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El-Habashy DM, Wahid KA, He R, McDonald B, Mulder SJ, Ding Y, Salzillo T, Lai SY, Christodouleas J, Dresner A, Wang J, Naser MA, Fuller CD, Mohamed ASR. Dataset of weekly intra-treatment diffusion weighted imaging in head and neck cancer patients treated with MR-Linac. Sci Data 2024; 11:487. [PMID: 38734679 PMCID: PMC11088675 DOI: 10.1038/s41597-024-03217-z] [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: 09/12/2023] [Accepted: 04/03/2024] [Indexed: 05/13/2024] Open
Abstract
Radiation therapy (RT) is a crucial treatment for head and neck squamous cell carcinoma (HNSCC); however, it can have adverse effects on patients' long-term function and quality of life. Biomarkers that can predict tumor response to RT are being explored to personalize treatment and improve outcomes. While tissue and blood biomarkers have limitations, imaging biomarkers derived from magnetic resonance imaging (MRI) offer detailed information. The integration of MRI and a linear accelerator in the MR-Linac system allows for MR-guided radiation therapy (MRgRT), offering precise visualization and treatment delivery. This data descriptor offers a valuable repository for weekly intra-treatment diffusion-weighted imaging (DWI) data obtained from head and neck cancer patients. By analyzing the sequential DWI changes and their correlation with treatment response, as well as oncological and survival outcomes, the study provides valuable insights into the clinical implications of DWI in HNSCC.
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Affiliation(s)
- Dina M El-Habashy
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Department of Clinical Oncology and Nuclear Medicine, Menoufia University, Shebin Elkom, Egypt.
| | - Kareem A Wahid
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Renjie He
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Brigid McDonald
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Samuel J Mulder
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yao Ding
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Travis Salzillo
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Stephen Y Lai
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Molecular and Cellular Oncology, Division of Basic Science Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Alex Dresner
- Philips Healthcare MR Oncology, Cleveland, Ohio, USA
| | - Jihong Wang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Mohamed A Naser
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Clifton D Fuller
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Abdallah Sherif Radwan Mohamed
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Department of Radiation Oncology, Baylor College of Medicine, Houston, TX, USA.
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Nachbar M, Lo Russo M, Gani C, Boeke S, Wegener D, Paulsen F, Zips D, Roque T, Paragios N, Thorwarth D. Automatic AI-based contouring of prostate MRI for online adaptive radiotherapy. Z Med Phys 2024; 34:197-207. [PMID: 37263911 DOI: 10.1016/j.zemedi.2023.05.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 04/03/2023] [Accepted: 05/02/2023] [Indexed: 06/03/2023]
Abstract
BACKGROUND AND PURPOSE MR-guided radiotherapy (MRgRT) online plan adaptation accounts for tumor volume changes, interfraction motion and thus allows daily sparing of relevant organs at risk. Due to the high interfraction variability of bladder and rectum, patients with tumors in the pelvic region may strongly benefit from adaptive MRgRT. Currently, fast automatic annotation of anatomical structures is not available within the online MRgRT workflow. Therefore, the aim of this study was to train and validate a fast, accurate deep learning model for automatic MRI segmentation at the MR-Linac for future implementation in a clinical MRgRT workflow. MATERIALS AND METHODS For a total of 47 patients, T2w MRI data were acquired on a 1.5 T MR-Linac (Unity, Elekta) on five different days. Prostate, seminal vesicles, rectum, anal canal, bladder, penile bulb, body and bony structures were manually annotated. These training data consisting of 232 data sets in total was used for the generation of a deep learning based autocontouring model and validated on 20 unseen T2w-MRIs. For quantitative evaluation the validation set was contoured by a radiation oncologist as gold standard contours (GSC) and compared in MATLAB to the automatic contours (AIC). For the evaluation, dice similarity coefficients (DSC), and 95% Hausdorff distances (95% HD), added path length (APL) and surface DSC (sDSC) were calculated in a caudal-cranial window of ± 4 cm with respect to the prostate ends. For qualitative evaluation, five radiation oncologists scored the AIC on the possible usage within an online adaptive workflow as follows: (1) no modifications needed, (2) minor adjustments needed, (3) major adjustments/ multiple minor adjustments needed, (4) not usable. RESULTS The quantitative evaluation revealed a maximum median 95% HD of 6.9 mm for the rectum and minimum median 95% HD of 2.7 mm for the bladder. Maximal and minimal median DSC were detected for bladder with 0.97 and for penile bulb with 0.73, respectively. Using a tolerance level of 3 mm, the highest and lowest sDSC were determined for rectum (0.94) and anal canal (0.68), respectively. Qualitative evaluation resulted in a mean score of 1.2 for AICs over all organs and patients across all expert ratings. For the different autocontoured structures, the highest mean score of 1.0 was observed for anal canal, sacrum, femur left and right, and pelvis left, whereas for prostate the lowest mean score of 2.0 was detected. In total, 80% of the contours were rated be clinically acceptable, 16% to require minor and 4% major adjustments for online adaptive MRgRT. CONCLUSION In this study, an AI-based autocontouring was successfully trained for online adaptive MR-guided radiotherapy on the 1.5 T MR-Linac system. The developed model can automatically generate contours accepted by physicians (80%) or only with the need of minor corrections (16%) for the irradiation of primary prostate on the clinically employed sequences.
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Affiliation(s)
- Marcel Nachbar
- Section for Biomedical Physics, Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University of Tübingen, Tübingen, Germany
| | - Monica Lo Russo
- Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University of Tübingen, Tübingen, Germany
| | - Cihan Gani
- Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University of Tübingen, Tübingen, Germany
| | - Simon Boeke
- Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University of Tübingen, Tübingen, Germany
| | - Daniel Wegener
- Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University of Tübingen, Tübingen, Germany
| | - Frank Paulsen
- Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University of Tübingen, Tübingen, Germany
| | - Daniel Zips
- Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University of Tübingen, Tübingen, Germany; German Cancer Consortium (DKTK), partner site Tübingen; and German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Radiation Oncology, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | | | - Nikos Paragios
- TheraPanacea, Paris, France; CentraleSupelec, University of Paris-Saclay, Gif-sur-Yvette, France
| | - Daniela Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University of Tübingen, Tübingen, Germany; German Cancer Consortium (DKTK), partner site Tübingen; and German Cancer Research Center (DKFZ), Heidelberg, Germany.
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3
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Wallimann P, Piccirelli M, Nowakowska S, Armstrong T, Mayinger M, Boss A, Bink A, Guckenberger M, Tanadini-Lang S, Andratschke N, Pouymayou B. Validation of echo planar imaging based diffusion-weighted magnetic resonance imaging on a 0.35 T MR-Linac. Phys Imaging Radiat Oncol 2024; 30:100579. [PMID: 38707628 PMCID: PMC11068927 DOI: 10.1016/j.phro.2024.100579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 03/08/2024] [Accepted: 04/17/2024] [Indexed: 05/07/2024] Open
Abstract
Background and Purpose The feasibility of acquiring diffusion-weighted imaging (DWI) images on an MR-Linac for quantitative response assessment during radiotherapy was explored. DWI data obtained with a Spin Echo Echo Planar Imaging sequence adapted for a 0.35 T MR-Linac were examined and compared with DWI data from a conventional 3 T scanner. Materials and Methods Apparent diffusion coefficient (ADC) measurements and a distortion correction technique were investigated using DWI-calibrated phantoms and in the brains of seven volunteers. All DWI utilized two phase-encoding directions for distortion correction and off-resonance field estimation. ADC maps in the brain were analyzed for automatically segmented normal tissues. Results Phantom ADC measurements on the MR-Linac were within a 3 % margin of those recorded by the 3 T scanner. The maximum distortion observed in the phantom was 2.0 mm prior to correction and 1.1 mm post-correction on the MR-Linac, compared to 6.0 mm before correction and 3.6 mm after correction at 3 T. In vivo, the average ADC values for gray and white matter exhibited variations of 14 % and 4 %, respectively, for different selections of b-values on the MR-Linac. Distortions in brain images before correction, estimated through the off-resonance field, reached 2.7 mm on the MR-Linac and 12 mm at 3 T. Conclusion Accurate ADC measurements are achievable on a 0.35 T MR-Linac, both in phantom and in vivo. The selection of b-values significantly influences ADC values in vivo. DWI on the MR-Linac demonstrated lower distortion levels, with a maximum distortion reduced to 1.1 mm after correction.
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Affiliation(s)
- Philipp Wallimann
- Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Marco Piccirelli
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Sylwia Nowakowska
- Institute for Diagnostic and Interventional Radiology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Tess Armstrong
- ViewRay Inc., 2 Thermo Fisher Way, Oakwood Village, OH 44146, USA
| | - Michael Mayinger
- Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Andreas Boss
- Institute for Diagnostic and Interventional Radiology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Andrea Bink
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Matthias Guckenberger
- Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Stephanie Tanadini-Lang
- Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Nicolaus Andratschke
- Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Bertrand Pouymayou
- Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich and University of Zurich, Zurich, Switzerland
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Wong OL, Yuan J, Poon DMC, Chiu ST, Yang B, Chiu G, Yu SK, Cheung KY. Prostate diffusion-weighted imaging (DWI) in MR-guided radiotherapy: Reproducibility assessment on 1.5 T MR-Linac and 1.5 T MR-simulator. Magn Reson Imaging 2024; 111:47-56. [PMID: 38513789 DOI: 10.1016/j.mri.2024.03.020] [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: 01/11/2024] [Revised: 03/11/2024] [Accepted: 03/16/2024] [Indexed: 03/23/2024]
Abstract
PURPOSE Diffusion-weighted imaging (DWI) holds promise for image-guided radiotherapy (MRgRT) in prostate cancer. However, challenges persist due to image distortion, artifacts, and apparent diffusion coefficient (ADC) reproducibility issues. This study aimed to assess DWI image quality and ADC reproducibility on both a 1.5 T MR-simulator and a 1.5 T MR-Linac, employing measurements from both an ACR MRI phantom and prostate cancer patients undergoing MRgRT. METHODS DW-MRI scans were conducted on 19 patients (mean age = 69 ± 8 years, with 23 MR-visible intra-prostatic lesions) and an ACR MRI phantom using a 1.5 T MR-simulator (b-values = 0, 800, 1400s/mm2) and a 1.5 T MR-Linac (b-values = 50, 500, 800 s/mm2). ADC homogeneity in the phantom was evaluated via 1D profile flatness (FL) in three directions. Image quality was assessed through qualitative 5-point Likert scale ratings and quantitative ADC and signal-to-noise ratio (SNR) measurements. Intra-observer reproducibility of image quality scores was evaluated using ICC(1, 2). Geometric distortion was measured by comparing landmark sizes on the ACR phantom against the ground truth. Mean ADC and reproducibility were assessed using Bland-Altman plots. RESULTS Both MR-simulator and MR-Linac demonstrated high ADC homogeneity (FL > 87.5% - MR-simulator: 97.23 ± 0.62%, MR-Linac: 94.75 ± 0.62%, p < 0.05) in the phantom. Image quality scores revealed acceptable ratings (≥3) for capsule demarcation, image artifacts, and geometric distortion in patients. However, intra-prostatic lesions were barely discernible in b800 images for both MR-simulator (average score = 2.37 ± 1.33) and MR-Linac (average score = 2.16 ± 1.28). While MR-Linac DWI scans exhibited significantly more severe geometric distortion than MR-simulator scans (p < 0.01), most phantom measurements fell within the image in-plane resolution of 3 mm. Significant differences were noted in MR-simulator ADC (CTV: 1.20 ± 0.14 × 10-3 mm2/s (MR-simulator) vs 1.06 ± 0.10 × 10-3 mm2/s (MR-Linac); GTV: 1.05 ± 0.21 × 10-3 mm2/s vs 0.91 ± 0.16 × 10 mm2/s, all p < 0.05), with a small non-zero bias observed in the Bland-Altman analysis (CTV: 12.3%; GTV: 14.5%). CONCLUSION The significantly larger MR-simulator ADC and the small non-zero bias hint at potential systematic differences in ADC values acquired from an MR-simulator and an MR-Linac, both at 1.5 T. Although acceptable ADC homogeneity was noted, caution is warranted in interpreting MR-Linac DWI images due to occasional severe artifacts. Further studies are essential to validate DWI and ADC as reliable imaging markers in prostate cancer MRgRT.
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Affiliation(s)
- Oi Lei Wong
- Research Department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong SAR, China.
| | - Jing Yuan
- Research Department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong SAR, China
| | - Darren M C Poon
- Comprehensive Oncology Center, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong SAR, China
| | - Sin Ting Chiu
- Department of Radiotherapy, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong SAR, China
| | - Bin Yang
- Medical Physics Department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong SAR, China
| | - George Chiu
- Department of Radiotherapy, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong SAR, China
| | - Siu Ki Yu
- Medical Physics Department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong SAR, China
| | - Kin Yin Cheung
- Medical Physics Department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong SAR, China
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Rabe M, Dietrich O, Forbrig R, Niyazi M, Belka C, Corradini S, Landry G, Kurz C. Repeatability quantification of brain diffusion-weighted imaging for future clinical implementation at a low-field MR-linac. Radiat Oncol 2024; 19:31. [PMID: 38448888 PMCID: PMC10916154 DOI: 10.1186/s13014-024-02424-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 02/26/2024] [Indexed: 03/08/2024] Open
Abstract
BACKGROUND Longitudinal assessments of apparent diffusion coefficients (ADCs) derived from diffusion-weighted imaging (DWI) during intracranial radiotherapy at magnetic resonance imaging-guided linear accelerators (MR-linacs) could enable early response assessment by tracking tumor diffusivity changes. However, DWI pulse sequences are currently unavailable in clinical practice at low-field MR-linacs. Quantifying the in vivo repeatability of ADC measurements is a crucial step towards clinical implementation of DWI sequences but has not yet been reported on for low-field MR-linacs. This study assessed ADC measurement repeatability in a phantom and in vivo at a 0.35 T MR-linac. METHODS Eleven volunteers and a diffusion phantom were imaged on a 0.35 T MR-linac. Two echo-planar imaging DWI sequence variants, emphasizing high spatial resolution ("highRes") and signal-to-noise ratio ("highSNR"), were investigated. A test-retest study with an intermediate outside-scanner-break was performed to assess repeatability in the phantom and volunteers' brains. Mean ADCs within phantom vials, cerebrospinal fluid (CSF), and four brain tissue regions were compared to literature values. Absolute relative differences of mean ADCs in pre- and post-break scans were calculated for the diffusion phantom, and repeatability coefficients (RC) and relative RC (relRC) with 95% confidence intervals were determined for each region-of-interest (ROI) in volunteers. RESULTS Both DWI sequence variants demonstrated high repeatability, with absolute relative deviations below 1% for water, dimethyl sulfoxide, and polyethylene glycol in the diffusion phantom. RelRCs were 7% [5%, 12%] (CSF; highRes), 12% [9%, 22%] (CSF; highSNR), 9% [8%, 12%] (brain tissue ROIs; highRes), and 6% [5%, 7%] (brain tissue ROIs; highSNR), respectively. ADCs measured with the highSNR variant were consistent with literature values for volunteers, while smaller mean values were measured for the diffusion phantom. Conversely, the highRes variant underestimated ADCs compared to literature values, indicating systematic deviations. CONCLUSIONS High repeatability of ADC measurements in a diffusion phantom and volunteers' brains were measured at a low-field MR-linac. The highSNR variant outperformed the highRes variant in accuracy and repeatability, at the expense of an approximately doubled voxel volume. The observed high in vivo repeatability confirms the potential utility of DWI at low-field MR-linacs for early treatment response assessment.
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Affiliation(s)
- Moritz Rabe
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany.
| | - Olaf Dietrich
- Department of Radiology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Robert Forbrig
- Institute of Neuroradiology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Maximilian Niyazi
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, a Partnership Between DKFZ and LMU University Hospital Munich, Munich, Germany
- Bavarian Cancer Research Center (BZKF), Munich, Germany
- Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Claus Belka
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
- German Cancer Consortium (DKTK), Partner Site Munich, a Partnership Between DKFZ and LMU University Hospital Munich, Munich, Germany
- Bavarian Cancer Research Center (BZKF), Munich, Germany
| | - Stefanie Corradini
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Guillaume Landry
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Christopher Kurz
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
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Mesny E, Leporq B, Chapet O, Beuf O. Towards tumour hypoxia imaging: Incorporating relative oxygen extraction fraction mapping of prostate with multi-parametric quantitative MRI on a 1.5T MR-linac. J Med Imaging Radiat Oncol 2024. [PMID: 38415384 DOI: 10.1111/1754-9485.13626] [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: 06/29/2023] [Accepted: 02/03/2024] [Indexed: 02/29/2024]
Abstract
Hypoxia plays a central role in tumour radioresistance. Reliable tumour hypoxia imaging would allow the monitoring of tumour response and a more personalized adaptation of radiotherapy planning. Here, we showed a proof of concept of the feasibility and repeatability of relative oxygen extraction fraction (rOEF) mapping of prostate using multi-parametric quantitative MRI (qMRI) achieved for the first time on a 1.5T MR-linac. T2, T2* relaxation times maps, and intra-voxel incoherent motion (IVIM) parametric maps mapping were computed on a 29 years old healthy volunteer. R2' and rOEF maps were calculated based on a multi-parametric model. Long-term repeatability and repeatability coefficient (RC) were determined for each parameter according to QIBA recommendations. Mean values for the entire healthy prostate were 0.99 ± 0.14 × 10-3 mm/s2 , 81 ± 2.1 × 10-3 mm/s2 , 21.6 ± 3.6%, 92.7 ± 19.7 ms and 62.4 ± 17.3 ms for Dslow , Dfast , f, T2 and T2*, respectively. R2' and rOEF in the prostate were 6.1 ± 3.4 s-1 and 18.2 ± 10.1% respectively. The RC of rOEF was 4.43%. Long-term repeatability of quantitative parameters based on a test-retest ranged from 2 to 18%. qMRI parameters are measurable and repeatable on 1.5T MR LINAC. From T2, T2* and IVIM parameters maps, we were able to obtain a rOEF mapping of the prostate. These results are the first step to a non-invasive imaging of tumour hypoxia during radiotherapy leading to a biological image-guided adaptive radiotherapy.
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Affiliation(s)
- Emmanuel Mesny
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, CNRS, Inserm, CREATIS UMR 5220, U1294, Lyon, France
- Radiation Oncology Department, Center Hospitalier Lyon Sud, Lyon, France
| | - Benjamin Leporq
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, CNRS, Inserm, CREATIS UMR 5220, U1294, Lyon, France
| | - Olivier Chapet
- Radiation Oncology Department, Center Hospitalier Lyon Sud, Lyon, France
- Université Claude Bernard Lyon 1, Lyon, France
| | - Olivier Beuf
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, CNRS, Inserm, CREATIS UMR 5220, U1294, Lyon, France
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Habrich J, Boeke S, Fritz V, Koerner E, Nikolaou K, Schick F, Gani C, Zips D, Thorwarth D. Reproducibility of diffusion-weighted magnetic resonance imaging in head and neck cancer assessed on a 1.5 T MR-Linac and comparison to parallel measurements on a 3 T diagnostic scanner. Radiother Oncol 2024; 191:110046. [PMID: 38070687 DOI: 10.1016/j.radonc.2023.110046] [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: 05/25/2023] [Revised: 11/27/2023] [Accepted: 12/03/2023] [Indexed: 02/02/2024]
Abstract
BACKGROUND AND PURPOSE Before quantitative imaging biomarkers (QIBs) acquired with magnetic resonance imaging (MRI) can be used for interventional trials in radiotherapy (RT), technical validation of these QIBs is necessary. The aim of this study was to assess the reproducibility of apparent diffusion coefficient (ADC) values, derived from diffusion-weighted (DW) MRI, in head and neck cancer using a 1.5 T MR-Linac (MRL) by comparison to a 3 T diagnostic scanner (DS). MATERIAL AND METHODS DW-MRIs were acquired on MRL and DS for 15 head and neck cancer patients before RT and in week 2 and rigidly registered to the planning computed tomography. Mean ADC values were calculated for submandibular (SG) and parotid (PG) glands as well as target volumes (TV, gross tumor volume and lymph nodes), which were delineated based on computed tomography. Mean absolute ADC differences as well as within-subject coefficient of variation (wCV) and intraclass correlation coefficients (ICCs) were calculated for all volumes of interest. RESULTS A total of 23 datasets were analyzed. Mean ADC difference (DS-MRL) for SG, PG and TV resulted in 142, 254 and 93·10-6 mm2/s. wCVs/ICCs, comparing MRL and DS, were determined as 13.7 %/0.26, 24.4 %/0.23 and 16.1 %/0.73 for SG, PG and TV, respectively. CONCLUSION ADC values, measured on the 1.5 T MRL, showed reasonable reproducibility with an ADC underestimation in contrast to the DS. This ADC shift must be validated in further experiments and considered for future translation of QIB candidates from DS to MRL for response adaptive RT.
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Affiliation(s)
- Jonas Habrich
- Section for Biomedical Physics, Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany.
| | - Simon Boeke
- German Cancer Consortium (DKTK), partner site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany
| | - Victor Fritz
- Section for Experimental Radiology, Department of Diagnostic and Interventional Radiology, University of Tübingen, Germany
| | - Elisa Koerner
- Section for Biomedical Physics, Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany
| | - Konstantin Nikolaou
- Department of Diagnostic and Interventional Radiology, University of Tübingen, Germany
| | - Fritz Schick
- Section for Experimental Radiology, Department of Diagnostic and Interventional Radiology, University of Tübingen, Germany
| | - Cihan Gani
- Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany
| | - Daniel Zips
- German Cancer Consortium (DKTK), partner site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany; Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Daniela Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany; German Cancer Consortium (DKTK), partner site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany
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8
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Yang B, Liu Y, Zhu J, Lu N, Dai J, Men K. Pretreatment information-aided automatic segmentation for online magnetic resonance imaging-guided prostate radiotherapy. Med Phys 2024; 51:922-932. [PMID: 37449545 DOI: 10.1002/mp.16608] [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: 02/22/2023] [Revised: 06/20/2023] [Accepted: 06/20/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND It is necessary to contour regions of interest (ROIs) for online magnetic resonance imaging (MRI)-guided adaptive radiotherapy (MRIgART). These updated contours are used for online replanning to obtain maximum dosimetric benefits. Contouring can be accomplished using deformable image registration (DIR) and deep learning (DL)-based autosegmentation methods. However, these methods may require considerable manual editing and thus prolong treatment time. PURPOSE The present study aimed to improve autosegmentation performance by integrating patients' pretreatment information in a DL-based segmentation algorithm. It is expected to improve the efficiency of current MRIgART process. METHODS Forty patients with prostate cancer were enrolled retrospectively. The online adaptive MR images, patient-specific planning computed tomography (CT), and contours in CT were used for segmentation. The deformable registration of planning CT and MR images was performed first to obtain a deformable CT and corresponding contours. A novel DL network, which can integrate such patient-specific information (deformable CT and corresponding contours) into the segmentation task of MR images was designed. We performed a four-fold cross-validation for the DL models. The proposed method was compared with DIR and DL methods on segmentation of prostate cancer. The ROIs included the clinical target volume (CTV), bladder, rectum, left femur head, and right femur head. Dosimetric parameters of automatically generated ROIs were evaluated using a clinical treatment planning system. RESULTS The proposed method enhanced the segmentation accuracy of conventional procedures. Its mean value of the dice similarity coefficient (93.5%) over the five ROIs was higher than both DIR (87.5%) and DL (87.2%). The number of patients (n = 40) that required major editing using DIR, DL, and our method were 12, 18, and 7 (CTV); 17, 4, and 1 (bladder); 8, 11, and 5 (rectum); 2, 4, and 1 (left femur head); and 3, 7, and 1 (right femur head), respectively. The Spearman rank correlation coefficient of dosimetry parameters between the proposed method and ground truth was 0.972 ± 0.040, higher than that of DIR (0.897 ± 0.098) and DL (0.871 ± 0.134). CONCLUSION This study proposed a novel method that integrates patient-specific pretreatment information into DL-based segmentation algorithm. It outperformed baseline methods, thereby improving the efficiency and segmentation accuracy in adaptive radiotherapy.
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Affiliation(s)
- Bining Yang
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yuxiang Liu
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ji Zhu
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ningning Lu
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jianrong Dai
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Kuo Men
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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9
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Abstract
Magnetic resonance imaging-guided radiation therapy (MRIgRT) has improved soft tissue contrast over computed tomography (CT) based image-guided RT. Superior visualization of the target and surrounding radiosensitive structures has the potential to improve oncological outcomes partly due to safer dose-escalation and adaptive planning. In this review, we highlight the workflow of adaptive MRIgRT planning, which includes simulation imaging, daily MRI, identifying isocenter shifts, contouring, plan optimization, quality control, and delivery. Increased utilization of MRIgRT will depend on addressing technical limitations of this technology, while addressing treatment efficacy, cost-effectiveness, and workflow training.
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Affiliation(s)
- Cecil M Benitez
- Department of Radiation Oncology, UCLA Medical Center, Los Angeles, CA
| | - Michael D Chuong
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health South Florida; Miami, FL
| | - Luise A Künzel
- National Center for Tumor Diseases (NCT), Dresden; German Cancer Research Center (DKFZ), Heidelberg; Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden; Helmholtz-Zentrum Dresden - Rossendorf (HZDR), Dresden, Germany; Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.; OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden Rossendorf, Dresden, Germany
| | - Daniela Thorwarth
- Department of Radiation Oncology, Section for Biomedical Physics, University of Tübingen, Tübingen, Germany..
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10
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McDonald BA, Dal Bello R, Fuller CD, Balermpas P. The Use of MR-Guided Radiation Therapy for Head and Neck Cancer and Recommended Reporting Guidance. Semin Radiat Oncol 2024; 34:69-83. [PMID: 38105096 DOI: 10.1016/j.semradonc.2023.10.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Although magnetic resonance imaging (MRI) has become standard diagnostic workup for head and neck malignancies and is currently recommended by most radiological societies for pharyngeal and oral carcinomas, its utilization in radiotherapy has been heterogeneous during the last decades. However, few would argue that implementing MRI for annotation of target volumes and organs at risk provides several advantages, so that implementation of the modality for this purpose is widely accepted. Today, the term MR-guidance has received a much broader meaning, including MRI for adaptive treatments, MR-gating and tracking during radiotherapy application, MR-features as biomarkers and finally MR-only workflows. First studies on treatment of head and neck cancer on commercially available dedicated hybrid-platforms (MR-linacs), with distinct common features but also differences amongst them, have also been recently reported, as well as "biological adaptation" based on evaluation of early treatment response via functional MRI-sequences such as diffusion weighted ones. Yet, all of these approaches towards head and neck treatment remain at their infancy, especially when compared to other radiotherapy indications. Moreover, the lack of standardization for reporting MR-guided radiotherapy is a major obstacle both to further progress in the field and to conduct and compare clinical trials. Goals of this article is to present and explain all different aspects of MR-guidance for radiotherapy of head and neck cancer, summarize evidence, as well as possible advantages and challenges of the method and finally provide a comprehensive reporting guidance for use in clinical routine and trials.
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Affiliation(s)
- Brigid A McDonald
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Riccardo Dal Bello
- Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Clifton D Fuller
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Panagiotis Balermpas
- Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
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11
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Riis HL, Chick J, Dunlop A, Tilly D. The Quality Assurance of a 1.5 T MR-Linac. Semin Radiat Oncol 2024; 34:120-128. [PMID: 38105086 DOI: 10.1016/j.semradonc.2023.10.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
The recent introduction of a commercial 1.5 T MR-linac system has considerably improved the image quality of the patient acquired in the treatment unit as well as enabling online adaptive radiation therapy (oART) treatment strategies. Quality Assurance (QA) of this new technology requires new methodology that allows for the high field MR in a linac environment. The presence of the magnetic field requires special attention to the phantoms, detectors, and tools to perform QA. Due to the design of the system, the integrated megavoltage imager (MVI) is essential for radiation beam calibrations and QA. Additionally, the alignment between the MR image system and the radiation isocenter must be checked. The MR-linac system has vendor-supplied phantoms for calibration and QA tests. However, users have developed their own routine QA systems to independently check that the machine is performing as required, as to ensure we are able to deliver the intended dose with sufficient certainty. The aim of this work is therefore to review the MR-linac specific QA procedures reported in the literature.
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Affiliation(s)
- Hans Lynggaard Riis
- Department of Oncology, Odense University Hospital, Odense, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
| | - Joan Chick
- The Joint Department of Physics, The Royal Marsden Hospital and the Institute of Cancer Research, London, UK
| | - Alex Dunlop
- The Joint Department of Physics, The Royal Marsden Hospital and the Institute of Cancer Research, London, UK
| | - David Tilly
- Department of Immunology, Genetics and Pathology, Medical Radiation Physics, Uppsala University, Uppsala, Sweden; Medical Physics, Uppsala University Hospital, Uppsala, Sweden
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12
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van Houdt PJ, Li S, Yang Y, van der Heide UA. Quantitative MRI on MR-Linacs: Towards Biological Image-Guided Adaptive Radiotherapy. Semin Radiat Oncol 2024; 34:107-119. [PMID: 38105085 DOI: 10.1016/j.semradonc.2023.10.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Recognizing the potential of quantitative imaging biomarkers (QIBs) in radiotherapy, many studies have investigated the prognostic value of quantitative MRI (qMRI). With the introduction of MRI-guided radiotherapy systems, the practical challenges of repeated imaging have been substantially reduced. Since patients are treated inside an MRI scanner, acquisition of qMRI can be done during each fraction with limited or no prolongation of the fraction duration. In this review paper, we identify the steps that need been taken to move from MR as an imaging technique to a useful biomarker for MRI-guided radiotherapy (MRgRT).
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Affiliation(s)
- Petra J van Houdt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Shaolei Li
- SJTU-Ruijing, UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.; Department of Radiology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Yingli Yang
- SJTU-Ruijing, UIH Institute for Medical Imaging Technology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.; Department of Radiology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Uulke A van der Heide
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands..
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13
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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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14
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Bryant JM, Doniparthi A, Weygand J, Cruz-Chamorro R, Oraiqat IM, Andreozzi J, Graham J, Redler G, Latifi K, Feygelman V, Rosenberg SA, Yu HHM, Oliver DE. Treatment of Central Nervous System Tumors on Combination MR-Linear Accelerators: Review of Current Practice and Future Directions. Cancers (Basel) 2023; 15:5200. [PMID: 37958374 PMCID: PMC10649155 DOI: 10.3390/cancers15215200] [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: 09/16/2023] [Revised: 10/26/2023] [Accepted: 10/27/2023] [Indexed: 11/15/2023] Open
Abstract
Magnetic resonance imaging (MRI) provides excellent visualization of central nervous system (CNS) tumors due to its superior soft tissue contrast. Magnetic resonance-guided radiotherapy (MRgRT) has historically been limited to use in the initial treatment planning stage due to cost and feasibility. MRI-guided linear accelerators (MRLs) allow clinicians to visualize tumors and organs at risk (OARs) directly before and during treatment, a process known as online MRgRT. This novel system permits adaptive treatment planning based on anatomical changes to ensure accurate dose delivery to the tumor while minimizing unnecessary toxicity to healthy tissue. These advancements are critical to treatment adaptation in the brain and spinal cord, where both preliminary MRI and daily CT guidance have typically had limited benefit. In this narrative review, we investigate the application of online MRgRT in the treatment of various CNS malignancies and any relevant ongoing clinical trials. Imaging of glioblastoma patients has shown significant changes in the gross tumor volume over a standard course of chemoradiotherapy. The use of adaptive online MRgRT in these patients demonstrated reduced target volumes with cavity shrinkage and a resulting reduction in radiation dose to uninvolved tissue. Dosimetric feasibility studies have shown MRL-guided stereotactic radiotherapy (SRT) for intracranial and spine tumors to have potential dosimetric advantages and reduced morbidity compared with conventional linear accelerators. Similarly, dosimetric feasibility studies have shown promise in hippocampal avoidance whole brain radiotherapy (HA-WBRT). Next, we explore the potential of MRL-based multiparametric MRI (mpMRI) and genomically informed radiotherapy to treat CNS disease with cutting-edge precision. Lastly, we explore the challenges of treating CNS malignancies and special limitations MRL systems face.
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Affiliation(s)
- John Michael Bryant
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA (I.M.O.); (J.A.); (G.R.); (K.L.); (H.-H.M.Y.)
| | - Ajay Doniparthi
- Morsani College of Medicine, University of South Florida, Tampa, FL 33602, USA;
| | - Joseph Weygand
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA (I.M.O.); (J.A.); (G.R.); (K.L.); (H.-H.M.Y.)
| | - Ruben Cruz-Chamorro
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA (I.M.O.); (J.A.); (G.R.); (K.L.); (H.-H.M.Y.)
| | - Ibrahim M. Oraiqat
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA (I.M.O.); (J.A.); (G.R.); (K.L.); (H.-H.M.Y.)
| | - Jacqueline Andreozzi
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA (I.M.O.); (J.A.); (G.R.); (K.L.); (H.-H.M.Y.)
| | - Jasmine Graham
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA (I.M.O.); (J.A.); (G.R.); (K.L.); (H.-H.M.Y.)
| | - Gage Redler
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA (I.M.O.); (J.A.); (G.R.); (K.L.); (H.-H.M.Y.)
| | - Kujtim Latifi
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA (I.M.O.); (J.A.); (G.R.); (K.L.); (H.-H.M.Y.)
| | - Vladimir Feygelman
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA (I.M.O.); (J.A.); (G.R.); (K.L.); (H.-H.M.Y.)
| | - Stephen A. Rosenberg
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA (I.M.O.); (J.A.); (G.R.); (K.L.); (H.-H.M.Y.)
| | - Hsiang-Hsuan Michael Yu
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA (I.M.O.); (J.A.); (G.R.); (K.L.); (H.-H.M.Y.)
| | - Daniel E. Oliver
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA (I.M.O.); (J.A.); (G.R.); (K.L.); (H.-H.M.Y.)
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15
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Weygand J, Armstrong T, Bryant JM, Andreozzi JM, Oraiqat IM, Nichols S, Liveringhouse CL, Latifi K, Yamoah K, Costello JR, Frakes JM, Moros EG, El Naqa IM, Naghavi AO, Rosenberg SA, Redler G. Accurate, repeatable, and geometrically precise diffusion-weighted imaging on a 0.35 T magnetic resonance imaging-guided linear accelerator. Phys Imaging Radiat Oncol 2023; 28:100505. [PMID: 38045642 PMCID: PMC10692914 DOI: 10.1016/j.phro.2023.100505] [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: 08/24/2023] [Revised: 10/04/2023] [Accepted: 10/30/2023] [Indexed: 12/05/2023] Open
Abstract
Background and purpose Diffusion weighted imaging (DWI) allows for the interrogation of tissue cellularity, which is a surrogate for cellular proliferation. Previous attempts to incorporate DWI into the workflow of a 0.35 T MR-linac (MRL) have lacked quantitative accuracy. In this study, accuracy, repeatability, and geometric precision of apparent diffusion coefficient (ADC) maps produced using an echo planar imaging (EPI)-based DWI protocol on the MRL system is illustrated, and in vivo potential for longitudinal patient imaging is demonstrated. Materials and methods Accuracy and repeatability were assessed by measuring ADC values in a diffusion phantom at three timepoints and comparing to reference ADC values. System-dependent geometric distortion was quantified by measuring the distance between 93 pairs of phantom features on ADC maps acquired on a 0.35 T MRL and a 3.0 T diagnostic scanner and comparing to spatially precise CT images. Additionally, for five sarcoma patients receiving radiotherapy on the MRL, same-day in vivo ADC maps were acquired on both systems, one of which at multiple timepoints. Results Phantom ADC quantification was accurate on the 0.35 T MRL with significant discrepancies only seen at high ADC. Average geometric distortions were 0.35 (±0.02) mm and 0.85 (±0.02) mm in the central slice and 0.66 (±0.04) mm and 2.14 (±0.07) mm at 5.4 cm off-center for the MRL and diagnostic system, respectively. In the sarcoma patients, a mean pretreatment ADC of 910x10-6 (±100x10-6) mm2/s was measured on the MRL. Conclusions The acquisition of accurate, repeatable, and geometrically precise ADC maps is possible at 0.35 T with an EPI approach.
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Affiliation(s)
- Joseph Weygand
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | | | | | | | | | - Steven Nichols
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | | | - Kujtim Latifi
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | - Kosj Yamoah
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | | | - Jessica M. Frakes
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | - Eduardo G. Moros
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | - Issam M. El Naqa
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
- Department of Machine Learning, Moffitt Cancer Center, Tampa, FL, USA
| | - Arash O. Naghavi
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | | | - Gage Redler
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
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16
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Bisgaard ALH, Keesman R, van Lier ALHMW, Coolens C, van Houdt PJ, Tree A, Wetscherek A, Romesser PB, Tyagi N, Lo Russo M, Habrich J, Vesprini D, Lau AZ, Mook S, Chung P, Kerkmeijer LGW, Gouw ZAR, Lorenzen EL, van der Heide UA, Schytte T, Brink C, Mahmood F. Recommendations for improved reproducibility of ADC derivation on behalf of the Elekta MRI-linac consortium image analysis working group. Radiother Oncol 2023; 186:109803. [PMID: 37437609 DOI: 10.1016/j.radonc.2023.109803] [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: 01/19/2023] [Revised: 06/30/2023] [Accepted: 07/06/2023] [Indexed: 07/14/2023]
Abstract
BACKGROUND AND PURPOSE The apparent diffusion coefficient (ADC), a potential imaging biomarker for radiotherapy response, needs to be reproducible before translation into clinical use. The aim of this study was to evaluate the multi-centre delineation- and calculation-related ADC variation and give recommendations to minimize it. MATERIALS AND METHODS Nine centres received identical diffusion-weighted and anatomical magnetic resonance images of different cancerous tumours (adrenal gland, pelvic oligo metastasis, pancreas, and prostate). All centres delineated the gross tumour volume (GTV), clinical target volume (CTV), and viable tumour volume (VTV), and calculated ADCs using both their local calculation methods and each of the following calculation conditions: b-values 0-500 vs. 150-500 s/mm2, region-of-interest (ROI)-based vs. voxel-based calculation, and mean vs. median. ADC variation was assessed using the mean coefficient of variation across delineations (CVD) and calculation methods (CVC). Absolute ADC differences between calculation conditions were evaluated using Friedman's test. Recommendations for ADC calculation were formulated based on observations and discussions within the Elekta MRI-linac consortium image analysis working group. RESULTS The median (range) CVD and CVC were 0.06 (0.02-0.32) and 0.17 (0.08-0.26), respectively. The ADC estimates differed 18% between b-value sets and 4% between ROI/voxel-based calculation (p-values < 0.01). No significant difference was observed between mean and median (p = 0.64). Aligning calculation conditions between centres reduced CVC to 0.04 (0.01-0.16). CVD was comparable between ROI types. CONCLUSION Overall, calculation methods had a larger impact on ADC reproducibility compared to delineation. Based on the results, significant sources of variation were identified, which should be considered when initiating new studies, in particular multi-centre investigations.
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Affiliation(s)
- Anne L H Bisgaard
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Kløvervænget 19, 5000 Odense, Denmark; Department of Clinical Research, University of Southern Denmark, J.B. Winsløws Vej 19.3, 5000 Odense Denmark.
| | - Rick Keesman
- Department of Radiation Oncology, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands.
| | - Astrid L H M W van Lier
- Department of Radiotherapy, University Medical Centre Utrecht, Heidelberglaan 100, 3584 CX,Utrecht, The Netherlands.
| | - Catherine Coolens
- Department of Medical Physics, Princess Margaret Cancer Centre, University Health Network, 610 University Avenue, M5G 2M9 Toronto, ON, Canada.
| | - Petra J van Houdt
- Department of Radiation Oncology, the Netherlands Cancer Institute, Postbus 90203, 1006 BE Amsterdam, The Netherlands.
| | - Alison Tree
- Department of Urology, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, Downs Road, Sutton, Surrey, SM2 5PT London, UK.
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, SM2 5NG London, UK.
| | - Paul B Romesser
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, Box 22, NY 10065, New York, USA.
| | - Neelam Tyagi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 545 E. 73rd street, NY 10021, New York, USA.
| | - Monica Lo Russo
- Department of Radiation Oncology, University Hospital and Medical Faculty, Eberhard Karls University, Hoppe-Seyler-Str. 3, 72076 Tübingen, Germany.
| | - Jonas Habrich
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Hoppe-Seyler-Str. 3, 72076 Tübingen, Germany.
| | - Danny Vesprini
- Department of Radiation Oncology, Sunnybrook Odette Cancer Centre, University of Toronto, 2075 Bayview Avenue, M4N 3M5 Toronto, ON, Canada.
| | - Angus Z Lau
- Physical Sciences Platform, Sunnybrook Research Institute. Department of Medical Biophysics, University of Toronto, 2075 Bayview Avenue, M4N 3M5 Toronto, ON, Canada.
| | - Stella Mook
- Department of Radiotherapy, University Medical Centre Utrecht, Heidelberglaan 100, 3584 CX,Utrecht, The Netherlands.
| | - Peter Chung
- Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network. Department of Radiation Oncology, University of Toronto, 610 University Avenue, M5G 2M9 Toronto, ON, Canada.
| | - Linda G W Kerkmeijer
- Department of Radiation Oncology, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands.
| | - Zeno A R Gouw
- Department of Radiation Oncology, the Netherlands Cancer Institute, Postbus 90203, 1006 BE Amsterdam, The Netherlands.
| | - Ebbe L Lorenzen
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Kløvervænget 19, 5000 Odense, Denmark.
| | - Uulke A van der Heide
- Department of Radiation Oncology, the Netherlands Cancer Institute, Postbus 90203, 1006 BE Amsterdam, The Netherlands.
| | - Tine Schytte
- Department of Clinical Research, University of Southern Denmark, J.B. Winsløws Vej 19.3, 5000 Odense Denmark; Department of Oncology, Odense University Hospital, Kløvervænget 19, 5000 Odense, Denmark.
| | - Carsten Brink
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Kløvervænget 19, 5000 Odense, Denmark; Department of Clinical Research, University of Southern Denmark, J.B. Winsløws Vej 19.3, 5000 Odense Denmark.
| | - Faisal Mahmood
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Kløvervænget 19, 5000 Odense, Denmark; Department of Clinical Research, University of Southern Denmark, J.B. Winsløws Vej 19.3, 5000 Odense Denmark.
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McDonald BA, Salzillo T, Mulder S, Ahmed S, Dresner A, Preston K, He R, Christodouleas J, Mohamed ASR, Philippens M, van Houdt P, Thorwarth D, Wang J, Shukla Dave A, Boss M, Fuller CD. Prospective evaluation of in vivo and phantom repeatability and reproducibility of diffusion-weighted MRI sequences on 1.5 T MRI-linear accelerator (MR-Linac) and MR simulator devices for head and neck cancers. Radiother Oncol 2023; 185:109717. [PMID: 37211282 PMCID: PMC10527507 DOI: 10.1016/j.radonc.2023.109717] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 05/12/2023] [Accepted: 05/13/2023] [Indexed: 05/23/2023]
Abstract
INTRODUCTION Diffusion-weighted imaging (DWI) on MRI-linear accelerator (MR-linac) systems can potentially be used for monitoring treatment response and adaptive radiotherapy in head and neck cancers (HNC) but requires extensive validation. We performed technical validation to compare six total DWI sequences on an MR-linac and MR simulator (MR sim) in patients, volunteers, and phantoms. METHODS Ten human papillomavirus-positive oropharyngeal cancer patients and ten healthy volunteers underwent DWI on a 1.5 T MR-linac with three DWI sequences: echo planar imaging (EPI), split acquisition of fast spin echo signals (SPLICE), and turbo spin echo (TSE). Volunteers were also imaged on a 1.5 T MR sim with three sequences: EPI, BLADE (vendor tradename), and readout segmentation of long variable echo trains (RESOLVE). Participants underwent two scan sessions per device and two repeats of each sequence per session. Repeatability and reproducibility within-subject coefficient of variation (wCV) of mean ADC were calculated for tumors and lymph nodes (patients) and parotid glands (volunteers). ADC bias, repeatability/reproducibility metrics, SNR, and geometric distortion were quantified using a phantom. RESULTS In vivo repeatability/reproducibility wCV for parotids were 5.41%/6.72%, 3.83%/8.80%, 5.66%/10.03%, 3.44%/5.70%, 5.04%/5.66%, 4.23%/7.36% for EPIMR-linac, SPLICE, TSE, EPIMR sim, BLADE, RESOLVE. Repeatability/reproducibility wCV for EPIMR-linac, SPLICE, TSE were 9.64%/10.28%, 7.84%/8.96%, 7.60%/11.68% for tumors and 7.80%/9.95%, 7.23%/8.48%, 10.82%/10.44% for nodes. All sequences except TSE had phantom ADC biases within ± 0.1x10-3 mm2/s for most vials (EPIMR-linac, SPLICE, and BLADE had 2, 3, and 1 vials out of 13 with larger biases, respectively). SNR of b = 0 images was 87.3, 180.5, 161.3, 171.0, 171.9, 130.2 for EPIMR-linac, SPLICE, TSE, EPIMR sim, BLADE, RESOLVE. CONCLUSION MR-linac DWI sequences demonstrated near-comparable performance to MR sim sequences and warrant further clinical validation for treatment response assessment in HNC.
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Affiliation(s)
| | | | - Samuel Mulder
- The University of Texas MD Anderson Cancer Center, USA
| | - Sara Ahmed
- The University of Texas MD Anderson Cancer Center, USA
| | | | | | - Renjie He
- The University of Texas MD Anderson Cancer Center, USA
| | | | | | | | | | | | - Jihong Wang
- The University of Texas MD Anderson Cancer Center, USA
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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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Boeke S, Winter RM, Leibfarth S, Krueger MA, Bowden G, Cotton J, Pichler BJ, Zips D, Thorwarth D. Machine learning identifies multi-parametric functional PET/MR imaging cluster to predict radiation resistance in preclinical head and neck cancer models. Eur J Nucl Med Mol Imaging 2023; 50:3084-3096. [PMID: 37148296 PMCID: PMC10382355 DOI: 10.1007/s00259-023-06254-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 04/25/2023] [Indexed: 05/08/2023]
Abstract
PURPOSE Tumor hypoxia and other microenvironmental factors are key determinants of treatment resistance. Hypoxia positron emission tomography (PET) and functional magnetic resonance imaging (MRI) are established prognostic imaging modalities to identify radiation resistance in head-and-neck cancer (HNC). The aim of this preclinical study was to develop a multi-parametric imaging parameter specifically for focal radiotherapy (RT) dose escalation using HNC xenografts of different radiation sensitivities. METHODS A total of eight human HNC xenograft models were implanted into 68 immunodeficient mice. Combined PET/MRI using dynamic [18F]-fluoromisonidazole (FMISO) hypoxia PET, diffusion-weighted (DW), and dynamic contrast-enhanced MRI was carried out before and after fractionated RT (10 × 2 Gy). Imaging data were analyzed on voxel-basis using principal component (PC) analysis for dynamic data and apparent diffusion coefficients (ADCs) for DW-MRI. A data- and hypothesis-driven machine learning model was trained to identify clusters of high-risk subvolumes (HRSs) from multi-dimensional (1-5D) pre-clinical imaging data before and after RT. The stratification potential of each 1D to 5D model with respect to radiation sensitivity was evaluated using Cohen's d-score and compared to classical features such as mean/peak/maximum standardized uptake values (SUVmean/peak/max) and tumor-to-muscle-ratios (TMRpeak/max) as well as minimum/valley/maximum/mean ADC. RESULTS Complete 5D imaging data were available for 42 animals. The final preclinical model for HRS identification at baseline yielding the highest stratification potential was defined in 3D imaging space based on ADC and two FMISO PCs ([Formula: see text]). In 1D imaging space, only clusters of ADC revealed significant stratification potential ([Formula: see text]). Among all classical features, only ADCvalley showed significant correlation to radiation resistance ([Formula: see text]). After 2 weeks of RT, FMISO_c1 showed significant correlation to radiation resistance ([Formula: see text]). CONCLUSION A quantitative imaging metric was described in a preclinical study indicating that radiation-resistant subvolumes in HNC may be detected by clusters of ADC and FMISO using combined PET/MRI which are potential targets for future functional image-guided RT dose-painting approaches and require clinical validation.
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Affiliation(s)
- Simon Boeke
- Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
- German Cancer Consortium (DKTK), partner site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - René M Winter
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany
| | - Sara Leibfarth
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany
| | - Marcel A Krueger
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tübingen, Tübingen, Germany
| | - Gregory Bowden
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tübingen, Tübingen, Germany
| | - Jonathan Cotton
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tübingen, Tübingen, Germany
| | - Bernd J Pichler
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC 2180) "Image Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
| | - Daniel Zips
- Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
- German Cancer Consortium (DKTK), partner site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniela Thorwarth
- German Cancer Consortium (DKTK), partner site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany.
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany.
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20
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Bryant JM, Weygand J, Keit E, Cruz-Chamorro R, Sandoval ML, Oraiqat IM, Andreozzi J, Redler G, Latifi K, Feygelman V, Rosenberg SA. Stereotactic Magnetic Resonance-Guided Adaptive and Non-Adaptive Radiotherapy on Combination MR-Linear Accelerators: Current Practice and Future Directions. Cancers (Basel) 2023; 15:2081. [PMID: 37046741 PMCID: PMC10093051 DOI: 10.3390/cancers15072081] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 03/27/2023] [Accepted: 03/29/2023] [Indexed: 04/03/2023] Open
Abstract
Stereotactic body radiotherapy (SBRT) is an effective radiation therapy technique that has allowed for shorter treatment courses, as compared to conventionally dosed radiation therapy. As its name implies, SBRT relies on daily image guidance to ensure that each fraction targets a tumor, instead of healthy tissue. Magnetic resonance imaging (MRI) offers improved soft-tissue visualization, allowing for better tumor and normal tissue delineation. MR-guided RT (MRgRT) has traditionally been defined by the use of offline MRI to aid in defining the RT volumes during the initial planning stages in order to ensure accurate tumor targeting while sparing critical normal tissues. However, the ViewRay MRIdian and Elekta Unity have improved upon and revolutionized the MRgRT by creating a combined MRI and linear accelerator (MRL), allowing MRgRT to incorporate online MRI in RT. MRL-based MR-guided SBRT (MRgSBRT) represents a novel solution to deliver higher doses to larger volumes of gross disease, regardless of the proximity of at-risk organs due to the (1) superior soft-tissue visualization for patient positioning, (2) real-time continuous intrafraction assessment of internal structures, and (3) daily online adaptive replanning. Stereotactic MR-guided adaptive radiation therapy (SMART) has enabled the safe delivery of ablative doses to tumors adjacent to radiosensitive tissues throughout the body. Although it is still a relatively new RT technique, SMART has demonstrated significant opportunities to improve disease control and reduce toxicity. In this review, we included the current clinical applications and the active prospective trials related to SMART. We highlighted the most impactful clinical studies at various tumor sites. In addition, we explored how MRL-based multiparametric MRI could potentially synergize with SMART to significantly change the current treatment paradigm and to improve personalized cancer care.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Stephen A. Rosenberg
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA; (J.M.B.)
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Jassar H, Tai A, Chen X, Keiper TD, Paulson E, Lathuilière F, Bériault S, Hébert F, Savard L, Cooper DT, Cloake S, Li XA. Real-time motion monitoring using orthogonal cine MRI during MR-guided adaptive radiation therapy for abdominal tumors on 1.5T MR-Linac. Med Phys 2023; 50:3103-3116. [PMID: 36893292 DOI: 10.1002/mp.16342] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 02/01/2023] [Accepted: 02/24/2023] [Indexed: 03/11/2023] Open
Abstract
BACKGROUND Real-time motion monitoring (RTMM) is necessary for accurate motion management of intrafraction motions during radiation therapy (RT). PURPOSE Building upon a previous study, this work develops and tests an improved RTMM technique based on real-time orthogonal cine magnetic resonance imaging (MRI) acquired during magnetic resonance-guided adaptive RT (MRgART) for abdominal tumors on MR-Linac. METHODS A motion monitoring research package (MMRP) was developed and tested for RTMM based on template rigid registration between beam-on real-time orthogonal cine MRI and pre-beam daily reference 3D-MRI (baseline). The MRI data acquired under free-breathing during the routine MRgART on a 1.5T MR-Linac for 18 patients with abdominal malignancies of 8 liver, 4 adrenal glands (renal fossa), and 6 pancreas cases were used to evaluate the MMRP package. For each patient, a 3D mid-position image derived from an in-house daily 4D-MRI was used to define a target mask or a surrogate sub-region encompassing the target. Additionally, an exploratory case reviewed for an MRI dataset of a healthy volunteer acquired under both free-breathing and deep inspiration breath-hold (DIBH) was used to test how effectively the RTMM using the MMRP can address through-plane motion (TPM). For all cases, the 2D T2/T1-weighted cine MRIs were captured with a temporal resolution of 200 ms interleaved between coronal and sagittal orientations. Manually delineated contours on the cine frames were used as the ground-truth motion. Common visible vessels and segments of target boundaries in proximity to the target were used as anatomical landmarks for reproducible delineations on both the 3D and the cine MRI images. Standard deviation of the error (SDE) between the ground-truth and the measured target motion from the MMRP package were analyzed to evaluate the RTMM accuracy. The maximum target motion (MTM) was measured on the 4D-MRI for all cases during free-breathing. RESULTS The mean (range) centroid motions for the 13 abdominal tumor cases were 7.69 (4.71-11.15), 1.73 (0.81-3.05), and 2.71 (1.45-3.93) mm with an overall accuracy of <2 mm in the superior-inferior (SI), the left-right (LR), and the anterior-posterior (AP) directions, respectively. The mean (range) of the MTM from the 4D-MRI was 7.38 (2-11) mm in the SI direction, smaller than the monitored motion of centroid, demonstrating the importance of the real-time motion capture. For the remaining patient cases, the ground-truth delineation was challenging under free-breathing due to the target deformation and the large TPM in the AP direction, the implant-induced image artifacts, and/or the suboptimal image plane selection. These cases were evaluated based on visual assessment. For the healthy volunteer, the TPM of the target was significant under free-breathing which degraded the RTMM accuracy. RTMM accuracy of <2 mm was achieved under DIBH, indicating DIBH is an effective method to address large TPM. CONCLUSIONS We have successfully developed and tested the use of a template-based registration method for an accurate RTMM of abdominal targets during MRgART on a 1.5T MR-Linac without using injected contrast agents or radio-opaque implants. DIBH may be used to effectively reduce or eliminate TPM of abdominal targets during RTMM.
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Affiliation(s)
- Hassan Jassar
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - An Tai
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Xinfeng Chen
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Timothy D Keiper
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Eric Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | | | | | | | | | | | | | - X Allen Li
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
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22
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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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Paquier Z, Chao SL, Bregni G, Sanchez AV, Guiot T, Dhont J, Gulyban A, Levillain H, Sclafani F, Reynaert N, Bali MA. Pre-trial quality assurance of diffusion-weighted MRI for radiomic analysis and the role of harmonisation. Phys Med 2022; 103:138-146. [DOI: 10.1016/j.ejmp.2022.10.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 09/30/2022] [Accepted: 10/08/2022] [Indexed: 11/17/2022] Open
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Gurney-Champion OJ, Landry G, Redalen KR, Thorwarth D. Potential of Deep Learning in Quantitative Magnetic Resonance Imaging for Personalized Radiotherapy. Semin Radiat Oncol 2022; 32:377-388. [DOI: 10.1016/j.semradonc.2022.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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Habrich J, Boeke S, Nachbar M, Nikolaou K, Schick F, Gani C, Zips D, Thorwarth D. Repeatability of diffusion-weighted magnetic resonance imaging in head and neck cancer at a 1.5 T MR-Linac. Radiother Oncol 2022; 174:141-148. [PMID: 35902042 DOI: 10.1016/j.radonc.2022.07.020] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 07/18/2022] [Accepted: 07/19/2022] [Indexed: 11/26/2022]
Abstract
BACKGROUND AND PURPOSE Functional information acquired through diffusion-weighted magnetic resonance imaging (DW-MRI) may be beneficial for personalized head and neck cancer (HNC) radiotherapy. Technical validation is required before DW-MRI based radiotherapy interventions can be realized clinically. The aim of this study was to assess the repeatability of apparent diffusion coefficients (ADC) derived from DW-MRI in HNC using echo-planar imaging (EPI) on a 1.5 T MR-Linac. MATERIAL AND METHODS A total of eleven HNC patients underwent test/retest DW-MRI scans at least once per week during fractionated radiotherapy at the MR-Linac. An EPI DW-MRI test scan (b=0, 150, 500 s/mm2) was acquired before the start of adaptive MR-guided radiotherapy in addition to an identical retest scan after irradiation. Volumes-of-interest (VOI) were defined manually for parotid (PTs) and submandibular glands (SMs), gross tumor volume (GTV) and lymph nodes (LNs). Mean ADC was calculated for all VOI in all test/retest scans. Absolute/relative repeatability coefficients (RCs/relRCs) as well as intraclass correlation coefficients (ICCs) were determined for all VOI. RESULTS A total of 81 datasets were analyzed. Mean test ADC values were 1380/1416, 950/1010, 1520 and 1344·10-6 mm2/s for left/right SM and PT, GTV and LNs, respectively. Accordingly, RC (relRC) values were determined as 271/281 (19.4/21.8%) and 138/155 (13.3/15.2%), 457 (31.3%) and 310·10-6 mm2/s (23.5%). ICC resulted in 0.80/0.87, 0.97/0.94, 0.75 and 0.83 for left/right SM and PT, GTV and LNs, respectively. CONCLUSION The repeatability of ADC derived from EPI DW-MRI at the 1.5 T MR-Linac appears reasonable to be used for future biologically adapted MR-guided radiotherapy.
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Affiliation(s)
- Jonas Habrich
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Germany.
| | - Simon Boeke
- German Cancer Consortium (DKTK), partner site Tübingen; and German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Radiation Oncology, University of Tübingen, Germany
| | - Marcel Nachbar
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Germany
| | - Konstantin Nikolaou
- Department of Diagnostic and Interventional Radiology, University of Tübingen, Germany
| | - Fritz Schick
- Section for Experimental Radiology, Department of Diagnostic and Interventional Radiology, University of Tübingen, Germany
| | - Cihan Gani
- Department of Radiation Oncology, University of Tübingen, Germany
| | - Daniel Zips
- German Cancer Consortium (DKTK), partner site Tübingen; and German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Radiation Oncology, University of Tübingen, Germany
| | - Daniela Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Germany; German Cancer Consortium (DKTK), partner site Tübingen; and German Cancer Research Center (DKFZ), Heidelberg, Germany
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Ingle M, Blackledge M, White I, Wetscherek A, Lalondrelle S, Hafeez S, Bhide S. Quantitative analysis of diffusion weighted imaging in rectal cancer during radiotherapy using a magnetic resonance imaging integrated linear accelerator. Phys Imaging Radiat Oncol 2022; 23:32-37. [PMID: 35756883 PMCID: PMC9214864 DOI: 10.1016/j.phro.2022.06.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 05/16/2022] [Accepted: 06/02/2022] [Indexed: 11/25/2022] Open
Abstract
Background and purpose Magnetic resonance imaging integrated linear accelerator (MR-Linac) platforms enable acquisition of diffusion weighted imaging (DWI) during treatment providing potential information about treatment response. Obtaining DWI on these platforms is technically different from diagnostic magnetic resonance imaging (MRI) scanners. The aim of this project was to determine feasibility of obtaining DWI and calculating apparent diffusion coefficient (ADC) parameters longitudinally in rectal cancer patients on the MR-Linac. Materials and methods Nine patients undergoing treatment on MR-Linac had DWI acquired using b-values 0, 30, 150, 500 s/mm2. Gross tumour volume (GTV) and normal tissue was delineated on DWI throughout treatment and median ADC was calculated using an in-house tool (pyOsirix ®). Results Seven out of nine patients were included in the analysis; all demonstrated downstaging at follow-up. A total of 63 out of 70 DWI were analysed (7 excluded due to poor image quality). An increasing trend of ADC median for GTV (1.15 × 10-3 mm2/s interquartile range (IQ): 1.05-1.17 vs 1.59 × 10-3 mm2/s IQ: 1.37 - 1.64; p = 0.0156), correlating to treatment response. In comparison ADC median for normal tissue remained the same between first and last fraction (1.61 × 10-3 mm2/s IQ: 1.56-1.71 vs 1.67 × 10-3 mm2/s IQ: 1.37-2.00; p = 0.9375). Conclusions DWI assessment in rectal cancer patients on MR-Linac is feasible. Initial results provide foundations for further studies to determine DWI use for treatment adaptation in rectal cancer.
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Affiliation(s)
- Manasi Ingle
- The Royal Marsden Hospital NHS Trust, 203 Fulham Road, London SW3 6JJ, UK
- The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
| | - Matthew Blackledge
- The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
| | - Ingrid White
- Guys and St Thomas NHS Trust, Great Maze Pond, London SE1 9RT, UK
| | - Andreas Wetscherek
- The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
| | - Susan Lalondrelle
- The Royal Marsden Hospital NHS Trust, 203 Fulham Road, London SW3 6JJ, UK
- The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
| | - Shaista Hafeez
- The Royal Marsden Hospital NHS Trust, 203 Fulham Road, London SW3 6JJ, UK
- The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
| | - Shreerang Bhide
- The Royal Marsden Hospital NHS Trust, 203 Fulham Road, London SW3 6JJ, UK
- The Institute of Cancer Research, 123 Old Brompton Road, London SW7 3RP, UK
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Keall PJ, Brighi C, Glide-Hurst C, Liney G, Liu PZY, Lydiard S, Paganelli C, Pham T, Shan S, Tree AC, van der Heide UA, Waddington DEJ, Whelan B. Integrated MRI-guided radiotherapy - opportunities and challenges. Nat Rev Clin Oncol 2022; 19:458-470. [PMID: 35440773 DOI: 10.1038/s41571-022-00631-3] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/31/2022] [Indexed: 12/25/2022]
Abstract
MRI can help to categorize tissues as malignant or non-malignant both anatomically and functionally, with a high level of spatial and temporal resolution. This non-invasive imaging modality has been integrated with radiotherapy in devices that can differentially target the most aggressive and resistant regions of tumours. The past decade has seen the clinical deployment of treatment devices that combine imaging with targeted irradiation, making the aspiration of integrated MRI-guided radiotherapy (MRIgRT) a reality. The two main clinical drivers for the adoption of MRIgRT are the ability to image anatomical changes that occur before and during treatment in order to adapt the treatment approach, and to image and target the biological features of each tumour. Using motion management and biological targeting, the radiation dose delivered to the tumour can be adjusted during treatment to improve the probability of tumour control, while simultaneously reducing the radiation delivered to non-malignant tissues, thereby reducing the risk of treatment-related toxicities. The benefits of this approach are expected to increase survival and quality of life. In this Review, we describe the current state of MRIgRT, and the opportunities and challenges of this new radiotherapy approach.
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Affiliation(s)
- Paul J Keall
- ACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia.
| | - Caterina Brighi
- ACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia
| | - Carri Glide-Hurst
- Department of Human Oncology, University of Wisconsin, Madison, WI, USA
| | - Gary Liney
- Ingham Institute of Applied Medical Research, Sydney, New South Wales, Australia
| | - Paul Z Y Liu
- ACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia
| | - Suzanne Lydiard
- ACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia
| | - Chiara Paganelli
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy
| | - Trang Pham
- Faculty of Medicine and Health, The University of New South Wales, Sydney, New South Wales, Australia
| | - Shanshan Shan
- ACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia
| | - Alison C Tree
- The Royal Marsden NHS Foundation Trust and the Institute of Cancer Research, London, UK
| | - Uulke A van der Heide
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - David E J Waddington
- ACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia
| | - Brendan Whelan
- ACRF Image X Institute, The University of Sydney, Sydney, New South Wales, Australia
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Wong KL, Cheng KH, Lam SK, Liu C, Cai J. Review of functional magnetic resonance imaging in the assessment of nasopharyngeal carcinoma treatment response. PRECISION RADIATION ONCOLOGY 2022. [DOI: 10.1002/pro6.1161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Affiliation(s)
- Kwun Lam Wong
- Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong SAR People's Republic of China
- Department of Radiotherapy Hong Kong Sanatorium & Hospital HKSH Medical Group Hong Kong SAR People's Republic of China
| | - Ka Hei Cheng
- Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong SAR People's Republic of China
| | - Sai Kit Lam
- Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong SAR People's Republic of China
| | - Chenyang Liu
- Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong SAR People's Republic of China
| | - Jing Cai
- Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong SAR People's Republic of China
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29
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Welz S, Paulsen F, Pfannenberg C, Reimold M, Reischl G, Nikolaou K, La Fougère C, Alber M, Belka C, Zips D, Thorwarth D. Dose escalation to hypoxic subvolumes in head and neck cancer: A randomized phase II study using dynamic [ 18F]FMISO PET/CT. Radiother Oncol 2022; 171:30-36. [PMID: 35395276 DOI: 10.1016/j.radonc.2022.03.021] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 03/15/2022] [Accepted: 03/30/2022] [Indexed: 02/07/2023]
Abstract
BACKGROUND AND PURPOSE Tumor hypoxia is a major cause of resistance to radiochemotherapy in locally advanced head-and-neck cancer (LASCCHN). We present results of a randomized phase II trial on hypoxia dose escalation (DE) in LASCCHN based on dynamic [18F]FMISO (dynFMISO) positron emission tomography (PET). The purpose was to confirm the prognostic value of hypoxia PET and assess feasibility, toxicity and efficacy of hypoxia-DE. MATERIALS AND METHODS Patients with LASCCHN underwent baseline dynFMISO PET/CT. Hypoxic volumes (HV) were derived from dynFMISO data. Patients with hypoxic tumors (HV>0) were randomized into standard radiotherapy (ST: 70Gy/35fx) or dose escalation (DE: 77Gy/35fx) to the HV. Patients with non-hypoxic tumors were treated with ST. After a minimum follow-up of 2 years, feasibility, acute/late toxicity and local control (LC) were analyzed. RESULTS The study was closed prematurely due to slow accrual. Between 2009 and 2017, 53 patients were enrolled, 39 (74%) had hypoxic tumors and were randomized into ST or DE. For non-hypoxic patients, 100% 5-year LC was observed compared to 74% in patients with hypoxic tumors (p=0.039). The difference in 5-year LC between DE (16/19) and ST (10/17) was 25%, p=0.150. No relevant differences related to acute and late toxicities between the groups were observed. CONCLUSION This study confirmed the prognostic value of hypoxia PET in LASCCHN for LC. Outcome after hypoxia DE appears promising and may support the concept of DE. Slow accrual and premature closure may partly be due to a high complexity of the study setup which needs to be considered for future multicenter trials.
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Affiliation(s)
- Stefan Welz
- Department of Radiation Oncology, University Hospital Tübingen, University of Tübingen, Tübingen, Germany
| | - Frank Paulsen
- Department of Radiation Oncology, University Hospital Tübingen, University of Tübingen, Tübingen, Germany
| | - Christina Pfannenberg
- Department of Radiology, Diagnostic and Interventional Radiology, University Hospital Tübingen, University of Tübingen, Tübingen, Germany
| | - Matthias Reimold
- Department of Nuclear Medicine, University Hospital Tübingen, University of Tübingen, Tübingen, Germany
| | - Gerald Reischl
- Department of Preclinical Imaging and Radiopharmacy, University Hospital Tübingen, University of Tübingen, Tübingen, Germany; Cluster of Excellence iFIT (EXC 2180) "Image Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Germany
| | - Konstantin Nikolaou
- Department of Radiology, Diagnostic and Interventional Radiology, University Hospital Tübingen, University of Tübingen, Tübingen, Germany
| | - Christian La Fougère
- Department of Nuclear Medicine, University Hospital Tübingen, University of Tübingen, Tübingen, Germany
| | - Markus Alber
- Section for Medical Physics, Department of Radiation Oncology, Heidelberg University, Heidelberg, Germany
| | - Claus Belka
- Department of Radiation Oncology, University of Munich, Germany; Department of Radiation Oncology, LMU Munich, Germany
| | - Daniel Zips
- Department of Radiation Oncology, University Hospital Tübingen, University of Tübingen, Tübingen, Germany; German Cancer Consortium (DKTK), partner site Tübingen, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniela Thorwarth
- German Cancer Consortium (DKTK), partner site Tübingen, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany; Section for Biomedical Physics, Department of Radiation Oncology, University Hospital Tübingen, University of Tübingen, Tübingen, Germany.
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Carr ME, Keenan KE, Rai R, Boss MA, Metcalfe P, Walker A, Holloway L. Conformance of a 3T Radiotherapy MRI Scanner to the QIBA Diffusion Profile. Med Phys 2022; 49:4508-4517. [PMID: 35365884 PMCID: PMC9543906 DOI: 10.1002/mp.15645] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 03/12/2022] [Accepted: 03/16/2022] [Indexed: 11/11/2022] Open
Abstract
Purpose To assess the technical performance of the apparent diffusion coefficient (ADC) on a dedicated 3T radiotherapy scanner, using a standardized phantom and sequences. Investigations into factors that could impact the technical performance of ADC in the clinic were also completed, including changing the slice‐encoded imaging direction and the reference sample ADC value. Methods ADC acquisitions were performed monthly on an isotropic diffusion phantom over 1 year. Measurements of ADC %bias, coefficients of variation for short‐/long‐term repeatability and precision (CVST/CVLT and CVP), and b‐value dependency (Depb) were calculated. The measurements were then assessed according to the Quantitative Imaging Biomarker Alliance (QIBA) Diffusion Profile specifications. Results The average of all measurements over the year was within Profile recommended ranges. This included when testing was performed in different imaging directions, and on samples that had different ADC reference values (0.4–1.1 μm2/ms). Results in the axial plane for the central water vial included a bias of +0.05%, CVST /CVLT/CVP = 0.1%/ 0.9%/0.4% and Depb = 0.4%. Conclusions The technical performance of ADC on a radiotherapy dedicated MRI scanner over the course of 12 months was considered conformant to the QIBA Profile. Quantifying these metrics and factors that may affect the performance is essential in progressing the use of ADC clinically: ensuring that the observed change of ADC in a tissue is due to a physiological response and not measurement variability.
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Affiliation(s)
- Madeline E Carr
- Centre for Medical and Radiation Physics, University of Wollongong, Wollongong, Australia.,Ingham Institute for Applied Medical Research, Liverpool, Australia.,Liverpool and Macarthur Cancer Therapy Centres, Sydney, Australia
| | - Kathryn E Keenan
- National Institute of Standards and Technology, Boulder, United States
| | - Robba Rai
- Ingham Institute for Applied Medical Research, Liverpool, Australia.,Liverpool and Macarthur Cancer Therapy Centres, Sydney, Australia.,Institute of Medical Physics, University of Sydney, Camperdown, Australia
| | - Michael A Boss
- American College of Radiology, Philadelphia, United States
| | - Peter Metcalfe
- Centre for Medical and Radiation Physics, University of Wollongong, Wollongong, Australia.,Ingham Institute for Applied Medical Research, Liverpool, Australia
| | - Amy Walker
- Centre for Medical and Radiation Physics, University of Wollongong, Wollongong, Australia.,Ingham Institute for Applied Medical Research, Liverpool, Australia.,Liverpool and Macarthur Cancer Therapy Centres, Sydney, Australia.,Institute of Medical Physics, University of Sydney, Camperdown, Australia
| | - Lois Holloway
- Centre for Medical and Radiation Physics, University of Wollongong, Wollongong, Australia.,Ingham Institute for Applied Medical Research, Liverpool, Australia.,Liverpool and Macarthur Cancer Therapy Centres, Sydney, Australia.,Institute of Medical Physics, University of Sydney, Camperdown, Australia.,South Western Sydney Clinical School, University of New South Wales, Liverpool, Australia
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31
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Subashi E, Dresner A, Tyagi N. Longitudinal assessment of quality assurance measurements in a 1.5 T MR-linac: Part II-Magnetic resonance imaging. J Appl Clin Med Phys 2022; 23:e13586. [PMID: 35332990 PMCID: PMC9398228 DOI: 10.1002/acm2.13586] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 02/05/2022] [Accepted: 02/25/2022] [Indexed: 11/08/2022] Open
Abstract
PURPOSE To describe and report longitudinal quality assurance (QA) measurements for the magnetic resonance imaging (MRI) component of the Elekta Unity MR-linac during the first year of clinical use in our institution. MATERIALS AND METHODS The performance of the MRI component of Unity was evaluated with daily, weekly, monthly, and annual QA testing. The measurements monitor image uniformity, signal-to-noise ratio (SNR), resolution/detectability, slice position/thickness, linearity, central frequency, and geometric accuracy. In anticipation of routine use of quantitative imaging (qMRI), we characterize B0/B1 uniformity and the bias/reproducibility of longitudinal/transverse relaxation times (T1/T2) and apparent diffusion coefficient (ADC). Tolerance levels for QA measurements of qMRI biomarkers are derived from weekly monitoring of T1, T2, and ADC. RESULTS The 1-year assessment of QA measurements shows that daily variations in each MR quality metric are well below the threshold for failure. Routine testing procedures can reproducibly identify machine issues. The longitudinal three-dimensional (3D) geometric analysis reveals that the maximum distortion in a diameter of spherical volume (DSV) of 20, 30, 40, and 50 cm is 0.4, 0.6, 1.0, and 3.1 mm, respectively. The main source of distortion is gradient nonlinearity. Maximum peak-to-peak B0 inhomogeneity is 3.05 ppm, with gantry induced B0 inhomogeneities an order of magnitude smaller. The average deviation from the nominal B1 is within 2%, with minimal dependence on gantry angle. Mean ADC, T1, and T2 values are measured with high reproducibility. The median coefficient of variation for ADC, T1, and T2 is 1.3%, 1.1%, and 0.5%, respectively. The median bias for ADC, T1, and T2 is -0.8%, -0.1%, and 3.9%, respectively. CONCLUSION The MRI component of Unity operates within the guidelines and recommendations for scanner performance and stability. Our findings support the recently published guidance in establishing clinically acceptable tolerance levels for image quality. Highly reproducible qMRI measurements are feasible in Unity.
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Affiliation(s)
- Ergys Subashi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Alex Dresner
- Philips Healthcare MR Oncology, Cleveland, Ohio, USA
| | - Neelam Tyagi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
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32
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Snyder JE, St-Aubin J, Yaddanapudi S, Marshall S, Strand S, Kruger S, Flynn R, Hyer DE. Reducing MRI-guided radiotherapy planning and delivery times via efficient leaf sequencing and segment shape optimization algorithms. Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac5299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 02/07/2022] [Indexed: 11/12/2022]
Abstract
Abstract
Objective. Extended treatment session times are an operational limitation in magnetic resonance imaging guided adaptive radiotherapy (MRIgRT). In this study a novel leaf sequencing algorithm called optimal fluence levels (OFL) and an optimization algorithm called pseudo gradient descent (PGD) are evaluated with respect to plan quality, beam complexity, and the ability to reduce treatment session times on the Elekta Unity MRIgRT system. Approach. Ten total patients were evaluated on this Institutional Review Board approved study: three with prostate cancer, three with oligometastases, two with pancreatic cancer, and two with liver cancer. Plans were generated using the clinical Monaco Hyperion optimizer and leaf sequencer and then re-optimized using OFL and PGD (OFL + PGD) while holding all IMRT constraints and planning parameters constant. All plans were normalized to ensure 95% of the PTV received the prescription dose. A paired t-test was used to evaluate statistical significance. Main Results. Plan quality in terms of dosimetric OAR sparing was found to be equivalent between the OFL + PGD and conventional Monaco Hyperion optimizer plans. The OFL + PGD plans had a reduction in optimization time of 51.4% ± 5.0% (p = 0.002) and reduction in treatment delivery time of 10.6% ± 7.5% (p = 0.005). OFL + PGD generated plans had on average 13.2% ± 12.6% fewer multi-leaf collimator (MLC) segments (p = 0.009) and 0.1 ± 0.1 lower plan averaged beam modulation (PM) (p = 0.004) relative to the Monaco Hyperion plans. Significance. The OFL + PGD algorithms more quickly generate Unity treatment plans that are faster to deliver than with the conventional approach and without compromising dosimetric plan quality. This is likely due to a delivery complexity reduction enabled by OFL + PGD relative to the Monaco Hyperion plans.
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Sritharan K, Tree A. MR-guided radiotherapy for prostate cancer: state of the art and future perspectives. Br J Radiol 2022; 95:20210800. [PMID: 35073158 PMCID: PMC8978250 DOI: 10.1259/bjr.20210800] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 11/16/2021] [Accepted: 12/22/2021] [Indexed: 12/25/2022] Open
Abstract
Advances in radiotherapy technology have increased precision of treatment delivery and in some tumour types, improved cure rates and decreased side effects. A new generation of radiotherapy machines, hybrids of an MRI scanner and a linear accelerator, has the potential to further transform the practice of radiation therapy in some cancers. Facilitating superior image quality and the ability to change the dose distribution online on a daily basis (termed "daily adaptive replanning"), MRI-guided radiotherapy machines allow for new possibilities including increasing dose, for hard to treat cancers, and more selective sparing of healthy tissues, where toxicity reduction is the key priority.These machines have already been used to treat most types of cancer, although experience is still in its infancy. This review summarises the potential and current evidence for MRI-guided radiotherapy, with a predominant focus on prostate cancer. Current advantages and disadvantages are discussed including a realistic appraisal of the likely potential to improve patient outcomes. In addition, horizon scanning for near-term possibilities for research and development will hopefully delineate the potential role for this technology over the next decade.
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34
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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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Overgaard J, Aznar MC, Bacchus C, Coppes RP, Deutsch E, Georg D, Haustermans K, Hoskin P, Krause M, Lartigau EF, Lee AWM, Löck S, Offersen BV, Thwaites DI, van der Kogel AJ, van der Heide UA, Valentini V, Baumann M. Personalised radiation therapy taking both the tumour and patient into consideration. Radiother Oncol 2022; 166:A1-A5. [PMID: 35051440 DOI: 10.1016/j.radonc.2022.01.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 01/04/2022] [Indexed: 12/14/2022]
Affiliation(s)
- Jens Overgaard
- Department of Experimental Clinical Oncology, Aarhus University Hospital, Denmark.
| | - Marianne C Aznar
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, The Christie NHS Foundation Trust, United Kingdom
| | - Carol Bacchus
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Rob P Coppes
- Departments of Radiation Oncology and Biomedical Sciences of Cells & Systems, Section Molecular Cell Biology, University of Groningen, University Medical Center Groningen, the Netherlands
| | - Eric Deutsch
- Department of Radiation Oncology, Institut d'Oncologie Thoracique (IOT), Gustave Roussy, France
| | - Dietmar Georg
- Division Medical Radiation Physics, Department of Radiation Oncology, Medical University of Vienna/AKH Wien, Austria
| | - Karin Haustermans
- Department of Radiation Oncology, University Hospitals Leuven, Belgium
| | - Peter Hoskin
- Mount Vernon Cancer Centre and University of Manchester, United Kingdom
| | - Mechthild Krause
- Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Germany; OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Germany
| | - Eric F Lartigau
- Academic Department of Radiotherapy, Oscar Lambret Comprehensive Cancer Center, Lille, France
| | - Anne W M Lee
- Department of Clinical Oncology, University of Hong Kong - Shenzhen Hospital and University of Hong Kong, China
| | - Steffen Löck
- OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Germany
| | - Birgitte V Offersen
- Department of Experimental Clinical Oncology, Aarhus University Hospital, Denmark
| | - David I Thwaites
- Institute of Medical Physics, School of Physics, The University of Sydney, Australia; Medical Physics Group, Leeds Institute of Medical Research, School of Medicine, University of Leeds, United Kingdom
| | - Albert J van der Kogel
- Department of Human Oncology, University of Wisconsin School of Medicine and Public Health, Madison, USA
| | - Uulke A van der Heide
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Vincenzo Valentini
- Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia, UOC Radioterapia Oncologica, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy
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Akdag O, Mandija S, van Lier AL, Borman PT, Schakel T, Alberts E, van der Heide O, Hassink RJ, Verhoeff JJ, Mohamed Hoesein FA, Raaymakers BW, Fast MF. Feasibility of cardiac-synchronized quantitative T1 and T2 mapping on a hybrid 1.5 Tesla magnetic resonance imaging and linear accelerator system. Phys Imaging Radiat Oncol 2022; 21:153-159. [PMID: 35287380 PMCID: PMC8917300 DOI: 10.1016/j.phro.2022.02.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 02/18/2022] [Accepted: 02/20/2022] [Indexed: 11/30/2022] Open
Abstract
Background and Purpose Materials and methods Results Conclusions
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Affiliation(s)
- Osman Akdag
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
- Corresponding author.
| | - Stefano Mandija
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
- Computational Imaging Group for MR Diagnostics and Therapy, Center for Image Sciences, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Astrid L.H.M.W. van Lier
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Pim T.S. Borman
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Tim Schakel
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Eveline Alberts
- Philips Healthcare, Veenpluis 6 5684 PC Best, The Netherlands
| | - Oscar van der Heide
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
- Computational Imaging Group for MR Diagnostics and Therapy, Center for Image Sciences, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Rutger J. Hassink
- Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Joost J.C. Verhoeff
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Firdaus A.A. Mohamed Hoesein
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Bas W. Raaymakers
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Martin F. Fast
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
- Corresponding author.
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Kim N, Tringale KR, Crane C, Tyagi N, Otazo R. MR SIGnature MAtching (MRSIGMA) with retrospective self-evaluation for real-time volumetric motion imaging. Phys Med Biol 2021; 66. [PMID: 34619666 DOI: 10.1088/1361-6560/ac2dd2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 10/07/2021] [Indexed: 11/11/2022]
Abstract
Objective. MR SIGnature MAtching (MRSIGMA) is a real-time volumetric MRI technique to image tumor and organs at risk motion in real-time for radiotherapy applications, where a dictionary of high-resolution 3D motion states and associated motion signatures are computed first during offline training and real-time 3D imaging is performed afterwards using fast signature-only acquisition and signature matching. However, the lack of a reference image with similar spatial resolution and temporal resolution introduces significant challenges forin vivovalidation.Approach. This work proposes a retrospective self-validation for MRSIGMA, where the same data used for real-time imaging are used to create a non-real-time reference for comparison. MRSIGMA with self-validation is tested in patients with liver tumors using quantitative metrics defined on the tumor and nearby organs-at-risk structures. The dice coefficient between contours defined on the real-time MRSIGMA and non-real-time reference was used to assess motion imaging performance.Main Results. Total latency (including signature acquisition and signature matching) was between 250 and 314 ms, which is sufficient for organs affected by respiratory motion. Mean ± standard deviation dice coefficient over time was 0.74 ± 0.03 for patients imaged without contrast agent and 0.87 ± 0.03 for patients imaged with contrast agent, which demonstrated high-performance real-time motion imaging.Signficance. MRSIGMA with self-evaluation provides a means to perform real-time volumetric MRI for organ motion tracking with quantitative performance measures.
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Affiliation(s)
- Nathanael Kim
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America
| | - Kathryn R Tringale
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America
| | - Christopher Crane
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America
| | - Neelam Tyagi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America
| | - Ricardo Otazo
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.,Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America
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de Leon J, Crawford D, Moutrie Z, Alvares S, Hogan L, Pagulayan C, Jelen U, Loo C, Aylward JD, Condon K, Dunkerley N, Heinke MY, Sampaio S, Simon K, Twentyman T, Jameson MG. Early experience with MR-guided adaptive radiotherapy using a 1.5 T MR-Linac: First 6 months of operation using adapt to shape workflow. J Med Imaging Radiat Oncol 2021; 66:138-145. [PMID: 34643065 DOI: 10.1111/1754-9485.13336] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 09/17/2021] [Indexed: 11/26/2022]
Abstract
INTRODUCTION The magnetic resonance linear accelerator (MRL) offers improved soft tissue visualization to guide daily adaptive radiotherapy treatment. This manuscript aims to report initial experience using a 1.5 T MRL in the first 6 months of operation, including training, workflows, timings and dosimetric accuracy. METHODS All staff received training in MRI safety and MRL workflows. Initial sites chosen for treatment were stereotactic and hypofractionated prostate, thoraco-abdomino-pelvic metastasis, prostate bed and bladder. The Adapt To Shape (ATS) workflow was chosen to be the focus of treatment as it is the most robust solution for daily adaptive radiotherapy. A workflow was created addressing patient suitability, simulation, planning, treatment and peer review. Treatment times were recorded breaking down into the various stages of treatment. RESULTS A total of 37 patients were treated and 317 fractions delivered (of which 313 were delivered using an ATS workflow) in our initial 6 months. Average treatment times over the entire period were 50 and 38 min for stereotactic and non-stereotactic treatments respectively. Average treatment times reduced each month. The average difference between reference planned and ionization chamber measured dose was 0.0 ± 1.4%. CONCLUSION The MRL was successfully established in an Australian setting. A focus on training and creating a detailed workflow from patient selection, review and treatment are paramount to establishing new treatment programmes.
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Affiliation(s)
| | | | - Zoë Moutrie
- GenesisCare, Sydney, New South Wales, Australia
| | | | | | | | | | - Conrad Loo
- GenesisCare, Sydney, New South Wales, Australia
| | - Jack D Aylward
- GenesisCare, Sydney, New South Wales, Australia.,Division of Cancer Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Manchester, UK.,Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, The University of Manchester, Manchester, UK
| | | | | | | | | | - Kathy Simon
- GenesisCare, Sydney, New South Wales, Australia
| | | | - Michael G Jameson
- GenesisCare, Sydney, New South Wales, Australia.,Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
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Lawrence LSP, Chan RW, Chen H, Keller B, Stewart J, Ruschin M, Chugh B, Campbell M, Theriault A, Stanisz GJ, MacKenzie S, Myrehaug S, Detsky J, Maralani PJ, Tseng CL, Czarnota GJ, Sahgal A, Lau AZ. Accuracy and precision of apparent diffusion coefficient measurements on a 1.5 T MR-Linac in central nervous system tumour patients. Radiother Oncol 2021; 164:155-162. [PMID: 34592363 DOI: 10.1016/j.radonc.2021.09.020] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 09/20/2021] [Accepted: 09/22/2021] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND PURPOSE MRI linear accelerators (MR-Linacs) may allow treatment adaptation to be guided by quantitative MRI including diffusion-weighted imaging (DWI). The aim of this study was to evaluate the accuracy and precision of apparent diffusion coefficient (ADC) measurements from DWI on a 1.5 T MR-Linac in patients with central nervous system (CNS) tumours through comparison with a diagnostic scanner. MATERIALS AND METHODS CNS patients were treated using a 1.5 T Elekta Unity MR-Linac. DWI was acquired during MR-Linac treatment and on a Philips Ingenia 1.5 T. The agreement between the two scanners on median ADC over the gross tumour/clinical target volumes (GTV/CTV) and in brain regions (white/grey matter, cerebrospinal fluid (CSF)) was computed. Repeated scans were used to estimate ADC repeatability. Daily changes in ADC over the GTV of high-grade gliomas were characterized from MR-Linac scans. RESULTS DWI from 59 patients was analyzed. MR-Linac ADC measurements showed a small bias relative to Ingenia measurements in white matter, grey matter, GTV, and CTV (bias: -0.05 ± 0.03, -0.08 ± 0.05, -0.1 ± 0.1, -0.08 ± 0.07 μm2/ms). ADC differed substantially in CSF (bias: -0.5 ± 0.3 μm2/ms). The repeatability of MR-Linac ADC over white/grey matter was similar to previous reports (coefficients of variation for median ADC: 1.4%/1.8%). MR-Linac ADC changes in the GTV were detectable. CONCLUSIONS It is possible to obtain ADC measurements in the brain on a 1.5 T MR-Linac that are comparable to those of diagnostic-quality scanners. This technical validation study adds to the foundation for future studies that will correlate brain tumour ADC with clinical outcomes.
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Affiliation(s)
- Liam S P Lawrence
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Rachel W Chan
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada
| | - Hanbo Chen
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Brian Keller
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - James Stewart
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Mark Ruschin
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Brige Chugh
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada; Department of Physics, Ryerson University, Toronto, Canada
| | - Mikki Campbell
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Aimee Theriault
- Department of Medical Biophysics, University of Toronto, Toronto, Canada; Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Neurosurgery and Paediatric Neurosurgery, Medical University, Lublin, Poland
| | - Greg J Stanisz
- Department of Medical Biophysics, University of Toronto, Toronto, Canada; Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Neurosurgery and Paediatric Neurosurgery, Medical University, Lublin, Poland
| | - Scott MacKenzie
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Sten Myrehaug
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Jay Detsky
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Pejman J Maralani
- Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Chia-Lin Tseng
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Greg J Czarnota
- Department of Medical Biophysics, University of Toronto, Toronto, Canada; Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada; Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Arjun Sahgal
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Angus Z Lau
- Department of Medical Biophysics, University of Toronto, Toronto, Canada; Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada.
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Xue C, Yuan J, Poon DM, Zhou Y, Yang B, Yu SK, Cheung YK. Reliability of MRI radiomics features in MR-guided radiotherapy for prostate cancer: Repeatability, reproducibility, and within-subject agreement. Med Phys 2021; 48:6976-6986. [PMID: 34562286 DOI: 10.1002/mp.15232] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 08/27/2021] [Accepted: 09/03/2021] [Indexed: 01/06/2023] Open
Abstract
PURPOSE The MR-guided radiotherapy (MRgRT) images on the integrated MRI and linear accelerator (MR-LINAC) might facilitate radiomics analysis for longitudinal treatment response assessment. However, the reliability of MRgRT radiomics features is largely unknown. This study aims to investigate MRgRT radiomics feature reliability acquired using a standardized 3D-T2W-TSE sequence in terms of repeatability, reproducibility, and within-subject feature agreement on a 1.5T MR-simulator and a 1.5T MR-LINAC for prostate cancer (PC). METHODS Twenty-six consecutive PC patients who underwent one MRI-simulator scan and two MR-LINAC scans before dose delivery were retrospectively included. The three MRI datasets were rigidly co-registered. 1023 first-order and texture radiomics features were extracted with different intensity bin widths for each scan in the manually segmented clinical target volume (CTV) and planning target volume (PTV) by an experienced radiation oncologist. Intraclass correlation coefficient (ICC) was used to evaluate feature repeatability between MR-LINAC scans and reproducibility between MRI-simulator and MR-LINAC scans. The within-subject feature value agreements were evaluated using Bland-Altman analysis. The impact of inter-observer segmentation on the radiomics feature reliability was also examined based on the second manual segmentation of CTV and PTV by an MRI researcher. RESULTS Based on the segmentation by the radiation oncologist and the default bin width of 25, 9.6%, 24.1%, 49.6%, and 16.8% of the total 1023 features exhibited excellent (ICC > 0.9), good (0.9 > ICC > 0.75), moderate (0.75 > ICC > 0.5), and poor (ICC < 0.5) repeatability in the CTV, and 9.2%, 26.8%, 50.5%, and 13.5% in the PTV, respectively. For reproducibility, the corresponding feature percentages were 8.9%, 19.7%, 41.9%, and 29.6% in the CTV, and 8.4%, 17.8%, 47.9%, and 26% in the PTV. Feature reliability was not notably influenced by intensity bin width for discretization. BA analysis revealed wide 95% limit-of-agreements and substantial biases of feature values between CTV and PTV and between any two MRI scans. The features even with excellent ICC were still subjected to considerable inter-scan feature variations in each individual subject. The analysis on the second segmentation by the MRI researcher showed insignificantly different feature repeatability and reproducibility in terms of ICC values. CONCLUSIONS Only a small proportion of features exhibited excellent/good repeatability and reproducibility, highlighting the importance of reliable MRgRT feature selection. The within-subject feature values were subjected to considerable inter-scan variations, imposing a challenge on the determination of the smallest detectable change in future MRgRT delta-radiomics studies.
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Affiliation(s)
- Cindy Xue
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, Hong Kong, SAR, China
| | - Jing Yuan
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, Hong Kong, SAR, China
| | - Darren Mc Poon
- Comprehensive Oncology Center, Hong Kong Sanatorium & Hospital, Hong Kong, Hong Kong, SAR, China
| | - Yihang Zhou
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, Hong Kong, SAR, China
| | - Bin Yang
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, Hong Kong, SAR, China
| | - Siu Ki Yu
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, Hong Kong, SAR, China
| | - Yin Kin Cheung
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, Hong Kong, SAR, China
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Salzillo TC, Taku N, Wahid KA, McDonald BA, Wang J, van Dijk LV, Rigert JM, Mohamed ASR, Wang J, Lai SY, Fuller CD. Advances in Imaging for HPV-Related Oropharyngeal Cancer: Applications to Radiation Oncology. Semin Radiat Oncol 2021; 31:371-388. [PMID: 34455992 DOI: 10.1016/j.semradonc.2021.05.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
While there has been an overall decline of tobacco and alcohol-related head and neck cancer in recent decades, there has been an increased incidence of HPV-associated oropharyngeal cancer (OPC). Recent research studies and clinical trials have revealed that the cancer biology and clinical progression of HPV-positive OPC is unique relative to its HPV-negative counterparts. HPV-positive OPC is associated with higher rates of disease control following definitive treatment when compared to HPV-negative OPC. Thus, these conditions should be considered unique diseases with regards to treatment strategies and survival. In order to sufficiently characterize HPV-positive OPC and guide treatment strategies, there has been a considerable effort to diagnose, prognose, and track the treatment response of HPV-associated OPC through advanced imaging research. Furthermore, HPV-positive OPC patients are prime candidates for radiation de-escalation protocols, which will ideally reduce toxicities associated with radiation therapy and has prompted additional imaging research to detect radiation-induced changes in organs at risk. This manuscript reviews the various imaging modalities and current strategies for tackling these challenges as well as provides commentary on the potential successes and suggested improvements for the optimal treatment of these tumors.
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Affiliation(s)
- Travis C Salzillo
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX.
| | - Nicolette Taku
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX.
| | - Kareem A Wahid
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX.
| | - Brigid A McDonald
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX; Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX.
| | - Jarey Wang
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX.
| | - Lisanne V van Dijk
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX.
| | - Jillian M Rigert
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX; Department of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX.
| | - Abdallah S R Mohamed
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX.
| | - Jihong Wang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX.
| | - Stephen Y Lai
- Department of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX.
| | - Clifton D Fuller
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX.
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Kooreman ES, van Houdt PJ, Keesman R, van Pelt VWJ, Nowee ME, Pos F, Sikorska K, Wetscherek A, Müller AC, Thorwarth D, Tree AC, van der Heide UA. Daily Intravoxel Incoherent Motion (IVIM) In Prostate Cancer Patients During MR-Guided Radiotherapy-A Multicenter Study. Front Oncol 2021; 11:705964. [PMID: 34485138 PMCID: PMC8415108 DOI: 10.3389/fonc.2021.705964] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 07/16/2021] [Indexed: 12/11/2022] Open
Abstract
PURPOSE Daily quantitative MR imaging during radiotherapy of cancer patients has become feasible with MRI systems integrated with linear accelerators (MR-linacs). Quantitative images could be used for treatment response monitoring. With intravoxel incoherent motion (IVIM) MRI, it is possible to acquire perfusion information without the use of contrast agents. In this multicenter study, daily IVIM measurements were performed in prostate cancer patients to identify changes that potentially reflect response to treatment. MATERIALS AND METHODS Forty-three patients were included, treated with 20 fractions of 3 Gy on a 1.5 T MR-linac. IVIM measurements were performed on each treatment day. The diffusion coefficient (D), perfusion fraction (f), and pseudo-diffusion coefficient (D*) were calculated based on the median signal intensities in the non-cancerous prostate and the tumor. Repeatability coefficients (RCs) were determined based on the first two treatment fractions. Separate linear mixed-effects models were constructed for the three IVIM parameters. RESULTS In total, 726 fractions were analyzed. Pre-treatment average values, measured on the first fraction before irradiation, were 1.46 × 10-3 mm2/s, 0.086, and 28.7 × 10-3 mm2/s in the non-cancerous prostate and 1.19 × 10-3 mm2/s, 0.088, and 28.9 × 10-3 mm2/s in the tumor, for D, f, and D*, respectively. The repeatability coefficients for D, f, and D* in the non-cancerous prostate were 0.09 × 10-3 mm2/s, 0.05, and 15.3 × 10-3 mm2/s. In the tumor, these values were 0.44 × 10-3 mm2/s, 0.16, and 76.4 × 10-3 mm2/s. The mixed effects analysis showed an increase in D of the tumors over the course of treatment, while remaining stable in the non-cancerous prostate. The f and D* increased in both the non-cancerous prostate and tumor. CONCLUSIONS It is feasible to perform daily IVIM measurements on an MR-linac system. Although the repeatability coefficients were high, changes in IVIM perfusion parameters were measured on a group level, indicating that IVIM has potential for measuring treatment response.
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Affiliation(s)
- Ernst S. Kooreman
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Petra J. van Houdt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Rick Keesman
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Vivian W. J. van Pelt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Marlies E. Nowee
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Floris Pos
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Karolina Sikorska
- Department of Biometrics, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Andreas Wetscherek
- Joint Department of Physics, The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London, United Kingdom
| | | | - Daniela Thorwarth
- Section of Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Alison C. Tree
- Joint Department of Physics, The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London, United Kingdom
| | - Uulke A. van der Heide
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
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van Houdt PJ, Saeed H, Thorwarth D, Fuller CD, Hall WA, McDonald BA, Shukla-Dave A, Kooreman ES, Philippens MEP, van Lier ALHMW, Keesman R, Mahmood F, Coolens C, Stanescu T, Wang J, Tyagi N, Wetscherek A, van der Heide UA. Integration of quantitative imaging biomarkers in clinical trials for MR-guided radiotherapy: Conceptual guidance for multicentre studies from the MR-Linac Consortium Imaging Biomarker Working Group. Eur J Cancer 2021; 153:64-71. [PMID: 34144436 PMCID: PMC8340311 DOI: 10.1016/j.ejca.2021.04.041] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 04/27/2021] [Indexed: 12/14/2022]
Abstract
Quantitative imaging biomarkers (QIBs) derived from MRI techniques have the potential to be used for the personalised treatment of cancer patients. However, large-scale data are missing to validate their added value in clinical practice. Integrated MRI-guided radiotherapy (MRIgRT) systems, such as hybrid MRI-linear accelerators, have the unique advantage that MR images can be acquired during every treatment session. This means that high-frequency imaging of QIBs becomes feasible with reduced patient burden, logistical challenges, and costs compared to extra scan sessions. A wealth of valuable data will be collected before and during treatment, creating new opportunities to advance QIB research at large. The aim of this paper is to present a roadmap towards the clinical use of QIBs on MRIgRT systems. The most important need is to gather and understand how the QIBs collected during MRIgRT correlate with clinical outcomes. As the integrated MRI scanner differs from traditional MRI scanners, technical validation is an important aspect of this roadmap. We propose to integrate technical validation with clinical trials by the addition of a quality assurance procedure at the start of a trial, the acquisition of in vivo test-retest data to assess the repeatability, as well as a comparison between QIBs from MRIgRT systems and diagnostic MRI systems to assess the reproducibility. These data can be collected with limited extra time for the patient. With integration of technical validation in clinical trials, the results of these trials derived on MRIgRT systems will also be applicable for measurements on other MRI systems.
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Affiliation(s)
- Petra J van Houdt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 102, Amsterdam, 1066CX, the Netherlands.
| | - Hina Saeed
- Department of Radiation Oncology, Medical College of Wisconsin, 9200 W Wisconsin Av, Milwaukee, WI, 53226, USA.
| | - Daniela Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Hoppe-Seyler-Str. 3, Tübingen, 72076, Germany.
| | - Clifton D Fuller
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 0097, Houston, TX, 77030, USA.
| | - William A Hall
- Department of Radiation Oncology, Medical College of Wisconsin, 9200 W Wisconsin Av, Milwaukee, WI, 53226, USA.
| | - Brigid A McDonald
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 0097, Houston, TX, 77030, USA.
| | - Amita Shukla-Dave
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA.
| | - Ernst S Kooreman
- Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 102, Amsterdam, 1066CX, the Netherlands.
| | - Marielle E P Philippens
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, the Netherlands.
| | - Astrid L H M W van Lier
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, the Netherlands.
| | - Rick Keesman
- Department of Radiation Oncology, Radboud University Medical Center, Geert Grooteplein Zuid 32, Nijmegen, 6525GA, the Netherlands.
| | - Faisal Mahmood
- Laboratory of Radiation Physics, Department of Oncology, Odense University Hospital, Kløvervænget 19, Odense C, 5000, Denmark; Department of Clinical Research, University of Southern Denmark, J. B. Winsløws Vej 19.3, Odense C, 5000, Denmark.
| | - Catherine Coolens
- Department of Medical Physics, Princess Margaret Cancer Centre and University Health Network, 700 University Avenue, Toronto, Ontario, M5M 1G7, Canada.
| | - Teodor Stanescu
- Department of Medical Physics, Princess Margaret Cancer Centre and University Health Network, 700 University Avenue, Toronto, Ontario, M5M 1G7, Canada; Department of Radiation Oncology, University of Toronto, 610 University Avenue, Toronto, Ontario, M5G 2M9, Canada.
| | - Jihong Wang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Unit 0097, Houston, TX, 77030, USA.
| | - Neelam Tyagi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA.
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and the Royal Marsden NHS Foundation Trust, 15 Cotswold Road, London, SM2 5NG, United Kingdom.
| | - Uulke A van der Heide
- Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 102, Amsterdam, 1066CX, the Netherlands.
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Wegener D, Zips D, Gani C, Boeke S, Nikolaou K, Othman AE, Almansour H, Paulsen F, Müller AC. [Primary treatment of prostate cancer using 1.5 T MR-linear accelerator]. Radiologe 2021; 61:839-845. [PMID: 34297139 PMCID: PMC8410708 DOI: 10.1007/s00117-021-00882-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/17/2021] [Indexed: 11/26/2022]
Abstract
Hintergrund Der potenzielle Nutzen des verbesserten Weichteilkontrastes von MR-Sequenzen gegenüber der Computertomographie (CT) für die Radiotherapie des Prostatakarzinoms ist bekannt und führt zu konsistenteren und kleineren Zielvolumina sowie verbesserter Risikoorganschonung. Hybridgeräte aus Magnetresonanztomographie (MRT) und Linearbeschleuniger (MR-Linac) stellen eine neue vielversprechende Erweiterung der radioonkologischen Therapieoptionen dar. Material und Methoden Dieser Artikel gibt eine Übersicht über bisherige Erfahrungen, Indikationen, Vorteile und Herausforderungen für die Radiotherapie des primären Prostatakarzinoms mit dem 1,5-T-MR-Linac. Ergebnisse Alle strahlentherapeutischen Therapieindikationen für das primäre Prostatakarzinom können mit dem 1,5-T-MR-Linac abgedeckt werden. Die potenziellen Vorteile umfassen die tägliche MR-basierte Lagekontrolle in Bestrahlungsposition und die Möglichkeit der täglichen Echtzeitanpassung des Bestrahlungsplans an die aktuelle Anatomie der Beckenorgane (adaptive Strahlentherapie). Zusätzlich werden am 1,5-T-MR-Linac funktionelle MRT-Sequenzen für individuelles Response-Assessment für die Therapieanpassung untersucht. Dadurch soll das therapeutische Fenster weiter optimiert werden. Herausforderungen stellen u. a. die technische Komplexität und die Dauer der Behandlungssitzung dar. Schlussfolgerung Der 1,5-T-MR-Linac erweitert das radioonkologische Spektrum in der Therapie des Prostatakarzinoms und bietet Vorteile durch tagesaktuelle MRT-basierte Zielvolumendefinition und Planadaptation. Weitere klinische Untersuchungen sind notwendig, um die Patienten zu identifizieren, die von der Behandlung am MR-Linac gegenüber anderen strahlentherapeutischen Methoden besonders profitieren.
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Affiliation(s)
- Daniel Wegener
- Universitätsklinik für Radioonkologie, Universitätsklinikum Tübingen, Eberhard Karls Universität Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Deutschland.
| | - Daniel Zips
- Universitätsklinik für Radioonkologie, Universitätsklinikum Tübingen, Eberhard Karls Universität Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Deutschland
| | - Cihan Gani
- Universitätsklinik für Radioonkologie, Universitätsklinikum Tübingen, Eberhard Karls Universität Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Deutschland
| | - Simon Boeke
- Universitätsklinik für Radioonkologie, Universitätsklinikum Tübingen, Eberhard Karls Universität Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Deutschland
| | - Konstantin Nikolaou
- Universitätsklinik für Radiologie, Eberhard Karls Universität Tübingen, Tübingen, Deutschland
| | - Ahmed E Othman
- Universitätsklinik für Radiologie, Eberhard Karls Universität Tübingen, Tübingen, Deutschland
- Universitätsklink für Neuroradiologie, Johannes Gutenberg-Universität Mainz, Mainz, Deutschland
| | - Haidara Almansour
- Universitätsklinik für Radiologie, Eberhard Karls Universität Tübingen, Tübingen, Deutschland
| | - Frank Paulsen
- Universitätsklinik für Radioonkologie, Universitätsklinikum Tübingen, Eberhard Karls Universität Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Deutschland
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45
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Wang YF, Tadimalla S, Hayden AJ, Holloway L, Haworth A. Artificial intelligence and imaging biomarkers for prostate radiation therapy during and after treatment. J Med Imaging Radiat Oncol 2021; 65:612-626. [PMID: 34060219 DOI: 10.1111/1754-9485.13242] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 04/18/2021] [Accepted: 05/02/2021] [Indexed: 12/15/2022]
Abstract
Magnetic resonance imaging (MRI) is increasingly used in the management of prostate cancer (PCa). Quantitative MRI (qMRI) parameters, derived from multi-parametric MRI, provide indirect measures of tumour characteristics such as cellularity, angiogenesis and hypoxia. Using Artificial Intelligence (AI), relevant information and patterns can be efficiently identified in these complex data to develop quantitative imaging biomarkers (QIBs) of tumour function and biology. Such QIBs have already demonstrated potential in the diagnosis and staging of PCa. In this review, we explore the role of these QIBs in monitoring treatment response during and after PCa radiotherapy (RT). Recurrence of PCa after RT is not uncommon, and early detection prior to development of metastases provides an opportunity for salvage treatments with curative intent. However, the current method of monitoring treatment response using prostate-specific antigen levels lacks specificity. QIBs, derived from qMRI and developed using AI techniques, can be used to monitor biological changes post-RT providing the potential for accurate and early diagnosis of recurrent disease.
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Affiliation(s)
- Yu-Feng Wang
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
- Ingham Institute for Applied Medical Research, Liverpool, New South Wales, Australia
| | - Sirisha Tadimalla
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
| | - Amy J Hayden
- Sydney West Radiation Oncology, Westmead Hospital, Wentworthville, New South Wales, Australia
- Faculty of Medicine, Western Sydney University, Sydney, New South Wales, Australia
- Faculty of Medicine, Health & Human Sciences, Macquarie University, Sydney, New South Wales, Australia
| | - Lois Holloway
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
- Ingham Institute for Applied Medical Research, Liverpool, New South Wales, Australia
- Liverpool and Macarthur Cancer Therapy Centre, Liverpool Hospital, Liverpool, New South Wales, Australia
| | - Annette Haworth
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
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46
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Cusumano D, Boldrini L, Dhont J, Fiorino C, Green O, Güngör G, Jornet N, Klüter S, Landry G, Mattiucci GC, Placidi L, Reynaert N, Ruggieri R, Tanadini-Lang S, Thorwarth D, Yadav P, Yang Y, Valentini V, Verellen D, Indovina L. Artificial Intelligence in magnetic Resonance guided Radiotherapy: Medical and physical considerations on state of art and future perspectives. Phys Med 2021; 85:175-191. [PMID: 34022660 DOI: 10.1016/j.ejmp.2021.05.010] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Revised: 04/15/2021] [Accepted: 05/04/2021] [Indexed: 12/14/2022] Open
Abstract
Over the last years, technological innovation in Radiotherapy (RT) led to the introduction of Magnetic Resonance-guided RT (MRgRT) systems. Due to the higher soft tissue contrast compared to on-board CT-based systems, MRgRT is expected to significantly improve the treatment in many situations. MRgRT systems may extend the management of inter- and intra-fraction anatomical changes, offering the possibility of online adaptation of the dose distribution according to daily patient anatomy and to directly monitor tumor motion during treatment delivery by means of a continuous cine MR acquisition. Online adaptive treatments require a multidisciplinary and well-trained team, able to perform a series of operations in a safe, precise and fast manner while the patient is waiting on the treatment couch. Artificial Intelligence (AI) is expected to rapidly contribute to MRgRT, primarily by safely and efficiently automatising the various manual operations characterizing online adaptive treatments. Furthermore, AI is finding relevant applications in MRgRT in the fields of image segmentation, synthetic CT reconstruction, automatic (on-line) planning and the development of predictive models based on daily MRI. This review provides a comprehensive overview of the current AI integration in MRgRT from a medical physicist's perspective. Medical physicists are expected to be major actors in solving new tasks and in taking new responsibilities: their traditional role of guardians of the new technology implementation will change with increasing emphasis on the managing of AI tools, processes and advanced systems for imaging and data analysis, gradually replacing many repetitive manual tasks.
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Affiliation(s)
- Davide Cusumano
- Fondazione Policlinico Universitario Agostino Gemelli, IRCCS, Rome, Italy
| | - Luca Boldrini
- Fondazione Policlinico Universitario Agostino Gemelli, IRCCS, Rome, Italy
| | | | - Claudio Fiorino
- Medical Physics, San Raffaele Scientific Institute, Milan, Italy
| | - Olga Green
- Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, USA
| | - Görkem Güngör
- Acıbadem MAA University, School of Medicine, Department of Radiation Oncology, Maslak Istanbul, Turkey
| | - Núria Jornet
- Servei de Radiofísica i Radioprotecció, Hospital de la Santa Creu i Sant Pau, Spain
| | - Sebastian Klüter
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Guillaume Landry
- Department of Radiation Oncology, LMU Munich, Munich, Germany; German Cancer Consortium (DKTK), Munich, Germany
| | | | - Lorenzo Placidi
- Fondazione Policlinico Universitario Agostino Gemelli, IRCCS, Rome, Italy.
| | - Nick Reynaert
- Department of Medical Physics, Institut Jules Bordet, Belgium
| | - Ruggero Ruggieri
- Dipartimento di Radioterapia Oncologica Avanzata, IRCCS "Sacro cuore - don Calabria", Negrar di Valpolicella (VR), Italy
| | - Stephanie Tanadini-Lang
- Department of Radiation Oncology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Daniela Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, University Hospital Tüebingen, Tübingen, Germany
| | - Poonam Yadav
- Department of Human Oncology School of Medicine and Public Heath University of Wisconsin - Madison, USA
| | - Yingli Yang
- Department of Radiation Oncology, David Geffen School of Medicine, University of California Los Angeles, USA
| | - Vincenzo Valentini
- Fondazione Policlinico Universitario Agostino Gemelli, IRCCS, Rome, Italy
| | - Dirk Verellen
- Department of Medical Physics, Iridium Cancer Network, Belgium; Faculty of Medicine and Health Sciences, Antwerp University, Antwerp, Belgium
| | - Luca Indovina
- Fondazione Policlinico Universitario Agostino Gemelli, IRCCS, Rome, Italy
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47
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Keller B, Bruynzeel AME, Tang C, Swaminath A, Kerkmeijer L, Chu W. Adaptive Magnetic Resonance-Guided Stereotactic Body Radiotherapy: The Next Step in the Treatment of Renal Cell Carcinoma. Front Oncol 2021; 11:634830. [PMID: 34046341 PMCID: PMC8144516 DOI: 10.3389/fonc.2021.634830] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Accepted: 03/22/2021] [Indexed: 12/15/2022] Open
Abstract
Adaptive MR-guided radiotherapy (MRgRT) is a new treatment paradigm and its role as a non-invasive treatment option for renal cell carcinoma is evolving. The early clinical experience to date shows that real-time plan adaptation based on the daily MRI anatomy can lead to improved target coverage and normal tissue sparing. Continued technological innovations will further mitigate the challenges of organ motion and enable more advanced treatment adaptation, and potentially lead to enhanced oncologic outcomes and preservation of renal function. Future applications look promising to make a positive clinical impact and further the personalization of radiotherapy in the management of renal cell carcinoma.
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Affiliation(s)
- Brian Keller
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Anna M. E. Bruynzeel
- Department of Radiation Oncology, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Chad Tang
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Anand Swaminath
- Department of Radiation Oncology, Juravinski Cancer Centre, McMaster University, Hamilton, ON, Canada
| | - Linda Kerkmeijer
- Department of Radiation Oncology, Radboudumc, Nijmegen, Netherlands
| | - William Chu
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
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48
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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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49
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McDonald BA, Vedam S, Yang J, Wang J, Castillo P, Lee B, Sobremonte A, Ahmed S, Ding Y, Mohamed ASR, Balter P, Hughes N, Thorwarth D, Nachbar M, Philippens MEP, Terhaard CHJ, Zips D, Böke S, Awan MJ, Christodouleas J, Fuller CD. Initial Feasibility and Clinical Implementation of Daily MR-Guided Adaptive Head and Neck Cancer Radiation Therapy on a 1.5T MR-Linac System: Prospective R-IDEAL 2a/2b Systematic Clinical Evaluation of Technical Innovation. Int J Radiat Oncol Biol Phys 2021; 109:1606-1618. [PMID: 33340604 PMCID: PMC7965360 DOI: 10.1016/j.ijrobp.2020.12.015] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 11/04/2020] [Accepted: 12/11/2020] [Indexed: 01/20/2023]
Abstract
PURPOSE This prospective study is, to our knowledge, the first report of daily adaptive radiation therapy (ART) for head and neck cancer (HNC) using a 1.5T magnetic resonance imaging-linear accelerator (MR-linac) with particular focus on safety and feasibility and dosimetric results of an online rigid registration-based adapt to position (ATP) workflow. METHODS AND MATERIALS Ten patients with HNC received daily ART on a 1.5T/7MV MR-linac, 6 using ATP only and 4 using ATP with 1 offline adapt-to-shape replan. Setup variability with custom immobilization masks was assessed by calculating the mean systematic error (M), standard deviation of the systematic error (Σ), and standard deviation of the random error (σ) of the isocenter shifts. Quality assurance was performed with a cylindrical diode array using 3%/3 mm γ criteria. Adaptive treatment plans were summed for each patient to compare the delivered dose with the planned dose from the reference plan. The impact of dosimetric variability between adaptive fractions on the summation plan doses was assessed by tracking the number of optimization constraint violations at each individual fraction. RESULTS The random errors (mm) for the x, y, and z isocenter shifts, respectively, were M = -0.3, 0.7, 0.1; Σ = 3.3, 2.6, 1.4; and σ = 1.7, 2.9, 1.0. The median (range) γ pass rate was 99.9% (90.9%-100%). The differences between the reference and summation plan doses were -0.61% to 1.78% for the clinical target volume and -11.74% to 8.11% for organs at risk (OARs), although an increase greater than 2% in OAR dose only occurred in 3 cases, each for a single OAR. All cases had at least 2 fractions with 1 or more constraint violations. However, in nearly all instances, constraints were still met in the summation plan despite multiple single-fraction violations. CONCLUSIONS Daily ART on a 1.5T MR-linac using an online ATP workflow is safe and clinically feasible for HNC and results in delivered doses consistent with planned doses.
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Affiliation(s)
- Brigid A McDonald
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas; The University of Texas MD Anderson Cancer Center, UTHealth Graduate School of Biomedical Sciences, Houston, Texas
| | - Sastry Vedam
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jinzhong Yang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jihong Wang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Pamela Castillo
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Belinda Lee
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Angela Sobremonte
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Sara Ahmed
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Yao Ding
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Abdallah S R Mohamed
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas; The University of Texas MD Anderson Cancer Center, UTHealth Graduate School of Biomedical Sciences, Houston, Texas
| | - Peter Balter
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Neil Hughes
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Daniela Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Marcel Nachbar
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | | | - Chris H J Terhaard
- Department of Radiotherapy, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Daniel Zips
- Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Simon Böke
- Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
| | - Musaddiq J Awan
- Department of Radiation Oncology, Medical College of Wisconsin, Wauwatosa, Wisconsin
| | - John Christodouleas
- Elekta, Inc., Stockholm, Sweden; Department of Radiation Oncology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Clifton D Fuller
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
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50
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Romesser PB, Tyagi N, Crane CH. Magnetic Resonance Imaging-Guided Adaptive Radiotherapy for Colorectal Liver Metastases. Cancers (Basel) 2021; 13:cancers13071636. [PMID: 33915810 PMCID: PMC8036824 DOI: 10.3390/cancers13071636] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 03/22/2021] [Accepted: 03/28/2021] [Indexed: 12/16/2022] Open
Abstract
Technological advances have enabled well tolerated and effective radiation treatment for small liver metastases. Stereotactic ablative radiation therapy (SABR) refers to ablative dose delivery (>100 Gy BED) in five fractions or fewer. For larger tumors, the safe delivery of SABR can be challenging due to a more limited volume of healthy normal liver parenchyma and the proximity of the tumor to radiosensitive organs such as the stomach, duodenum, and large intestine. In addition to stereotactic treatment delivery, controlling respiratory motion, the use of image guidance, adaptive planning and increasing the number of radiation fractions are sometimes necessary for the safe delivery of SABR in these situations. Magnetic Resonance (MR) image-guided adaptive radiation therapy (MRgART) is a new and rapidly evolving treatment paradigm. MR imaging before, during and after treatment delivery facilitates direct visualization of both the tumor target and the adjacent normal healthy organs as well as potential intrafraction motion. Real time MR imaging facilitates non-invasive tumor tracking and treatment gating. While daily adaptive re-planning permits treatment plans to be adjusted based on the anatomy of the day. MRgART therapy is a promising radiation technology advance that can overcome many of the challenges of liver SABR and may facilitate the safe tumor dose escalation of colorectal liver metastases.
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Affiliation(s)
- Paul B. Romesser
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA;
- Early Drug Development Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Neelam Tyagi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA;
| | - Christopher H. Crane
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA;
- Correspondence:
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