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Parisi S, Sciacca M, Ferrantelli G, Chillari F, Critelli P, Venuti V, Lillo S, Arcieri M, Martinelli C, Pontoriero A, Minutoli F, Ercoli A, Pergolizzi S. Locally advanced squamous cervical carcinoma (M0): management and emerging therapeutic options in the precision radiotherapy era. Jpn J Radiol 2024; 42:354-366. [PMID: 37987880 DOI: 10.1007/s11604-023-01510-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 10/26/2023] [Indexed: 11/22/2023]
Abstract
Squamous cervical carcinoma (SCC) requires particular attention in diagnostic and clinical management. New diagnostic tools, such as (positron emission tomography-magnetic resonance imaging) PET-MRI, consent to ameliorate clinical staging accuracy. The availability of new technologies in radiation therapy permits to deliver higher dose lowering toxicities. In this clinical scenario, new surgical concepts could aid in general management. Lastly, new targeted therapies and immunotherapy will have more room in this setting. The aim of this narrative review is to focus both on clinical management and new therapies in the precision radiotherapy era.
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Affiliation(s)
- S Parisi
- Radiation Oncology Unit, Department of Biomedical, Dental Science and Morphological and Functional Images, University of Messina, Via Consolare Valeria, 1, 98124, Messina, ME, Italy
| | - M Sciacca
- Radiation Oncology Unit, Department of Biomedical, Dental Science and Morphological and Functional Images, University of Messina, Via Consolare Valeria, 1, 98124, Messina, ME, Italy
| | - G Ferrantelli
- Radiation Oncology Unit, Department of Biomedical, Dental Science and Morphological and Functional Images, University of Messina, Via Consolare Valeria, 1, 98124, Messina, ME, Italy.
| | - F Chillari
- Radiation Oncology Unit, Department of Biomedical, Dental Science and Morphological and Functional Images, University of Messina, Via Consolare Valeria, 1, 98124, Messina, ME, Italy
| | - P Critelli
- Radiation Oncology Unit, Department of Biomedical, Dental Science and Morphological and Functional Images, University of Messina, Via Consolare Valeria, 1, 98124, Messina, ME, Italy
| | - V Venuti
- Radiation Oncology Unit, Department of Biomedical, Dental Science and Morphological and Functional Images, University of Messina, Via Consolare Valeria, 1, 98124, Messina, ME, Italy
| | - S Lillo
- Radiation Oncology Unit, Clinical Department, National Center for Oncological Hadrontherapy (CNAO), Pavia, Italy
| | - M Arcieri
- Obstetrics and Gynecology Unit, Department of Human Pathology of Adult and Childhood ``G. Baresi'', University Hospital ``G. Martino'', Messina, Italy
| | - C Martinelli
- Obstetrics and Gynecology Unit, Department of Human Pathology of Adult and Childhood ``G. Baresi'', University Hospital ``G. Martino'', Messina, Italy
| | - A Pontoriero
- Radiation Oncology Unit, Department of Biomedical, Dental Science and Morphological and Functional Images, University of Messina, Via Consolare Valeria, 1, 98124, Messina, ME, Italy
| | - F Minutoli
- Radiation Oncology Unit, Department of Biomedical, Dental Science and Morphological and Functional Images, University of Messina, Via Consolare Valeria, 1, 98124, Messina, ME, Italy
| | - A Ercoli
- Obstetrics and Gynecology Unit, Department of Human Pathology of Adult and Childhood ``G. Baresi'', University Hospital ``G. Martino'', Messina, Italy
| | - S Pergolizzi
- Radiation Oncology Unit, Department of Biomedical, Dental Science and Morphological and Functional Images, University of Messina, Via Consolare Valeria, 1, 98124, Messina, ME, Italy
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Fujimoto D, Takatsu J, Hara N, Oshima M, Tomihara J, Segawa E, Inoue T, Shikama N. Dosimetric comparison of four-dimensional computed tomography based internal target volume against variations in respiratory motion during treatment between volumetric modulated arc therapy and three-dimensional conformal radiotherapy in lung stereotactic body radiotherapy. Radiol Phys Technol 2024; 17:143-152. [PMID: 37930563 DOI: 10.1007/s12194-023-00757-8] [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: 04/09/2023] [Revised: 10/19/2023] [Accepted: 10/19/2023] [Indexed: 11/07/2023]
Abstract
This study focused on the dosimetric impact of variations in respiratory motion during lung stereotactic body radiotherapy (SBRT). Dosimetric comparisons between volumetric modulated arc therapy (VMAT) and three-dimensional conformal radiotherapy (3DCRT) were performed using four-dimensional computed tomography (4DCT)-based internal target volumes (ITV). We created retrospective plans for ten patients with lung cancer who underwent SBRT using 3DCRT and VMAT techniques. A Delta4 Phantom + (ScandiDos, Uppsala, Sweden) was used to evaluate the dosimetric robustness of 4DCT-based ITV against variations in respiratory motion during treatment. We analyzed respiratory motion during treatment. Dose-volume histogram parameters were evaluated for the 95% dose (D95%) to the planning target volume (PTV) contoured on CT images obtained under free breathing. The correlations between patient respiratory parameters and dosimetric errors were also evaluated. In the phantom study, the average PTV D95% dose differences for all fractions were - 2.9 ± 4.4% (- 16.0 - 1.2%) and - 2.0 ± 2.8% (- 11.2 - 0.7%) for 3DCRT and VMAT, respectively. The average dose difference was < 3% for both 3DCRT and VMAT; however, in 5 out of 42 fractions in 3DCRT, the difference in PTV D95% was > 10%. Dosimetric errors were correlated with respiratory amplitude and velocity, and differences in respiratory amplitude between 4DCT and treatment days were the main factors causing dosimetric errors. The overall average dose error of the PTV D95% was small; however, both 3DCRT and VMAT cases exceeding 10% error were observed. Larger errors occurred with amplitude variation or baseline drift, indicating limited robustness of 4DCT-based ITV.
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Affiliation(s)
- Daimu Fujimoto
- Department of Radiation Oncology, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Jun Takatsu
- Department of Radiation Oncology, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan.
| | - Naoya Hara
- Department of Radiology, Juntendo University Hospital, 3-1-3 Hongo, Bunkyo-ku, Tokyo, 113-8431, Japan
| | - Masaki Oshima
- Department of Radiation Oncology, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Jun Tomihara
- Department of Radiology, Juntendo University Hospital, 3-1-3 Hongo, Bunkyo-ku, Tokyo, 113-8431, Japan
| | - Eisuke Segawa
- Department of Radiology, Juntendo University Hospital, 3-1-3 Hongo, Bunkyo-ku, Tokyo, 113-8431, Japan
| | - Tatsuya Inoue
- Department of Radiation Oncology, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
- Department of Radiology, Juntendo University Urayasu Hospital, 2-1-1 Tomioka, Urayasu-shi, Chiba, 279-0021, Japan
| | - Naoto Shikama
- Department of Radiation Oncology, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
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Csiki E, Simon M, Papp J, Barabás M, Mikáczó J, Gál K, Sipos D, Kovács Á. Stereotactic body radiotherapy in lung cancer: a contemporary review. Pathol Oncol Res 2024; 30:1611709. [PMID: 38476352 PMCID: PMC10928908 DOI: 10.3389/pore.2024.1611709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 02/15/2024] [Indexed: 03/14/2024]
Abstract
The treatment of early stage non-small cell lung cancer (NSCLC) has improved enormously in the last two decades. Although surgery is not the only choice, lobectomy is still the gold standard treatment type for operable patients. For inoperable patients stereotactic body radiotherapy (SBRT) should be offered, reaching very high local control and overall survival rates. With SBRT we can precisely irradiate small, well-defined lesions with high doses. To select the appropriate fractionation schedule it is important to determine the size, localization and extent of the lung tumor. The introduction of novel and further developed planning (contouring guidelines, diagnostic image application, planning systems) and delivery techniques (motion management, image guided radiotherapy) led to lower rates of side effects and more conformal target volume coverage. The purpose of this study is to summarize the current developments, randomised studies, guidelines about lung SBRT, with emphasis on the possibility of increasing local control and overall rates in "fit," operable patients as well, so SBRT would be eligible in place of surgery.
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Affiliation(s)
- Emese Csiki
- Department of Oncoradiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
- Doctoral School of Clinical Medicine, University of Debrecen, Debrecen, Hungary
| | - Mihály Simon
- Department of Oncoradiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - Judit Papp
- Department of Oncoradiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - Márton Barabás
- Department of Oncoradiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
- Doctoral School of Clinical Medicine, University of Debrecen, Debrecen, Hungary
| | - Johanna Mikáczó
- Department of Oncoradiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
- Doctoral School of Clinical Medicine, University of Debrecen, Debrecen, Hungary
| | - Kristóf Gál
- Department of Oncoradiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
| | - David Sipos
- Faculty of Health Sciences, University of Pécs, Pecs, Hungary
| | - Árpád Kovács
- Department of Oncoradiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary
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Rabe M, Paganelli C, Schmitz H, Meschini G, Riboldi M, Hofmaier J, Nierer-Kohlhase L, Dinkel J, Reiner M, Parodi K, Belka C, Landry G, Kurz C, Kamp F. Continuous time-resolved estimated synthetic 4D-CTs for dose reconstruction of lung tumor treatments at a 0.35 T MR-linac. Phys Med Biol 2023; 68:235008. [PMID: 37669669 DOI: 10.1088/1361-6560/acf6f0] [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: 05/10/2023] [Accepted: 09/05/2023] [Indexed: 09/07/2023]
Abstract
Objective.To experimentally validate a method to create continuous time-resolved estimated synthetic 4D-computed tomography datasets (tresCTs) based on orthogonal cine MRI data for lung cancer treatments at a magnetic resonance imaging (MRI) guided linear accelerator (MR-linac).Approach.A breathing porcine lung phantom was scanned at a CT scanner and 0.35 T MR-linac. Orthogonal cine MRI series (sagittal/coronal orientation) at 7.3 Hz, intersecting tumor-mimicking gelatin nodules, were deformably registered to mid-exhale 3D-CT and 3D-MRI datasets. The time-resolved deformation vector fields were extrapolated to 3D and applied to a reference synthetic 3D-CT image (sCTref), while accounting for breathing phase-dependent lung density variations, to create 82 s long tresCTs at 3.65 Hz. Ten tresCTs were created for ten tracked nodules with different motion patterns in two lungs. For each dataset, a treatment plan was created on the mid-exhale phase of a measured ground truth (GT) respiratory-correlated 4D-CT dataset with the tracked nodule as gross tumor volume (GTV). Each plan was recalculated on the GT 4D-CT, randomly sampled tresCT, and static sCTrefimages. Dose distributions for corresponding breathing phases were compared in gamma (2%/2 mm) and dose-volume histogram (DVH) parameter analyses.Main results.The mean gamma pass rate between all tresCT and GT 4D-CT dose distributions was 98.6%. The mean absolute relative deviations of the tresCT with respect to GT DVH parameters were 1.9%, 1.0%, and 1.4% for the GTVD98%,D50%, andD2%, respectively, 1.0% for the remaining nodulesD50%, and 1.5% for the lungV20Gy. The gamma pass rate for the tresCTs was significantly larger (p< 0.01), and the GTVD50%deviations with respect to the GT were significantly smaller (p< 0.01) than for the sCTref.Significance.The results suggest that tresCTs could be valuable for time-resolved reconstruction and intrafractional accumulation of the dose to the GTV for lung cancer patients treated at MR-linacs in the future.
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Affiliation(s)
- Moritz Rabe
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Chiara Paganelli
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy
| | - Henning Schmitz
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Giorgia Meschini
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy
| | - Marco Riboldi
- Department of Medical Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching (Munich), Germany
| | - Jan Hofmaier
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Lukas Nierer-Kohlhase
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Julien Dinkel
- Department of Radiology, LMU University Hospital, LMU Munich, Munich, Germany
- Comprehensive Pneumology Center, German Center for Lung Research (DZL), Munich, Germany
| | - Michael Reiner
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Katia Parodi
- Department of Medical Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching (Munich), 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, Germany
- Bavarian Cancer Research Center (BZKF), 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
| | - Florian Kamp
- Department of Radiation Oncology, LMU University Hospital, LMU Munich, Munich, Germany
- Department of Radiation Oncology, University Hospital Cologne, Cologne, Germany
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Terpstra ML, Maspero M, Verhoeff JJC, van den Berg CAT. Accelerated respiratory-resolved 4D-MRI with separable spatio-temporal neural networks. Med Phys 2023; 50:5331-5342. [PMID: 37527331 DOI: 10.1002/mp.16643] [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: 11/16/2022] [Revised: 05/30/2023] [Accepted: 06/20/2023] [Indexed: 08/03/2023] Open
Abstract
BACKGROUND Respiratory-resolved four-dimensional magnetic resonance imaging (4D-MRI) provides essential motion information for accurate radiation treatments of mobile tumors. However, obtaining high-quality 4D-MRI suffers from long acquisition and reconstruction times. PURPOSE To develop a deep learning architecture to quickly acquire and reconstruct high-quality 4D-MRI, enabling accurate motion quantification for MRI-guided radiotherapy (MRIgRT). METHODS A small convolutional neural network called MODEST is proposed to reconstruct 4D-MRI by performing a spatial and temporal decomposition, omitting the need for 4D convolutions to use all the spatio-temporal information present in 4D-MRI. This network is trained on undersampled 4D-MRI after respiratory binning to reconstruct high-quality 4D-MRI obtained by compressed sensing reconstruction. The network is trained, validated, and tested on 4D-MRI of 28 lung cancer patients acquired with a T1-weighted golden-angle radial stack-of-stars (GA-SOS) sequence. The 4D-MRI of 18, 5, and 5 patients were used for training, validation, and testing. Network performances are evaluated on image quality measured by the structural similarity index (SSIM) and motion consistency by comparing the position of the lung-liver interface on undersampled 4D-MRI before and after respiratory binning. The network is compared to conventional architectures such as a U-Net, which has 30 times more trainable parameters. RESULTS MODEST can reconstruct high-quality 4D-MRI with higher image quality than a U-Net, despite a thirty-fold reduction in trainable parameters. High-quality 4D-MRI can be obtained using MODEST in approximately 2.5 min, including acquisition, processing, and reconstruction. CONCLUSION High-quality accelerated 4D-MRI can be obtained using MODEST, which is particularly interesting for MRIgRT.
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Affiliation(s)
- Maarten L Terpstra
- Department of Radiotherapy, 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
| | - Matteo Maspero
- Department of Radiotherapy, 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
| | - Joost J C Verhoeff
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Cornelis A T van den Berg
- Department of Radiotherapy, 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
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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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Subashi E, Segars P, Veeraraghavan H, Deasy J, Tyagi N. A model for gastrointestinal tract motility in a 4D imaging phantom of human anatomy. Med Phys 2023; 50:3066-3075. [PMID: 36808107 PMCID: PMC10561541 DOI: 10.1002/mp.16305] [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: 07/19/2022] [Revised: 01/26/2023] [Accepted: 01/29/2023] [Indexed: 02/23/2023] Open
Abstract
BACKGROUND Gastrointestinal (GI) tract motility is one of the main sources for intra/inter-fraction variability and uncertainty in radiation therapy for abdominal targets. Models for GI motility can improve the assessment of delivered dose and contribute to the development, testing, and validation of deformable image registration (DIR) and dose-accumulation algorithms. PURPOSE To implement GI tract motion in the 4D extended cardiac-torso (XCAT) digital phantom of human anatomy. MATERIALS AND METHODS Motility modes that exhibit large amplitude changes in the diameter of the GI tract and may persist over timescales comparable to online adaptive planning and radiotherapy delivery were identified based on literature research. Search criteria included amplitude changes larger than planning risk volume expansions and durations of the order of tens of minutes. The following modes were identified: peristalsis, rhythmic segmentation, high amplitude propagating contractions (HAPCs), and tonic contractions. Peristalsis and rhythmic segmentations were modeled by traveling and standing sinusoidal waves. HAPCs and tonic contractions were modeled by traveling and stationary Gaussian waves. Wave dispersion in the temporal and spatial domain was implemented by linear, exponential, and inverse power law functions. Modeling functions were applied to the control points of the nonuniform rational B-spline surfaces defined in the reference XCAT library. GI motility was combined with the cardiac and respiratory motions available in the standard 4D-XCAT phantom. Default model parameters were estimated based on the analysis of cine MRI acquisitions in 10 patients treated in a 1.5T MR-linac. RESULTS We demonstrate the ability to generate realistic 4D multimodal images that simulate GI motility combined with respiratory and cardiac motion. All modes of motility, except tonic contractions, were observed in the analysis of our cine MRI acquisitions. Peristalsis was the most common. Default parameters estimated from cine MRI were used as initial values for simulation experiments. It is shown that in patients undergoing stereotactic body radiotherapy for abdominal targets, the effects of GI motility can be comparable or larger than the effects of respiratory motion. CONCLUSION The digital phantom provides realistic models to aid in medical imaging and radiation therapy research. The addition of GI motility will further contribute to the development, testing, and validation of DIR and dose accumulation algorithms for MR-guided radiotherapy.
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Affiliation(s)
- Ergys Subashi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Paul Segars
- Department of Radiology, Duke University Medical Center, Durham, North Carolina
| | - Harini Veeraraghavan
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Joseph Deasy
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Neelam Tyagi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
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van der Pol LHG, Hackett SL, Hoesein FAAM, Snoeren LMW, Pomp J, Raaymakers BW, Verhoeff JJC, Fast MF. On the feasibility of cardiac substructure sparing in magnetic resonance imaging guided stereotactic lung radiotherapy. Med Phys 2023; 50:397-409. [PMID: 36210631 PMCID: PMC10092491 DOI: 10.1002/mp.16028] [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: 06/20/2022] [Revised: 08/26/2022] [Accepted: 09/25/2022] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Lung stereotactic body radiotherapy (SBRT) has proven an effective treatment for medically inoperable lung tumors, even for (ultra-)central tumors. Recently, there has been growing interest in radiation-induced cardiac toxicity in lung radiotherapy. More specifically, dose to cardiac (sub-)structures (CS) was found to correlate with survival after radiotherapy. PURPOSE Our goal is first, to investigate the percentage of patients who require CS sparing in an magnetic resonance imaging guided lung SBRT workflow, and second, to quantify how successful implementation of cardiac sparing would be. METHODS The patient cohort consists of 34 patients with stage II-IV lung cancer who were treated with SBRT between 2017 and 2020. A mid-position computed tomography (CT) image was used to create treatment plans for the 1.5 T Unity MR-linac (Elekta AB, Stockholm, Sweden) following clinical templates. Under guidance of a cardio-thoracic radiologist, 11 CS were contoured manually for each patient. Dose constraints for five CS were extracted from the literature. Patients were stratified according to their need for cardiac sparing depending on the CS dose in their non-CS constrained MR-linac treatment plans. Cardiac sparing treatment plans (CSPs) were then created and dosimetrically compared with their non-CS constrained treatment plan counterparts. CSPs complied with the departmental constraints and were considered successful when fulfilling all CS constraints, and partially successful if some CS constraints could be fulfilled. Predictors for the need for and feasibility of cardiac sparing were explored, specifically planning target volume (PTV) size, cranio-caudal (CC) distance, 3D distance, and in-field overlap volume histograms (iOVH). RESULTS 47% of the patients (16 out of 34) were in need of cardiac sparing. A successful CSP could be created for 62.5% (10 out of 16) of these patients. Partially successful CSPs still complied with two to four CS constraints. No significant difference in dose to organs at risk (OARs) or targets was identified between CSPs and the corresponding non-CS constrained MR-linac plans. The need for cardiac sparing was found to correlate with distance in the CC direction between target and all of the individual CS (Mann-Whitney U-test p-values <10-6 ). iOVHs revealed that complying with dose constraints for CS is primarily determined by in-plane distance and secondarily by PTV size. CONCLUSION We demonstrated that CS can be successfully spared in lung SBRT on the MR-linac for most of this patient cohort, without compromising doses to the tumor or to other OARs. CC distance between the target and CS can be used to predict the need for cardiac sparing. iOVHs, in combination with PTV size, can be used to predict if cardiac sparing will be successful for all constrained CS except the left ventricle.
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Affiliation(s)
- Luuk H G van der Pol
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Sara L Hackett
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | | | - Louk M W Snoeren
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Jacqueline Pomp
- 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
| | - Joost J C Verhoeff
- 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
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Tanabe Y, Kiritani M, Deguchi T, Hira N, Tomimoto S. Patient-specific respiratory motion management using lung tumors vs fiducial markers for real-time tumor-tracking stereotactic body radiotherapy. Phys Imaging Radiat Oncol 2022; 25:100405. [PMID: 36655212 PMCID: PMC9841282 DOI: 10.1016/j.phro.2022.12.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 11/17/2022] [Accepted: 12/21/2022] [Indexed: 12/25/2022] Open
Abstract
Background and purpose In real-time lung tumor-tracking stereotactic body radiotherapy (SBRT), tracking accuracy is related to radiotherapy efficacy. This study aimed to evaluate the respiratory movement relationship between a lung tumor and a fiducial marker position in each direction using four-dimensional (4D) computed tomography (CT) images. Materials and methods A series of 31 patients with a fiducial marker for lung SBRT was retrospectively analyzed using 4DCT. In the upper (UG) and middle and lower lobe groups (MLG), the cross-correlation coefficients of respiratory movement between the lung tumor and fiducial marker position in four directions (anterior-posterior, left-right, superior-inferior [SI], and three-dimensional [3D]) were calculated for each gating window (≤1, ≤2, and ≤ 3 mm). Subsequently, the proportions of phase numbers in unplanned irradiation (with lung tumors outside the gating window and fiducial markers inside the gating window) were calculated for each gating window. Results In the SI and 3D directions, the cross-correlation coefficients were significantly different between UG (mean r = 0.59, 0.63, respectively) and MLG (mean r = 0.95, 0.97, respectively). In both the groups, the proportions of phase numbers in unplanned irradiation were 11 %, 28 %, and 63 % for the ≤ 1-, ≤2-, and ≤ 3-mm gating windows, respectively. Conclusions Compared with MLG, fiducial markers for UG have low cross-correlation coefficients between the lung tumor and the fiducial marker position. Using 4DCT to assess the risk of unplanned irradiation in a gating window setting and selecting a high cross-correlation coefficient fiducial marker in advance are important for accurate treatment using lung SBRT.
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Affiliation(s)
- Yoshinori Tanabe
- Faculty of Medicine, Graduate School of Health Sciences, Okayama University, 2-5-1, Shikata, Kita, Okayama 700-8525, Japan,Corresponding author.
| | - Michiru Kiritani
- Facilty of Health Sciences, Okayama University Medical School, 2-5-1, Shikata, Kita, Okayama 700-8525, Japan
| | - Tomomi Deguchi
- Facilty of Health Sciences, Okayama University Medical School, 2-5-1, Shikata, Kita, Okayama 700-8525, Japan
| | - Nanami Hira
- Facilty of Health Sciences, Okayama University Medical School, 2-5-1, Shikata, Kita, Okayama 700-8525, Japan
| | - Syouta Tomimoto
- Facilty of Health Sciences, Okayama University Medical School, 2-5-1, Shikata, Kita, Okayama 700-8525, Japan
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10
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Shao HC, Li T, Dohopolski MJ, Wang J, Cai J, Tan J, Wang K, Zhang Y. Real-time MRI motion estimation through an unsupervised k-space-driven deformable registration network (KS-RegNet). Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac762c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Accepted: 06/06/2022] [Indexed: 11/12/2022]
Abstract
Abstract
Purpose. Real-time three-dimensional (3D) magnetic resonance (MR) imaging is challenging because of slow MR signal acquisition, leading to highly under-sampled k-space data. Here, we proposed a deep learning-based, k-space-driven deformable registration network (KS-RegNet) for real-time 3D MR imaging. By incorporating prior information, KS-RegNet performs a deformable image registration between a fully-sampled prior image and on-board images acquired from highly-under-sampled k-space data, to generate high-quality on-board images for real-time motion tracking. Methods. KS-RegNet is an end-to-end, unsupervised network consisting of an input data generation block, a subsequent U-Net core block, and following operations to compute data fidelity and regularization losses. The input data involved a fully-sampled, complex-valued prior image, and the k-space data of an on-board, real-time MR image (MRI). From the k-space data, under-sampled real-time MRI was reconstructed by the data generation block to input into the U-Net core. In addition, to train the U-Net core to learn the under-sampling artifacts, the k-space data of the prior image was intentionally under-sampled using the same readout trajectory as the real-time MRI, and reconstructed to serve an additional input. The U-Net core predicted a deformation vector field that deforms the prior MRI to on-board real-time MRI. To avoid adverse effects of quantifying image similarity on the artifacts-ridden images, the data fidelity loss of deformation was evaluated directly in k-space. Results. Compared with Elastix and other deep learning network architectures, KS-RegNet demonstrated better and more stable performance. The average (±s.d.) DICE coefficients of KS-RegNet on a cardiac dataset for the 5- , 9- , and 13-spoke k-space acquisitions were 0.884 ± 0.025, 0.889 ± 0.024, and 0.894 ± 0.022, respectively; and the corresponding average (±s.d.) center-of-mass errors (COMEs) were 1.21 ± 1.09, 1.29 ± 1.22, and 1.01 ± 0.86 mm, respectively. KS-RegNet also provided the best performance on an abdominal dataset. Conclusion. KS-RegNet allows real-time MRI generation with sub-second latency. It enables potential real-time MR-guided soft tissue tracking, tumor localization, and radiotherapy plan adaptation.
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11
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Keijnemans K, Borman PTS, Uijtewaal P, Woodhead PL, Raaymakers BW, Fast MF. A hybrid 2D/4D-MRI methodology using simultaneous multislice imaging for radiotherapy guidance. Med Phys 2022; 49:6068-6081. [PMID: 35694905 PMCID: PMC9545880 DOI: 10.1002/mp.15802] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 04/18/2022] [Accepted: 05/27/2022] [Indexed: 11/24/2022] Open
Abstract
Purpose Respiratory motion management is important in abdominothoracic radiotherapy. Fast imaging of the tumor can facilitate multileaf collimator (MLC) tracking that allows for smaller treatment margins, while repeatedly imaging the full field‐of‐view is necessary for 4D dose accumulation. This study introduces a hybrid 2D/4D‐MRI methodology that can be used for simultaneous MLC tracking and dose accumulation on a 1.5 T Unity MR‐linac (Elekta AB, Stockholm, Sweden). Methods We developed a hybrid 2D/4D‐MRI methodology that uses a simultaneous multislice (SMS) accelerated MRI sequence, which acquires two coronal slices simultaneously and repeatedly cycles through slice positions over the image volume. As a result, the fast 2D imaging can be used prospectively for MLC tracking and the SMS slices can be sorted retrospectively into respiratory‐correlated 4D‐MRIs for dose accumulation. Data were acquired in five healthy volunteers with an SMS‐bTFE and SMS‐TSE MRI sequence. For each sequence, a prebeam dataset and a beam‐on dataset were acquired simulating the two phases of MR‐linac treatments. Prebeam data were used to generate a 4D‐based motion model and a reference mid‐position volume, while beam‐on data were used for real‐time motion extraction and reconstruction of beam‐on 4D‐MRIs. In addition, an in‐silico computational phantom was used for validation of the hybrid 2D/4D‐MRI methodology. MLC tracking experiments were performed with the developed methodology, for which real‐time SMS data reconstruction was enabled on the scanner. A 15‐beam 8× 7.5 Gy intensity‐modulated radiotherapy plan for lung stereotactic body radiotherapy with isotropic 3 mm GTV‐to‐PTV margins was created. Dosimetry experiments were performed using a 4D motion phantom. The latency between target motion and updating the radiation beam was determined and compensated. Local gamma analyses were performed to quantify dose differences compared to a static reference delivery, and dose area histograms (DAHs) were used to quantify the GTV and PTV coverage. Results In‐vivo data acquisition and MLC tracking experiments were successfully performed with the developed hybrid 2D/4D‐MRI methodology. Real‐time liver–lung interface motion estimation had a Pearson's correlation of 0.996 (in‐vivo) and 0.998 (in‐silico). A median (5th–95th percentile) error of 0.0 (−0.9 to 0.7) mm and 0.0 (−0.2 to 0.2) mm was found for real‐time motion estimation for in‐vivo and in‐silico, respectively. Target motion prediction beyond the liver–lung interface had a median root mean square error of 1.6 mm (in‐vivo) and 0.5 mm (in‐silico). Beam‐on 4D MRI reconstruction required a median amount of data equal to an acquisition time of 2:21–3:17 min, which was 20% less data compared to the prebeam‐derived 4D‐MRI. System latency was reduced from 501 ± 12 ms to −1 ± 3 ms (SMS‐TSE) and from 398 ± 10 ms to −10 ± 4 ms (SMS‐bTFE) by a linear regression prediction filter. The local gamma analysis agreed within −3.8% to 3.3% (SMS‐bTFE) and −5.3% to 10% (SMS‐TSE) with a reference MRI sequence. The DAHs revealed a relative D98% GTV coverage between 97% and 100% (SMS‐bTFE) and 100% and 101% (SMS‐TSE) compared to the static reference. Conclusions The presented 2D/4D‐MRI methodology demonstrated the potential for accurately extracting real‐time motion for MLC tracking in abdominothoracic radiotherapy, while simultaneously reconstructing contiguous respiratory‐correlated 4D‐MRIs for dose accumulation.
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Affiliation(s)
- Katrinus Keijnemans
- 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
| | - Prescilla Uijtewaal
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Peter L Woodhead
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands.,Elekta AB, kungstensgatan 18, 113 57 Stockholm, Sweden
| | - 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
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Auxiliary Diagnosis of Lung Cancer with Magnetic Resonance Imaging Data under Deep Learning. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:1994082. [PMID: 35572829 PMCID: PMC9095378 DOI: 10.1155/2022/1994082] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 03/30/2022] [Accepted: 04/04/2022] [Indexed: 11/30/2022]
Abstract
This study was aimed at two image segmentation methods of three-dimensional (3D) U-shaped network (U-Net) and multilevel boundary sensing residual U-shaped network (RUNet) and their application values on the auxiliary diagnosis of lung cancer. In this study, on the basis of the 3D U-Net segmentation method, the multilevel boundary sensing RUNet was worked out after optimization. 92 patients with lung cancer were selected, and their clinical data were counted; meanwhile, the lung nodule detection was performed to obtain the segmentation effect under 3D U-Net. The accuracy of 3D U-Net and multilevel boundary sensing RUNet was compared on lung magnetic resonance imaging (MRI) after lung nodule segmentation. Patients with benign lung tumors were taken as controls; the blood immune biochemical indicators progastrin-releasing peptide (pro-CRP), carcinoembryonic antigen (CEA), and neuron-specific enolase (NSE) in patients with malignant lung tumors were analyzed. It was found that the accuracy, sensitivity, and specificity were all greater than 90% under the algorithm-based MRI of benign and malignant tumor patients. Based on the imaging signs for the MRI image of lung nodules, the segmentation effect of the RUNet was clearer than that of the 3D U-Net. In addition, serum levels of pro-CRP, NSE, and CAE in patients with benign lung tumors were 28.9 pg/mL, 12.5 ng/mL, and 10.8 ng/mL, respectively, which were lower than 175.6 pg/mL, 33.6 ng/mL, and 31.9 ng/mL in patients with malignant lung tumors significantly (P < 0.05). Thus, the RUNet image segmentation method was better than the 3D U-Net. The pro-CRP, CEA, and NSE could be used as diagnostic indicators for malignant lung tumors.
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13
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Ligtenberg H, Hackett SL, Merckel LG, Snoeren L, Kontaxis C, Zachiu C, Bol GH, Verhoeff J, Fast MF. Towards mid-position based Stereotactic Body Radiation Therapy on the MR-linac for central lung tumours. Phys Imaging Radiat Oncol 2022; 23:24-31. [PMID: 35923896 PMCID: PMC9341269 DOI: 10.1016/j.phro.2022.05.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 04/28/2022] [Accepted: 05/04/2022] [Indexed: 11/30/2022] Open
Abstract
Background and purpose: Central lung tumours can be treated by magnetic resonance (MR)-guided radiotherapy. Complications might be reduced by decreasing the Planning Target Volume (PTV) using mid-position (midP)-based planning instead of Internal Target Volume (ITV)-based planning. In this study, we aimed to verify a method to automatically derive patient-specific PTV margins for midP-based planning, and show dosimetric robustness of midP-based planning for a 1.5T MR-linac. Materials and methods: Central(n = 12) and peripheral(n = 4) central lung tumour cases who received 8x7.5 Gy were included. A midP-image was reconstructed from ten phases of the 4D-Computed Tomography using deformable image registration. The Gross Tumor Volume (GTV) was delineated on the midP-image and the PTV margin was automatically calculated based on van Herk’s margin recipe, treating the standard deviation of all Deformation Vector Fields, within the GTV, as random error component. Dosimetric robustness of midP-based planning for MR-linac using automatically derived margins was verified by 4D dose-accumulation. MidP-based plans were compared to ITV-based plans. Automatically derived margins were verified with manually derived margins. Results: The mean D95% target coverage in GTV + 2 mm was 59.9 Gy and 62.0 Gy for midP- and ITV-based central lung plans, respectively. The mean lung dose was significantly lower for midP-based treatment plans (difference:-0.3 Gy; p<0.042). Automatically derived margins agreed within one millimeter with manually derived margins. Conclusions: This retrospective study indicates that mid-position-based treatment plans for central lung Stereotactic Body Radiation Therapy yield lower OAR doses compared to ITV-based treatment plans on the MR-linac. Patient-specific GTV-to-PTV margins can be derived automatically and result in clinically acceptable target coverage.
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14
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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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15
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Nierer L, Eze C, da Silva Mendes V, Braun J, Thum P, von Bestenbostel R, Kurz C, Landry G, Reiner M, Niyazi M, Belka C, Corradini S. Dosimetric benefit of MR-guided online adaptive radiotherapy in different tumor entities: liver, lung, abdominal lymph nodes, pancreas and prostate. Radiat Oncol 2022; 17:53. [PMID: 35279185 PMCID: PMC8917666 DOI: 10.1186/s13014-022-02021-6] [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: 12/23/2021] [Accepted: 02/27/2022] [Indexed: 01/18/2023] Open
Abstract
Background Hybrid magnetic resonance (MR)-Linac systems have recently been introduced into clinical practice. The systems allow online adaption of the treatment plan with the aim of compensating for interfractional anatomical changes. The aim of this study was to evaluate the dose volume histogram (DVH)-based dosimetric benefits of online adaptive MR-guided radiotherapy (oMRgRT) across different tumor entities and to investigate which subgroup of plans improved the most from adaption. Methods Fifty patients treated with oMRgRT for five different tumor entities (liver, lung, multiple abdominal lymph nodes, pancreas, and prostate) were included in this retrospective analysis. Various target volume (gross tumor volume GTV, clinical target volume CTV, and planning target volume PTV) and organs at risk (OAR) related DVH parameters were compared between the dose distributions before and after plan adaption. Results All subgroups clearly benefited from online plan adaption in terms of improved PTV coverage. For the liver, lung and abdominal lymph nodes cases, a consistent improvement in GTV coverage was found, while many fractions of the prostate subgroup showed acceptable CTV coverage even before plan adaption. The largest median improvements in GTV near-minimum dose (D98%) were found for the liver (6.3%, p < 0.001), lung (3.9%, p < 0.001), and abdominal lymph nodes (6.8%, p < 0.001) subgroups. Regarding OAR sparing, the largest median OAR dose reduction during plan adaption was found for the pancreas subgroup (-87.0%). However, in the pancreas subgroup an optimal GTV coverage was not always achieved because sparing of OARs was prioritized. Conclusion With online plan adaptation, it was possible to achieve significant improvements in target volume coverage and OAR sparing for various tumor entities and account for interfractional anatomical changes.
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16
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Hadi I, Eze C, Schönecker S, von Bestenbostel R, Rogowski P, Nierer L, Bodensohn R, Reiner M, Landry G, Belka C, Niyazi M, Corradini S. MR-guided SBRT boost for patients with locally advanced or recurrent gynecological cancers ineligible for brachytherapy: feasibility and early clinical experience. Radiat Oncol 2022; 17:8. [PMID: 35033132 PMCID: PMC8760788 DOI: 10.1186/s13014-022-01981-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 12/31/2021] [Indexed: 11/10/2022] Open
Abstract
Background and purpose Chemoradiotherapy (CRT) followed by a brachytherapy (BT) boost is the standard of care for patients with locally advanced or recurrent gynecological cancer (LARGC). However, not every patient is suitable for BT. Therefore, we investigated the feasibility of an MR-guided SBRT boost (MRg-SBRT boost) following CRT of the pelvis. Material and methods Ten patients with LARGC were analyzed retrospectively. The patients were not suitable for BT due to extensive infiltration of the pelvic wall (10%), other adjacent organs (30%), or both (50%), or ineligibility for anesthesia (10%). Online-adaptive treatment planning was performed to control for interfractional anatomical changes. Treatment parameters and toxicity were evaluated to assess the feasibility of MRg-SBRT boost. Results MRg-SBRT boost was delivered to a median total dose of 21.0 Gy in 4 fractions. The median optimized PTV (PTVopt) size was 43.5ccm. The median cumulative dose of 73.6Gy10 was delivered to PTVopt. The cumulative median D2ccm of the rectum was 63.7 Gy; bladder 72.2 Gy; sigmoid 65.8 Gy; bowel 59.9 Gy (EQD23). The median overall treatment time/fraction was 77 min, including the adaptive workflow in 100% of fractions. The median duration of the entire treatment was 50 days. After a median follow-up of 9 months, we observed no CTCAE ≥ °II toxicities. Conclusion These early results report the feasibility of an MRg-SBRT boost approach in patients with LARGC, who were not candidates for BT. When classical BT-OAR constraints are followed, the therapy was well tolerated. Long-term follow-up is needed to validate the results.
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Affiliation(s)
- Indrawati Hadi
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistrasse 15, 81377, Munich, Germany
| | - Chukwuka Eze
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistrasse 15, 81377, Munich, Germany.
| | - Stephan Schönecker
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistrasse 15, 81377, Munich, Germany
| | - Rieke von Bestenbostel
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistrasse 15, 81377, Munich, Germany
| | - Paul Rogowski
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistrasse 15, 81377, Munich, Germany
| | - Lukas Nierer
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistrasse 15, 81377, Munich, Germany
| | - Raphael Bodensohn
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistrasse 15, 81377, Munich, Germany
| | - Michael Reiner
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistrasse 15, 81377, Munich, Germany
| | - Guillaume Landry
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistrasse 15, 81377, Munich, Germany
| | - Claus Belka
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistrasse 15, 81377, Munich, Germany.,German Cancer Consortium (DKTK), Partner site Munich, Munich, Germany
| | - Maximilian Niyazi
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistrasse 15, 81377, Munich, Germany.,German Cancer Consortium (DKTK), Partner site Munich, Munich, Germany
| | - Stefanie Corradini
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistrasse 15, 81377, Munich, Germany
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Hall WA, Paulson E, Li XA, Erickson B, Schultz C, Tree A, Awan M, Low DA, McDonald BA, Salzillo T, Glide-Hurst CK, Kishan AU, Fuller CD. Magnetic resonance linear accelerator technology and adaptive radiation therapy: An overview for clinicians. CA Cancer J Clin 2022; 72:34-56. [PMID: 34792808 PMCID: PMC8985054 DOI: 10.3322/caac.21707] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 09/01/2021] [Accepted: 09/22/2021] [Indexed: 12/25/2022] Open
Abstract
Radiation therapy (RT) continues to play an important role in the treatment of cancer. Adaptive RT (ART) is a novel method through which RT treatments are evolving. With the ART approach, computed tomography or magnetic resonance (MR) images are obtained as part of the treatment delivery process. This enables the adaptation of the irradiated volume to account for changes in organ and/or tumor position, movement, size, or shape that may occur over the course of treatment. The advantages and challenges of ART maybe somewhat abstract to oncologists and clinicians outside of the specialty of radiation oncology. ART is positioned to affect many different types of cancer. There is a wide spectrum of hypothesized benefits, from small toxicity improvements to meaningful gains in overall survival. The use and application of this novel technology should be understood by the oncologic community at large, such that it can be appropriately contextualized within the landscape of cancer therapies. Likewise, the need to test these advances is pressing. MR-guided ART (MRgART) is an emerging, extended modality of ART that expands upon and further advances the capabilities of ART. MRgART presents unique opportunities to iteratively improve adaptive image guidance. However, although the MRgART adaptive process advances ART to previously unattained levels, it can be more expensive, time-consuming, and complex. In this review, the authors present an overview for clinicians describing the process of ART and specifically MRgART.
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MESH Headings
- History, 20th Century
- History, 21st Century
- Humans
- Magnetic Resonance Imaging, Interventional/history
- Magnetic Resonance Imaging, Interventional/instrumentation
- Magnetic Resonance Imaging, Interventional/methods
- Magnetic Resonance Imaging, Interventional/trends
- Neoplasms/diagnostic imaging
- Neoplasms/radiotherapy
- Particle Accelerators
- Radiation Oncology/history
- Radiation Oncology/instrumentation
- Radiation Oncology/methods
- Radiation Oncology/trends
- Radiotherapy Planning, Computer-Assisted/history
- Radiotherapy Planning, Computer-Assisted/instrumentation
- Radiotherapy Planning, Computer-Assisted/methods
- Radiotherapy Planning, Computer-Assisted/trends
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Affiliation(s)
- William A. Hall
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Eric Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - X. Allen Li
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Beth Erickson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Christopher Schultz
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Alison Tree
- The Royal Marsden National Health Service Foundation Trust and the Institute of Cancer Research, London, United Kingdom
| | - Musaddiq Awan
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Daniel A. Low
- Department of Radiation Oncology, University of California-Los Angeles, Los Angeles, California
| | - Brigid A. McDonald
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - Travis Salzillo
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - Carri K. Glide-Hurst
- Department of Radiation Oncology, University of Wisconsin-Madison, Madison, Wisconsin
| | - Amar U. Kishan
- Department of Radiation Oncology, University of California-Los Angeles, Los Angeles, California
| | - Clifton D. Fuller
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, Texas
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Shao HC, Huang X, Folkert MR, Wang J, Zhang Y. Automatic liver tumor localization using deep learning-based liver boundary motion estimation and biomechanical modeling (DL-Bio). Med Phys 2021; 48:7790-7805. [PMID: 34632589 DOI: 10.1002/mp.15275] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 10/01/2021] [Accepted: 10/02/2021] [Indexed: 12/25/2022] Open
Abstract
PURPOSE Recently, two-dimensional-to-three-dimensional (2D-3D) deformable registration has been applied to deform liver tumor contours from prior reference images onto estimated cone-beam computed tomography (CBCT) target images to automate on-board tumor localizations. Biomechanical modeling has also been introduced to fine-tune the intra-liver deformation-vector-fields (DVFs) solved by 2D-3D deformable registration, especially at low-contrast regions, using tissue elasticity information and liver boundary DVFs. However, the caudal liver boundary shows low contrast from surrounding tissues in the cone-beam projections, which degrades the accuracy of the intensity-based 2D-3D deformable registration there and results in less accurate boundary conditions for biomechanical modeling. We developed a deep-learning (DL)-based method to optimize the liver boundary DVFs after 2D-3D deformable registration to further improve the accuracy of subsequent biomechanical modeling and liver tumor localization. METHODS The DL-based network was built based on the U-Net architecture. The network was trained in a supervised fashion to learn motion correlation between cranial and caudal liver boundaries to optimize the liver boundary DVFs. Inputs of the network had three channels, and each channel featured the 3D DVFs estimated by the 2D-3D deformable registration along one Cartesian direction (x, y, z). To incorporate patient-specific liver boundary information into the DVFs, the DVFs were masked by a liver boundary ring structure generated from the liver contour of the prior reference image. The network outputs were the optimized DVFs along the liver boundary with higher accuracy. From these optimized DVFs, boundary conditions were extracted for biomechanical modeling to further optimize the solution of intra-liver tumor motion. We evaluated the method using 34 liver cancer patient cases, with 24 for training and 10 for testing. We evaluated and compared the performance of three methods: 2D-3D deformable registration, 2D-3D-Bio (2D-3D deformable registration with biomechanical modeling), and DL-Bio (DL model prediction with biomechanical modeling). The tumor localization errors were quantified through calculating the center-of-mass-errors (COMEs), DICE coefficients, and Hausdorff distance between deformed liver tumor contours and manually segmented "gold-standard" contours. RESULTS The predicted DVFs by the DL model showed improved accuracy at the liver boundary, which translated into more accurate liver tumor localizations through biomechanical modeling. On a total of 90 evaluated images and tumor contours, the average (± sd) liver tumor COMEs of the 2D-3D, 2D-3D-Bio, and DL-Bio techniques were 4.7 ± 1.9 mm, 2.9 ± 1.0 mm, and 1.7 ± 0.4 mm. The corresponding average (± sd) DICE coefficients were 0.60 ± 0.12, 0.71 ± 0.07, and 0.78 ± 0.03; and the average (± sd) Hausdorff distances were 7.0 ± 2.6 mm, 5.4 ± 1.5 mm, and 4.5 ± 1.3 mm, respectively. CONCLUSION DL-Bio solves a general correlation model to improve the accuracy of the DVFs at the liver boundary. With improved boundary conditions, the accuracy of biomechanical modeling can be further increased for accurate intra-liver low-contrast tumor localization.
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Affiliation(s)
- Hua-Chieh Shao
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Xiaokun Huang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Michael R Folkert
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Jing Wang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - You Zhang
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
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Terpstra ML, Maspero M, Bruijnen T, Verhoeff JJC, Lagendijk JJW, van den Berg CAT. Real-time 3D motion estimation from undersampled MRI using multi-resolution neural networks. Med Phys 2021; 48:6597-6613. [PMID: 34525223 PMCID: PMC9298075 DOI: 10.1002/mp.15217] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Revised: 08/12/2021] [Accepted: 08/30/2021] [Indexed: 12/25/2022] Open
Abstract
Purpose: To enable real‐time adaptive magnetic resonance imaging–guided radiotherapy (MRIgRT) by obtaining time‐resolved three‐dimensional (3D) deformation vector fields (DVFs) with high spatiotemporal resolution and low latency (<500 ms). Theory and Methods: Respiratory‐resolved T1‐weighted 4D‐MRI of 27 patients with lung cancer were acquired using a golden‐angle radial stack‐of‐stars readout. A multiresolution convolutional neural network (CNN) called TEMPEST was trained on up to 32× retrospectively undersampled MRI of 17 patients, reconstructed with a nonuniform fast Fourier transform, to learn optical flow DVFs. TEMPEST was validated using 4D respiratory‐resolved MRI, a digital phantom, and a physical motion phantom. The time‐resolved motion estimation was evaluated in‐vivo using two volunteer scans, acquired on a hybrid MR‐scanner with integrated linear accelerator. Finally, we evaluated the model robustness on a publicly‐available four‐dimensional computed tomography (4D‐CT) dataset. Results: TEMPEST produced accurate DVFs on respiratory‐resolved MRI at 20‐fold acceleration, with the average end‐point‐error <2 mm, both on respiratory‐sorted MRI and on a digital phantom. TEMPEST estimated accurate time‐resolved DVFs on MRI of a motion phantom, with an error <2 mm at 28× undersampling. On two volunteer scans, TEMPEST accurately estimated motion compared to the self‐navigation signal using 50 spokes per dynamic (366× undersampling). At this undersampling factor, DVFs were estimated within 200 ms, including MRI acquisition. On fully sampled CT data, we achieved a target registration error of 1.87±1.65 mm without retraining the model. Conclusion: A CNN trained on undersampled MRI produced accurate 3D DVFs with high spatiotemporal resolution for MRIgRT.
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Affiliation(s)
- Maarten L Terpstra
- Department of Radiotherapy, 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
| | - Matteo Maspero
- Department of Radiotherapy, 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
| | - Tom Bruijnen
- Department of Radiotherapy, 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
| | - Joost J C Verhoeff
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jan J W Lagendijk
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Cornelis A T van den Berg
- Department of Radiotherapy, 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
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20
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Subashi E, Lim SB, Gonzalez X, Tyagi N. Longitudinal assessment of quality assurance measurements in a 1.5T MR-linac: Part I-Linear accelerator. J Appl Clin Med Phys 2021; 22:190-201. [PMID: 34505349 PMCID: PMC8504604 DOI: 10.1002/acm2.13418] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 08/16/2021] [Accepted: 08/29/2021] [Indexed: 01/04/2023] Open
Abstract
Purpose To describe and report longitudinal quality assurance (QA) measurements for the mechanical and dosimetric performance of an Elekta Unity MR‐linac during the first year of clinical use in our institution. Materials and methods The mechanical and dosimetric performance of the MR‐linac was evaluated with daily, weekly, monthly, and annual QA testing. The measurements monitor the size of the radiation isocenter, the MR‐to‐MV isocenter concordance, MLC and jaw position, the accuracy and reproducibility of step‐and‐shoot delivery, radiation output and beam profile constancy, and patient‐specific QA for the first 50 treatments in our institution. Results from end‐to‐end QA using anthropomorphic phantoms are also included as a reference for baseline comparisons. Measurements were performed in water or water‐equivalent plastic using ion chambers of various sizes, an ion chamber array, MR‐compatible 2D/3D diode array, portal imager, MRI, and radiochromic film. Results The diameter of the radiation isocenter and the distance between the MR/MV isocenters was (μ ± σ) 0.39 ± 0.01 mm and 0.89 ± 0.05 mm, respectively. Trend analysis shows both measurements to be well within the tolerance of 1.0 mm. MLC and jaw positional accuracy was within 1.0 mm while the dosimetric performance of step‐and‐shoot delivery was within 2.0%, irrespective of gantry angle. Radiation output and beam profile constancy were within 2.0% and 1.0%, respectively. End‐to‐end testing performed with ion‐chamber and radiochromic film showed excellent agreement with treatment plan. Patient‐specific QA using a 3D diode array identified gantry angles with low‐pass rates allowing for improvements in plan quality after necessary adjustments. Conclusion The MR‐linac operates within the guidelines of current recommendations for linear accelerator performance, stability, and safety. The analysis of the data supports the recently published guidance in establishing clinically acceptable tolerance levels for relative and absolute measurements.
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Affiliation(s)
- Ergys Subashi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Seng Boh Lim
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
| | | | - Neelam Tyagi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
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21
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Ghandourh W, Batumalai V, Boxer M, Holloway L. Can reducing planning safety margins broaden the inclusion criteria for lung stereotactic ablative body radiotherapy? J Med Radiat Sci 2021; 68:298-309. [PMID: 33934559 PMCID: PMC8424332 DOI: 10.1002/jmrs.469] [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] [Received: 09/17/2020] [Revised: 01/31/2021] [Accepted: 03/24/2021] [Indexed: 11/29/2022] Open
Abstract
INTRODUCTION Stereotactic ablative body radiotherapy (SABR) is currently indicated for inoperable, early-stage non-small cell lung carcinoma (NSCLC). Advancements in image-guidance technology continue to improve treatment precision and enable reductions in planning safety margins. We investigated the dosimetric benefits of margin reduction, its potential to extend SABR to more NSCLC patients and the factors influencing plan acceptability. METHODS This retrospective analysis included 61 patients (stage IA-IIIA) treated with conventional radiotherapy. Patients were ineligible for SABR due to tumour size or proximity to organs at risk (OAR). Using Pinnacle auto-planning, three SABR plans were generated for each patient: a regular planning target volume margin plan, a reduced margin plan (gross tumour volume GTV+3 mm) and a non-margin plan. Targets were planned to 48Gy/4 or 50Gy/5 fractions depending on location. Plans were compared in terms of target coverage, OAR doses and dosimetric acceptability based on local guidelines. Predictors of acceptability were investigated using logistic regression analysis. RESULTS Compared to regular margin plans, both reduced margin and non-margin plans resulted in significant reductions to almost all dose constraints. Dose conformity was significantly worse in non-margin plans (P < 0.05) and strongly correlated with targets' surface area/volume ratio (R2 = 0.9, P < 0.05). 26% of reduced margin plans were acceptable, compared to 54% of non-margin plans. GTV overlap with OARs significantly affected plan acceptability (OR 0.008, 95% CI 0.001-0.073). CONCLUSION Margin reduction significantly reduced OAR doses enabling acceptable plans to be achieved for patients previously excluded from SABR. Indications for lung SABR may broaden as treatment accuracy continues to improve; further work is needed to identify patients most likely to benefit.
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Affiliation(s)
- Wsam Ghandourh
- South Western Clinical SchoolFaculty of MedicineUniversity of New South WalesSydneyNew South WalesAustralia
- Liverpool and Macarthur Cancer Therapy CentresSydneyNew South WalesAustralia
- Ingham Institute of Applied Medical ResearchSydneyNew South WalesAustralia
| | - Vikneswary Batumalai
- South Western Clinical SchoolFaculty of MedicineUniversity of New South WalesSydneyNew South WalesAustralia
- Liverpool and Macarthur Cancer Therapy CentresSydneyNew South WalesAustralia
- Ingham Institute of Applied Medical ResearchSydneyNew South WalesAustralia
- Collaboration for Cancer Outcomes Research and Evaluation (CCORE)SydneyNew South WalesAustralia
| | - Miriam Boxer
- GenesisCare ConcordSydneyNew South WalesAustralia
| | - Lois Holloway
- South Western Clinical SchoolFaculty of MedicineUniversity of New South WalesSydneyNew South WalesAustralia
- Liverpool and Macarthur Cancer Therapy CentresSydneyNew South WalesAustralia
- Ingham Institute of Applied Medical ResearchSydneyNew South WalesAustralia
- Centre for Medical Radiation PhysicsUniversity of WollongongWollongongNew South WalesAustralia
- Institute of Medical PhysicsSchool of PhysicsUniversity of SydneySydneyNew South WalesAustralia
- Department of Human OncologySchool of Medicine and Public HealthUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
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22
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Wang X, Pan H, Cheng Q, Wang X, Xu W. Dosimetric Deviations of Bragg-Peak Position Shifts in Uniform Magnetic Fields for Magnetic Resonance Imaging-Guiding Proton Radiotherapy: A Monte Carlo Study. Front Public Health 2021; 9:641915. [PMID: 34414150 PMCID: PMC8369236 DOI: 10.3389/fpubh.2021.641915] [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: 12/15/2020] [Accepted: 06/02/2021] [Indexed: 11/15/2022] Open
Abstract
Objective: To investigate dosimetric deviations in scanning protons for Bragg-peak position shifts, which were caused by proton spiral tracks in an ideal uniform field of magnetic resonance (MRI) imaging-guided proton radiotherapy (MRI-IGPRT). Methods: The FLUKA Monte-Carlo (MC) code was used to simulate the spiral tracks of protons penetrating water with initial energies of 70–270 MeV under the influence of field strength of 0.0–3.0 Tesla in commercial MRI systems. Two indexes, lateral shift (marked as WD) perpendicular to the field and a penetration-depth shift (marked as ΔDD) along the beam path, were employed for the Bragg-peak position of spiral proton track analysis. A comparison was performed between MC and classical analytical model to check the simulation results. The shape of the 2D/3D dose distribution of proton spots at the depth of Bragg-Peak was also investigated. The ratio of Gaussian-fit value between longitudinal and transverse major axes was used to indicate the asymmetric index. The skewness of asymmetry was evaluated at various dose levels by the radius ratio of circumscribed and inscribed circles by fitting a semi-ellipse circle of 2D distribution. Results: The maximum of WD deflection is 2.82 cm while the maximum of shortening ΔDD is 0.44 cm for proton at 270 MeV/u under a magnetic field of 3.0 Tesla. The trend of WD and ΔDD from MC simulation was consistent with the analytical model, which means the reverse equation of the analytical model can be applied to determine the proper field strength of the magnet and the initial energy of the proton for the planned dose. The asymmetry of 2D/3D dose distribution under the influence of a magnetic field was increased with higher energy, and the skewness of asymmetry for one proton energy at various dose levels was also increased with a larger radius, i.e., a lower dose level. Conclusions: The trend of the spiral proton track under a uniform magnetic field was obtained in this study using either MC simulation or the analytical model, which can provide an optimized and planned dose of the proton beam in the clinical application of MRI-IGPRT.
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Affiliation(s)
- Xiaowa Wang
- Department of Nulcear Science and Technology, Institute of Modern Physics, Fudan University, Shanghai, China.,Key Laboratory of Nuclear Physics and Ion-Beam Application (MOE), Fudan University, Shanghai, China.,Shanghai Proton and Heavy Ion Center, Shanghai, China.,Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China
| | - Hailun Pan
- Department of Nulcear Science and Technology, Institute of Modern Physics, Fudan University, Shanghai, China.,Key Laboratory of Nuclear Physics and Ion-Beam Application (MOE), Fudan University, Shanghai, China
| | - Qinqin Cheng
- Department of Nulcear Science and Technology, Institute of Modern Physics, Fudan University, Shanghai, China.,Key Laboratory of Nuclear Physics and Ion-Beam Application (MOE), Fudan University, Shanghai, China
| | - Xufei Wang
- Department of Nulcear Science and Technology, Institute of Modern Physics, Fudan University, Shanghai, China.,Key Laboratory of Nuclear Physics and Ion-Beam Application (MOE), Fudan University, Shanghai, China
| | - Wenzhen Xu
- Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China
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23
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Freedman JN, Gurney-Champion OJ, Nill S, Shiarli AM, Bainbridge HE, Mandeville HC, Koh DM, McDonald F, Kachelrieß M, Oelfke U, Wetscherek A. Rapid 4D-MRI reconstruction using a deep radial convolutional neural network: Dracula. Radiother Oncol 2021; 159:209-217. [PMID: 33812914 PMCID: PMC8216429 DOI: 10.1016/j.radonc.2021.03.034] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 03/07/2021] [Accepted: 03/26/2021] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE 4D and midposition MRI could inform plan adaptation in lung and abdominal MR-guided radiotherapy. We present deep learning-based solutions to overcome long 4D-MRI reconstruction times while maintaining high image quality and short scan times. METHODS Two 3D U-net deep convolutional neural networks were trained to accelerate the 4D joint MoCo-HDTV reconstruction. For the first network, gridded and joint MoCo-HDTV-reconstructed 4D-MRI were used as input and target data, respectively, whereas the second network was trained to directly calculate the midposition image. For both networks, input and target data had dimensions of 256 × 256 voxels (2D) and 16 respiratory phases. Deep learning-based MRI were verified against joint MoCo-HDTV-reconstructed MRI using the structural similarity index (SSIM) and the naturalness image quality evaluator (NIQE). Moreover, two experienced observers contoured the gross tumour volume and scored the images in a blinded study. RESULTS For 12 subjects, previously unseen by the networks, high-quality 4D and midposition MRI (1.25 × 1.25 × 3.3 mm3) were each reconstructed from gridded images in only 28 seconds per subject. Excellent agreement was found between deep-learning-based and joint MoCo-HDTV-reconstructed MRI (average SSIM ≥ 0.96, NIQE scores 7.94 and 5.66). Deep-learning-based 4D-MRI were clinically acceptable for target and organ-at-risk delineation. Tumour positions agreed within 0.7 mm on midposition images. CONCLUSION Our results suggest that the joint MoCo-HDTV and midposition algorithms can each be approximated by a deep convolutional neural network. This rapid reconstruction of 4D and midposition MRI facilitates online treatment adaptation in thoracic or abdominal MR-guided radiotherapy.
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Affiliation(s)
- Joshua N Freedman
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Oliver J Gurney-Champion
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom; Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, The Netherlands.
| | - Simeon Nill
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Anna-Maria Shiarli
- Department of Radiotherapy, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Hannah E Bainbridge
- Department of Radiotherapy, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom; Department of Radiotherapy, Portsmouth Hospitals University NHS Trust, Queen Alexandra Hospital, United Kingdom.
| | - Henry C Mandeville
- Department of Radiotherapy, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Dow-Mu Koh
- Department of Radiology, The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Fiona McDonald
- Department of Radiotherapy, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Marc Kachelrieß
- Division of X-Ray Imaging and CT, German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Uwe Oelfke
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
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24
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Ohno T, Kubota T, Yano M, Fujiwara Y, Araki F. Monte Carlo study of dosimetric impact of gadolinium contrast medium in transverse field MR-Linac system. Phys Med 2021; 86:19-30. [PMID: 34049117 DOI: 10.1016/j.ejmp.2021.05.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 04/19/2021] [Accepted: 05/12/2021] [Indexed: 12/01/2022] Open
Abstract
The aim of this study is to evaluate the dosimetric impact of gadolinium contrast medium (Gadovist) in a transverse MR-Linac system using Monte Carlo methods. The dose distributions were calculated using two heterogeneous multi-layer phantoms consisting of Gadovist, water, bone, and lung. The photon beam was irradiated with a filed size of 5 × 5 cm2, and a transverse magnetic field of 0-3.0 T was applied perpendicular to the incident photon beam. Next, dose distributions for brain, head and neck (H&N), and lung cancer patients were calculated using a patient voxel-based phantom with and without replacing the patient's GTV with Gadovist. The dose at the water-Gadovist interface increased by 8% without a magnetic field. A similar dose increment was observed at 0.35 T. In contrast, the dose increment at the water-Gadovist interface was small at 1.5 T and a dose decrement of 5% was observed at 3.0 T. The dose variation at the lung-Gadovist interface was larger than that at the water-Gadovist interface. The mass collision stopping power ratio for Gadovist was 7% lower than that for water, whereas, the electron fluence spectra at the water-Gadovist interface increased by 17.5%. In a patient study, Gadovist increased the Dmean for brain, H&N, and lung cancer patients by 0.65-8.9%. The dose variation due to Gadovist grew large in the low-dose region in H&N and lung cancer. The GTV dose variation due to Gadovist in all treatment site was below 2% at 0-3 T if the Gadovist concentration was lower than 0.2 mmol/ml-1.
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Affiliation(s)
- Takeshi Ohno
- Department of Health Sciences, Faculty of Life Sciences, Kumamoto University, 4-24-1 Kuhonji, Kumamoto, Japan.
| | - Takahiro Kubota
- Kokura Memorial Hospital, 3-2-1 Asano, Kokura, Fukuoka, Japan
| | - Masayuki Yano
- Saga Heavy Ion Medical Accelerator in Tosu, Koga-machi, Tosu, Saga, Japan
| | - Yasuhiro Fujiwara
- Department of Health Sciences, Faculty of Life Sciences, Kumamoto University, 4-24-1 Kuhonji, Kumamoto, Japan
| | - Fujio Araki
- Department of Health Sciences, Faculty of Life Sciences, Kumamoto University, 4-24-1 Kuhonji, Kumamoto, Japan
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Yuan J, Xue C, Lo G, Wong OL, Zhou Y, Yu SK, Cheung KY. Quantitative assessment of acquisition imaging parameters on MRI radiomics features: a prospective anthropomorphic phantom study using a 3D-T2W-TSE sequence for MR-guided-radiotherapy. Quant Imaging Med Surg 2021; 11:1870-1887. [PMID: 33936971 DOI: 10.21037/qims-20-865] [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] [Indexed: 01/01/2023]
Abstract
Background MRI pulse sequences and imaging parameters substantially influence the variation of MRI radiomics features, thus impose a critical challenge on MRI radiomics reproducibility and reliability. This study aims to prospectively investigate the impact of various imaging parameters on MRI radiomics features in a 3D T2-weighted (T2W) turbo-spin-echo (TSE) pulse sequence for MR-guided-radiotherapy (MRgRT). Methods An anthropomorphic phantom was scanned using a 3D-T2W-TSE MRgRT sequence at 1.5T under a variety of acquisition imaging parameter changes. T1 and T2 relaxation times of the phantom were also measured. 93 first-order and texture radiomics features in the original and 14 transformed images, yielding 1,395 features in total, were extracted from 10 volumes-of-interest (VOIs). The percentage deviation (d%) of radiomics feature values from the baseline values and intra-class correlation coefficient (ICC) with the baseline were calculated. Robust radiomics features were identified based on the excellent agreement of radiomics feature values with the baseline, i.e., the averaged d% <5% and ICC >0.90 in all VOIs for all imaging parameter variations. Results The radiomics feature values changed considerably but to different degrees with different imaging parameter adjustments, in the ten VOIs. The deviation d% ranged from 0.02% to 321.3%, with a mean of 12.5% averaged for all original features in all ten VOIs. First-order and GLCM features were generally more robust to imaging parameters than other features in the original images. There were also significantly different radiomics feature values (ANOVA, P<0.001) between the original and the transformed images, exhibiting quite different robustness to imaging parameters. 330 out of 1395 features (23.7%) robust to imaging parameters were identified. GLCM and GLSZM features had the most (42.5%, 153/360) and least (3.8%, 9/240) robust features in the original and transformed images, respectively. Conclusions This study helps better understand the quantitative dependence of radiomics feature values on imaging parameters in a 3D-T2W-TSE sequence for MRgRT. Imaging parameter heterogeneity should be considered as a significant source of radiomics variability and uncertainty, which must be well harmonized for reliable clinical use. The identified robust features to imaging parameters are helpful for the pre-selection of radiomics features for reliable radiomics modeling.
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Affiliation(s)
- Jing Yuan
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong, Hong Kong SAR, China
| | - Cindy Xue
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong, Hong Kong SAR, China
| | - Gladys Lo
- Department of Diagnostic & Interventional Radiology, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong, Hong Kong SAR, China
| | - Oi Lei Wong
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong, Hong Kong SAR, China
| | - Yihang Zhou
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong, Hong Kong SAR, China
| | - Siu Ki Yu
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong, Hong Kong SAR, China
| | - Kin Yin Cheung
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Happy Valley, Hong Kong, Hong Kong SAR, China
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Park S, Gach HM, Kim S, Lee SJ, Motai Y. Autoencoder-Inspired Convolutional Network-Based Super-Resolution Method in MRI. IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE 2021; 9:1800113. [PMID: 34168920 PMCID: PMC8216682 DOI: 10.1109/jtehm.2021.3076152] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 04/14/2021] [Accepted: 04/24/2021] [Indexed: 12/11/2022]
Abstract
OBJECTIVE To introduce an MRI in-plane resolution enhancement method that estimates High-Resolution (HR) MRIs from Low-Resolution (LR) MRIs. METHOD & MATERIALS Previous CNN-based MRI super-resolution methods cause loss of input image information due to the pooling layer. An Autoencoder-inspired Convolutional Network-based Super-resolution (ACNS) method was developed with the deconvolution layer that extrapolates the missing spatial information by the convolutional neural network-based nonlinear mapping between LR and HR features of MRI. Simulation experiments were conducted with virtual phantom images and thoracic MRIs from four volunteers. The Peak Signal-to-Noise Ratio (PSNR), Structure SIMilarity index (SSIM), Information Fidelity Criterion (IFC), and computational time were compared among: ACNS; Super-Resolution Convolutional Neural Network (SRCNN); Fast Super-Resolution Convolutional Neural Network (FSRCNN); Deeply-Recursive Convolutional Network (DRCN). RESULTS ACNS achieved comparable PSNR, SSIM, and IFC results to SRCNN, FSRCNN, and DRCN. However, the average computation speed of ACNS was 6, 4, and 35 times faster than SRCNN, FSRCNN, and DRCN, respectively under the computer setup used with the actual average computation time of 0.15 s per [Formula: see text].
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Affiliation(s)
- Seonyeong Park
- Department of BioengineeringUniversity of Illinois at Urbana-ChampaignUrbanaIL61820USA
| | - H. Michael Gach
- Department of Radiation OncologyWashington University in St. LouisSt. LouisMO63130USA
| | - Siyong Kim
- Department of Radiation OncologyDivision of Medical PhysicsVirginia Commonwealth UniversityRichmondVA23284USA
| | - Suk Jin Lee
- TSYS School of Computer ScienceColumbus State UniversityColumbusGA31907USA
| | - Yuichi Motai
- Department of Electrical and Computer EngineeringVirginia Commonwealth UniversityRichmondVA23284USA
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Uijtewaal P, Borman PTS, Woodhead PL, Hackett SL, Raaymakers BW, Fast MF. Dosimetric evaluation of MRI-guided multi-leaf collimator tracking and trailing for lung stereotactic body radiation therapy. Med Phys 2021; 48:1520-1532. [PMID: 33583042 PMCID: PMC8251582 DOI: 10.1002/mp.14772] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 01/12/2021] [Accepted: 02/04/2021] [Indexed: 12/25/2022] Open
Abstract
PURPOSE The treatment margins for lung stereotactic body radiotherapy (SBRT) are often large to cover the tumor excursions resulting from respiration, such that underdosage of the tumor can be avoided. Magnetic resonance imaging (MRI)-guided multi-leaf collimator (MLC) tracking can potentially reduce the influence of respiration to allow for smaller treatment margins. However, tracking is accompanied by system latency that may induce residual tracking errors. Alternatively, a simpler mid-position delivery combined with trailing can be used. Trailing reduces influences of respiration by compensating for baseline motion, to potentially improve target coverage. In this study, we aim to show the feasibility of MRI-guided tracking and trailing to reduce influences of respiration during lung SBRT. METHODS We implemented MRI-guided tracking on the MR-linac using an Elekta research tracking interface to track tumor motion during intensity modulated radiotherapy (IMRT). A Quasar MRI 4 D phantom was used to generate Lujan motion ( cos 4 , 4 s period, 20 mm peak-to-peak amplitude) with and without 1.0 mm/min cranial drift. Phantom tumor positions were estimated from sagittal 2D cine-MRI (4 or 8 Hz) using cross-correlation-based template matching. To compensate the anticipated system latency, a linear ridge regression predictor was optimized for online MRI by comparing two predictor training approaches: training on multiple traces and training on a single trace. We created 15-beam clinical-grade lung SBRT plans for central targets (8 × 7.5 Gy) and peripheral targets (3 × 18 Gy) with different PTV margins for mid-position based motion management (3-5 mm) and for MLC tracking (3 mm). We used a film insert with a 3 cm spherical target to measure the spatial distribution and quantity of the delivered dose. A 1%/1 mm local gamma-analysis quantified dose differences between motion management strategies and reference cases. Additionally, a dose area histogram (DAH) revealed the target coverage relative to the reference scenario. RESULTS The prediction filter gain was on average 25% when trained on multiple traces and 44% when trained on a single trace. The filter reduced system latency from 313 ± 2 ms to 0 ± 5 ms for 4 Hz imaging and from 215 ± 3 ms to 3 ± 3 ms for 8 Hz. The local gamma analysis for the central delivery showed that tracking improved the gamma pass-rate from 23% to 96% for periodic motion and from 14% to 93% when baseline drift was applied. For the peripheral delivery during periodic motion, delivery pass-rates improved from 22% to 93%. Comparing mid-position delivery to trailing for periodic+drift motion increased the local gamma pass rate from 15% to 98% for a central delivery and from 8% to 98% for a peripheral delivery. Furthermore, the DAHs revealed a relative D 98 % GTV coverage of 101% and 97% compared to the reference scenario for, respectively, central and peripheral tracking of periodic+drift motion. For trailing, a relative D 98 % of 99% for central and 98% for peripheral trailing was found. CONCLUSIONS We provided a first experimental demonstration of the technical feasibility of MRI-guided MLC tracking and trailing for central and peripheral lung SBRT. Tracking maximizes the sparing of healthy tissue, while trailing is highly effective in mitigating baseline motion.
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Affiliation(s)
- Prescilla Uijtewaal
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Pim T S Borman
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Peter L Woodhead
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Sara L Hackett
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Bas W Raaymakers
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
| | - Martin F Fast
- Department of Radiotherapy, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584 CX, The Netherlands
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Pomp J, van Asselen B, Tersteeg RHA, Vink A, Hassink RJ, van der Kaaij NP, van Aarnhem GEEHL, Verhoeff JJC. Sarcoma of the Heart Treated with Stereotactic MR-Guided Online Adaptive Radiation Therapy. Case Rep Oncol 2021; 14:453-458. [PMID: 33790766 PMCID: PMC7983626 DOI: 10.1159/000513623] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 12/07/2020] [Indexed: 12/25/2022] Open
Abstract
We present the first case in the literature of a patient with a histology-proven intimal sarcoma of the heart, recurrent after surgery, treated with stereotactic MR-guided online adaptive radiation therapy on an MR-Linac machine. The treatment was feasible and well tolerated. The CT scan 6 months after the last treatment showed stable disease.
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Affiliation(s)
- Jacquelien Pomp
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Bram van Asselen
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Robbert H A Tersteeg
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Aryan Vink
- Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Rutger J Hassink
- Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Niels P van der Kaaij
- Department of Cardiothoracic Surgery, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | - Joost J C Verhoeff
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands
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29
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Crockett CB, Samson P, Chuter R, Dubec M, Faivre-Finn C, Green OL, Hackett SL, McDonald F, Robinson C, Shiarli AM, Straza MW, Verhoeff JJC, Werner-Wasik M, Vlacich G, Cobben D. Initial Clinical Experience of MR-Guided Radiotherapy for Non-Small Cell Lung Cancer. Front Oncol 2021; 11:617681. [PMID: 33777759 PMCID: PMC7988221 DOI: 10.3389/fonc.2021.617681] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 01/12/2021] [Indexed: 02/06/2023] Open
Abstract
Curative-intent radiotherapy plays an integral role in the treatment of lung cancer and therefore improving its therapeutic index is vital. MR guided radiotherapy (MRgRT) systems are the latest technological advance which may help with achieving this aim. The majority of MRgRT treatments delivered to date have been stereotactic body radiation therapy (SBRT) based and include the treatment of (ultra-) central tumors. However, there is a move to also implement MRgRT as curative-intent treatment for patients with inoperable locally advanced NSCLC. This paper presents the initial clinical experience of using the two commercially available systems to date: the ViewRay MRIdian and Elekta Unity. The challenges and potential solutions associated with MRgRT in lung cancer will also be highlighted.
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Affiliation(s)
- Cathryn B. Crockett
- Radiotherapy Related Research, The Christie NHS Foundation Trust, Manchester, United Kingdom
| | - Pamela Samson
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, MO, United States
| | - Robert Chuter
- Radiotherapy Related Research, The Christie NHS Foundation Trust, Manchester, United Kingdom
- Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom
| | - Michael Dubec
- Radiotherapy Related Research, The Christie NHS Foundation Trust, Manchester, United Kingdom
- Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom
| | - Corinne Faivre-Finn
- Radiotherapy Related Research, The Christie NHS Foundation Trust, Manchester, United Kingdom
- Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom
| | - Olga L. Green
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, MO, United States
| | - Sara L. Hackett
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Fiona McDonald
- Department of Radiotherapy, Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Clifford Robinson
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, MO, United States
| | - Anna-Maria Shiarli
- Department of Radiotherapy, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Michael W. Straza
- Department of Radiation Oncology, Froedtert and the Medical College of Wisconsin, Milwaukee, WI, United States
| | - Joost J. C. Verhoeff
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Maria Werner-Wasik
- Department of Radiation Oncology, Sidney Kimmel Cancer Center at Thomas Jefferson University, Philadelphia, PA, United States
| | - Gregory Vlacich
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, MO, United States
| | - David Cobben
- Radiotherapy Related Research, The Christie NHS Foundation Trust, Manchester, United Kingdom
- Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom
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30
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Rabe M, Paganelli C, Riboldi M, Bondesson D, Jörg Schneider M, Chmielewski T, Baroni G, Dinkel J, Reiner M, Landry G, Parodi K, Belka C, Kamp F, Kurz C. Porcine lung phantom-based validation of estimated 4D-MRI using orthogonal cine imaging for low-field MR-Linacs. Phys Med Biol 2021; 66:055006. [PMID: 33171458 DOI: 10.1088/1361-6560/abc937] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Real-time motion monitoring of lung tumors with low-field magnetic resonance imaging-guided linear accelerators (MR-Linacs) is currently limited to sagittal 2D cine magnetic resonance imaging (MRI). To provide input data for improved intrafractional and interfractional adaptive radiotherapy, the 4D anatomy has to be inferred from data with lower dimensionality. The purpose of this study was to experimentally validate a previously proposed propagation method that provides continuous time-resolved estimated 4D-MRI based on orthogonal cine MRI for a low-field MR-Linac. Ex vivo porcine lungs were injected with artificial nodules and mounted in a dedicated phantom that allows for the simulation of periodic and reproducible breathing motion. The phantom was scanned with a research version of a commercial 0.35 T MR-Linac. Respiratory-correlated 4D-MRI were reconstructed and served as ground truth images. Series of interleaved orthogonal slices in sagittal and coronal orientation, intersecting the injected targets, were acquired at 7.3 Hz. Estimated 4D-MRI at 3.65 Hz were created in post-processing using the propagation method and compared to the ground truth 4D-MRI. Eight datasets at different breathing frequencies and motion amplitudes were acquired for three porcine lungs. The overall median (95[Formula: see text] percentile) deviation between ground truth and estimated deformation vector fields was 2.3 mm (5.7 mm), corresponding to 0.7 (1.6) times the in-plane imaging resolution (3.5 × 3.5 mm2). Median (95[Formula: see text] percentile) estimated nodule position errors were 1.5 mm (3.8 mm) for nodules intersected by orthogonal slices and 2.1 mm (7.1 mm) for nodules located more than 2 cm away from either of the orthogonal slices. The estimation error depended on the breathing phase, the motion amplitude and the location of the estimated position with respect to the orthogonal slices. By using the propagation method, the 4D motion within the porcine lung phantom could be accurately and robustly estimated. The method could provide valuable information for treatment planning, real-time motion monitoring, treatment adaptation, and post-treatment evaluation of MR-guided radiotherapy treatments.
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Affiliation(s)
- Moritz Rabe
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Chiara Paganelli
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy
| | - Marco Riboldi
- Department of Medical Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching (Munich), Germany
| | - David Bondesson
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany.,Comprehensive Pneumology Center, German Center for Lung Research (DZL), Munich, Germany
| | - Moritz Jörg Schneider
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany.,Comprehensive Pneumology Center, German Center for Lung Research (DZL), Munich, Germany
| | | | - Guido Baroni
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy.,Bioengineering Unit, Centro Nazionale di Adroterapia Oncologica, Pavia, Italy
| | - Julien Dinkel
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany.,Comprehensive Pneumology Center, German Center for Lung Research (DZL), Munich, Germany
| | - Michael Reiner
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Guillaume Landry
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.,Department of Medical Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching (Munich), Germany
| | - Katia Parodi
- Department of Medical Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching (Munich), Germany
| | - Claus Belka
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany
| | - Florian Kamp
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Christopher Kurz
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.,Department of Medical Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching (Munich), Germany
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31
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Kroll C, Dietrich O, Bortfeldt J, Kamp F, Neppl S, Belka C, Parodi K, Baroni G, Paganelli C, Riboldi M. Integration of spatial distortion effects in a 4D computational phantom for simulation studies in extra-cranial MRI-guided radiation therapy: Initial results. Med Phys 2020; 48:1646-1660. [PMID: 33220073 DOI: 10.1002/mp.14611] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Revised: 09/15/2020] [Accepted: 09/16/2020] [Indexed: 12/18/2022] Open
Abstract
PURPOSE Spatial distortions in magnetic resonance imaging (MRI) are mainly caused by inhomogeneities of the static magnetic field, nonlinearities in the applied gradients, and tissue-specific magnetic susceptibility variations. These factors may significantly alter the geometrical accuracy of the reconstructed MR image, thus questioning the reliability of MRI for guidance in image-guided radiation therapy. In this work, we quantified MRI spatial distortions and created a quantitative model where different sources of distortions can be separated. The generated model was then integrated into a four-dimensional (4D) computational phantom for simulation studies in MRI-guided radiation therapy at extra-cranial sites. METHODS A geometrical spatial distortion phantom was designed in four modules embedding laser-cut PMMA grids, providing 3520 landmarks in a field of view of (345 × 260 × 480) mm3 . The construction accuracy of the phantom was verified experimentally. Two fast MRI sequences for extra-cranial imaging at 1.5 T were investigated, considering axial slices acquired with online distortion correction, in order to mimic practical use in MRI-guided radiotherapy. Distortions were separated into their sources by acquisition of images with gradient polarity reversal and dedicated susceptibility calculations. Such a separation yielded a quantitative spatial distortion model to be used for MR imaging simulations. Finally, the obtained spatial distortion model was embedded into an anthropomorphic 4D computational phantom, providing registered virtual CT/MR images where spatial distortions in MRI acquisition can be simulated. RESULTS The manufacturing accuracy of the geometrical distortion phantom was quantified to be within 0.2 mm in the grid planes and 0.5 mm in depth, including thickness variations and bending effects of individual grids. Residual spatial distortions after MRI distortion correction were strongly influenced by the applied correction mode, with larger effects in the trans-axial direction. In the axial plane, gradient nonlinearities caused the main distortions, with values up to 3 mm in a 1.5 T magnet, whereas static field and susceptibility effects were below 1 mm. The integration in the 4D anthropomorphic computational phantom highlighted that deformations can be severe in the region of the thoracic diaphragm, especially when using axial imaging with 2D distortion correction. Adaptation of the phantom based on patient-specific measurements was also verified, aiming at increased realism in the simulation. CONCLUSIONS The implemented framework provides an integrated approach for MRI spatial distortion modeling, where different sources of distortion can be quantified in time-dependent geometries. The computational phantom represents a valuable platform to study motion management strategies in extra-cranial MRI-guided radiotherapy, where the effects of spatial distortions can be modeled on synthetic images in a virtual environment.
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Affiliation(s)
- C Kroll
- Department of Medical Physics, Ludwig-Maximilians University, Garching, 85748, Germany
| | - O Dietrich
- Department of Radiology, University Hospital, LMU Munich, Munich, 81377, Germany
| | - J Bortfeldt
- Department of Medical Physics, Ludwig-Maximilians University, Garching, 85748, Germany.,European Organization for Nuclear Research (CERN), Geneva 23, 1211, Switzerland
| | - F Kamp
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, 81377, Germany
| | - S Neppl
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, 81377, Germany
| | - C Belka
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, 81377, Germany.,German Cancer Consortium (DKTK), Munich, 81377, Germany
| | - K Parodi
- Department of Medical Physics, Ludwig-Maximilians University, Garching, 85748, Germany
| | - G Baroni
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, 20133, Italy.,Bioengineering Unit, Centro Nazionale di Adroterapia Oncologica, Pavia, 27100, Italy
| | - C Paganelli
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, 20133, Italy
| | - M Riboldi
- Department of Medical Physics, Ludwig-Maximilians University, Garching, 85748, Germany
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Impact of lung density on isolated lung tumor dose in VMAT using inline MR-Linac. Phys Med 2020; 80:65-74. [DOI: 10.1016/j.ejmp.2020.10.009] [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: 08/24/2020] [Revised: 09/24/2020] [Accepted: 10/12/2020] [Indexed: 11/21/2022] Open
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Image-guided Radiotherapy to Manage Respiratory Motion: Lung and Liver. Clin Oncol (R Coll Radiol) 2020; 32:792-804. [PMID: 33036840 DOI: 10.1016/j.clon.2020.09.008] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 08/26/2020] [Accepted: 09/18/2020] [Indexed: 12/25/2022]
Abstract
Organ motion as a result of respiratory and cardiac motion poses significant challenges for the accurate delivery of radiotherapy to both the thorax and the upper abdomen. Modern imaging techniques during radiotherapy simulation and delivery now permit better quantification of organ motion, which in turn reduces tumour and organ at risk position uncertainty. These imaging advances, coupled with respiratory correlated radiotherapy delivery techniques, have led to the development of a range of approaches to manage respiratory motion. This review summarises the key strategies of image-guided respiratory motion management with a focus on lung and liver radiotherapy.
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Tsai P, Yan G, Liu C, Hung Y, Kahler DL, Park J, Potter N, Li JG, Lu B. Tumor phase recognition using cone‐beam computed tomography projections and external surrogate information. Med Phys 2020; 47:5077-5089. [DOI: 10.1002/mp.14298] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Revised: 05/10/2020] [Accepted: 05/18/2020] [Indexed: 12/25/2022] Open
Affiliation(s)
- Pingfang Tsai
- Department of Radiation Oncology College of Medicine University of Florida Gainesville Fl32610‐0385 USA
| | - Guanghua Yan
- Department of Radiation Oncology College of Medicine University of Florida Gainesville Fl32610‐0385 USA
| | - Chihray Liu
- Department of Radiation Oncology College of Medicine University of Florida Gainesville Fl32610‐0385 USA
| | - Ying‐Chao Hung
- Department of Statistics National Chengchi University Taipei11604 Taiwan
| | - Darren L. Kahler
- Department of Radiation Oncology College of Medicine University of Florida Gainesville Fl32610‐0385 USA
| | - Ji‐Yeon Park
- Department of Radiation Oncology College of Medicine University of Florida Gainesville Fl32610‐0385 USA
| | - Nick Potter
- Department of Radiation Oncology College of Medicine University of Florida Gainesville Fl32610‐0385 USA
| | - Jonathan G. Li
- Department of Radiation Oncology College of Medicine University of Florida Gainesville Fl32610‐0385 USA
| | - Bo Lu
- Department of Radiation Oncology College of Medicine University of Florida Gainesville Fl32610‐0385 USA
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Sayan M, Serbez I, Teymur B, Gur G, Zoto Mustafayev T, Gungor G, Atalar B, Ozyar E. Patient-Reported Tolerance of Magnetic Resonance-Guided Radiation Therapy. Front Oncol 2020; 10:1782. [PMID: 33072560 PMCID: PMC7537416 DOI: 10.3389/fonc.2020.01782] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 08/11/2020] [Indexed: 12/17/2022] Open
Abstract
Purpose Magnetic resonance-guided radiation therapy (MRgRT) has been incorporated into a growing number of clinical practices world-wide, however, there is limited data on patient experiences with MRgRT. The purpose of this study was to prospectively evaluate patient tolerance of MRgRT using patient reported outcome questionnaires (PRO-Q). Methods Ninety patients were enrolled in this prospective observational study and treated with MRgRT (MRIdian Linac System, ViewRay Inc. Oakwood Village, OH, United States) between September 2018 and September 2019. Breath-hold-gated dose delivery with audiovisual feedback was completed as needed. Patients completed an in-house developed PRO-Q after the first and last fraction of MRgRT. Results The most commonly treated anatomic sites were the abdomen (47%) and pelvis (33%). Respiratory gating was utilized in 62% of the patients. Patients rated their experience as positive or at least tolerable with mean scores of 1.0–2.8. The most common complaint was the temperature in the room (61%) followed by paresthesias (57%). The degree of anxiety reported by 45% of the patients significantly decreased at the completion of treatment (mean score 1.54 vs. 1.36, p = 0.01). Forty-three percent of the patients reported some degree of disturbing noise which was improved considerably by use of music. All patients appreciated their active role during the treatment. Conclusion This evaluation of PROs indicates that MRgRT was well-tolerated by our patients. Patients’ experience may further improve with adjustment of room temperature and noise reduction.
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Affiliation(s)
- Mutlay Sayan
- Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States
| | - Ilkay Serbez
- Department of Radiation Oncology, School of Medicine, Mehmet Ali Aydınlar Acıbadem University, Istanbul, Turkey
| | - Bilgehan Teymur
- Department of Radiation Oncology, School of Medicine, Mehmet Ali Aydınlar Acıbadem University, Istanbul, Turkey
| | - Gokhan Gur
- Department of Radiation Oncology, School of Medicine, Mehmet Ali Aydınlar Acıbadem University, Istanbul, Turkey
| | - Teuta Zoto Mustafayev
- Department of Radiation Oncology, School of Medicine, Mehmet Ali Aydınlar Acıbadem University, Istanbul, Turkey
| | - Gorkem Gungor
- Department of Radiation Oncology, School of Medicine, Mehmet Ali Aydınlar Acıbadem University, Istanbul, Turkey
| | - Banu Atalar
- Department of Radiation Oncology, School of Medicine, Mehmet Ali Aydınlar Acıbadem University, Istanbul, Turkey
| | - Enis Ozyar
- Department of Radiation Oncology, School of Medicine, Mehmet Ali Aydınlar Acıbadem University, Istanbul, Turkey
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Sim AJ, Kaza E, Singer L, Rosenberg SA. A review of the role of MRI in diagnosis and treatment of early stage lung cancer. Clin Transl Radiat Oncol 2020; 24:16-22. [PMID: 32596518 PMCID: PMC7306507 DOI: 10.1016/j.ctro.2020.06.002] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 05/25/2020] [Accepted: 06/01/2020] [Indexed: 12/14/2022] Open
Abstract
Despite magnetic resonance imaging (MRI) being a mainstay in the oncologic care for many disease sites, it has not routinely been used in early lung cancer diagnosis, staging, and treatment. While MRI provides improved soft tissue contrast compared to computed tomography (CT), an advantage in multiple organs, the physical properties of the lungs and mediastinum create unique challenges for lung MRI. Although multi-detector CT remains the gold standard for lung imaging, advances in MRI technology have led to its increased clinical relevance in evaluating early stage lung cancer. Even though positron emission tomography is used more frequently in this context, functional MR imaging, including diffusion-weighted MRI and dynamic contrast-enhanced MRI, are emerging as useful modalities for both diagnosis and evaluation of treatment response for lung cancer. In parallel with these advances, the development of combined MRI and linear accelerator devices (MR-linacs), has spurred the integration of MRI into radiation treatment delivery in the form of MR-guided radiotherapy (MRgRT). Despite challenges for MRgRT in early stage lung cancer radiotherapy, early data utilizing MR-linacs shows potential for the treatment of early lung cancer. In both diagnosis and treatment, MRI is a promising modality for imaging early lung cancer.
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Affiliation(s)
- Austin J. Sim
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, 12902 USF Magnolia Dr., Tampa, FL, USA
| | - Evangelia Kaza
- Department of Radiation Oncology, Dana Farber Cancer Institute, Brigham & Women’s Hospital & Harvard Medical School, 75 Francis St., Boston, MA, USA
| | - Lisa Singer
- Department of Radiation Oncology, Dana Farber Cancer Institute, Brigham & Women’s Hospital & Harvard Medical School, 75 Francis St., Boston, MA, USA
| | - Stephen A. Rosenberg
- Department of Radiation Oncology, H. Lee Moffitt Cancer Center and Research Institute, 12902 USF Magnolia Dr., Tampa, FL, USA
- University of South Florida Morsani College of Medicine, 12901 Bruce B. Downs Blvd., Tampa, FL, USA
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Vergalasova I, Cai J. A modern review of the uncertainties in volumetric imaging of respiratory-induced target motion in lung radiotherapy. Med Phys 2020; 47:e988-e1008. [PMID: 32506452 DOI: 10.1002/mp.14312] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 05/15/2020] [Accepted: 05/26/2020] [Indexed: 12/25/2022] Open
Abstract
Radiotherapy has become a critical component for the treatment of all stages and types of lung cancer, often times being the primary gateway to a cure. However, given that radiation can cause harmful side effects depending on how much surrounding healthy tissue is exposed, treatment of the lung can be particularly challenging due to the presence of moving targets. Careful implementation of every step in the radiotherapy process is absolutely integral for attaining optimal clinical outcomes. With the advent and now widespread use of stereotactic body radiation therapy (SBRT), where extremely large doses are delivered, accurate, and precise dose targeting is especially vital to achieve an optimal risk to benefit ratio. This has largely become possible due to the rapid development of image-guided technology. Although imaging is critical to the success of radiotherapy, it can often be plagued with uncertainties due to respiratory-induced target motion. There has and continues to be an immense research effort aimed at acknowledging and addressing these uncertainties to further our abilities to more precisely target radiation treatment. Thus, the goal of this article is to provide a detailed review of the prevailing uncertainties that remain to be investigated across the different imaging modalities, as well as to highlight the more modern solutions to imaging motion and their role in addressing the current challenges.
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Affiliation(s)
- Irina Vergalasova
- Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, USA
| | - Jing Cai
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong
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Jones KC, Turian J, Redler G, Cifter G, Strologas J, Templeton A, Bernard D, Chu JCH. Scatter imaging during lung stereotactic body radiation therapy characterized with phantom studies. Phys Med Biol 2020; 65:155013. [PMID: 32408276 DOI: 10.1088/1361-6560/ab9355] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
By collecting photons scattered out of the therapy beam, scatter imaging creates images of the treated volume. Two phantoms were used to assess the possible application of scatter imaging for markerless tracking of lung tumors during stereotactic body radiation therapy (SBRT) treatment. A scatter-imaging camera was assembled with a CsI flat-panel detector and a 5 mm diameter pinhole collimator. Scatter images were collected during the irradiation of phantoms with megavoltage photons. To assess scatter image quality, spherical phantom lung tumors of 2.1-2.8 cm diameters were placed inside a static, anthropomorphic phantom. To show the efficacy of the technique with a moving target (3 cm diameter), the position of a simulated tumor was tracked in scatter images during sinusoidal motion (15 mm amplitude, 0.25 Hz frequency) in a dynamic lung phantom in open-field, dynamic conformal arc (DCA), and volumetric modulated arc therapy (VMAT) deliveries. Anatomical features are identifiable on static phantom scatter images collected with 10 MU of delivered dose (2.1 cm diameter lung tumor contrast-to-noise ratio of 4.4). The contrast-to-noise ratio increases with tumor size and delivered dose. During dynamic motion, the position of the 3.0 cm diameter lung tumor was identified with a root-mean-square error of 0.8, 1.2, and 2.9 mm for open field (0.3 s frame integration), DCA (0.5 s), and VMAT (0.5 s), respectively. Based on phantom studies, scatter imaging is a potential technique for markerless lung tumor tracking during SBRT without additional imaging dose. Quality scatter images may be collected at low, clinically relevant doses (10 MU). Scatter images are capable of sub-millimeter tracking precision, but modulation decreases accuracy.
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Affiliation(s)
- Kevin C Jones
- Department of Radiation Oncology, Rush University Medical Center, Chicago, IL, United States of America. Author to whom any correspondence should be addressed
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Hama Y, Tate E. Comparison of gross tumor volumes of pulmonary metastasis defined by CT and MRI in 0.345 T MRI-guided radiotherapy. BJR Open 2020; 2:20200010. [PMID: 33178974 PMCID: PMC7594882 DOI: 10.1259/bjro.20200010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 05/30/2020] [Accepted: 07/17/2020] [Indexed: 11/27/2022] Open
Abstract
OBJECTIVE To assess the difference in gross tumor volumes (GTVs) defined by CT (GTV-CT) and by low magnetic field strength (0.345 T) MRI (GTV-MRI) in patients simulated for MRI-guided radiotherapy forlung metastasis. METHODS 28 patients (148 lesions) who underwent CT and MRI simulation with the tri-60Co MRI-guided radiotherapy system (MRIdian, ViewRay) were included in this study. GTV-CT and GTV-MRI were compared using the paired t-test. The equivalence of variance between GTV-CT and GTV-MRI of small lesions (GTV-CT <1 ml) and large ones (GTV-CT >= 1 ml) was evaluated using F-test. The correlation between GTV-CT and GTV-MRI was evaluated by the correlation coefficient. RESULTS GTV-MRI was 120% larger than GTV-CT (p < 0.001) for small lesions, whereas GTV-MRI was 40% larger than GTV-CT (p < 0.001) for large lesions. In small lesions, the variation in GTV-MRI was significantly larger than that of GTV-CT (p < 0.001). There was no significant difference in the variation of GTV-MRI and GTV-CT in large lesions (p = 0.121). The correlation coefficient for small lesions was 0.93, whereas that for large lesions was 0.99, with large lesions having better correlation. CONCLUSIONS GTV-MRI was larger than GTV-CT and the correlation between GTV-MRI and GTV-CT was better in large lesions. If the tumor volume is 1 ml or larger, the lesion can be accurately monitored even with a low magnetic field strength MRI. ADVANCES IN KNOWLEDGE This study is the first clinical report to evaluate the tolerability of MRI images in 0.345 T MRI-guided radiotherapy for lung metastasis. GTV contoured by MRI was larger than GTV by CT, and this tendency was more pronounced in small tumors of less than 1 ml.
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Affiliation(s)
- Yukihiro Hama
- Department of Radiation Oncology, Tokyo-Edogawa Cancer Centre, Edogawa Hospital, Tokyo, Japan
| | - Etsuko Tate
- Department of Radiation Oncology, Tokyo-Edogawa Cancer Centre, Edogawa Hospital, Tokyo, Japan
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Bertho A, Dos Santos M, François A, Milliat F. Histoire de la prise en charge des cancers bronchopulmonaires non à petites cellules de stade précoce : de la chirurgie à la radiothérapie stéréotaxique. RADIOPROTECTION 2020; 55:165-172. [DOI: 10.1051/radiopro/2020050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/30/2023]
Abstract
Avant le début du XXe siècle, le cancer bronchopulmonaire était une maladie rare. Aujourd’hui, c’est le quatrième cancer le plus fréquent en France et concerne, chaque année, près de 50 000 patients. Si à travers l’histoire, la pierre angulaire de la prise en charge thérapeutique du cancer bronchopulmonaire reste la chirurgie, la radiothérapie en est un des piliers, notamment chez les patients à haut risque chirurgical. La radiothérapie est apparue quelques mois après la découverte des rayons X en 1896 et, rapidement, des protocoles standardisés ont été mis au point par les premiers radiobiologistes. Ces protocoles sont ceux que nous connaissons encore aujourd’hui : 2 Gy par fraction et 5 fractions par semaine sur une durée totale de 5 à 8 semaines. Si les protocoles ont peu changé en un siècle, la technique et la balistique ont connu de grandes avancées. Ces améliorations ont mené à un bouleversement profond des protocoles. Les améliorations techniques de délivrance de dose, par l’optimisation de l’imagerie, de la précision du positionnement des patients et dans la modulation de la géométrie des faisceaux ont conduit au développement de la radiothérapie en conditions stéréotaxiques ou radiothérapie stéréotaxique. Aujourd’hui, la radiothérapie stéréotaxique est utilisée pour la prise en charge des tumeurs bronchopulmonaires de stade précoce comme alternative à la chirurgie.
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Respiratory Motion Prediction Using Fusion-Based Multi-Rate Kalman Filtering and Real-Time Golden-Angle Radial MRI. IEEE Trans Biomed Eng 2020; 67:1727-1738. [DOI: 10.1109/tbme.2019.2944803] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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42
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Finazzi T, Haasbeek CJ, Spoelstra FO, Palacios MA, Admiraal MA, Bruynzeel AM, Slotman BJ, Lagerwaard FJ, Senan S. Clinical Outcomes of Stereotactic MR-Guided Adaptive Radiation Therapy for High-Risk Lung Tumors. Int J Radiat Oncol Biol Phys 2020; 107:270-278. [DOI: 10.1016/j.ijrobp.2020.02.025] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 02/13/2020] [Accepted: 02/17/2020] [Indexed: 12/21/2022]
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Kalantzopoulos C, Meschini G, Paganelli C, Fontana G, Vai A, Preda L, Vitolo V, Valvo F, Baroni G. Organ motion quantification and margins evaluation in carbon ion therapy of abdominal lesions. Phys Med 2020; 75:33-39. [PMID: 32485596 DOI: 10.1016/j.ejmp.2020.05.014] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Revised: 04/03/2020] [Accepted: 05/17/2020] [Indexed: 12/11/2022] Open
Abstract
PURPOSE In image-guided particle radiotherapy of abdominal lesions, respiratory motion hinders treatment accuracy. In this study, 2D cineMRI data were used to quantify the tumor (GTV) motion and to evaluate the clinical approach based on deriving an internal target volume (ITV) from a planning 4DCT for gating treatments. METHODS Seven patients with abdominal lesions were treated with carbon-ion therapy at the National Centre of Oncological Hadron-therapy (Italy). The MR scan was performed on the same day of the 4DCT acquisition. For four patients, an additional MR was acquired approximately after 1 week. The cineMRI combined with deformable image registration algorithm was used to quantify tumor motion. Afterwards, two ITVs were defined considering (1) all phases (ITVFB) and (2) only phases within the gating window (ITVG), and then compared with the clinical (4DCT-derived) ITVs (ITVCG and ITVCFB). RESULTS Tumor residual motion estimated by cineMRI data in the two MRI sessions resulted not significantly different from 4DCT, although cineMRI accounted for cycle-to-cycle variations. The ITV normalized for the GTV median values were higher for ITVFB with respect to ITVG, ITVCFB and ITVCG. The Hausdorff distances with respect to the GTV were up to 10.55 mm, 3.13 mm, 5.56 mm and 2.51 mm, for ITVFB, ITVG, ITVCFB and ITVCG, respectively. According to both metrics, ITVCG and ITVG were not found significantly different. CONCLUSIONS CineMRI acquisitions allowed to quantify organ motion without delivering additional dose to the patient and to verify treatment margins in gated carbon-ion therapy of abdominal lesions.
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Affiliation(s)
| | - Giorgia Meschini
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy
| | - Chiara Paganelli
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy
| | - Giulia Fontana
- Centro Nazionale di Adroterapia Oncologica, Str. Campeggi, 53, 27100 Pavia, Italy
| | - Alessandro Vai
- Centro Nazionale di Adroterapia Oncologica, Str. Campeggi, 53, 27100 Pavia, Italy
| | - Lorenzo Preda
- Centro Nazionale di Adroterapia Oncologica, Str. Campeggi, 53, 27100 Pavia, Italy
| | - Viviana Vitolo
- Centro Nazionale di Adroterapia Oncologica, Str. Campeggi, 53, 27100 Pavia, Italy
| | - Francesca Valvo
- Centro Nazionale di Adroterapia Oncologica, Str. Campeggi, 53, 27100 Pavia, Italy
| | - Guido Baroni
- Centro Nazionale di Adroterapia Oncologica, Str. Campeggi, 53, 27100 Pavia, Italy; Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy
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Hoffmann A, Oborn B, Moteabbed M, Yan S, Bortfeld T, Knopf A, Fuchs H, Georg D, Seco J, Spadea MF, Jäkel O, Kurz C, Parodi K. MR-guided proton therapy: a review and a preview. Radiat Oncol 2020; 15:129. [PMID: 32471500 PMCID: PMC7260752 DOI: 10.1186/s13014-020-01571-x] [Citation(s) in RCA: 73] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 05/17/2020] [Indexed: 02/14/2023] Open
Abstract
Background The targeting accuracy of proton therapy (PT) for moving soft-tissue tumours is expected to greatly improve by real-time magnetic resonance imaging (MRI) guidance. The integration of MRI and PT at the treatment isocenter would offer the opportunity of combining the unparalleled soft-tissue contrast and real-time imaging capabilities of MRI with the most conformal dose distribution and best dose steering capability provided by modern PT. However, hybrid systems for MR-integrated PT (MRiPT) have not been realized so far due to a number of hitherto open technological challenges. In recent years, various research groups have started addressing these challenges and exploring the technical feasibility and clinical potential of MRiPT. The aim of this contribution is to review the different aspects of MRiPT, to report on the status quo and to identify important future research topics. Methods Four aspects currently under study and their future directions are discussed: modelling and experimental investigations of electromagnetic interactions between the MRI and PT systems, integration of MRiPT workflows in clinical facilities, proton dose calculation algorithms in magnetic fields, and MRI-only based proton treatment planning approaches. Conclusions Although MRiPT is still in its infancy, significant progress on all four aspects has been made, showing promising results that justify further efforts for research and development to be undertaken. First non-clinical research solutions have recently been realized and are being thoroughly characterized. The prospect that first prototype MRiPT systems for clinical use will likely exist within the next 5 to 10 years seems realistic, but requires significant work to be performed by collaborative efforts of research groups and industrial partners.
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Affiliation(s)
- Aswin Hoffmann
- 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.,Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiooncology-OncoRay, Dresden, Germany.,Department of Radiotherapy and Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Bradley Oborn
- Centre for Medical Radiation Physics, University of Wollongong, Wollongong, Australia.,Illawarra Cancer Care Centre, Wollongong Hospital, Wollongong, Australia
| | - Maryam Moteabbed
- Division of Radiation Biophysics, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, USA
| | - Susu Yan
- Division of Radiation Biophysics, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, USA
| | - Thomas Bortfeld
- Division of Radiation Biophysics, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, USA
| | - Antje Knopf
- Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Herman Fuchs
- Department of Radiation Oncology, Medical University of Vienna/AKH, Vienna, Austria.,Christian Doppler Laboratory for Medical Radiation Research for Radiation Oncology, Medical University of Vienna, Vienna, Austria
| | - Dietmar Georg
- Department of Radiation Oncology, Medical University of Vienna/AKH, Vienna, Austria.,Christian Doppler Laboratory for Medical Radiation Research for Radiation Oncology, Medical University of Vienna, Vienna, Austria
| | - Joao Seco
- Biomedical Physics in Radiation Oncology, Deutsches Krebsforschungszentrum DKFZ, Heidelberg, Germany.,Department of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
| | - Maria Francesca Spadea
- Biomedical Physics in Radiation Oncology, Deutsches Krebsforschungszentrum DKFZ, Heidelberg, Germany.,Department of Experimental and Clinical Medicine, Magna Graecia University, Catanzaro, Italy
| | - Oliver Jäkel
- Medical Physics in Radiation Oncology, Deutsches Krebsforschungszentrum DKFZ and Heidelberg Ion-Beam Therapy Center at the University Medical Center, Heidelberg, Germany
| | - Christopher Kurz
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.,Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Garching, Germany
| | - Katia Parodi
- Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Garching, Germany.
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Kurz C, Buizza G, Landry G, Kamp F, Rabe M, Paganelli C, Baroni G, Reiner M, Keall PJ, van den Berg CAT, Riboldi M. Medical physics challenges in clinical MR-guided radiotherapy. Radiat Oncol 2020; 15:93. [PMID: 32370788 PMCID: PMC7201982 DOI: 10.1186/s13014-020-01524-4] [Citation(s) in RCA: 79] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Accepted: 03/24/2020] [Indexed: 12/18/2022] Open
Abstract
The integration of magnetic resonance imaging (MRI) for guidance in external beam radiotherapy has faced significant research and development efforts in recent years. The current availability of linear accelerators with an embedded MRI unit, providing volumetric imaging at excellent soft tissue contrast, is expected to provide novel possibilities in the implementation of image-guided adaptive radiotherapy (IGART) protocols. This study reviews open medical physics issues in MR-guided radiotherapy (MRgRT) implementation, with a focus on current approaches and on the potential for innovation in IGART.Daily imaging in MRgRT provides the ability to visualize the static anatomy, to capture internal tumor motion and to extract quantitative image features for treatment verification and monitoring. Those capabilities enable the use of treatment adaptation, with potential benefits in terms of personalized medicine. The use of online MRI requires dedicated efforts to perform accurate dose measurements and calculations, due to the presence of magnetic fields. Likewise, MRgRT requires dedicated quality assurance (QA) protocols for safe clinical implementation.Reaction to anatomical changes in MRgRT, as visualized on daily images, demands for treatment adaptation concepts, with stringent requirements in terms of fast and accurate validation before the treatment fraction can be delivered. This entails specific challenges in terms of treatment workflow optimization, QA, and verification of the expected delivered dose while the patient is in treatment position. Those challenges require specialized medical physics developments towards the aim of fully exploiting MRI capabilities. Conversely, the use of MRgRT allows for higher confidence in tumor targeting and organs-at-risk (OAR) sparing.The systematic use of MRgRT brings the possibility of leveraging IGART methods for the optimization of tumor targeting and quantitative treatment verification. Although several challenges exist, the intrinsic benefits of MRgRT will provide a deeper understanding of dose delivery effects on an individual basis, with the potential for further treatment personalization.
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Affiliation(s)
- Christopher Kurz
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistraße 15, 81377, Munich, Germany
- Department of Medical Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, 85748, Garching, Germany
| | - Giulia Buizza
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, P.za Leonardo da Vinci 32, 20133, Milano, Italy
| | - Guillaume Landry
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistraße 15, 81377, Munich, Germany
- Department of Medical Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, 85748, Garching, Germany
- German Cancer Consortium (DKTK), 81377, Munich, Germany
| | - Florian Kamp
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistraße 15, 81377, Munich, Germany
| | - Moritz Rabe
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistraße 15, 81377, Munich, Germany
| | - Chiara Paganelli
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, P.za Leonardo da Vinci 32, 20133, Milano, Italy
| | - Guido Baroni
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, P.za Leonardo da Vinci 32, 20133, Milano, Italy
- Bioengineering Unit, National Center of Oncological Hadrontherapy (CNAO), Strada Privata Campeggi 53, 27100, Pavia, Italy
| | - Michael Reiner
- Department of Radiation Oncology, University Hospital, LMU Munich, Marchioninistraße 15, 81377, Munich, Germany
| | - Paul J Keall
- ACRF Image X Institute, University of Sydney, Sydney, NSW, 2006, Australia
| | - Cornelis A T van den Berg
- Department of Radiotherapy, University Medical Centre Utrecht, PO box 85500, 3508 GA, Utrecht, The Netherlands
| | - Marco Riboldi
- Department of Medical Physics, Ludwig-Maximilians-Universität München, Am Coulombwall 1, 85748, Garching, Germany.
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Finazzi T, van Sörnsen de Koste JR, Palacios MA, Spoelstra FO, Slotman BJ, Haasbeek CJ, Senan S. Delivery of magnetic resonance-guided single-fraction stereotactic lung radiotherapy. Phys Imaging Radiat Oncol 2020; 14:17-23. [PMID: 33458309 PMCID: PMC7807654 DOI: 10.1016/j.phro.2020.05.002] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 04/15/2020] [Accepted: 05/11/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND AND PURPOSE Single-fraction stereotactic ablative radiotherapy (SABR) is an effective treatment for early-stage lung cancer, but concerns remain about the accurate delivery of SABR in a single session. We evaluated the delivery of single-fraction lung SABR using magnetic resonance (MR)-guidance. MATERIALS AND METHODS An MR-simulation was performed in 17 patients, seven of whom were found to be unsuitable, largely due to unreliable tracking of small tumors. Ten patients underwent single-fraction SABR to 34 Gy on a 0.35 T MR-linac system, with online plan adaptation. Gated breath-hold SABR was delivered using a planning target volume (PTV) margin of 5 mm, and a 3 mm gating window. Continuous MR-tracking of the gross tumor volume (GTVt) was performed in sagittal plane, with visual patient feedback provided using an in-room monitor. The real-time MR images were analyzed to determine precision and efficiency of gated delivery. RESULTS All but one patient completed treatment in a single session. The median total in-room procedure was 120 min, with a median SABR delivery session of 39 min. Review of 7.4 h of cine-MR imaging revealed a mean GTVt coverage by the PTV during beam-on of 99.6%. Breath-hold patterns were variable, resulting in a mean duty cycle efficiency of 51%, but GTVt coverage was not influenced due to real-time MR-guidance. On-table adaptation improved PTV coverage, but had limited impact on GTV doses. CONCLUSIONS Single-fraction gated SABR of lung tumors can be performed with high precision using MR-guidance. However, improvements are needed to ensure MR-tracking of small tumors, and to reduce treatment times.
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Affiliation(s)
- Tobias Finazzi
- Corresponding author at: Amsterdam University Medical Centers, Location VUmc, Postbox 7057, 1007 MB Amsterdam, The Netherlands.
| | | | - Miguel A. Palacios
- Department of Radiation Oncology, Amsterdam University Medical Centers, Location VUmc, de Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Femke O.B. Spoelstra
- Department of Radiation Oncology, Amsterdam University Medical Centers, Location VUmc, de Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Berend J. Slotman
- Department of Radiation Oncology, Amsterdam University Medical Centers, Location VUmc, de Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Cornelis J.A. Haasbeek
- Department of Radiation Oncology, Amsterdam University Medical Centers, Location VUmc, de Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - Suresh Senan
- Department of Radiation Oncology, Amsterdam University Medical Centers, Location VUmc, de Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
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Liu X, Liang Y, Zhu J, Yu G, Yu Y, Cao Q, Li XA, Li B. A Fast Online Replanning Algorithm Based on Intensity Field Projection for Adaptive Radiotherapy. Front Oncol 2020; 10:287. [PMID: 32195188 PMCID: PMC7063069 DOI: 10.3389/fonc.2020.00287] [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: 11/01/2019] [Accepted: 02/19/2020] [Indexed: 11/13/2022] Open
Abstract
Purpose: The purpose of this work was to propose an online replanning algorithm, named intensity field projection (IFP), that directly adjusts intensity distributions for each beam based on the deformation of structures. IFP can be implemented within a reasonably acceptable time frame. Methods and Materials: The online replanning method is based on the gradient-based free form deformation (GFFD) algorithm, which we have previously proposed. The method involves the following steps: The planning computed tomography (CT) and cone-beam CT image are registered to generate a three-dimensional (3-D) deformation field. According to the 3-D deformation field, the registered image and a new delineation are generated. The two-dimensional (2-D) deformation field of ray intensity in each beam direction is determined based on the 3-D deformation field in the region of interest. The 2-D ray intensity distribution in the corresponding beam direction is deformed to generate a new 2-D ray intensity distribution. According to the new 2-D ray intensity distribution, corresponding multi-leaf collimator (MLC), and jaw motion data are generated. The feasibility and advantages of our method have been demonstrated in 20 lung cancer intensity modulated radiation therapy (IMRT) cases. Results: Substantial underdosing in the CTV is seen in the original and the repositioning plans. The average prescription dose coverage (V100%) and D95 for CTV were 100% and 60.3 Gy for the IFP plans compared to 82.6% (P < 0.01) and 44.0 Gy (P < 0.01) for original plans, 86.7% (P < 0.01), and 58.5 Gy (P < 0.01) for repositioning plans. On average, the mean total lung doses were 12.2 Gy for the IFP plan compared to the 12.4 Gy (P < 0.01) and 12.6 Gy (P < 0.01) for the original and the repositioning plans. The entire process of IFP can be completed within 3 min. Conclusions: We proposed an online replanning strategy for automatically correcting interfractional anatomy variations. The preliminary results indicate that the IFP method substantially increased planning speed for online adaptive replanning.
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Affiliation(s)
- Xiaomeng Liu
- School of Medicine and Life Sciences, University of Jinan-Shandong Academy of Medical Sciences, Jinan, China.,Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Yueqiang Liang
- Software Research and Development Department, STFK Medical Device Co, Ltd., Zhangjiagang, China
| | - Jian Zhu
- Shandong Key Laboratory of Medical Physics and Image Processing, School of Physics and Electronics, Shandong Normal University, Jinan, China
| | - Gang Yu
- Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Yanyan Yu
- Department of Neurology, Shandong Provincial Qianfoshan Hospital, Jinan, China
| | - Qiang Cao
- Laboratory of Image Science and Technology, Southeast University, Nanjing, Jiangsu, China
| | - X Allen Li
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Baosheng Li
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
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Finazzi T, Palacios MA, Haasbeek CJ, Admiraal MA, Spoelstra FO, Bruynzeel AM, Slotman BJ, Lagerwaard FJ, Senan S. Stereotactic MR-guided adaptive radiation therapy for peripheral lung tumors. Radiother Oncol 2020; 144:46-52. [DOI: 10.1016/j.radonc.2019.10.013] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Revised: 09/25/2019] [Accepted: 10/18/2019] [Indexed: 12/22/2022]
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Rabe M, Thieke C, Düsberg M, Neppl S, Gerum S, Reiner M, Nicolay NH, Schlemmer H, Debus J, Dinkel J, Landry G, Parodi K, Belka C, Kurz C, Kamp F. Real‐time 4DMRI‐based internal target volume definition for moving lung tumors. Med Phys 2020; 47:1431-1442. [DOI: 10.1002/mp.14023] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 12/20/2019] [Accepted: 01/07/2020] [Indexed: 12/25/2022] Open
Affiliation(s)
- Moritz Rabe
- Department of Radiation Oncology University Hospital, LMU Munich Munich 81377 Germany
| | - Christian Thieke
- Department of Radiation Oncology University Hospital, LMU Munich Munich 81377 Germany
| | - Mathias Düsberg
- Department of Radiation Oncology Klinikum rechts der Isar, Technical University Munich 81675 Germany
| | - Sebastian Neppl
- Department of Radiation Oncology University Hospital, LMU Munich Munich 81377 Germany
| | - Sabine Gerum
- Department of Radiation Oncology University Hospital, LMU Munich Munich 81377 Germany
| | - Michael Reiner
- Department of Radiation Oncology University Hospital, LMU Munich Munich 81377 Germany
| | | | | | - Jürgen Debus
- Department of Radiation Oncology University Hospital of Heidelberg Heidelberg 69120 Germany
- Heidelberg Institute of Radiation Oncology (HIRO) Heidelberg 69120 Germany
| | - Julien Dinkel
- Department of Radiology University Hospital, LMU Munich Munich 81377 Germany
| | - Guillaume Landry
- Department of Radiation Oncology University Hospital, LMU Munich Munich 81377 Germany
- Department of Medical Physics Ludwig‐Maximilians‐Universität München (LMU Munich) Garching 85748 Germany
| | - Katia Parodi
- Department of Medical Physics Ludwig‐Maximilians‐Universität München (LMU Munich) Garching 85748 Germany
| | - Claus Belka
- Department of Radiation Oncology University Hospital, LMU Munich Munich 81377 Germany
- German Cancer Consortium (DKTK) Munich 81377 Germany
| | - Christopher Kurz
- Department of Radiation Oncology University Hospital, LMU Munich Munich 81377 Germany
- Department of Medical Physics Ludwig‐Maximilians‐Universität München (LMU Munich) Garching 85748 Germany
| | - Florian Kamp
- Department of Radiation Oncology University Hospital, LMU Munich Munich 81377 Germany
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Chin S, Eccles CL, McWilliam A, Chuter R, Walker E, Whitehurst P, Berresford J, Van Herk M, Hoskin PJ, Choudhury A. Magnetic resonance-guided radiation therapy: A review. J Med Imaging Radiat Oncol 2020; 64:163-177. [PMID: 31646742 DOI: 10.1111/1754-9485.12968] [Citation(s) in RCA: 88] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Accepted: 09/24/2019] [Indexed: 12/11/2022]
Abstract
Magnetic resonance-guided radiation therapy (MRgRT) is a promising approach to improving clinical outcomes for patients treated with radiation therapy. The roles of image guidance, adaptive planning and magnetic resonance imaging in radiation therapy have been increasing over the last two decades. Technical advances have led to the feasible combination of magnetic resonance imaging and radiation therapy technologies, leading to improved soft-tissue visualisation, assessment of inter- and intrafraction motion, motion management, online adaptive radiation therapy and the incorporation of functional information into treatment. MRgRT can potentially transform radiation oncology by improving tumour control and quality of life after radiation therapy and increasing convenience of treatment by shortening treatment courses for patients. Multiple groups have developed clinical implementations of MRgRT predominantly in the abdomen and pelvis, with patients having been treated since 2014. While studies of MRgRT have primarily been dosimetric so far, an increasing number of trials are underway examining the potential clinical benefits of MRgRT, with coordinated efforts to rigorously evaluate the benefits of the promising technology. This review discusses the current implementations, studies, potential benefits and challenges of MRgRT.
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Affiliation(s)
- Stephen Chin
- Department of Clinical Oncology, The Christie NHS Foundation Trust, Manchester, UK
- Westmead Clinical School, University of Sydney, Sydney, New South Wales, Australia
| | - Cynthia L Eccles
- Department of Radiotherapy, The Christie NHS Foundation Trust, Manchester, UK
- Division of Cancer Sciences, The University of Manchester, Manchester, UK
| | - Alan McWilliam
- Division of Cancer Sciences, The University of Manchester, Manchester, UK
- Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, UK
| | - Robert Chuter
- Division of Cancer Sciences, The University of Manchester, Manchester, UK
- Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, UK
| | - Emma Walker
- Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, UK
| | - Philip Whitehurst
- Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, UK
| | - Joseph Berresford
- Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, UK
| | - Marcel Van Herk
- Division of Cancer Sciences, The University of Manchester, Manchester, UK
- Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, UK
| | - Peter J Hoskin
- Department of Clinical Oncology, The Christie NHS Foundation Trust, Manchester, UK
- Division of Cancer Sciences, The University of Manchester, Manchester, UK
| | - Ananya Choudhury
- Department of Clinical Oncology, The Christie NHS Foundation Trust, Manchester, UK
- Division of Cancer Sciences, The University of Manchester, Manchester, UK
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