Düzkalir
- Gamma Knife Center, Department of Neurosurgery, Koc University Hospital, Istanbul, Turkey
- Department of Neurosurgery, Koc University Hospital, Istanbul, Turkey
| | - Selcuk Peker
- Department of Neurosurgery, Koc University School of Medicine, Istanbul, Turkey
- Gamma Knife Center, Department of Neurosurgery, Koc University Hospital, Istanbul, Turkey
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Olsson LE, Af Wetterstedt S, Scherman J, Gunnlaugsson A, Persson E, Jamtheim Gustafsson C. Evaluation of a deep learning magnetic resonance imaging reconstruction method for synthetic computed tomography generation in prostate radiotherapy. Phys Imaging Radiat Oncol 2024; 29:100557. [PMID: 38414521 PMCID: PMC10897922 DOI: 10.1016/j.phro.2024.100557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 02/07/2024] [Accepted: 02/08/2024] [Indexed: 02/29/2024] Open
Abstract
Background and Purpose In magnetic resonance imaging (MRI) only radiotherapy computed tomography (CT) is excluded. The method relies entirely on synthetic CT images generated from MRI. This study evaluates the compatibility of a commercial synthetic CT (sCT) with an accelerated commercial deep learning reconstruction (DLR) in MRI-only prostate radiotherapy. Materials and Methods For a group of 24 patients (cohort 1) the effects of DLR were studied in isolation. MRI data were reconstructed conventionally and with DLR from identical k-space data, and sCTs were generated for both reconstructions. The sCT quality, Hounsfield Unit (HU) and dosimetric impact were investigated. In another group of 15 patients (cohort 2) effects on sCT generation using accelerated MRI acquisition (40 % time reduction) reconstructed with DLR were investigated. Results sCT images from both cohorts, generated from DLR MRI data, were of clinically expected image quality. The mean dose differences for targets and organs at risks in cohort 1 were <0.06 Gy, corresponding to a 0.1 % prescribed dose difference. Similar dose differences were observed in cohort 2. Gamma pass rates for cohort 1 were 100 % for criteria 3 %/3mm, 2 %/2mm and 1 %/1mm for all dose levels. Mean error and mean absolute error inside the body, between sCTs, averaged over all cohort 1 subjects, were -1.1 ± 0.6 [-2.4 0.2] and 2.9 ± 0.4 [2.3 3.9] HU, respectively. Conclusions DLR was suitable for sCT generation with clinically negligible differences in HU and calculated dose compared to the conventional MRI reconstruction method. For sCT generation DLR enables scan time reduction, without compromised sCT quality.
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Affiliation(s)
- Lars E Olsson
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, Lund 221 85, Sweden
- Department of Translational Medicine, Medical Radiation Physics, Lund University, Carl Bertil Laurells gata 9, Malmö 205 02, Sweden
| | - Sacha Af Wetterstedt
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, Lund 221 85, Sweden
| | - Jonas Scherman
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, Lund 221 85, Sweden
| | - Adalsteinn Gunnlaugsson
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, Lund 221 85, Sweden
| | - Emilia Persson
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, Lund 221 85, Sweden
- Department of Translational Medicine, Medical Radiation Physics, Lund University, Carl Bertil Laurells gata 9, Malmö 205 02, Sweden
| | - Christian Jamtheim Gustafsson
- Radiation Physics, Department of Hematology, Oncology, and Radiation Physics, Skåne University Hospital, Klinikgatan 5, Lund 221 85, Sweden
- Department of Translational Medicine, Medical Radiation Physics, Lund University, Carl Bertil Laurells gata 9, Malmö 205 02, Sweden
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Putz F, Bock M, Schmitt D, Bert C, Blanck O, Ruge MI, Hattingen E, Karger CP, Fietkau R, Grigo J, Schmidt MA, Bäuerle T, Wittig A. Quality requirements for MRI simulation in cranial stereotactic radiotherapy: a guideline from the German Taskforce "Imaging in Stereotactic Radiotherapy". Strahlenther Onkol 2024; 200:1-18. [PMID: 38163834 PMCID: PMC10784363 DOI: 10.1007/s00066-023-02183-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 11/06/2023] [Indexed: 01/03/2024]
Abstract
Accurate Magnetic Resonance Imaging (MRI) simulation is fundamental for high-precision stereotactic radiosurgery and fractionated stereotactic radiotherapy, collectively referred to as stereotactic radiotherapy (SRT), to deliver doses of high biological effectiveness to well-defined cranial targets. Multiple MRI hardware related factors as well as scanner configuration and sequence protocol parameters can affect the imaging accuracy and need to be optimized for the special purpose of radiotherapy treatment planning. MRI simulation for SRT is possible for different organizational environments including patient referral for imaging as well as dedicated MRI simulation in the radiotherapy department but require radiotherapy-optimized MRI protocols and defined quality standards to ensure geometrically accurate images that form an impeccable foundation for treatment planning. For this guideline, an interdisciplinary panel including experts from the working group for radiosurgery and stereotactic radiotherapy of the German Society for Radiation Oncology (DEGRO), the working group for physics and technology in stereotactic radiotherapy of the German Society for Medical Physics (DGMP), the German Society of Neurosurgery (DGNC), the German Society of Neuroradiology (DGNR) and the German Chapter of the International Society for Magnetic Resonance in Medicine (DS-ISMRM) have defined minimum MRI quality requirements as well as advanced MRI simulation options for cranial SRT.
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Affiliation(s)
- Florian Putz
- Strahlenklinik, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
| | - Michael Bock
- Klinik für Radiologie-Medizinphysik, Universitätsklinikum Freiburg, Freiburg, Germany
| | - Daniela Schmitt
- Klinik für Strahlentherapie und Radioonkologie, Universitätsmedizin Göttingen, Göttingen, Germany
| | - Christoph Bert
- Strahlenklinik, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Oliver Blanck
- Klinik für Strahlentherapie, Universitätsklinikum Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Maximilian I Ruge
- Klinik für Stereotaxie und funktionelle Neurochirurgie, Zentrum für Neurochirurgie, Universitätsklinikum Köln, Cologne, Germany
| | - Elke Hattingen
- Institut für Neuroradiologie, Universitätsklinikum Frankfurt, Frankfurt am Main, Germany
| | - Christian P Karger
- Abteilung Medizinische Physik in der Strahlentherapie, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany
- Nationales Zentrum für Strahlenforschung in der Onkologie (NCRO), Heidelberger Institut für Radioonkologie (HIRO), Heidelberg, Germany
| | - Rainer Fietkau
- Strahlenklinik, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Johanna Grigo
- Strahlenklinik, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Manuel A Schmidt
- Neuroradiologisches Institut, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Tobias Bäuerle
- Radiologisches Institut, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Andrea Wittig
- Klinik und Poliklinik für Strahlentherapie und Radioonkologie, Universitätsklinikum Würzburg, Würzburg, Germany
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Koori N, Kamekawa H, Mukawa N, Fuse H, Miyakawa S, Yasue K, Takahashi M, Yamada M, Henmi A, Kusumoto T, Kurata K. Relationship between imaging parameters and distortion in magnetic resonance images for gamma knife treatment planning. J Appl Clin Med Phys 2023; 24:e14205. [PMID: 37975638 PMCID: PMC10691626 DOI: 10.1002/acm2.14205] [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: 07/04/2023] [Revised: 09/27/2023] [Accepted: 10/23/2023] [Indexed: 11/19/2023] Open
Abstract
In magnetic resonance imaging (MRI), it is necessary to reduce image distortion as much as possible because it suppresses the increase in the planning target volume. This study investigated the relationship between imaging parameters and image distortion when using G-frames. The images were obtained using a 1.5-T MRI system with a 09-101 Pro-MRI phantom. Image distortion was measured by changing the RF pulse mode, gradient mode, asymmetric echo, and bandwidth (BW). The image distortion was increased in the high RF mode than in the Normal mode. The image distortion increased in the following order: Whisper ≦ Normal < Fast in the different gradient modes. The image distortion increased in the following order: Without ≦ Weak < Strong in the different asymmetric echo modes. The image distortion increased in the following order: 300 Hz/pixel > 670 Hz/pixel ≧ REF (150 Hz/pixel) in the different Bw. The relationship between parameters and image distortion was clarified in this study when G-frames were used for gamma knife therapy. There is had relationship between the parameters causing variation in the gradient magnetic field and image distortion. Therefore, these parameters should be adjusted to minimize distortion.
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Affiliation(s)
- Norikazu Koori
- School of Health SciencesIbaraki Prefectural University of Health SciencesAmiIbarakiJapan
- Division of Health SciencesKanazawa University Graduate School of Medical SciencesKanazawaIshikawaJapan
| | | | - Nanami Mukawa
- School of Health SciencesIbaraki Prefectural University of Health SciencesAmiIbarakiJapan
| | - Hiraku Fuse
- School of Health SciencesIbaraki Prefectural University of Health SciencesAmiIbarakiJapan
| | - Shin Miyakawa
- School of Health SciencesIbaraki Prefectural University of Health SciencesAmiIbarakiJapan
| | - Kenji Yasue
- School of Health SciencesIbaraki Prefectural University of Health SciencesAmiIbarakiJapan
| | - Masato Takahashi
- School of Health SciencesIbaraki Prefectural University of Health SciencesAmiIbarakiJapan
| | | | - Atsushi Henmi
- Department of RadiologyKomaki City HospitalKomakiAichiJapan
| | | | - Kazuma Kurata
- Department of RadiologyKomaki City HospitalKomakiAichiJapan
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Hasler SW, Kallehauge JF, Hansen RH, Samsøe E, Arp DT, Nissen HD, Edmund JM, Bernchou U, Mahmood F. Geometric distortions in clinical MRI sequences for radiotherapy: insights gained from a multicenter investigation. Acta Oncol 2023; 62:1551-1560. [PMID: 37815867 DOI: 10.1080/0284186x.2023.2266560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 09/28/2023] [Indexed: 10/12/2023]
Abstract
BACKGROUND As magnetic resonance imaging (MRI) becomes increasingly integrated into radiotherapy (RT) for enhanced treatment planning and adaptation, the inherent geometric distortion in acquired MR images pose a potential challenge to treatment accuracy. This study aimed to evaluate the geometric distortion levels in the clinical MRI protocols used across Danish RT centers and discuss influence of specific sequence parameters. Based on the variety in geometric performance across centers, we assess if harmonization of MRI sequences is a relevant measure. MATERIALS AND METHODS Nine centers participated with 12 MRI scanners and MRI-Linacs (MRL). Using a travelling phantom approach, a reference MRI sequence was used to assess variation in baseline distortion level between scanners. The phantom was also scanned with local clinical MRI sequences for brain, head/neck (H/N), abdomen, and pelvis. The influence of echo time, receiver bandwidth, image weighting, and 2D/3D acquisition was investigated. RESULTS We found a large variation in geometric accuracy across 93 clinical sequences examined, exceeding the baseline variation found between MRI scanners (σ = 0.22 mm), except for abdominal sequences where the variation was lower. Brain and abdominal sequences showed lowest distortion levels ([0.22, 2.26] mm), and a large variation in performance was found for H/N and pelvic sequences ([0.19, 4.07] mm). Post hoc analyses revealed that distortion levels decreased with increasing bandwidth and a less clear increase in distortion levels with increasing echo time. 3D MRI sequences had lower distortion levels than 2D (median of 1.10 and 2.10 mm, respectively), and in DWI sequences, the echo-planar imaging read-out resulted in highest distortion levels. CONCLUSION There is a large variation in the geometric distortion levels of clinical MRI sequences across Danish RT centers, and between anatomical sites. The large variation observed makes harmonization of MRI sequences across institutions and adoption of practices from well-performing anatomical sites, a relevant measure within RT.
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Affiliation(s)
- Signe Winther Hasler
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Odense, Denmark
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Jesper Folsted Kallehauge
- Danish Centre for Particle Therapy, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Rasmus Hvass Hansen
- Section for Radiation Therapy, Department of Oncology, Center for Cancer and Organ Diseases, Copenhagen University Hospital, Copenhagen, Denmark
| | - Eva Samsøe
- Department of Clinical Oncology, Zealand University Hospital, Naestved, Denmark
| | - Dennis Tideman Arp
- Department of Medical Physics, Department of Oncology, Aalborg University Hospital, Aalborg, Denmark
| | - Henrik Dahl Nissen
- Department of Medical Physics, Vejle Hospital, University Hospital of Southern Denmark, Vejle, Denmark
| | - Jens M Edmund
- Radiotherapy Research Unit, Department of Oncology, Herlev and Gentofte Hospital, Herlev, Denmark
- Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
| | - Uffe Bernchou
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Odense, Denmark
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Faisal Mahmood
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Odense, Denmark
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
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Li T, Wang J, Yang Y, Glide-Hurst CK, Wen N, Cai J. Multi-parametric MRI for radiotherapy simulation. Med Phys 2023; 50:5273-5293. [PMID: 36710376 PMCID: PMC10382603 DOI: 10.1002/mp.16256] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 09/10/2022] [Accepted: 12/06/2022] [Indexed: 01/31/2023] Open
Abstract
Magnetic resonance imaging (MRI) has become an important imaging modality in the field of radiotherapy (RT) in the past decade, especially with the development of various novel MRI and image-guidance techniques. In this review article, we will describe recent developments and discuss the applications of multi-parametric MRI (mpMRI) in RT simulation. In this review, mpMRI refers to a general and loose definition which includes various multi-contrast MRI techniques. Specifically, we will focus on the implementation, challenges, and future directions of mpMRI techniques for RT simulation.
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Affiliation(s)
- Tian Li
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
| | - Jihong Wang
- Department of Radiation Physics, Division of Radiation Oncology, MD Anderson Cancer Center, Houston, Texas, USA
| | - Yingli Yang
- Department of Radiology, Ruijin Hospital, Shanghai Jiaotong Univeristy School of Medicine, Shanghai, China
- SJTU-Ruijing-UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Carri K Glide-Hurst
- Department of Radiation Oncology, University of Wisconsin, Madison, Wisconsin, USA
| | - Ning Wen
- Department of Radiology, Ruijin Hospital, Shanghai Jiaotong Univeristy School of Medicine, Shanghai, China
- SJTU-Ruijing-UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- The Global Institute of Future Technology, Shanghai Jiaotong University, Shanghai, China
| | - Jing Cai
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
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Dorsch S, Paul K, Beyer C, Karger CP, Jäkel O, Debus J, Klüter S. Quality assurance and temporal stability of a 1.5 T MRI scanner for MR-guided Photon and Particle Therapy. Z Med Phys 2023:S0939-3889(23)00046-6. [PMID: 37150727 DOI: 10.1016/j.zemedi.2023.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 03/12/2023] [Accepted: 04/04/2023] [Indexed: 05/09/2023]
Abstract
PURPOSE To describe performance measurements, adaptations and time stability over 20 months of a diagnostic MR scanner for integration into MR-guided photon and particle radiotherapy. MATERIAL AND METHODS For realization of MR-guided photon and particle therapy (MRgRT/MRgPT), a 1.5 T MR scanner was installed at the Heidelberg Ion Beam Therapy Center. To integrate MRI into the treatment process, a flat tabletop and dedicated coil holders for flex coils were used, which prevent deformation of the patient external contour and allow for the use of immobilization tools for reproducible positioning. The signal-to-noise ratio (SNR) was compared for the diagnostic and therapy-specific setup using the flat couch top and flexible coils for the a) head & neck and b) abdominal region as well as for different bandwidths and clinical pulse sequences. Additionally, a quality assurance (QA) protocol with monthly measurements of the ACR phantom and measurement of geometric distortions for a large field-of-view (FOV) was implemented to assess the imaging quality parameters of the device over the course of 20 months. RESULTS The SNR measurements showed a decreased SNR for the RT-specific as compared to the diagnostic setup of (a) 26% to 34% and (b) 11% to 33%. No significant bandwidth dependency for this ratio was found. The longitudinal assessment of the image quality parameters with the ACR and distortion phantom confirmed the long-term stability of the MRI device. CONCLUSION A diagnostic MRI was commissioned for use in MR-guided particle therapy. Using a radiotherapy specific setup, a high geometric accuracy and signal homogeneity was obtained after some adaptions and the measured parameters were shown to be stable over a period of 20 months.
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Affiliation(s)
- Stefan Dorsch
- Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), INF 280, 69120 Heidelberg, Germany; National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany; Department of Radiation Oncology, University Hospital Heidelberg, INF 400, 69120 Heidelberg, Germany.
| | - Katharina Paul
- National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany; Department of Radiation Oncology, University Hospital Heidelberg, INF 400, 69120 Heidelberg, Germany
| | - Cedric Beyer
- National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany; Department of Radiation Oncology, University Hospital Heidelberg, INF 400, 69120 Heidelberg, Germany
| | - Christian P Karger
- Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), INF 280, 69120 Heidelberg, Germany; National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany
| | - Oliver Jäkel
- Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), INF 280, 69120 Heidelberg, Germany; National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany; Heidelberg Ion-Beam Therapy Center (HIT), Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Jürgen Debus
- National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany; Department of Radiation Oncology, University Hospital Heidelberg, INF 400, 69120 Heidelberg, Germany; Heidelberg Ion-Beam Therapy Center (HIT), Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany; Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Core center Heidelberg, German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Sebastian Klüter
- National Center for Radiation Research in Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany; Department of Radiation Oncology, University Hospital Heidelberg, INF 400, 69120 Heidelberg, Germany.
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Haskell MW, Nielsen JF, Noll DC. Off-resonance artifact correction for MRI: A review. NMR IN BIOMEDICINE 2023; 36:e4867. [PMID: 36326709 PMCID: PMC10284460 DOI: 10.1002/nbm.4867] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 09/25/2022] [Accepted: 11/01/2022] [Indexed: 06/06/2023]
Abstract
In magnetic resonance imaging (MRI), inhomogeneity in the main magnetic field used for imaging, referred to as off-resonance, can lead to image artifacts ranging from mild to severe depending on the application. Off-resonance artifacts, such as signal loss, geometric distortions, and blurring, can compromise the clinical and scientific utility of MR images. In this review, we describe sources of off-resonance in MRI, how off-resonance affects images, and strategies to prevent and correct for off-resonance. Given recent advances and the great potential of low-field and/or portable MRI, we also highlight the advantages and challenges of imaging at low field with respect to off-resonance.
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Affiliation(s)
- Melissa W Haskell
- Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan, USA
- Hyperfine Research, Guilford, Connecticut, USA
| | | | - Douglas C Noll
- Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
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10
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Korte JC, Chin Z, Carr M, Holloway L, Franich R. Magnetic resonance biomarker assessment software (MR-BIAS): an automated open-source tool for the ISMRM/NIST system phantom. Phys Med Biol 2023; 68. [PMID: 36796102 DOI: 10.1088/1361-6560/acbcbb] [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: 11/10/2022] [Accepted: 02/16/2023] [Indexed: 02/18/2023]
Abstract
Objective.To provide an open-source software for repeatable and efficient quantification ofT1andT2relaxation times with the ISMRM/NIST system phantom. Quantitative magnetic resonance imaging (qMRI) biomarkers have the potential to improve disease detection, staging and monitoring of treatment response. Reference objects, such as the system phantom, play a major role in translating qMRI methods into the clinic. The currently available open-source software for ISMRM/NIST system phantom analysis, Phantom Viewer (PV), includes manual steps that are subject to variability.Approach.We developed the Magnetic Resonance BIomarker Assessment Software (MR-BIAS) to automatically extract system phantom relaxation times. The inter-observer variability (IOV) and time efficiency of MR-BIAS and PV was observed in six volunteers analysing three phantom datasets. The IOV was measured with the coefficient of variation (CV) of percent bias (%bias) inT1andT2with respect to NMR reference values. The accuracy of MR-BIAS was compared to a custom script from a published study of twelve phantom datasets. This included comparison of overall bias and %bias for variable inversion recovery (T1VIR), variable flip angle (T1VFA) and multiple spin-echo (T2MSE) relaxation models.Main results.MR-BIAS had a lower mean CV withT1VIR(0.03%) andT2MSE(0.05%) in comparison to PV withT1VIR(1.28%) andT2MSE(4.55%). The mean analysis duration was 9.7 times faster for MR-BIAS (0.8 min) than PV (7.6 min). There was no statistically significant difference in the overall bias, or the %bias for the majority of ROIs, as calculated by MR-BIAS or the custom script for all models.Significance.MR-BIAS has demonstrated repeatable and efficient analysis of the ISMRM/NIST system phantom, with comparable accuracy to previous studies. The software is freely available to the MRI community, providing a framework to automate required analysis tasks, with the flexibility to explore open questions and accelerate biomarker research.
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Affiliation(s)
- James C Korte
- Peter MacCallum Cancer Centre, Department of Physical Sciences, Melbourne, Australia.,The University of Melbourne, Department of Biomedical Engineering, Melbourne, Australia
| | - Zachary Chin
- RMIT University, School of Science, Melbourne, Australia
| | - Madeline Carr
- University of Wollongong, Centre for Medical Radiation Physics, Wollongong, Australia.,Liverpool and Macarthur Cancer Therapy Centres and Ingham Institute, Liverpool, Sydney, Australia.,GenesisCare, Sydney, New South Wales, Australia
| | - Lois Holloway
- University of Wollongong, Centre for Medical Radiation Physics, Wollongong, Australia.,Liverpool and Macarthur Cancer Therapy Centres and Ingham Institute, Liverpool, Sydney, Australia
| | - Rick Franich
- Peter MacCallum Cancer Centre, Department of Physical Sciences, Melbourne, Australia.,RMIT University, School of Science, Melbourne, Australia
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11
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De-Colle C, Kirby A, Russell N, Shaitelman S, Currey A, Donovan E, Hahn E, Han K, Anandadas C, Mahmood F, Lorenzen E, van den Bongard D, Groot Koerkamp M, Houweling A, Nachbar M, Thorwarth D, Zips D. Adaptive radiotherapy for breast cancer. Clin Transl Radiat Oncol 2023; 39:100564. [PMID: 36632056 PMCID: PMC9826896 DOI: 10.1016/j.ctro.2022.100564] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 12/07/2022] [Accepted: 12/14/2022] [Indexed: 12/24/2022] Open
Abstract
Research in the field of local and locoregional breast cancer radiotherapy aims to maintain excellent oncological outcomes while reducing treatment-related toxicity. Adaptive radiotherapy (ART) considers variations in target and organs at risk (OARs) anatomy occurring during the treatment course and integrates these in re-optimized treatment plans. Exploiting ART routinely in clinic may result in smaller target volumes and better OAR sparing, which may lead to reduction of acute as well as late toxicities. In this review MR-guided and CT-guided ART for breast cancer patients according to different clinical scenarios (neoadjuvant and adjuvant partial breast irradiation, whole breast, chest wall and regional nodal irradiation) are reviewed and their advantages as well as challenging aspects discussed.
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Affiliation(s)
- C. De-Colle
- Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Tübingen, Germany
| | - A. Kirby
- Department of Radiotherapy, Royal Marsden NHS Foundation Trust and Institute of Cancer Research, Sutton, United Kingdom
| | - N. Russell
- Department of Radiotherapy, The Netherlands Cancer Institute–Antoni van Leeuwenhoek Hospital, Amsterdam, Netherlands
| | - S.F. Shaitelman
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - A. Currey
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - E. Donovan
- Department of Radiation Oncology, Odette Cancer Centre - Sunnybrook Health Sciences Centre, Toronto, Canada
| | - E. Hahn
- Department of Radiation Oncology, Princess Margaret Cancer Centre, Toronto, Canada
| | - K. Han
- Department of Radiation Oncology, Princess Margaret Cancer Centre, Toronto, Canada
| | - C.N. Anandadas
- Department of Clinical Oncology, The Christie NHS Foundation Trust, Manchester, United Kingdom
| | - F. Mahmood
- Department of Oncology, Odense University Hospital, Odense, Denmark
| | - E.L. Lorenzen
- Department of Oncology, Odense University Hospital, Odense, Denmark
| | | | - M.L. Groot Koerkamp
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, Netherlands
| | - A.C. Houweling
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, Netherlands
| | - M. Nachbar
- Section for Biomedical Physics, Department of Radiation Oncology. University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Tübingen, Germany
| | - D. Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology. University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Tübingen, Germany
- German Cancer Consortium (DKTK), partner site Tübingen; and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - D. Zips
- Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Tübingen, Germany
- German Cancer Consortium (DKTK), partner site Tübingen; and German Cancer Research Center (DKFZ), Heidelberg, Germany
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12
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Moore-Palhares D, Ho L, Lu L, Chugh B, Vesprini D, Karam I, Soliman H, Symons S, Leung E, Loblaw A, Myrehaug S, Stanisz G, Sahgal A, Czarnota GJ. Clinical implementation of magnetic resonance imaging simulation for radiation oncology planning: 5 year experience. Radiat Oncol 2023; 18:27. [PMID: 36750891 PMCID: PMC9903411 DOI: 10.1186/s13014-023-02209-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Accepted: 01/16/2023] [Indexed: 02/09/2023] Open
Abstract
PURPOSE Integrating magnetic resonance (MR) into radiotherapy planning has several advantages. This report details the clinical implementation of an MR simulation (MR-planning) program for external beam radiotherapy (EBRT) in one of North America's largest radiotherapy programs. METHODS AND MATERIALS An MR radiotherapy planning program was developed and implemented at Sunnybrook Health Sciences Center in 2016 with two dedicated wide-bore MR platforms (1.5 and 3.0 Tesla). Planning MR was sequentially implemented every 3 months for separate treatment sites, including the central nervous system (CNS), gynecologic (GYN), head and neck (HN), genitourinary (GU), gastrointestinal (GI), breast, and brachial plexus. Essential protocols and processes were detailed in this report, including clinical workflow, optimized MR-image acquisition protocols, MR-adapted patient setup, strategies to overcome risks and challenges, and an MR-planning quality assurance program. This study retrospectively reviewed simulation site data for all MR-planning sessions performed for EBRT over the past 5 years. RESULTS From July 2016 to December 2021, 8798 MR-planning sessions were carried out, which corresponds to 25% of all computer tomography (CT) simulations (CT-planning) performed during the same period at our institution. There was a progressive rise from 80 MR-planning sessions in 2016 to 1126 in 2017, 1492 in 2018, 1824 in 2019, 2040 in 2020, and 2236 in 2021. As a result, the relative number of planning MR/CT increased from 3% of all planning sessions in 2016 to 36% in 2021. The most common site of MR-planning was CNS (49%), HN (13%), GYN (12%), GU (12%), and others (8%). CONCLUSION Detailed clinical processes and protocols of our MR-planning program were presented, which have been improved over more than 5 years of robust experience. Strategies to overcome risks and challenges in the implementation process are highlighted. Our work provides details that can be used by institutions interested in implementing an MR-planning program.
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Affiliation(s)
- Daniel Moore-Palhares
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada ,grid.17063.330000 0001 2157 2938Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
| | - Ling Ho
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada
| | - Lin Lu
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada
| | - Brige Chugh
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada ,grid.17063.330000 0001 2157 2938Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
| | - Danny Vesprini
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Irene Karam
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Hany Soliman
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Sean Symons
- grid.17063.330000 0001 2157 2938Physical Sciences, Sunnybrook Research Institute, Toronto, Canada ,grid.413104.30000 0000 9743 1587Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Eric Leung
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Andrew Loblaw
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Sten Myrehaug
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Greg Stanisz
- grid.17063.330000 0001 2157 2938Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
| | - Arjun Sahgal
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada
| | - Gregory J. Czarnota
- grid.413104.30000 0000 9743 1587Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, T2, Toronto, ON M4N3M5 Canada ,grid.17063.330000 0001 2157 2938Department of Radiation Oncology, University of Toronto, Toronto, Canada ,grid.17063.330000 0001 2157 2938Physical Sciences, Sunnybrook Research Institute, Toronto, Canada ,grid.17063.330000 0001 2157 2938Department of Medical Biophysics, University of Toronto, Toronto, Canada
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13
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Goodburn RJ, Philippens MEP, Lefebvre TL, Khalifa A, Bruijnen T, Freedman JN, Waddington DEJ, Younus E, Aliotta E, Meliadò G, Stanescu T, Bano W, Fatemi‐Ardekani A, Wetscherek A, Oelfke U, van den Berg N, Mason RP, van Houdt PJ, Balter JM, Gurney‐Champion OJ. The future of MRI in radiation therapy: Challenges and opportunities for the MR community. Magn Reson Med 2022; 88:2592-2608. [PMID: 36128894 PMCID: PMC9529952 DOI: 10.1002/mrm.29450] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 08/17/2022] [Accepted: 08/22/2022] [Indexed: 01/11/2023]
Abstract
Radiation therapy is a major component of cancer treatment pathways worldwide. The main aim of this treatment is to achieve tumor control through the delivery of ionizing radiation while preserving healthy tissues for minimal radiation toxicity. Because radiation therapy relies on accurate localization of the target and surrounding tissues, imaging plays a crucial role throughout the treatment chain. In the treatment planning phase, radiological images are essential for defining target volumes and organs-at-risk, as well as providing elemental composition (e.g., electron density) information for radiation dose calculations. At treatment, onboard imaging informs patient setup and could be used to guide radiation dose placement for sites affected by motion. Imaging is also an important tool for treatment response assessment and treatment plan adaptation. MRI, with its excellent soft tissue contrast and capacity to probe functional tissue properties, holds great untapped potential for transforming treatment paradigms in radiation therapy. The MR in Radiation Therapy ISMRM Study Group was established to provide a forum within the MR community to discuss the unmet needs and fuel opportunities for further advancement of MRI for radiation therapy applications. During the summer of 2021, the study group organized its first virtual workshop, attended by a diverse international group of clinicians, scientists, and clinical physicists, to explore our predictions for the future of MRI in radiation therapy for the next 25 years. This article reviews the main findings from the event and considers the opportunities and challenges of reaching our vision for the future in this expanding field.
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Affiliation(s)
- Rosie J. Goodburn
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | | | - Thierry L. Lefebvre
- Department of PhysicsUniversity of CambridgeCambridgeUnited Kingdom
- Cancer Research UK Cambridge Research InstituteUniversity of CambridgeCambridgeUnited Kingdom
| | - Aly Khalifa
- Department of Medical BiophysicsUniversity of TorontoTorontoOntarioCanada
| | - Tom Bruijnen
- Department of RadiotherapyUniversity Medical Center UtrechtUtrechtNetherlands
| | | | - David E. J. Waddington
- Faculty of Medicine and Health, Sydney School of Health Sciences, ACRF Image X InstituteThe University of SydneySydneyNew South WalesAustralia
| | - Eyesha Younus
- Department of Medical Physics, Odette Cancer CentreSunnybrook Health Sciences CentreTorontoOntarioCanada
| | - Eric Aliotta
- Department of Medical PhysicsMemorial Sloan Kettering Cancer CenterNew YorkNew YorkUSA
| | - Gabriele Meliadò
- Unità Operativa Complessa di Fisica SanitariaAzienda Ospedaliera Universitaria Integrata VeronaVeronaItaly
| | - Teo Stanescu
- Department of Radiation Oncology, University of Toronto and Medical Physics, Princess Margaret Cancer CentreUniversity Health NetworkTorontoOntarioCanada
| | - Wajiha Bano
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | - Ali Fatemi‐Ardekani
- Department of PhysicsJackson State University (JSU)JacksonMississippiUSA
- SpinTecxJacksonMississippiUSA
- Department of Radiation OncologyCommunity Health Systems (CHS) Cancer NetworkJacksonMississippiUSA
| | - Andreas Wetscherek
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | - Uwe Oelfke
- Joint Department of PhysicsInstitute of Cancer Research and Royal Marsden NHS Foundation TrustLondonUnited Kingdom
| | - Nico van den Berg
- Department of RadiotherapyUniversity Medical Center UtrechtUtrechtNetherlands
| | - Ralph P. Mason
- Department of RadiologyUniversity of Texas Southwestern Medical CenterDallasTexasUSA
| | - Petra J. van Houdt
- Department of Radiation OncologyNetherlands Cancer InstituteAmsterdamNetherlands
| | - James M. Balter
- Department of Radiation OncologyUniversity of MichiganAnn ArborMichiganUSA
| | - Oliver J. Gurney‐Champion
- Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam UMCUniversity of AmsterdamAmsterdamNetherlands
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14
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Manson EN, Inkoom S, Mumuni AN. Impact of Magnetic Field Inhomogeneity on the Quality of Magnetic Resonance Images and Compensation Techniques: A Review. REPORTS IN MEDICAL IMAGING 2022. [DOI: 10.2147/rmi.s369491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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15
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Nousiainen K, Mäkelä T, Peltonen JI. Characterizing geometric distortions of 3D sequences in clinical head MRI. MAGNETIC RESONANCE MATERIALS IN PHYSICS, BIOLOGY AND MEDICINE 2022; 35:983-995. [PMID: 35657535 PMCID: PMC9596562 DOI: 10.1007/s10334-022-01020-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 04/20/2022] [Accepted: 05/12/2022] [Indexed: 11/25/2022]
Abstract
Objective Phantoms are often used to estimate the geometric accuracy in magnetic resonance imaging (MRI). However, the distortions may differ between anatomical and phantom images. This study aimed to investigate the applicability of a phantom-based and a test-subject-based method in evaluating geometric distortion present in clinical head-imaging sequences. Materials and methods We imaged a 3D-printed phantom and test subjects with two MRI scanners using two clinical head-imaging 3D sequences with varying patient-table positions and receiver bandwidths. The geometric distortions were evaluated through nonrigid registrations: the displaced acquisitions were compared against the ideal isocenter positioning, and the varied bandwidth volumes against the volume with the highest bandwidth. The phantom acquisitions were also registered to a computed tomography scan. Results Geometric distortion magnitudes increased with larger table displacements and were in good agreement between the phantom and test-subject acquisitions. The effect of increased distortions with decreasing receiver bandwidth was more prominent for test-subject acquisitions. Conclusion Presented results emphasize the sensitivity of the geometric accuracy to positioning and imaging parameters. Phantom limitations may become an issue with some sequence types, encouraging the use of anatomical images for evaluating the geometric accuracy.
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Affiliation(s)
- Katri Nousiainen
- HUS Medical Imaging Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.
- Department of Physics, University of Helsinki, Helsinki, Finland.
| | - Teemu Mäkelä
- HUS Medical Imaging Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
- Department of Physics, University of Helsinki, Helsinki, Finland
| | - Juha I Peltonen
- HUS Medical Imaging Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
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16
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Rees J, Abrar R, Stapleton E. A comparison of imaging techniques to measure skin flap thickness in cochlear implant patients to enable pre-operative device selection. Cochlear Implants Int 2022; 23:179-188. [PMID: 35236259 DOI: 10.1080/14670100.2022.2045074] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
OBJECTIVES Magnetic resonance imaging (MRI)-compatible cochlear implants have weaker internal magnets than non-MRI-compatible devices. Their suitability for individual patients is limited by skin flap thickness, traditionally measured with a needle in the operating theatre. We aimed to establish the accuracy of imaging modalities to measure skin flap thickness pre-operatively, with the goal of streamlining device selection and simplifying the consent process. METHODS Skin flap measurements were taken using ultrasound (US), computed tomography (CT) and MRI and compared for agreement with intra-operative needle measurement. RESULTS Twenty-seven skin flaps were included. Absolute agreement between needle and imaging methods was low: needle/US: 44.4% (95% confidence interval [CI]: 27.7-62.7), needle/CT: 39.1% (95% CI: 22.2-59.2), needle/MRI: 20.8% (95% CI: 9.2-40.5). However, US and CT showed 95.7% agreement (95% CI: 76.0-99.8) with intraclass correlation of 0.996 (95% CI: 0.991-0.998) and narrow Bland-Altman limits of agreement (-0.37, 0.45 mm). BMI and skin flap thickness showed a significant positive correlation (rs = 0.664, P = 0.002) but no significant correlation was observed for age (P = 0.659). DISCUSSION The high level of agreement between US and CT suggests that there are more accurate measurements of skin flap thickness compared with needle or MRI. Needle measurements are consistently smaller. CONCLUSION The use of CT or US should be considered when making pre-operative device choices.
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Affiliation(s)
- Jacob Rees
- Manchester Academic Health Science Centre, The Richard Ramsden Centre for Hearing Implants, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Rohma Abrar
- Manchester Academic Health Science Centre, The Richard Ramsden Centre for Hearing Implants, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Emma Stapleton
- Manchester Academic Health Science Centre, The Richard Ramsden Centre for Hearing Implants, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
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17
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Yuan J, Poon DMC, Lo G, Wong OL, Cheung KY, Yu SK. A narrative review of MRI acquisition for MR-guided-radiotherapy in prostate cancer. Quant Imaging Med Surg 2022; 12:1585-1607. [PMID: 35111651 PMCID: PMC8739116 DOI: 10.21037/qims-21-697] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 08/20/2021] [Indexed: 08/24/2023]
Abstract
Magnetic resonance guided radiotherapy (MRgRT), enabled by the clinical introduction of the integrated MRI and linear accelerator (MR-LINAC), is a novel technique for prostate cancer (PCa) treatment, promising to further improve clinical outcome and reduce toxicity. The role of prostate MRI has been greatly expanded from the traditional PCa diagnosis to also PCa screening, treatment and surveillance. Diagnostic prostate MRI has been relatively familiar in the community, particularly with the development of Prostate Imaging - Reporting and Data System (PI-RADS). But, on the other hand, the use of MRI in the emerging clinical practice of PCa MRgRT, which is substantially different from that in PCa diagnosis, has been so far sparsely presented in the medical literature. This review attempts to give a comprehensive overview of MRI acquisition techniques currently used in the clinical workflows of PCa MRgRT, from treatment planning to online treatment guidance, in order to promote MRI practice and research for PCa MRgRT. In particular, the major differences in the MRI acquisition of PCa MRgRT from that of diagnostic prostate MRI are demonstrated and explained. Limitations in the current MRI acquisition for PCa MRgRT are analyzed. The future developments of MRI in the PCa MRgRT are also discussed.
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Affiliation(s)
- Jing Yuan
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Darren M. C. Poon
- Comprehensive Oncology Centre, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Gladys Lo
- Department of Diagnostic & Interventional Radiology, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Oi Lei Wong
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Kin Yin Cheung
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Siu Ki Yu
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
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18
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Florkow MC, Willemsen K, Mascarenhas VV, Oei EHG, van Stralen M, Seevinck PR. Magnetic Resonance Imaging Versus Computed Tomography for Three-Dimensional Bone Imaging of Musculoskeletal Pathologies: A Review. J Magn Reson Imaging 2022; 56:11-34. [PMID: 35044717 PMCID: PMC9305220 DOI: 10.1002/jmri.28067] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 12/31/2021] [Accepted: 01/05/2022] [Indexed: 12/18/2022] Open
Abstract
Magnetic resonance imaging (MRI) is increasingly utilized as a radiation‐free alternative to computed tomography (CT) for the diagnosis and treatment planning of musculoskeletal pathologies. MR imaging of hard tissues such as cortical bone remains challenging due to their low proton density and short transverse relaxation times, rendering bone tissues as nonspecific low signal structures on MR images obtained from most sequences. Developments in MR image acquisition and post‐processing have opened the path for enhanced MR‐based bone visualization aiming to provide a CT‐like contrast and, as such, ease clinical interpretation. The purpose of this review is to provide an overview of studies comparing MR and CT imaging for diagnostic and treatment planning purposes in orthopedic care, with a special focus on selective bone visualization, bone segmentation, and three‐dimensional (3D) modeling. This review discusses conventional gradient‐echo derived techniques as well as dedicated short echo time acquisition techniques and post‐processing techniques, including the generation of synthetic CT, in the context of 3D and specific bone visualization. Based on the reviewed literature, it may be concluded that the recent developments in MRI‐based bone visualization are promising. MRI alone provides valuable information on both bone and soft tissues for a broad range of applications including diagnostics, 3D modeling, and treatment planning in multiple anatomical regions, including the skull, spine, shoulder, pelvis, and long bones.
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Affiliation(s)
- Mateusz C Florkow
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Koen Willemsen
- Department of Orthopedics, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Vasco V Mascarenhas
- Musculoskeletal Imaging Unit, Imaging Center, Hospital da Luz, Lisbon, Portugal
| | - Edwin H G Oei
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Marijn van Stralen
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands.,MRIguidance BV, Utrecht, The Netherlands
| | - Peter R Seevinck
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands.,MRIguidance BV, Utrecht, The Netherlands
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19
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Law MWL, Yuan J, Wong OL, Ying AD, Zhou Y, Cheung KY, Yu SK. Phantom assessment of three-dimensional geometric distortion of a dedicated wide-bore MR-simulator for radiotherapy. Biomed Phys Eng Express 2021; 8. [PMID: 34874313 DOI: 10.1088/2057-1976/ac3f4f] [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: 07/20/2021] [Accepted: 12/02/2021] [Indexed: 11/11/2022]
Abstract
This study evaluated the machine-dependent three-dimensional geometric distortion images acquired from a 1.5T 700mm-wide bore MR-simulator based on a large geometric accuracy phantom. With the consideration of radiation therapy (RT) application requirements, every sequence was examined in various combinations of acquisition-orientations and receiver-bandwidths with console-integrated distortion correction enabled. Distortion was repeatedly measured over a six-month period. The distortion measured from the images acquired at the beginning of this period was employed to retrospectively correct the distortion in the subsequent acquisitions. Geometric distortion was analyzed within the largest field-of-view allowed. Six sequences were examined for comprehensive distortion analysis - VIBE, SPACE, TSE, FLASH, BLADE and PETRA. Based on optimal acquisition parameters, their diameter-sphere-volumes (DSVs) of CT-comparable geometric fidelity (where 1mm distortion was allowed) were 333.6mm, 315.1mm, 316.0mm, 318.9mm, 306.2mm and 314.5mm respectively. This was a significant increase from 254.0mm, 245.5mm, 228.9mm, 256.6mm, 230.8mm and 254.2mm DSVs respectively, when images were acquired using un-optimized parameters. The longitudinal stability of geometric distortion and the efficacy of retrospective correction of console-corrected images, based on prior distortion measurements, were inspected using VIBE and SPACE. The retrospectively corrected images achieved over 500mm DSVs with 1mm distortion allowed. The median distortion was below 1mm after retrospective correction, proving that obtaining prior distortion map for subsequent retrospective distortion correction is beneficial. The systematic evaluation of distortion using various combinations of sequence-type, acquisition-orientation and receiver-bandwidth in a six-month time span would be a valuable guideline for optimizing sequence for various RT applications.
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Affiliation(s)
- Max W L Law
- Medical Physics Department, Hong Kong Sanatorium and Hospital, 2nd Village Road, Happy Valley, Hong Kong Island, Hong Kong, 000, HONG KONG
| | - Jing Yuan
- Research Department, Hong Kong Sanatorium and Hospital, 2nd Village Road, Happy Valley, Hong Kong Island, Hong Kong, 000, HONG KONG
| | - Oi Lei Wong
- Research Department, Hong Kong Sanatorium and Hospital, 2nd Village Road, Happy Valley, Hong Kong Island, Hong Kong, NA, 000, HONG KONG
| | - Abby D Ying
- Medical Physics Department, Hong Kong Sanatorium and Hospital, Hong Kong Sanatorium and Hospital, Hong Kong, HONG KONG
| | - Yihang Zhou
- Research Department, Hong Kong Sanatorium and Hospital, 2nd Village Road, Happy Valley, Hong Kong Island, Hong Kong, 000, HONG KONG
| | - Kin Yin Cheung
- Medical Physics Department, Hong Kong Sanatorium and Hospital, 2nd Village Road, Happy Valley, Hong Kong Island, Hong Kong, 000, HONG KONG
| | - Siu Ki Yu
- Medical Physics Department, Hong Kong Sanatorium and Hospital, 2nd Village Road, Happy Valley, Hong Kong Island, Hong Kong, 000, HONG KONG
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20
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Torfeh T, Hammoud R, Paloor S, Arunachalam Y, Aouadi S, Al-Hammadi N. Design and construction of a customizable phantom for the characterization of the three-dimensional magnetic resonance imaging geometric distortion. J Appl Clin Med Phys 2021; 22:149-157. [PMID: 34719100 PMCID: PMC8664142 DOI: 10.1002/acm2.13462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Revised: 09/27/2021] [Accepted: 10/17/2021] [Indexed: 11/11/2022] Open
Abstract
One of the main challenges to using magnetic resonance imaging (MRI) in radiotherapy is the existence of system‐related geometric inaccuracies caused mainly by the inhomogeneity in the main magnetic field and the nonlinearities of the gradient coils. Several physical phantoms, with fixed configuration, have been developed and commercialized for the assessment of the MRI geometric distortion. In this study, we propose a new design of a customizable phantom that can fit any type of radio frequency (RF) coil. It is composed of 3D printed plastic blocks containing holes that can hold glass tubes which can be filled with any liquid. The blocks can be assembled to construct phantoms with any dimension. The feasibility of this design has been demonstrated by assembling four phantoms with high robustness allowing the assessment of the geometric distortion for the GE split head coil, the head and neck array coil, the anterior array coil, and the body coil. Phantom reproducibility was evaluated by analyzing the geometric distortion on CT acquisition of five independent assemblages of the phantom. This solution meets all expectations in terms of having a robust, lightweight, modular, and practical tool for measuring distortion in three dimensions. Mean error in the position of the tubes was less than 0.2 mm. For the geometric distortion, our results showed that for all typical MRI sequences used for radiotherapy, the mean geometric distortion was less than 1 mm and less than 2.5 mm over radial distances of 150 mm and 250 mm, respectively. These tools will be part of a quality assurance program aimed at monitoring the image quality of MRI scanners used to guide radiation therapy.
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Affiliation(s)
- Tarraf Torfeh
- Department of Radiation Oncology, National Center for Cancer Care and Research (NCCCR), Hamad Medical Corporation, Doha, Qatar
| | - Rabih Hammoud
- Department of Radiation Oncology, National Center for Cancer Care and Research (NCCCR), Hamad Medical Corporation, Doha, Qatar
| | - Satheesh Paloor
- Department of Radiation Oncology, National Center for Cancer Care and Research (NCCCR), Hamad Medical Corporation, Doha, Qatar
| | - Yoganathan Arunachalam
- Department of Radiation Oncology, National Center for Cancer Care and Research (NCCCR), Hamad Medical Corporation, Doha, Qatar
| | - Souha Aouadi
- Department of Radiation Oncology, National Center for Cancer Care and Research (NCCCR), Hamad Medical Corporation, Doha, Qatar
| | - Noora Al-Hammadi
- Department of Radiation Oncology, National Center for Cancer Care and Research (NCCCR), Hamad Medical Corporation, Doha, Qatar
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21
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The rationale for MR-only delineation and planning: retrospective CT–MR registration and target volume analysis for prostate radiotherapy. JOURNAL OF RADIOTHERAPY IN PRACTICE 2021. [DOI: 10.1017/s1460396920000230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
AbstractAim:Magnetic resonance imaging (MRI) is indispensable for treatment planning in prostate radiotherapy (PR). Registration of MRI when compared to planning CT (pCT) is prone to uncertainty and this is rarely reported. In this study, we have compared three different types of registration methods to justify the direct use of MRI in PR.Methods and materials:Thirty patients treated for PR were retrospectively selected for this study and all underwent both CT and MRI. The MR scans were registered to the pCT using markers, focused and unfocussed methods and their registration are REGM, REGF, and REGNF, respectively. Registration comparison is done using the translational differences of three axes from the centre-of-mass values of gross tumour volume (GTV) generated using MRI.Results:The average difference in all three axes (x, y, z) is (1, 2·5, 2·3 mm) and (1, 3, 2·3 mm) for REGF-REFNF and REGF-REGM, respectively. MR-based GTV Volume is less in comparison to CT-based GTV and it is significantly different (p < 0·001).Findings:Image registration uncertainty is unavoidable for a regular CT–MR workflow. Additional planning target volume margin ranging from 2 to 3mm could be avoided if MR-only workflow is employed. This reduction in the margin is beneficial for small tumours treated with hypofractionation.
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22
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Yuan J, Law SCK, Wong KK, Lo GG, Kam MKM, Kwan WH, Xue C, Wong OL, Yu SK, Cheung KY. 3D T1-weighted turbo spin echo contrast-enhanced MRI at 1.5 T for frameless brain metastases radiotherapy. J Cancer Res Clin Oncol 2021; 148:1749-1759. [PMID: 34363123 DOI: 10.1007/s00432-021-03755-8] [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: 06/03/2021] [Accepted: 07/31/2021] [Indexed: 11/27/2022]
Abstract
PURPOSE Performance of 3D-T1W-TSE has been proven superior to 3D-MP-GRE at 3 T on brain metastases (BM) contrast-enhanced (CE) MRI. However, its performance at 1.5 T is largely unknown and sparsely reported. This study aims to assess image quality, lesion detectability and conspicuity of 1.5 T 3D-T1W-TSE on planning MRI of frameless BM radiotherapy. METHODS 94 BM patients to be treated by frameless brain radiotherapy were scanned using 3D-T1W-TSE with immobilization on multi-vendor 1.5 T MRI-simulators. BMs were jointly diagnosed by 4 reviewers. Enhanced lesion conspicuity was quantitatively assessed by calculating contrast ratio (CR) and contrast-to-noise ratio (CNR). Signal-to-noise ratio (SNR) reduction of white matter due to the use of flexible coil was assessed. Lesion detectability and conspicuity were compared between 1.5 T planning MRI and 3 T diagnostic MRI by an oncologist and a radiologist in 10 patients. RESULTS 497 BMs were jointly diagnosed. The CR and CNR were 75.2 ± 39.9% and 14.2 ± 8.1, respectively. SNR reduced considerably from 31.7 ± 8.3 to 21.9 ± 5.4 with the longer distance to coils. 3 T diagnostic MRI and 1.5 T planning MRI yielded exactly the same detection of 84 BMs. Qualitatively, lesion conspicuity at 1.5 T was not inferior to that at 3 T. Quantitatively, lower brain SNR and lesion CNR were found at 1.5 T, while lesion CR at 1.5 T was highly comparable to that at 3 T. CONCLUSION 1.5 T 3D-T1W-TSE planning MRI of frameless BM radiotherapy was comprehensively assessed. Highly comparable BM detectability and conspicuity were achieved by 1.5 T planning MRI compared to 3 T diagnostic MRI. 1.5 T 3D-T1W-TSE should be valuable for frameless brain radiotherapy planning.
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Affiliation(s)
- Jing Yuan
- Medical Physics and Research Department, Hong Kong Sanatorium and Hospital, 8/F, Li Shu Fan Block, 2 Village Road, Happy Valley, Hong Kong SAR, China.
| | - Stephen C K Law
- Comprehensive Oncology Centre, Hong Kong Sanatorium and Hospital, Happy Valley, Hong Kong SAR, China
| | - Ka Kin Wong
- Department of Diagnostic and Interventional Radiology, Hong Kong Sanatorium and Hospital, Happy Valley, Hong Kong SAR, China
| | - Gladys G Lo
- Department of Diagnostic and Interventional Radiology, Hong Kong Sanatorium and Hospital, Happy Valley, Hong Kong SAR, China
| | - Michael K M Kam
- Comprehensive Oncology Centre, Hong Kong Sanatorium and Hospital, Happy Valley, Hong Kong SAR, China
| | - Wing Hong Kwan
- Comprehensive Oncology Centre, Hong Kong Sanatorium and Hospital, Happy Valley, Hong Kong SAR, China
| | - Cindy Xue
- Medical Physics and Research Department, Hong Kong Sanatorium and Hospital, 8/F, Li Shu Fan Block, 2 Village Road, Happy Valley, Hong Kong SAR, China
| | - Oi Lei Wong
- Medical Physics and Research Department, Hong Kong Sanatorium and Hospital, 8/F, Li Shu Fan Block, 2 Village Road, Happy Valley, Hong Kong SAR, China
| | - Siu Ki Yu
- Medical Physics and Research Department, Hong Kong Sanatorium and Hospital, 8/F, Li Shu Fan Block, 2 Village Road, Happy Valley, Hong Kong SAR, China
| | - Kin Yin Cheung
- Medical Physics and Research Department, Hong Kong Sanatorium and Hospital, 8/F, Li Shu Fan Block, 2 Village Road, Happy Valley, Hong Kong SAR, China
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23
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Ahangari S, Hansen NL, Olin AB, Nøttrup TJ, Ryssel H, Berthelsen AK, Löfgren J, Loft A, Vogelius IR, Schnack T, Jakoby B, Kjaer A, Andersen FL, Fischer BM, Hansen AE. Toward PET/MRI as one-stop shop for radiotherapy planning in cervical cancer patients. Acta Oncol 2021; 60:1045-1053. [PMID: 34107847 DOI: 10.1080/0284186x.2021.1936164] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
BACKGROUND Radiotherapy (RT) planning for cervical cancer patients entails the acquisition of both Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Further, molecular imaging by Positron Emission Tomography (PET) could contribute to target volume delineation as well as treatment response monitoring. The objective of this study was to investigate the feasibility of a PET/MRI-only RT planning workflow of patients with cervical cancer. This includes attenuation correction (AC) of MRI hardware and dedicated positioning equipment as well as evaluating MRI-derived synthetic CT (sCT) of the pelvic region for positioning verification and dose calculation to enable a PET/MRI-only setup. MATERIAL AND METHODS 16 patients underwent PET/MRI using a dedicated RT setup after the routine CT (or PET/CT), including eight pilot patients and eight cervical cancer patients who were subsequently referred for RT. Data from 18 patients with gynecological cancer were added for training a deep convolutional neural network to generate sCT from Dixon MRI. The mean absolute difference between the dose distributions calculated on sCT and a reference CT was measured in the RT target volume and organs at risk. PET AC by sCT and a reference CT were compared in the tumor volume. RESULTS All patients completed the examination. sCT was inferred for each patient in less than 5 s. The dosimetric analysis of the sCT-based dose planning showed a mean absolute error (MAE) of 0.17 ± 0.12 Gy inside the planning target volumes (PTV). PET images reconstructed with sCT and CT had no significant difference in quantification for all patients. CONCLUSIONS These results suggest that multiparametric PET/MRI can be successfully integrated as a one-stop-shop in the RT workflow of patients with cervical cancer.
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Affiliation(s)
- Sahar Ahangari
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Naja Liv Hansen
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Anders Beck Olin
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Trine Jakobi Nøttrup
- Department of Oncology, Section of Radiotherapy, University of Copenhagen, Rigshospitalet, Denmark
| | - Heidi Ryssel
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Anne Kiil Berthelsen
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Johan Löfgren
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Annika Loft
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Ivan Richter Vogelius
- Department of Oncology, Section of Radiotherapy, University of Copenhagen, Rigshospitalet, Denmark
| | - Tine Schnack
- Department of Gynecology, University of Copenhagen, Copenhagen, Denmark
- Department of Gynecology and Obstetrics, Odense University Hospital, Odense, Denmark
| | | | - Andreas Kjaer
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- Cluster for Molecular Imaging, University of Copenhagen, Copenhagen, Denmark
| | - Flemming Littrup Andersen
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Barbara Malene Fischer
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- The PET Centre, School of Biomedical Engineering and Imaging Sciences, Kings College London, St Thomas’ Hospital, London, UK
| | - Adam Espe Hansen
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Diagnostic Radiology, Rigshospitalet, University of Copenhagen, Denmark Copenhagen
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24
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Glide-Hurst CK, Paulson ES, McGee K, Tyagi N, Hu Y, Balter J, Bayouth J. Task group 284 report: magnetic resonance imaging simulation in radiotherapy: considerations for clinical implementation, optimization, and quality assurance. Med Phys 2021; 48:e636-e670. [PMID: 33386620 DOI: 10.1002/mp.14695] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 12/12/2020] [Accepted: 12/16/2020] [Indexed: 12/18/2022] Open
Abstract
The use of dedicated magnetic resonance simulation (MR-SIM) platforms in Radiation Oncology has expanded rapidly, introducing new equipment and functionality with the overall goal of improving the accuracy of radiation treatment planning. However, this emerging technology presents a new set of challenges that need to be addressed for safe and effective MR-SIM implementation. The major objectives of this report are to provide recommendations for commercially available MR simulators, including initial equipment selection, siting, acceptance testing, quality assurance, optimization of dedicated radiation therapy specific MR-SIM workflows, patient-specific considerations, safety, and staffing. Major contributions include guidance on motion and distortion management as well as MRI coil configurations to accommodate patients immobilized in the treatment position. Examples of optimized protocols and checklists for QA programs are provided. While the recommendations provided here are minimum requirements, emerging areas and unmet needs are also highlighted for future development.
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Affiliation(s)
- Carri K Glide-Hurst
- Department of Human Oncology, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | - Eric S Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Kiaran McGee
- Department of Diagnostic Radiology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Neelam Tyagi
- Medical Physics Department, Memorial Sloan-Kettering Cancer Center, New York, NY, 10065, USA
| | - Yanle Hu
- Department of Radiation Oncology, Mayo Clinic, Phoenix, Arizona, 85054, USA
| | - James Balter
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - John Bayouth
- Department of Human Oncology, University of Wisconsin-Madison, Madison, WI, 53792, USA
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25
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Neylon J, Cook KA, Yang Y, Du D, Sheng K, Chin RK, Kishan AU, Lamb JM, Low DA, Cao M. Clinical assessment of geometric distortion for a 0.35T MR-guided radiotherapy system. J Appl Clin Med Phys 2021; 22:303-309. [PMID: 34231963 PMCID: PMC8364259 DOI: 10.1002/acm2.13340] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Purpose To estimate the overall spatial distortion on clinical patient images for a 0.35 T MR‐guided radiotherapy system. Methods Ten patients with head‐and‐neck cancer underwent CT and MR simulations with identical immobilization. The MR images underwent the standard systematic distortion correction post‐processing. The images were rigidly registered and landmark‐based analysis was performed by an anatomical expert. Distortion was quantified using Euclidean distance between each landmark pair and tagged by tissue interface: bone‐tissue, soft tissue, or air‐tissue. For baseline comparisons, an anthropomorphic phantom was imaged and analyzed. Results The average spatial discrepancy between CT and MR landmarks was 1.15 ± 1.14 mm for the phantom and 1.46 ± 1.78 mm for patients. The error histogram peaked at 0–1 mm. 66% of the discrepancies were <2 mm and 51% <1 mm. In the patient data, statistically significant differences (p‐values < 0.0001) were found between the different tissue interfaces with averages of 0.88 ± 1.24 mm, 2.01 ± 2.20 mm, and 1.41 ± 1.56 mm for the air/tissue, bone/tissue, and soft tissue, respectively. The distortion generally correlated with the in‐plane radial distance from the image center along the longitudinal axis of the MR. Conclusion Spatial distortion remains in the MR images after systematic distortion corrections. Although the average errors were relatively small, large distortions observed at bone/tissue interfaces emphasize the need for quantitative methods for assessing and correcting patient‐specific spatial distortions.
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Affiliation(s)
- John Neylon
- Department of Radiation Oncology, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
| | - Kiri A Cook
- Department of Radiation Medicine, Oregon Health & Science University, Oregon, Portland, OR, USA
| | - Yingli Yang
- Department of Radiation Oncology, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
| | - Dongsu Du
- Department of Radiation Oncology, City of Hope Cancer Center, Los Angeles, CA, USA
| | - Ke Sheng
- Department of Radiation Oncology, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
| | - Robert K Chin
- Department of Radiation Oncology, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
| | - Amar U Kishan
- Department of Radiation Oncology, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
| | - James M Lamb
- Department of Radiation Oncology, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
| | - Daniel A Low
- Department of Radiation Oncology, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
| | - Minsong Cao
- Department of Radiation Oncology, University of California, Los Angeles (UCLA), Los Angeles, CA, USA
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26
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Caballero D, Pérez-Palacios T, Caro A, Ávila M, Antequera T. Optimization of the image acquisition procedure in low-field MRI for non-destructive analysis of loin using predictive models. PeerJ Comput Sci 2021; 7:e583. [PMID: 34179451 PMCID: PMC8205300 DOI: 10.7717/peerj-cs.583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 05/17/2021] [Indexed: 06/13/2023]
Abstract
The use of low-field magnetic resonance imaging (LF-MRI) scanners has increased in recent years. The low economic cost in comparison to high-field (HF-MRI) scanners and the ease of maintenance make this type of scanner the best choice for nonmedical purposes. However, LF-MRI scanners produce low-quality images, which encourages the identification of optimization procedures to generate the best possible images. In this paper, optimization of the image acquisition procedure for an LF-MRI scanner is presented, and predictive models are developed. The MRI acquisition procedure was optimized to determine the physicochemical characteristics of pork loin in a nondestructive way using MRI, feature extraction algorithms and data processing methods. The most critical parameters (relaxation times, repetition time, and echo time) of the LF-MRI scanner were optimized, presenting a procedure that could be easily reproduced in other environments or for other purposes. In addition, two feature extraction algorithms (gray level co-occurrence matrix (GLCM) and one point fractal texture algorithm (OPFTA)) were evaluated. The optimization procedure was validated by using several evaluation metrics, achieving reliable and accurate results (r > 0.85; weighted absolute percentage error (WAPE) lower than 0.1%; root mean square error of prediction (RMSEP) lower than 0.1%; true standard deviation (TSTD) lower than 2; and mean absolute error (MAE) lower than 2). These results support the high degree of feasibility and accuracy of the optimized procedure of LF-MRI acquisition. No other papers present a procedure to optimize the image acquisition process in LF-MRI. Eventually, the optimization procedure could be applied to other LF-MRI systems.
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Affiliation(s)
- Daniel Caballero
- Department of Computer Systems and Telematics Engineering, University of Extremadura, Caceres, Spain
- Faculty of Sciences and University of Copenhagen, Copenhagen, Denmark
| | | | - Andrés Caro
- Department of Computer Systems and Telematics Engineering, University of Extremadura, Caceres, Spain
| | - Mar Ávila
- Department of Computer Systems and Telematics Engineering, University of Extremadura, Caceres, Spain
| | - Teresa Antequera
- Food Technology Department and University of Extremadura, Caceres, Spain
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27
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Shan S, Li M, Li M, Tang F, Crozier S, Liu F. ReUINet: A fast GNL distortion correction approach on a 1.0 T MRI-Linac scanner. Med Phys 2021; 48:2991-3002. [PMID: 33763850 DOI: 10.1002/mp.14861] [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: 11/25/2020] [Revised: 03/17/2021] [Accepted: 03/19/2021] [Indexed: 11/12/2022] Open
Abstract
PURPOSE The hybrid system combining a magnetic resonance imaging (MRI) scanner with a linear accelerator (Linac) has become increasingly desirable for tumor treatment because of excellent soft tissue contrast and nonionizing radiation. However, image distortions caused by gradient nonlinearity (GNL) can have detrimental impacts on real-time radiotherapy using MRI-Linac systems, where accurate geometric information of tumors is essential. METHODS In this work, we proposed a deep convolutional neural network-based method to efficiently recover undistorted images (ReUINet) for real-time image guidance. The ReUINet, based on the encoder-decoder structure, was created to learn the relationship between the undistorted images and distorted images. The ReUINet was pretrained and tested on a publically available brain MR image dataset acquired from 23 volunteers. Then, transfer learning was adopted to implement the pretrained model (i.e., network with optimal weights) on the experimental three-dimensional (3D) grid phantom and in-vivo pelvis image datasets acquired from the 1.0 T Australian MRI-Linac system. RESULTS Evaluations on the phantom (768 slices) and pelvis data (88 slices) showed that the ReUINet achieved improvement over 15 times and 45 times on computational efficiency in comparison with standard interpolation and GNL-encoding methods, respectively. Moreover, qualitative and quantitative results demonstrated that the ReUINet provided better correction results than the standard interpolation method, and comparable performance compared to the GNL-encoding approach. CONCLUSIONS Validated by simulation and experimental results, the proposed ReUINet showed promise in obtaining accurate MR images for the implementation of real-time MRI-guided radiotherapy.
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Affiliation(s)
- Shanshan Shan
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia.,ACRF Image X Institute, School of Health Sciences, University of Sydney, Sydney, Australia
| | - Mao Li
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
| | - Mingyan Li
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
| | - Fangfang Tang
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
| | - Stuart Crozier
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
| | - Feng Liu
- School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
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28
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Groot Koerkamp ML, de Hond YJM, Maspero M, Kontaxis C, Mandija S, Vasmel JE, Charaghvandi RK, Philippens MEP, van Asselen B, van den Bongard HJGD, Hackett SS, Houweling AC. Synthetic CT for single-fraction neoadjuvant partial breast irradiation on an MRI-linac. Phys Med Biol 2021; 66. [PMID: 33761491 DOI: 10.1088/1361-6560/abf1ba] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 03/24/2021] [Indexed: 01/08/2023]
Abstract
A synthetic computed tomography (sCT) is required for daily plan optimization on an MRI-linac. Yet, only limited information is available on the accuracy of dose calculations on sCT for breast radiotherapy. This work aimed to (1) evaluate dosimetric accuracy of treatment plans for single-fraction neoadjuvant partial breast irradiation (PBI) on a 1.5 T MRI-linac calculated on a) bulk-density sCT mimicking the current MRI-linac workflow and b) deep learning-generated sCT, and (2) investigate the number of bulk-density levels required. For ten breast cancer patients we created three bulk-density sCTs of increasing complexity from the planning-CT, using bulk-density for: (1) body, lungs, and GTV (sCTBD1); (2) volumes for sCTBD1plus chest wall and ipsilateral breast (sCTBD2); (3) volumes for sCTBD2plus ribs (sCTBD3); and a deep learning-generated sCT (sCTDL) from a 1.5 T MRI in supine position. Single-fraction neoadjuvant PBI treatment plans for a 1.5 T MRI-linac were optimized on each sCT and recalculated on the planning-CT. Image evaluation was performed by assessing mean absolute error (MAE) and mean error (ME) in Hounsfield Units (HU) between the sCTs and the planning-CT. Dosimetric evaluation was performed by assessing dose differences, gamma pass rates, and dose-volume histogram (DVH) differences. The following results were obtained (median across patients for sCTBD1/sCTBD2/sCTBD3/sCTDLrespectively): MAE inside the body contour was 106/104/104/75 HU and ME was 8/9/6/28 HU, mean dose difference in the PTVGTVwas 0.15/0.00/0.00/-0.07 Gy, median gamma pass rate (2%/2 mm, 10% dose threshold) was 98.9/98.9/98.7/99.4%, and differences in DVH parameters were well below 2% for all structures except for the skin in the sCTDL. Accurate dose calculations for single-fraction neoadjuvant PBI on an MRI-linac could be performed on both bulk-density and deep learning sCT, facilitating further implementation of MRI-guided radiotherapy for breast cancer. Balancing simplicity and accuracy, sCTBD2showed the optimal number of bulk-density levels for a bulk-density approach.
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Affiliation(s)
- M L Groot Koerkamp
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Y J M de Hond
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.,Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - M Maspero
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.,Computational Imaging Group for MR diagnostics & therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - C Kontaxis
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - S Mandija
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.,Computational Imaging Group for MR diagnostics & therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - J E Vasmel
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - R K Charaghvandi
- Department of Radiation Oncology, Radboudumc, Nijmegen, The Netherlands
| | - M E P Philippens
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - B van Asselen
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | - S S Hackett
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - A C Houweling
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
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Wyatt JJ, Pearson RA, Walker CP, Brooks RL, Pilling K, McCallum HM. Cone beam computed tomography for dose calculation quality assurance for magnetic resonance-only radiotherapy. PHYSICS & IMAGING IN RADIATION ONCOLOGY 2021; 17:71-76. [PMID: 33898782 PMCID: PMC8058023 DOI: 10.1016/j.phro.2021.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 01/19/2021] [Accepted: 01/20/2021] [Indexed: 11/08/2022]
Abstract
Clinical Magnetic Resonance (MR)-only radiotherapy requires a dose quality assurance method. Doses calculated on Cone Beam Computed Tomography (CBCT) were within 2% of MR-only doses calculated using synthetic CT. CBCT with asymmetric dose difference tolerances of [−2%,1%] appears clinically feasible for quality assurance of prostate MR-only radiotherapy.
Background and purpose Magnetic Resonance (MR)-only prostate radiotherapy using synthetic Computed Tomography (sCT) algorithms with high dose accuracy has been clinically implemented. MR images can suffer from geometric distortions so Quality Assurance (QA) using an independent, geometrically accurate, image could be required. The first-fraction Cone Beam CT (CBCT) has demonstrated potential but has not been evaluated in a clinical MR-only pathway. This study evaluated the clinical use of CBCT for dose accuracy QA of MR-only radiotherapy. Materials and methods A total of 49 patients treated with MR-only prostate radiotherapy were divided into two cohorts. Cohort 1 (20 patients) received a back-up CT, whilst Cohort 2 (29 patients) did not. All patients were planned using the sCT and received daily CBCT imaging with MR-CBCT soft-tissue matching. Each CBCT was calibrated using a patient-specific stepwise Hounsfield Units-to-mass density curve. The treatment plan was recalculated on the first-fraction CBCT using the clinically applied soft-tissue match and the doses compared. For Cohort 1 the sCT was rigidly registered to the back-up CT, the plan recalculated and doses compared. Results Mean sCT-CBCT dose difference across both cohorts was -0.6±0.1% (standard error of the mean, range −2.3%,2.3%), with 47/49 patients within [-2%,1%]. The sCT-CBCT dose difference was systematically lower than the sCT-CT by -0.7±0.6% (±95% limits of agreement). The mean sCT-CBCT gamma pass rate (2%/2mm) was 96.1±0.4% (85.4%,99.7%). Conclusions CBCT-based dose accuracy QA for MR-only radiotherapy appears clinically feasible. There was a small systematic sCT-CBCT dose difference implying asymmetric tolerances of [-2%,1%] would be appropriate.
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Affiliation(s)
- Jonathan J Wyatt
- Northern Centre for Cancer Care, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle, UK.,Centre for Cancer, Newcastle University, Newcastle, UK
| | - Rachel A Pearson
- Northern Centre for Cancer Care, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle, UK.,Centre for Cancer, Newcastle University, Newcastle, UK
| | - Christopher P Walker
- Northern Centre for Cancer Care, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle, UK
| | - Rachel L Brooks
- Northern Centre for Cancer Care, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle, UK
| | - Karen Pilling
- Northern Centre for Cancer Care, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle, UK
| | - Hazel M McCallum
- Northern Centre for Cancer Care, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle, UK.,Centre for Cancer, Newcastle University, Newcastle, UK
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Evaluation of the influence of susceptibility-induced magnetic field distortions on the precision of contouring intracranial organs at risk for stereotactic radiosurgery. Phys Imaging Radiat Oncol 2021; 15:91-97. [PMID: 33458332 PMCID: PMC7807629 DOI: 10.1016/j.phro.2020.08.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 07/31/2020] [Accepted: 08/03/2020] [Indexed: 11/23/2022] Open
Abstract
45 data sets (18 on a 1.5 T MR and 27 on a 3 T MR) were evaluated for susceptibility induced distortions. Maximum distortions of up to 1.7 mm were found for organs at risk in standard diagnostic settings. Median distortions ranged between 0.1 and 0.2 mm for all organs at risk. Active shimming was estimated to reduce distortions by a factor of 2.3 to 2.9. A safety margin of 1 mm would have encompassed 99.8% of the distortions.
Background and purpose Magnetic resonance imaging (MRI) is a crucial factor in optimal treatment planning for stereotactic radiosurgery. To further the awareness of possible errors in MRI, this work aimed to investigate the magnitude of susceptibility induced MRI distortions for intracranial organs at risk (OARs) and test the effectiveness of actively shimming these distortions. Materials and methods Distortion maps for 45 exams of 42 patients (18 on a 1.5 T MRI scanner, 27 on a 3 T MRI scanner) were calculated based on a high-bandwidth double-echo gradient echo sequence. The investigated OARs were brainstem, chiasm, eyes, and optic nerves. The influence of active shimming was investigated by comparing unshimmed 1.5 T data with shimmed 3 T data and comparing the results to a model based prediction. Results The median distortion for the different OARs was found to be between 0.13 and 0.18 mm for 1.5 T and between 0.11 and 0.13 mm for 3 T. The maximum distortion was found to be between 1.3 and 1.7 mm for 1.5 T and between 1.1 and 1.4 mm for 3 T. The variation of values was much higher for 1.5 T than for 3 T across all investigated OARs. Active shimming was found to reduce distortions by a factor of 2.3 to 2.9 compared to the expected values. Conclusions Using a safety margin for OARs of 1 mm would have encompassed 99.8% of the distortions. Since distortions are inversely proportional to the readout bandwidth, they can be further reduced by increasing the bandwidth. Additional error sources like gradient nonlinearities need to be addressed separately.
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Baydoun A, Xu KE, Heo JU, Yang H, Zhou F, Bethell LA, Fredman ET, Ellis RJ, Podder TK, Traughber MS, Paspulati RM, Qian P, Traughber BJ, Muzic RF. Synthetic CT Generation of the Pelvis in Patients With Cervical Cancer: A Single Input Approach Using Generative Adversarial Network. IEEE ACCESS : PRACTICAL INNOVATIONS, OPEN SOLUTIONS 2021; 9:17208-17221. [PMID: 33747682 PMCID: PMC7978399 DOI: 10.1109/access.2021.3049781] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Multi-modality imaging constitutes a foundation of precision medicine, especially in oncology where reliable and rapid imaging techniques are needed in order to insure adequate diagnosis and treatment. In cervical cancer, precision oncology requires the acquisition of 18F-labeled 2-fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET), magnetic resonance (MR), and computed tomography (CT) images. Thereafter, images are co-registered to derive electron density attributes required for FDG-PET attenuation correction and radiation therapy planning. Nevertheless, this traditional approach is subject to MR-CT registration defects, expands treatment expenses, and increases the patient's radiation exposure. To overcome these disadvantages, we propose a new framework for cross-modality image synthesis which we apply on MR-CT image translation for cervical cancer diagnosis and treatment. The framework is based on a conditional generative adversarial network (cGAN) and illustrates a novel tactic that addresses, simplistically but efficiently, the paradigm of vanishing gradient vs. feature extraction in deep learning. Its contributions are summarized as follows: 1) The approach -termed sU-cGAN-uses, for the first time, a shallow U-Net (sU-Net) with an encoder/decoder depth of 2 as generator; 2) sU-cGAN's input is the same MR sequence that is used for radiological diagnosis, i.e. T2-weighted, Turbo Spin Echo Single Shot (TSE-SSH) MR images; 3) Despite limited training data and a single input channel approach, sU-cGAN outperforms other state of the art deep learning methods and enables accurate synthetic CT (sCT) generation. In conclusion, the suggested framework should be studied further in the clinical settings. Moreover, the sU-Net model is worth exploring in other computer vision tasks.
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Affiliation(s)
- Atallah Baydoun
- Department of Radiation Oncology, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA
| | - K E Xu
- School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, China
- Jiangsu Key Laboratory of Media Design and Software Technology, Jiangnan University, Wuxi 214122, China
| | - Jin Uk Heo
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
- Department of Radiology, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Huan Yang
- School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, China
- Jiangsu Key Laboratory of Media Design and Software Technology, Jiangnan University, Wuxi 214122, China
| | - Feifei Zhou
- Department of Radiology, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Latoya A Bethell
- Department of Radiology, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Elisha T Fredman
- Department of Radiation Oncology, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Rodney J Ellis
- Department of Radiation Oncology, Penn State Cancer Institute, Hershey, PA 17033, USA
| | - Tarun K Podder
- Department of Radiation Oncology, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA
- Department of Radiation Oncology, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
| | | | - Raj M Paspulati
- Department of Radiology, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA
| | - Pengjiang Qian
- School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, China
- Jiangsu Key Laboratory of Media Design and Software Technology, Jiangnan University, Wuxi 214122, China
| | - Bryan J Traughber
- Department of Radiation Oncology, Penn State Cancer Institute, Hershey, PA 17033, USA
| | - Raymond F Muzic
- Department of Radiology, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA
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Buckley JG, Dong B, Liney GP. Imaging performance of a high-field in-line magnetic resonance imaging linear accelerator with a patient rotation system for fixed-gantry radiotherapy. PHYSICS & IMAGING IN RADIATION ONCOLOGY 2020; 16:130-133. [PMID: 33458355 PMCID: PMC7807630 DOI: 10.1016/j.phro.2020.11.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 11/05/2020] [Accepted: 11/05/2020] [Indexed: 02/06/2023]
Abstract
This paper describes the imaging performance of a high-field in-line MRI linear accelerator with a patient rotation system in-situ. Signal quality was quantified using signal-to-noise ratio (SNR) and RF uniformity maps. B0-field inhomogeneity was assessed using magnetic field mapping. SNR was evaluated with various entries into the Faraday cage which were required for extended couch translations. SNR varied between 103 and 87 across PRS rotation angles. Maximum B0-field inhomogeneity corresponded to 0.7 mm of geometric distortion. A 45 × 55 cm2 aperture allowed PRS translation with no reduction in SNR. Imaging performance with the PRS in-situ was found to be acceptable.
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Affiliation(s)
- Jarryd G Buckley
- Centre for Medical Radiation Physics, University of Wollongong, Northfields Avenue, Wollongong, NSW 2522, Australia.,Ingham Institute for Applied Medical Research, 1 Campbell St, Liverpool, NSW 2170, Australia
| | - Bin Dong
- Ingham Institute for Applied Medical Research, 1 Campbell St, Liverpool, NSW 2170, Australia.,Liverpool and Macarthur Cancer Therapy Centre, Liverpool Hospital, 75 Elizabeth St, Liverpool, NSW 2170, Australia
| | - Gary P Liney
- Ingham Institute for Applied Medical Research, 1 Campbell St, Liverpool, NSW 2170, Australia.,Liverpool and Macarthur Cancer Therapy Centre, Liverpool Hospital, 75 Elizabeth St, Liverpool, NSW 2170, Australia
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Dumlu HS, Meschini G, Kurz C, Kamp F, Baroni G, Belka C, Paganelli C, Riboldi M. Dosimetric impact of geometric distortions in an MRI-only proton therapy workflow for lung, liver and pancreas. Z Med Phys 2020; 32:85-97. [PMID: 33168274 PMCID: PMC9948883 DOI: 10.1016/j.zemedi.2020.10.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 09/02/2020] [Accepted: 10/01/2020] [Indexed: 12/25/2022]
Abstract
In a radiation therapy workflow based on Magnetic Resonance Imaging (MRI), dosimetric errors may arise due to geometric distortions introduced by MRI. The aim of this study was to quantify the dosimetric effect of system-dependent geometric distortions in an MRI-only workflow for proton therapy applied at extra-cranial sites. An approach was developed, in which computed tomography (CT) images were distorted using an MRI displacement map, which represented the MR distortions in a spoiled gradient-echo sequence due to gradient nonlinearities and static magnetic field inhomogeneities. A retrospective study was conducted on 4DCT/MRI digital phantoms and 18 4DCT clinical datasets of the thoraco-abdominal site. The treatment plans were designed and separately optimized for each beam in a beam specific Planning Target Volume on the distorted CT, and the final dose distribution was obtained as the average. The dose was then recalculated in undistorted CT using the same beam geometry and beam weights. The analysis was performed in terms of Dose Volume Histogram (DVH) parameters. No clinically relevant dosimetric impact was observed on organs at risk, whereas in the target structure, geometric distortions caused statistically significant variations in the planned dose DVH parameters and dose homogeneity index (DHI). The dosimetric variations in the target structure were smaller in abdominal cases (ΔD2%, ΔD98%, and ΔDmean all below 0.1% and ΔDHI below 0.003) compared to the lung cases. Indeed, lung patients with tumors isolated inside lung parenchyma exhibited higher dosimetric variations (ΔD2%≥0.3%, ΔD98%≥15.9%, ΔDmean≥3.3% and ΔDHI≥0.102) than lung patients with tumor close to soft tissue (ΔD2%≤0.4%, ΔD98%≤5.6%, ΔDmean≤0.9% and ΔDHI≤0.027) potentially due to higher density variations along the beam path. Results suggest the potential applicability of MRI-only proton therapy, provided that specific analysis is applied for isolated lung tumors.
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Affiliation(s)
- Hatice Selcen Dumlu
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Via Ponzio 34/5, 20133 Milano, Italy; Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, 85748 Garching bei München, Germany
| | - Giorgia Meschini
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Via Ponzio 34/5, 20133 Milano, Italy
| | - Christopher Kurz
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistraße 15, 81377 München, Germany
| | - Florian Kamp
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistraße 15, 81377 München, Germany
| | - Guido Baroni
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Via Ponzio 34/5, 20133 Milano, Italy; Centro Nazionale di Adroterapia Oncologica, Strada Campeggi 53, 27100 Pavia, Italy
| | - Claus Belka
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistraße 15, 81377 München, Germany; German Cancer Consortium (DKTK) partner site Munich, Germany and German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
| | - Chiara Paganelli
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Via Ponzio 34/5, 20133 Milano, Italy
| | - Marco Riboldi
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, 85748 Garching bei München, Germany.
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Implementation of a dedicated 1.5 T MR scanner for radiotherapy treatment planning featuring a novel high-channel coil setup for brain imaging in treatment position. Strahlenther Onkol 2020; 197:246-256. [PMID: 33103231 PMCID: PMC7892740 DOI: 10.1007/s00066-020-01703-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 09/29/2020] [Indexed: 12/17/2022]
Abstract
Purpose To share our experiences in implementing a dedicated magnetic resonance (MR) scanner for radiotherapy (RT) treatment planning using a novel coil setup for brain imaging in treatment position as well as to present developed core protocols with sequences specifically tuned for brain and prostate RT treatment planning. Materials and methods Our novel setup consists of two large 18-channel flexible coils and a specifically designed wooden mask holder mounted on a flat tabletop overlay, which allows patients to be measured in treatment position with mask immobilization. The signal-to-noise ratio (SNR) of this setup was compared to the vendor-provided flexible coil RT setup and the standard setup for diagnostic radiology. The occurrence of motion artifacts was quantified. To develop magnetic resonance imaging (MRI) protocols, we formulated site- and disease-specific clinical objectives. Results Our novel setup showed mean SNR of 163 ± 28 anteriorly, 104 ± 23 centrally, and 78 ± 14 posteriorly compared to 84 ± 8 and 102 ± 22 anteriorly, 68 ± 6 and 95 ± 20 centrally, and 56 ± 7 and 119 ± 23 posteriorly for the vendor-provided and diagnostic setup, respectively. All differences were significant (p > 0.05). Image quality of our novel setup was judged suitable for contouring by expert-based assessment. Motion artifacts were found in 8/60 patients in the diagnostic setup, whereas none were found for patients in the RT setup. Site-specific core protocols were designed to minimize distortions while optimizing tissue contrast and 3D resolution according to indication-specific objectives. Conclusion We present a novel setup for high-quality imaging in treatment position that allows use of several immobilization systems enabling MR-only workflows, which could reduce unnecessary dose and registration inaccuracies. Electronic supplementary material The online version of this article (10.1007/s00066-020-01703-y) contains supplementary material, which is available to authorized users.
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Yahanda AT, Goble TJ, Sylvester PT, Lessman G, Goddard S, McCollough B, Shah A, Andrews T, Benzinger TLS, Chicoine MR. Impact of 3-Dimensional Versus 2-Dimensional Image Distortion Correction on Stereotactic Neurosurgical Navigation Image Fusion Reliability for Images Acquired With Intraoperative Magnetic Resonance Imaging. Oper Neurosurg (Hagerstown) 2020; 19:599-607. [PMID: 32521010 DOI: 10.1093/ons/opaa152] [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: 01/16/2020] [Accepted: 03/30/2020] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Fusion of preoperative and intraoperative magnetic resonance imaging (iMRI) studies during stereotactic navigation may be very useful for procedures such as tumor resections but can be subject to error because of image distortion. OBJECTIVE To assess the impact of 3-dimensional (3D) vs 2-dimensional (2D) image distortion correction on the accuracy of auto-merge image fusion for stereotactic neurosurgical images acquired with iMRI using a head phantom in different surgical positions. METHODS T1-weighted intraoperative images of the head phantom were obtained using 1.5T iMRI. Images were postprocessed with 2D and 3D image distortion correction. These studies were fused to T1-weighted preoperative MRI studies performed on a 1.5T diagnostic MRI. The reliability of the auto-merge fusion of these images for 2D and 3D correction techniques was assessed both manually using the stereotactic navigation system and via image analysis software. RESULTS Eight surgical positions of the head phantom were imaged with iMRI. Greater image distortion occurred with increased distance from isocenter in all 3 axes, reducing accuracy of image fusion to preoperative images. Visually reliable image fusions were accomplished in 2/8 surgical positions using 2D distortion correction and 5/8 using 3D correction. Three-dimensional correction yielded superior image registration quality as defined by higher maximum mutual information values, with improvements ranging between 2.3% and 14.3% over 2D correction. CONCLUSION Using 3D distortion correction enhanced the reliability of surgical navigation auto-merge fusion of phantom images acquired with iMRI across a wider range of head positions and may improve the accuracy of stereotactic navigation using iMRI images.
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Affiliation(s)
- Alexander T Yahanda
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri
| | | | - Peter T Sylvester
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri
| | | | | | | | - Amar Shah
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri
| | - Trevor Andrews
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Tammie L S Benzinger
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri.,Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Michael R Chicoine
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, Missouri
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36
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Li M, Shan S, Chandra SS, Liu F, Crozier S. Fast geometric distortion correction using a deep neural network: Implementation for the 1 Tesla MRI‐Linac system. Med Phys 2020; 47:4303-4315. [DOI: 10.1002/mp.14382] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 06/18/2020] [Accepted: 07/04/2020] [Indexed: 11/08/2022] Open
Affiliation(s)
- Mao Li
- School of Information Technology and Electrical Engineering University of Queensland Brisbane QLD 4067 Australia
| | - Shanshan Shan
- School of Information Technology and Electrical Engineering University of Queensland Brisbane QLD 4067 Australia
| | - Shekhar S. Chandra
- School of Information Technology and Electrical Engineering University of Queensland Brisbane QLD 4067 Australia
| | - Feng Liu
- School of Information Technology and Electrical Engineering University of Queensland Brisbane QLD 4067 Australia
| | - Stuart Crozier
- School of Information Technology and Electrical Engineering University of Queensland Brisbane QLD 4067 Australia
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Groot Koerkamp ML, Vasmel JE, Russell NS, Shaitelman SF, Anandadas CN, Currey A, Vesprini D, Keller BM, De-Colle C, Han K, Braunstein LZ, Mahmood F, Lorenzen EL, Philippens MEP, Verkooijen HM, Lagendijk JJW, Houweling AC, van den Bongard HJGD, Kirby AM. Optimizing MR-Guided Radiotherapy for Breast Cancer Patients. Front Oncol 2020; 10:1107. [PMID: 32850318 PMCID: PMC7399349 DOI: 10.3389/fonc.2020.01107] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Accepted: 06/03/2020] [Indexed: 01/01/2023] Open
Abstract
Current research in radiotherapy (RT) for breast cancer is evaluating neoadjuvant as opposed to adjuvant partial breast irradiation (PBI) with the aim of reducing the volume of breast tissue irradiated and therefore the risk of late treatment-related toxicity. The development of magnetic resonance (MR)-guided RT, including dedicated MR-guided RT systems [hybrid machines combining an MR scanner with a linear accelerator (MR-linac) or 60Co sources], could potentially reduce the irradiated volume even further by improving tumour visibility before and during each RT treatment. In this position paper, we discuss MR guidance in relation to each step of the breast RT planning and treatment pathway, focusing on the application of MR-guided RT to neoadjuvant PBI.
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Affiliation(s)
| | - Jeanine E. Vasmel
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Nicola S. Russell
- Department of Radiotherapy, The Netherlands Cancer Institute–Antoni van Leeuwenhoek Hospital, Amsterdam, Netherlands
| | - Simona F. Shaitelman
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Carmel N. Anandadas
- Department of Clinical Oncology, The Christie NHS Foundation Trust, Manchester, United Kingdom
| | - Adam Currey
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Danny Vesprini
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Brian M. Keller
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Chiara De-Colle
- Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Kathy Han
- Department of Radiation Oncology, Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Lior Z. Braunstein
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Faisal Mahmood
- Department of Oncology, Odense University Hospital, Odense, Denmark
- Research Unit for Oncology, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Ebbe L. Lorenzen
- Department of Oncology, Odense University Hospital, Odense, Denmark
| | | | | | - Jan J. W. Lagendijk
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Antonetta C. Houweling
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, Netherlands
| | | | - Anna M. Kirby
- Department of Radiotherapy, Royal Marsden NHS Foundation Trust and Institute of Cancer Research, Sutton, United Kingdom
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Ahmadian S, Jabbari I, Bagherimofidi SM, Saligheh Rad H. Characterization of hardware-related spatial distortions for IR-PETRA pulse sequence using a brain specific phantom. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2020; 34:213-228. [PMID: 32632747 DOI: 10.1007/s10334-020-00863-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Revised: 06/22/2020] [Accepted: 06/24/2020] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Inversion recovery-pointwise encoding time reduction with radial acquisition (IR-PETRA) is an effective magnetic resonance (MR) pulse sequence in generating pseudo-CTs. The hardware-related spatial-distortion (HRSD) in MR images potentially deteriorates the accuracy of pseudo-CTs. Thus, we aimed at characterizing HRSD for IR-PETRA. MATERIALS AND METHODS gross-HRSDoverall (Euclidean-sum of gross-HRSDi (i = x, y, z)) for IR-PETRA was assessed using a brain-specific phantom for two MR scanners (1.5 T-Aera and 3.0 T-Prisma). Moreover, hardware imperfections were analyzed by determining gradient-nonlinearity spatial-distortion (GNSD) and B0-inhomogeneity spatial-distortion (B0ISD) for magnetization-prepared rapid acquisition gradient-echo (MP-RAGE) which has well-known distortion characteristics. RESULTS In 3.0 T, maximum of gross-GNSDoverall (Euclidean-sum of gross-GNSDi) and gross-B0ISD for MP-RAGE was 2.77 mm and 0.57 mm, respectively. For this scanner, the mean and maximum of gross-HRSDoverall for IR-PETRA were 0.63 ± 0.38 mm and 1.91 mm, respectively. In 1.5 T, maximum of gross-GNSDoverall and gross-B0ISD for MP-RAGE was 3.41 mm and 0.78 mm, respectively. The mean and maximum of gross-HRSDoverall for IR-PETRA were 1.02 ± 0.50 mm and 3.12 mm, respectively. DISCUSSION The spatial accuracy of MR images, besides being impacted by hardware performance, scanner capabilities, and imaging parameters, is mainly affected by its imaging strategy and data acquisition scheme. In 3.0 T, even without applying vendor correction algorithms, spatial accuracy of IR-PETRA image is sufficient for generating pseudo-CTs. In 1.5 T, distortion-correction is required to provide this accuracy.
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Affiliation(s)
- Sima Ahmadian
- Faculty of Advanced Sciences and Technologies, University of Isfahan, Isfahan, Iran
| | - Iraj Jabbari
- Faculty of Advanced Sciences and Technologies, University of Isfahan, Isfahan, Iran.
| | - Seyed Mehdi Bagherimofidi
- Department of Biomedical Engineering, Aliabad Katoul Branch, Islamic Azad University, Aliabad-e-Katoul, Iran
| | - Hamidreza Saligheh Rad
- Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran
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39
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Head-and-Neck MRI-only radiotherapy treatment planning: From acquisition in treatment position to pseudo-CT generation. Cancer Radiother 2020; 24:288-297. [DOI: 10.1016/j.canrad.2020.01.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Revised: 01/08/2020] [Accepted: 01/15/2020] [Indexed: 12/25/2022]
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40
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Alzahrani M, Broadbent DA, Chuter R, Al-Qaisieh B, Jackson S, Michael H, Johnstone RI, Shah S, Wetscherek A, Chick HJ, Wyatt JJ, McCallum HM, Speight R. Audit feasibility for geometric distortion in magnetic resonance imaging for radiotherapy. Phys Imaging Radiat Oncol 2020; 15:80-84. [PMID: 33163632 PMCID: PMC7607582 DOI: 10.1016/j.phro.2020.07.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Revised: 06/27/2020] [Accepted: 07/22/2020] [Indexed: 11/02/2022] Open
Abstract
BACKGROUND AND PURPOSE Magnetic Resonance Imaging (MRI) is increasingly being used in radiotherapy (RT). However, geometric distortions are a known challenge of using MRI in RT. The aim of this study was to demonstrate feasibility of a national audit of MRI geometric distortions. This was achieved by assessing large field of view (FOV) MRI distortions on a number of scanners used clinically for RT. MATERIALS AND METHODS MRI scans of a large FOV MRI geometric distortion phantom were acquired on 11 MRI scanners that are used clinically for RT in the UK. The mean and maximum distortions and variance between scanners were reported at different distances from the isocentre. RESULTS For a small FOV representing a brain (100-150 mm from isocentre) all distortions were < 2 mm except for the maximum distortion of one scanner. For a large FOV representing a head and neck/pelvis (200-250 mm from isocentre) mean distortions were < 2 mm except for one scanner, maximum distortions were > 10 mm in some cases. The variance between scanners was low and was found to increase with distance from isocentre. CONCLUSIONS This study demonstrated feasibility of the technique to be repeated in a country wide geometric distortion audit of all MRI scanners used clinically for RT. Recommendations were made for performing such an audit and how to derive acceptable limits of distortion in such an audit.
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Affiliation(s)
- Meshal Alzahrani
- Department of Diagnostic Radiology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - David A Broadbent
- Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Robert Chuter
- Christie Medical Physics and Engineering (CMPE), The Christie NHS Foundation Trust, Manchester, UK
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Bashar Al-Qaisieh
- Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Steven Jackson
- Christie Medical Physics and Engineering (CMPE), The Christie NHS Foundation Trust, Manchester, UK
| | - Hutton Michael
- Christie Medical Physics and Engineering (CMPE), The Christie NHS Foundation Trust, Manchester, UK
| | | | - Simon Shah
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Andreas Wetscherek
- Joint Department of Physics at the Institute of Cancer Research and the Royal Marsden NHS Foundation Trust, London, UK
| | - H. Joan Chick
- Joint Department of Physics at the Institute of Cancer Research and the Royal Marsden NHS Foundation Trust, London, UK
| | - Jonathan J Wyatt
- Northern Centre for Cancer Care, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle, UK
- Centre for Cancer, Newcastle University, Newcastle, UK
| | - Hazel Mhairi McCallum
- Northern Centre for Cancer Care, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle, UK
- Centre for Cancer, Newcastle University, Newcastle, UK
| | - Richard Speight
- Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds, UK
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Magnetic resonance imaging for brain stereotactic radiotherapy : A review of requirements and pitfalls. Strahlenther Onkol 2020; 196:444-456. [PMID: 32206842 PMCID: PMC7182639 DOI: 10.1007/s00066-020-01604-0] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 03/03/2020] [Indexed: 12/29/2022]
Abstract
Due to its superior soft tissue contrast, magnetic resonance imaging (MRI) is essential for many radiotherapy treatment indications. This is especially true for treatment planning in intracranial tumors, where MRI has a long-standing history for target delineation in clinical practice. Despite its routine use, care has to be taken when selecting and acquiring MRI studies for the purpose of radiotherapy treatment planning. Requirements on MRI are particularly demanding for intracranial stereotactic radiotherapy, where accurate imaging has a critical role in treatment success. However, MR images acquired for routine radiological assessment are frequently unsuitable for high-precision stereotactic radiotherapy as the requirements for imaging are significantly different for radiotherapy planning and diagnostic radiology. To assure that optimal imaging is used for treatment planning, the radiation oncologist needs proper knowledge of the most important requirements concerning the use of MRI in brain stereotactic radiotherapy. In the present review, we summarize and discuss the most relevant issues when using MR images for target volume delineation in intracranial stereotactic radiotherapy.
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42
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Geometric inaccuracy and co-registration errors for CT, DynaCT and MRI images used in robotic stereotactic radiosurgery treatment planning. Phys Med 2020; 69:212-222. [PMID: 31918373 DOI: 10.1016/j.ejmp.2019.12.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 11/08/2019] [Accepted: 12/04/2019] [Indexed: 11/21/2022] Open
Abstract
PURPOSE To measure the combined errors due to geometric inaccuracy and image co-registration on secondary images (dynamic CT angiography (dCTA), 3D DynaCT angiography (DynaCTA), and magnetic resonance images (MRI)) that are routinely used to aid in target delineation and planning for stereotactic radiosurgery (SRS). METHODS Three phantoms (one commercial and two in-house built) and two different analysis approaches (commercial and MATLAB based) were used to quantify the magnitude of geometric image distortion and co-registration errors for different imaging modalities within CyberKnife's MultiPlan treatment planning software. For each phantom, the combined errors were reported as a mean target registration error (TRE). The mean TRE's for different intramodality imaging parameters (e.g., mAs, kVp, and phantom set-ups) and for dCTA, DynaCTA, and MRI systems were measured. RESULTS Only X-ray based imaging can be performed with the commercial phantom, and the mean TRE ± standard deviation values were large compared to the in-house analysis using MATLAB. With the 3D printed phantom, even drastic changes in treatment planning CT imaging protocols did not greatly influence the mean TRE (<0.5 mm for a 1 mm slice thickness CT). For all imaging modalities, the largest mean TRE was found on DynaCT, followed by T2-weighted MR images (albeit all <1 mm). CONCLUSIONS The user may overestimate the mean TRE if the commercial phantom and MultiPlan were used solely. The 3D printed phantom design is a sensitive and suitable quality assurance tool for measuring 3D geometric inaccuracy and co-registration errors across all imaging modalities.
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Sasamoto K, Kanamoto M, Ishida S, Shimada M, Kimura H, Adachi T. [Evaluation of Long-term Fluctuation of Geometric Distortion in MRI for Radiation Therapy Planning by Using an Automatic Analysis Tool]. Nihon Hoshasen Gijutsu Gakkai Zasshi 2020; 76:705-714. [PMID: 32684563 DOI: 10.6009/jjrt.2020_jjrt_76.7.705] [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] [Indexed: 06/11/2023]
Abstract
High tissue contrast in magnetic resonance imaging (MRI) allows better radiotherapy planning. However, geometric distortion in MRI induces inaccuracies affecting such planning, making it necessary to evaluate the characteristics of such geometric distortion. Although many studies have considered geometric distortion, most of these involved measurements performed only a few times. In this study, we evaluated MRI device-specific geometric distortion over long term and measured its variation by using an automatic analysis tool. The result showed that geometric distortion increased with distance from the center along both lateral and longitudinal directions. Specifically, the average distortion rate and average diameter error over the full measurement period increased by up to 1.02% and 1.96 mm, respectively, when using T1 weighted Image (WI) 3D fast spoiled gradient echo (FSPGR) at R15. In the case of T2 WI 2D fast spin echo (FSE) at R15, the standard deviation of the distortion rate and diameter error increased up to 0.38%, 0.72 mm, respectively. We conclude that periodic quality assurance of geometric distortion should be performed in order to maintain geometric distortion within allowable values.
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Affiliation(s)
| | | | | | | | | | - Toshiki Adachi
- Department of Radiological Technology, Niigata University of Health and Welfare
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44
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Spadea MF, Pileggi G, Zaffino P, Salome P, Catana C, Izquierdo-Garcia D, Amato F, Seco J. Deep Convolution Neural Network (DCNN) Multiplane Approach to Synthetic CT Generation From MR images—Application in Brain Proton Therapy. Int J Radiat Oncol Biol Phys 2019; 105:495-503. [DOI: 10.1016/j.ijrobp.2019.06.2535] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 06/18/2019] [Accepted: 06/21/2019] [Indexed: 10/26/2022]
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45
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Tang F, Liang S, Zhong T, Huang X, Deng X, Zhang Y, Zhou L. Postoperative glioma segmentation in CT image using deep feature fusion model guided by multi-sequence MRIs. Eur Radiol 2019; 30:823-832. [PMID: 31650265 DOI: 10.1007/s00330-019-06441-z] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Revised: 08/05/2019] [Accepted: 09/09/2019] [Indexed: 12/21/2022]
Abstract
OBJECTIVES Computed tomography (CT) and magnetic resonance imaging (MRI) are the most commonly selected methods for imaging gliomas. Clinically, radiotherapists always delineate the CT glioma region with reference to multi-modal MR image information. On this basis, we develop a deep feature fusion model (DFFM) guided by multi-sequence MRIs for postoperative glioma segmentation in CT images. METHODS DFFM is a multi-sequence MRI-guided convolutional neural network (CNN) that iteratively learns the deep features from CT images and multi-sequence MR images simultaneously by utilizing a multi-channel CNN architecture, and then combines these two deep features together to produce the segmentation result. The whole network is optimized together via a standard back-propagation. A total of 59 CT and MRI datasets (T1/T2-weighted FLAIR, T1-weighted contrast-enhanced, T2-weighted) of postoperative gliomas as tumor grade II (n = 24), grade III (n = 18), or grade IV (n = 17) were included. Dice coefficient (DSC), precision, and recall were used to measure the overlap between automated segmentation results and manual segmentation. The Wilcoxon signed-rank test was used for statistical analysis. RESULTS DFFM showed a significantly (p < 0.01) higher DSC of 0.836 than U-Net trained by single CT images and U-Net trained by stacking the CT and multi-sequence MR images, which yielded 0.713 DSC and 0.818 DSC, respectively. The precision values showed similar behavior as DSC. Moreover, DSC and precision values have no significant statistical difference (p > 0.01) with difference grades. CONCLUSIONS DFFM enables the accurate automated segmentation of CT postoperative gliomas of profit guided by multi-sequence MR images and may thus improve and facilitate radiotherapy planning. KEY POINTS • A fully automated deep learning method was developed to segment postoperative gliomas on CT images guided by multi-sequence MRIs. • CT and multi-sequence MR image integration allows for improvements in deep learning postoperative glioma segmentation method. • This deep feature fusion model produces reliable segmentation results and could be useful in delineating GTV in postoperative glioma radiotherapy planning.
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Affiliation(s)
- Fan Tang
- School of Biomedical Engineering, Southern Medical University, No. 1838 Guangzhou Northern Avenue, Baiyun District, Guangzhou, 510515, Guangdong, China.,Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, 510515, Guangdong, China.,Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Shujun Liang
- School of Biomedical Engineering, Southern Medical University, No. 1838 Guangzhou Northern Avenue, Baiyun District, Guangzhou, 510515, Guangdong, China.,Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Tao Zhong
- School of Biomedical Engineering, Southern Medical University, No. 1838 Guangzhou Northern Avenue, Baiyun District, Guangzhou, 510515, Guangdong, China.,Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Xia Huang
- School of Biomedical Engineering, Southern Medical University, No. 1838 Guangzhou Northern Avenue, Baiyun District, Guangzhou, 510515, Guangdong, China.,Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Xiaogang Deng
- Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Yu Zhang
- School of Biomedical Engineering, Southern Medical University, No. 1838 Guangzhou Northern Avenue, Baiyun District, Guangzhou, 510515, Guangdong, China. .,Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, 510515, Guangdong, China.
| | - Linghong Zhou
- School of Biomedical Engineering, Southern Medical University, No. 1838 Guangzhou Northern Avenue, Baiyun District, Guangzhou, 510515, Guangdong, China.
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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: 51] [Impact Index Per Article: 10.2] [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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Yuan J, Wong OL, Zhou Y, Chueng KY, Yu SK. A fast volumetric 4D-MRI with sub-second frame rate for abdominal motion monitoring and characterization in MRI-guided radiotherapy. Quant Imaging Med Surg 2019; 9:1303-1314. [PMID: 31448215 DOI: 10.21037/qims.2019.06.23] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Background To propose a fast volumetric 4D-MRI based on 3D pulse sequence acquisition for abdominal motion monitoring and characterization in MRI-guided radiotherapy (MRgRT). Methods A 3D spoiled gradient echo sequence volumetric interpolated breath-hold examination (VIBE) [repetition time/echo time (TR/TE) =0.53/1.57 ms, flip-angle =5°, receiver bandwidth (RBW) =1,400 Hz/voxel] based 4D-MRI acquisition, accelerated by 4-fold controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA), named CAIPIRINHA-VIBE 4D-MRI, was implemented on a 1.5T MRI simulator (MR-sim) and applied for abdominal imaging of nine healthy volunteers under free breathing. One hundred and forty-four dynamics of the entire abdomen volume (56 slices), in total 8,064 (144×56) images with a voxel size of 2.7×2.7×4.0 mm3, were acquired in 89 s for 4D-MRI. This CAIPIRINHA-VIBE 4D-MRI was qualitatively compared with a 2D half-Fourier acquisition single-shot turbo spin-echo (2D-HASTE) based 4D-MRI. The motions of liver dome, kidney and spleen were analyzed using the CAIPIRINHA-VIBE 4D-MRI data. The kidney motion was quantitatively characterized in terms of motion range and the correlations between left and right kidneys. Results CAIPIRINHA-VIBE 4D-MRI was successfully conducted in all subjects. CAIPIRINHA-VIBE 4D-MRI exhibited much higher effective volumetric temporal resolution (0.615 vs. ~5 s/volume) and better reconstructed volume consistency than 2D-HASTE 4D-MRI. CAIPIRINHA-VIBE 4D-MRI was able to characterize the respiratory motion of abdominal organs simultaneously in three orthogonal directions, and could potentially be used for whole abdomen deformable motion tracking. Renal motion range was most pronounced in superior-inferior (SI) direction (L: 10.03±2.65 mm; R: 10.38±2.80 mm), significantly larger (P<0.001) than that in anterior-posterior (AP) and the least in left-right (LR) directions. Right kidney had significantly larger mobility (4.18±2.19 vs. 2.32±1.34 mm, P=0.045) than left kidney in AP, but not in LR and SI directions. The Pearson correlation coefficients r between left and right kidney motion were 0.5063 (P=0.164), 0.6624 (P=0.052) and 0.5752 (P=0.105) in LR, AP and SI correspondingly. The correlation of renal motion in SI and AP was found significant in right kidney (r=0.843, P=0.004) but not in left kidney (r=0.467, P=0.205). Conclusions A fast volumetric 4D-MRI was implemented for abdominal motion monitoring in MRgRT. A sub-second volumetric temporal resolution of 0.615 s, covering the entire abdomen, was demonstrated for respiratory motion monitoring and characterization. This technique holds potentials for MRgRT applications.
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Affiliation(s)
- Jing Yuan
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Oi Lei Wong
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Yihang Zhou
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Kin Yin Chueng
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Siu Ki Yu
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
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Zhou Y, Wong OL, Cheung KY, Yu SK, Yuan J. A pilot study of highly accelerated 3D MRI in the head and neck position verification for MR-guided radiotherapy. Quant Imaging Med Surg 2019; 9:1255-1269. [PMID: 31448211 DOI: 10.21037/qims.2019.06.18] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Background To evaluate the performance of a highly accelerated 3D MRI on inter-fractional positional measurement for MR-guided radiotherapy (MRgRT) in the head and neck (HN). Methods Fourteen healthy volunteers received 159 scans on a 1.5 T MR-sim to simulate MRgRT fractions. MRI acquisition included a high-resolution (HQI-MRI, voxel-size =1.05×1.05×1.05 mm3, duration =5 min) and a highly-accelerated low-resolution (true-LQI-MRI, acceleration-factor =9, voxel-size =1.4×1.4×1.4 mm3, duration =86 s) T1w spin-echo sequence (TR/TE =420/7.2 ms). The first session HQI-MRI was used as the reference to mimic planning MRI. Other HQI-MRI was also retrospectively down-sampled in K-space and GRAPPA reconstructed to generate pseudo-LQI-MRI. Inter-sessional positional shift calculated from HQI-MRI, true-LQI-MRI and pseudo-LQI-MRI rigidly registering to the reference were analyzed and compared in the overall HN and the sub-regions of brain, nasopharynx, oropharynx and hypopharynx. Results The calculated SD of systematic errors (Σ) from HQI-MRI/pseudo-LQI-MRI/true-LQI-MRI images for overall HN were 1.11/1.14/1.08, 0.28/0.26/0.29, 0.43/0.44/0.60, and 0.77/0.79/0.74 mm for translation in LR, AP, SI and 3D, respectively; The corresponding RMS of random errors (σ) were 0.97/0.98/0.96, 0.28/0.27/0.26, 0.77/0.77/0.72, and 0.85/0.87/0.85 mm. For all sub-regions, brain showed the smallest Σ and σ in 3D. Other sub-regions showed direction-dependent error patterns, but the positioning results were consistent, independent of the datasets used for registration. Conclusions A highly-accelerated 3D-MRI could be used for MR-guided HN radiotherapy without compromising position verification accuracy.
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Affiliation(s)
- Yihang Zhou
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Oi Lei Wong
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Kin Yin Cheung
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Siu Ki Yu
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Jing Yuan
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
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Vickers AJ, Thiruthaneeswaran N, Coyle C, Manoharan P, Wylie J, Kershaw L, Choudhury A, Mcwilliam A. Does magnetic resonance imaging improve soft tissue sarcoma contouring for radiotherapy? BJR Open 2019; 1:20180022. [PMID: 33178916 PMCID: PMC7592468 DOI: 10.1259/bjro.20180022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Revised: 03/27/2019] [Accepted: 03/28/2019] [Indexed: 11/27/2022] Open
Abstract
Objective: Soft tissue sarcomas (STS) are a rare, heterogeneous tumour group. Radiotherapy improves local control. CT is used to plan radiotherapy, but has poor soft tissue definition. MRI has superior soft tissue definition. Contour variation amongst oncologists is an important factor in treatment failure. This study is the first to directly compare STS tumour contouring using CT vs MRI. Methods: Planning CT and T2 weighted MR images of eight patients with STS were distributed to four oncologists. Gross tumour volume was contoured on both imaging modalities using in-house software. Images were recontoured 6 weeks later. The mean distance to agreement (DTA), standard deviation of the DTA, dice similarity coefficient (DSC) and contour volume were calculated for each oncologist and compared to a median contour volume. Results for CT and MRI were compared using a pairwise Student's t-test. Results: When comparing MRI to CT, tumour volumes were significantly smaller, with a difference of 21.4 cm3 across all patients (p = 0.008). There was not a statistically significant difference in the mean distance to agreement or dice similarity coefficient, but the standard deviation of the DTA showed a statistically significant improvement ( p = 0.04). For intraobserver variation, there was no statistically significant improvement using MRI vs CT. Conclusion: Oncologists contour smaller tumour volumes using MRI, with reduced interobserver variation. Improving the reliability and consistency of contouring is needed for improved quality assurance. Advances in knowledge: With further experience, the use of MRI in STS radiotherapy planning may reduce variation between oncologists and contribute to improved local control and reduced treatment toxicities.
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Affiliation(s)
- Alexander John Vickers
- Department of Clinical Oncology, The Christie NHS Foundation Trust, 550 Wilmslow Road, Withington, Manchester, United Kingdom
| | | | - Catherine Coyle
- Department of Clinical Oncology, The Christie NHS Foundation Trust, 550 Wilmslow Road, Withington, Manchester, United Kingdom
| | - Prakash Manoharan
- Department of Clinical Oncology, The Christie NHS Foundation Trust, 550 Wilmslow Road, Withington, Manchester, United Kingdom
| | - James Wylie
- Department of Clinical Oncology, The Christie NHS Foundation Trust, 550 Wilmslow Road, Withington, Manchester, United Kingdom
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Ranta I, Kemppainen R, Keyriläinen J, Suilamo S, Heikkinen S, Kapanen M, Saunavaara J. Quality assurance measurements of geometric accuracy for magnetic resonance imaging-based radiotherapy treatment planning. Phys Med 2019; 62:47-52. [PMID: 31153398 DOI: 10.1016/j.ejmp.2019.04.022] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 03/29/2019] [Accepted: 04/24/2019] [Indexed: 10/26/2022] Open
Abstract
BACKGROUND Using magnetic resonance imaging (MRI) as the only imaging method for radiotherapy treatment planning (RTP) is becoming more common as MRI-only RTP solutions have evolved. The geometric accuracy of MR images is an essential factor of image quality when determining the suitability of MRI for RTP. The need is therefore clear for clinically feasible quality assurance (QA) methods for the geometric accuracy measurement. MATERIALS AND METHODS This work evaluates long-term stability of geometric accuracy and the validity of a 2D geometric accuracy QA method compared to a prototype 3D method and analysis software in routine QA. The long-term follow-up measurements were conducted on one of the 1.5 T scanners over a period of 19 months using both methods. Inter-scanner variability of geometric distortions was also evaluated in three 1.5 T and three 3 T MRI scanners from a single vendor by using the prototype 3D QA method. RESULTS The geometric accuracy of the magnetic resonance for radiotherapy (MR-RT) platform remained stable within 2 mm at distances of <250 mm from isocenter. All scanners achieved good geometric accuracy with mean geometric distortions of <1 mm at <150 mm and <2 mm at <250 mm from the isocenter. Both measurement methods provided relevant information about geometric distortions. CONCLUSIONS Geometric distortions are often considered a limitation of MRI-only RTP. Results indicate that geometric accuracy of modern scanners remain within acceptable limits by default even after many years of clinical use based on the 3D QA evaluation.
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Affiliation(s)
- Iiro Ranta
- Department of Physics and Astronomy, University of Turku, Vesilinnantie 5, FI-20014 Turku, Finland; Department of Medical Physics, Turku University Hospital, Hämeentie 11, P.O. Box 52, FI-20521 Turku, Finland; Department of Oncology and Radiotherapy, Turku University Hospital, Hämeentie 11, P.O. Box 52, FI-20521 Turku, Finland.
| | | | - Jani Keyriläinen
- Department of Physics and Astronomy, University of Turku, Vesilinnantie 5, FI-20014 Turku, Finland; Department of Medical Physics, Turku University Hospital, Hämeentie 11, P.O. Box 52, FI-20521 Turku, Finland; Department of Oncology and Radiotherapy, Turku University Hospital, Hämeentie 11, P.O. Box 52, FI-20521 Turku, Finland
| | - Sami Suilamo
- Department of Medical Physics, Turku University Hospital, Hämeentie 11, P.O. Box 52, FI-20521 Turku, Finland; Department of Oncology and Radiotherapy, Turku University Hospital, Hämeentie 11, P.O. Box 52, FI-20521 Turku, Finland
| | - Samuli Heikkinen
- Department of Medical Physics, Turku University Hospital, Hämeentie 11, P.O. Box 52, FI-20521 Turku, Finland
| | - Mika Kapanen
- Department of Medical Physics, Medical Imaging Center, Tampere University Hospital, P.O. Box 2000, FI-33521 Tampere, Finland; Department of Oncology, Unit of Radiotherapy, Tampere University Hospital, P.O. Box 2000, FI-33521 Tampere, Finland
| | - Jani Saunavaara
- Department of Medical Physics, Turku University Hospital, Hämeentie 11, P.O. Box 52, FI-20521 Turku, Finland
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