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Lee JKH, Lew KS, Koh CWY, Lee JCL, Bettiol AA, Park SY, Tan HQ. Comparison of translation algorithms in determining maximum allowable CTV shifts for Real-Time Gated Proton Therapy (RGPT) robustness evaluation in prostate cancers. J Appl Clin Med Phys 2024:e14543. [PMID: 39361510 DOI: 10.1002/acm2.14543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2024] [Revised: 07/29/2024] [Accepted: 08/22/2024] [Indexed: 10/05/2024] Open
Abstract
INTRODUCTION Real-Time Gated Proton Therapy (RGPT) is an active motion management technique that utilizes treatment gating and tumor tracking via fiducial markers. When performing RGPT treatment for prostate cancer, it is essential to account for the CTV displacement relative to the body in the clinical workflow. The workflow at the National Cancer Centre Singapore (NCCS) includes bone matching via CT-CBCT images, followed by fiducial matching via pulsed fluoroscopy (soft tissue matching), and finally, a robustness evaluation procedure to determine if the difference is within an allowable tolerance. In this study, we compare two CTV translation methods for robustness evaluation: (1) an in-house translation algorithm and (2) the RayStation "simulate organ motion" Deformable image registration (DIR) algorithm. METHODS Nine RGPT prostate patient plans with CTV volumes ranging from 17.1 to 96.72 cm2 were included in this study. An in-house translation algorithm and "simulate organ motion" DIR RayStation algorithm were used to generate CTV shifts along R-L, I-S, and P-A axes between ± $ \pm $ 10 mm at 2 mm steps. At each step, dose metrics, which include CTV Dmax, CTV D95%, and CTV D98%, were extracted and used as comparative metrics for CTV target coverage and hot spot evaluation. RESULTS Across all axes, there were no statistically significant differences between the two algorithms for all three dose metrics: CTV Dmax (P = 0.92, P = 0.91, and P = 0.47), CTV D95% (P = 0.97, P = 0.22, and P = 0.33), and CTV D98% (P = 0.85, P = 0.33, and P = 0.36). Further, the in-house translation algorithm evaluation time was less than 10 s, two orders of magnitude faster than the DIR algorithm. CONCLUSION Our results demonstrate that the simpler in-house algorithm performs equivalently to the realistic DIR algorithm when simulating CTV motion in prostate cancers. Furthermore, the in-house algorithm completes the robustness evaluation two orders of magnitude faster than the DIR algorithm. This significant reduction in evaluation time is crucial especially when preparatory time efficiency is of paramount importance in a busy clinic.
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Affiliation(s)
| | - Kah Seng Lew
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore, Singapore
| | - Calvin Wei Yang Koh
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore, Singapore
| | - James Cheow Lei Lee
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore, Singapore
| | - Andrew A Bettiol
- Department of Physics, National University Singapore, Singapore, Singapore
| | - Sung Yong Park
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore, Singapore
- Oncology Academic Clinical Programme, Duke-NUS Medical School, Singapore, Singapore
| | - Hong Qi Tan
- Division of Radiation Oncology, National Cancer Centre Singapore, Singapore, Singapore
- Oncology Academic Clinical Programme, Duke-NUS Medical School, Singapore, Singapore
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Nenoff L, Amstutz F, Murr M, Archibald-Heeren B, Fusella M, Hussein M, Lechner W, Zhang Y, Sharp G, Vasquez Osorio E. Review and recommendations on deformable image registration uncertainties for radiotherapy applications. Phys Med Biol 2023; 68:24TR01. [PMID: 37972540 PMCID: PMC10725576 DOI: 10.1088/1361-6560/ad0d8a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 10/30/2023] [Accepted: 11/15/2023] [Indexed: 11/19/2023]
Abstract
Deformable image registration (DIR) is a versatile tool used in many applications in radiotherapy (RT). DIR algorithms have been implemented in many commercial treatment planning systems providing accessible and easy-to-use solutions. However, the geometric uncertainty of DIR can be large and difficult to quantify, resulting in barriers to clinical practice. Currently, there is no agreement in the RT community on how to quantify these uncertainties and determine thresholds that distinguish a good DIR result from a poor one. This review summarises the current literature on sources of DIR uncertainties and their impact on RT applications. Recommendations are provided on how to handle these uncertainties for patient-specific use, commissioning, and research. Recommendations are also provided for developers and vendors to help users to understand DIR uncertainties and make the application of DIR in RT safer and more reliable.
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Affiliation(s)
- Lena Nenoff
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
- 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
| | - Florian Amstutz
- Department of Physics, ETH Zurich, Switzerland
- Center for Proton Therapy, Paul Scherrer Institute, Villigen PSI, Switzerland
- Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, and University of Bern, Bern, Switzerland
| | - Martina Murr
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Germany
| | | | - Marco Fusella
- Department of Radiation Oncology, Abano Terme Hospital, Italy
| | - Mohammad Hussein
- Metrology for Medical Physics, National Physical Laboratory, Teddington, United Kingdom
| | - Wolfgang Lechner
- Department of Radiation Oncology, Medical University of Vienna, Austria
| | - Ye Zhang
- Center for Proton Therapy, Paul Scherrer Institute, Villigen PSI, Switzerland
| | - Greg Sharp
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
| | - Eliana Vasquez Osorio
- Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom
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Li H, Dong L, Bert C, Chang J, Flampouri S, Jee KW, Lin L, Moyers M, Mori S, Rottmann J, Tryggestad E, Vedam S. Report of AAPM Task Group 290: Respiratory motion management for particle therapy. Med Phys 2022; 49:e50-e81. [PMID: 35066871 PMCID: PMC9306777 DOI: 10.1002/mp.15470] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 12/28/2021] [Accepted: 01/05/2022] [Indexed: 11/16/2022] Open
Abstract
Dose uncertainty induced by respiratory motion remains a major concern for treating thoracic and abdominal lesions using particle beams. This Task Group report reviews the impact of tumor motion and dosimetric considerations in particle radiotherapy, current motion‐management techniques, and limitations for different particle‐beam delivery modes (i.e., passive scattering, uniform scanning, and pencil‐beam scanning). Furthermore, the report provides guidance and risk analysis for quality assurance of the motion‐management procedures to ensure consistency and accuracy, and discusses future development and emerging motion‐management strategies. This report supplements previously published AAPM report TG76, and considers aspects of motion management that are crucial to the accurate and safe delivery of particle‐beam therapy. To that end, this report produces general recommendations for commissioning and facility‐specific dosimetric characterization, motion assessment, treatment planning, active and passive motion‐management techniques, image guidance and related decision‐making, monitoring throughout therapy, and recommendations for vendors. Key among these recommendations are that: (1) facilities should perform thorough planning studies (using retrospective data) and develop standard operating procedures that address all aspects of therapy for any treatment site involving respiratory motion; (2) a risk‐based methodology should be adopted for quality management and ongoing process improvement.
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Affiliation(s)
- Heng Li
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Lei Dong
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA, USA
| | - Christoph Bert
- Department of Radiation Oncology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Joe Chang
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Stella Flampouri
- Department of Radiation Oncology, Emory University, Atlanta, GA, USA
| | - Kyung-Wook Jee
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, MA, USA
| | - Liyong Lin
- Department of Radiation Oncology, Emory University, Atlanta, GA, USA
| | - Michael Moyers
- Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital, Shanghai, China
| | - Shinichiro Mori
- Research Center for Charged Particle Therapy, National Institute of Radiological Sciences, Chiba, Japan
| | - Joerg Rottmann
- Center for Proton Therapy, Proton Therapy Singapore, Proton Therapy Pte Ltd, Singapore
| | - Erik Tryggestad
- Department of Radiation Oncology, Mayo Clinic, Rochester, MN, USA
| | - Sastry Vedam
- Department of Radiation Oncology, University of Maryland, Baltimore, USA
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Zhi S, KachelrieB M, Pan F, Mou X. CycN-Net: A Convolutional Neural Network Specialized for 4D CBCT Images Refinement. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:3054-3064. [PMID: 34010129 DOI: 10.1109/tmi.2021.3081824] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Four-dimensional cone-beam computed tomography (4D CBCT) has been developed to provide a sequence of phase-resolved reconstructions in image-guided radiation therapy. However, 4D CBCT images are degraded by severe streaking artifacts and noise because the phase-resolved image is an extremely sparse-view CT procedure wherein a few under-sampled projections are used for the reconstruction of each phase. Aiming at improving the overall quality of 4D CBCT images, we proposed two CNN models, named N-Net and CycN-Net, respectively, by fully excavating the inherent property of 4D CBCT. To be specific, the proposed N-Net incorporates the prior image reconstructed from entire projection data based on U-Net to boost the image quality for each phase-resolved image. Based on N-Net, a temporal correlation among the phase-resolved images is also considered by the proposed CycN-Net. Extensive experiments on both XCAT simulation data and real patient 4D CBCT datasets were carried out to verify the feasibility of the proposed CNNs. Both networks can effectively suppress streaking artifacts and noise while restoring the distinct features simultaneously, compared with the existing CNN models and two state-of-the-art iterative algorithms. Moreover, the proposed method is robust in handling complicated tasks of various patient datasets and imaging devices, which implies its excellent generalization ability.
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Teng X, Chen Y, Zhang Y, Ren L. Respiratory deformation registration in 4D-CT/cone beam CT using deep learning. Quant Imaging Med Surg 2021; 11:737-748. [PMID: 33532273 PMCID: PMC7779910 DOI: 10.21037/qims-19-1058] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Accepted: 09/25/2020] [Indexed: 11/06/2022]
Abstract
BACKGROUND To investigate the feasibility of using a supervised convolutional neural network (CNN) to register phase-to-phase deformable vector field of lung 4D-CT/4D-cone beam CT for 4D dose accumulation, contour propagation, motion modeling, or target verification. METHODS We built a CNN-based deep learning method to register the deformation field directly between phases of patients' 4D-CT or 4D-cone beam CT. The input consists of patch pairs of two phases, while the output is the corresponding deformation field that registers the patch pairs. The centers of the patch pairs were uniformly sampled across the lung, and the size of the patches was chosen to cover the range of the respiratory motion. The network was trained to generate deformation field that matches with the reference deformation field generated by VelocityAI (Varian). The network is structured with four convolutional layers, two average pooling layers, and two fully connected layers. Half mean squared error is applied to guide the study as loss function. Nine patients with eleven sets of 4D-CT/cone beam CT image volumes were used for training and testing. The performance of the network was validated with intra-patient and inter-patient setups. RESULTS Registered images were generated with Velocity deformation field and the CNN deformation field, respectively. Main anatomic features such as the main vessels and the diaphragm matched well between two deformed images. In the diaphragm region, the coefficients of cross-correlation, root mean squared error, and structural similarity index measure (SSIM) between deformed images registered by CNN and VelocityAI was calculated. The cross-correlation was above 0.9 for all the intra-patient cases. CONCLUSIONS Patch-based deep learning methods achieved comparable deformable registration accuracy as VelocityAI. Compared to VelocityAI, the deep learning method is fully automatic and faster without user dependency, which makes it more preferable in clinical applications.
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Affiliation(s)
| | - Yingxuan Chen
- Department of Radiation Oncology, Duke University Medical Center, Durham, NC, USA
| | - Yawei Zhang
- Department of Radiation Oncology, Duke University Medical Center, Durham, NC, USA
| | - Lei Ren
- Department of Radiation Oncology, Duke University Medical Center, Durham, NC, USA
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Meschini G, Vai A, Paganelli C, Molinelli S, Maestri D, Fontana G, Pella A, Vitolo V, Valvo F, Ciocca M, Baroni G. Investigating the use of virtual 4DCT from 4DMRI in gated carbon ion radiation therapy of abdominal tumors. Z Med Phys 2020; 32:98-108. [PMID: 33069586 PMCID: PMC9948849 DOI: 10.1016/j.zemedi.2020.08.005] [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: 02/28/2020] [Revised: 07/27/2020] [Accepted: 08/31/2020] [Indexed: 12/22/2022]
Abstract
PURPOSE To generate virtual 4DCT from 4DMRI with field of view (FOV) extended to the entire involved patient anatomy, in order to evaluate its use in carbon ion radiation therapy (CIRT) of the abdominal site in a clinical scenario. MATERIALS AND METHODS The virtual 4DCT was generated by deforming a reference CT in order to (1) match the anatomy depicted in the 4DMRI within its FOV, by calculating deformation fields with deformable image registration to describe inter-fractional and breathing motion, and (2) obtain physically plausible deformation outside of the 4DMRI FOV, by propagating and modulating the previously obtained deformation fields. The implemented method was validated on a digital anthropomorphic phantom, for which a ground truth (GT) 4DCT was available. A CIRT treatment plan was optimized at the end-exhale reference CT and the RBE-weighted dose distribution was recalculated on both the virtual and GT 4DCTs. The method estimation error was quantified by comparing the virtual and GT 4DCTs and the corresponding recomputed doses. The method was then evaluated on 8 patients with pancreas or liver tumors treated with CIRT using respiratory gating at end-exhale. The clinical treatment plans adopted at the National Center for Oncological Hadrontherapy (CNAO, Pavia, Italy) were considered and the dose distribution was recomputed on all respiratory phases of the planning and virtual 4DCTs. By comparing the two datasets and the corresponding dose distributions, the geometrical and dosimetric impact of organ motion was assessed. RESULTS For the phantom, the error outside of the 4DMRI FOV was up to 4.5mm, but it remained sub-millimetric in correspondence to the target within the 4DMRI FOV. Although the impact of motion on the target D95% resulted in variations ranging from 22% to 90% between the planned dose and the doses recomputed on the GT 4DCT phases, the corresponding estimation error was ≤2.2%. In the patient cases, the variation of the baseline tumor position between the planning and the virtual end-exhale CTs presented a median (interquartile range) value of 6.0 (4.9) mm. For baseline variations larger than 5mm, the tumor D95% variation between the plan and the dose recomputed on the end-exhale virtual CT resulted larger than 10%. Median variations higher than 10% in the target D95% and gastro-intestinal OARs D2% were quantified at the end-inhale, whereas close to the end-exhale phase, limited variations of relevant dose metrics were found for both tumor and OARs. CONCLUSIONS The negligible impact of the geometrical inaccuracy in the estimated anatomy outside of the 4DMRI FOV on the overall dosimetric accuracy suggests the feasibility of virtual 4DCT with extended FOV in CIRT of the abdominal site. In the analyzed patient group, inter-fractional variations such as baseline variation and breathing variability were quantified, demonstrating the method capability to support treatment planning in gated CIRT of the abdominal site.
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Affiliation(s)
- Giorgia Meschini
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano 20133, Italy.
| | - Alessandro Vai
- Centro Nazionale di Adroterapia Oncologica, Pavia 27100, Italy
| | - Chiara Paganelli
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano 20133, Italy
| | | | - Davide Maestri
- Centro Nazionale di Adroterapia Oncologica, Pavia 27100, Italy
| | - Giulia Fontana
- Centro Nazionale di Adroterapia Oncologica, Pavia 27100, Italy
| | - Andrea Pella
- Centro Nazionale di Adroterapia Oncologica, Pavia 27100, Italy
| | - Viviana Vitolo
- Centro Nazionale di Adroterapia Oncologica, Pavia 27100, Italy
| | - Francesca Valvo
- Centro Nazionale di Adroterapia Oncologica, Pavia 27100, Italy
| | - Mario Ciocca
- Centro Nazionale di Adroterapia Oncologica, Pavia 27100, Italy
| | - Guido Baroni
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano 20133, Italy,Centro Nazionale di Adroterapia Oncologica, Pavia 27100, Italy
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Cusumano D, Dhont J, Boldrini L, Chiloiro G, Romano A, Votta C, Longo S, Placidi L, Azario L, De Spirito M, Verellen D, Valentini V. Reliability of ITV approach to varying treatment fraction time: a retrospective analysis based on 2D cine MR images. Radiat Oncol 2020; 15:152. [PMID: 32532334 PMCID: PMC7291491 DOI: 10.1186/s13014-020-01530-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Accepted: 04/03/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Internal Target Volume (ITV) is one of the most common strategies to passively manage tumour motion in Radiotherapy (RT). The reliability of this approach is based on the assumption that the tumour motion estimated during pre-treatment 4D Computed Tomography (CT) acquisition is representative of the motion during the whole RT treatment. With the introduction of Magnetic Resonance-guided RT (MRgRT), it has become possible to monitor tumour motion during the treatment and verify this assumption. Aim of this study was to investigate the reliability of the ITV approach with respect to the treatment fraction time (TFT) in abdominal and thoracic lesions. METHODS A total of 12 thoracic and 15 abdominal lesions was analysed. Before treatment, a 10-phase 4DCT was acquired and ITV margins were estimated considering the envelope of the lesion contoured on the different 4DCT phases. All patients underwent MRgRT treatment in free-breathing, monitoring the tumour position on a sagittal plane with 4 frames per second (sec). ITV margins were projected on the tumour trajectory and the percentage of treatment time in which the tumour was inside the ITV (%TT) was measured to varying of TFT. The ITV approach was considered moderately reliable when %TT ≥ 90% and strongly reliable when %TT ≥ 95%. Additional ITV margins required to achieve %TT ≥ 95% were also calculated. RESULTS In the analysed cohort of patients, ITV strategy can be considered strongly reliable only for lung lesions with TFT ≤ 7 min (min). The ITV strategy can be considered only moderately reliable for abdominal lesions, and additional margins are required to obtain %TT ≥ 95%. Considering a TFT ≤ 4 min, additional margins of 2 mm in cranio-caudal (CC) and 1 mm in antero-posterior (AP) are suggested for pancreatic lesions, 3 mm in CC and 2 mm in AP for renal and liver ones. CONCLUSIONS On the basis of the analysed cases, the ITV approach appears to be reliable in the thorax, while it results more challenging in the abdomen, due to the higher uncertainty in ITV definition and to the observed larger intra and inter-fraction motion variability. The addition of extra margins based on the TFT may represent a valid tool to compensate such limitations.
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Affiliation(s)
- Davide Cusumano
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Largo Agostino Gemelli,8, 00168 Rome, Italia
| | - Jennifer Dhont
- Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Pleinlaan 9, B-1050 Brussels, Imec, Leuven, Belgium
- Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Luca Boldrini
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Largo Agostino Gemelli,8, 00168 Rome, Italia
| | - Giuditta Chiloiro
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Largo Agostino Gemelli,8, 00168 Rome, Italia
| | - Angela Romano
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Largo Agostino Gemelli,8, 00168 Rome, Italia
| | - Claudio Votta
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Largo Agostino Gemelli,8, 00168 Rome, Italia
| | - Silvia Longo
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Largo Agostino Gemelli,8, 00168 Rome, Italia
| | - Lorenzo Placidi
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Largo Agostino Gemelli,8, 00168 Rome, Italia
| | - Luigi Azario
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Largo Agostino Gemelli,8, 00168 Rome, Italia
| | - Marco De Spirito
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Largo Agostino Gemelli,8, 00168 Rome, Italia
| | - Dirk Verellen
- Department of Radiotherapy, Iridium Kankernetwerk, University of Antwerp (Faculty of Medicine and Health Sciences), Antwerp, Belgium
| | - Vincenzo Valentini
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Largo Agostino Gemelli,8, 00168 Rome, Italia
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Morton N, Sykes J, Barber J, Hofmann C, Keall P, O’Brien R. Reducing 4D CT imaging artifacts at the source: first experimental results from the respiratory adaptive computed tomography (REACT) system. ACTA ACUST UNITED AC 2020; 65:075012. [DOI: 10.1088/1361-6560/ab7abe] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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Albertini F, Matter M, Nenoff L, Zhang Y, Lomax A. Online daily adaptive proton therapy. Br J Radiol 2020; 93:20190594. [PMID: 31647313 PMCID: PMC7066958 DOI: 10.1259/bjr.20190594] [Citation(s) in RCA: 81] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Revised: 10/15/2019] [Accepted: 10/22/2019] [Indexed: 12/11/2022] Open
Abstract
It is recognized that the use of a single plan calculated on an image acquired some time before the treatment is generally insufficient to accurately represent the daily dose to the target and to the organs at risk. This is particularly true for protons, due to the physical finite range. Although this characteristic enables the generation of steep dose gradients, which is essential for highly conformal radiotherapy, it also tightens the dependency of the delivered dose to the range accuracy. In particular, the use of an outdated patient anatomy is one of the most significant sources of range inaccuracy, thus affecting the quality of the planned dose distribution. A plan should be ideally adapted as soon as anatomical variations occur, ideally online. In this review, we describe in detail the different steps of the adaptive workflow and discuss the challenges and corresponding state-of-the art developments in particular for an online adaptive strategy.
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Affiliation(s)
| | | | | | - Ye Zhang
- Paul Scherrer Institute, Center for Proton Therapy, Switzerland
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Navest RJM, Mandija S, Bruijnen T, Stemkens B, Tijssen RHN, Andreychenko A, Lagendijk JJW, van den Berg CAT. The noise navigator: a surrogate for respiratory-correlated 4D-MRI for motion characterization in radiotherapy. Phys Med Biol 2020; 65:01NT02. [PMID: 31775130 DOI: 10.1088/1361-6560/ab5c62] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Respiratory-correlated 4D-MRI can characterize respiratory-induced motion of tumors and organs-at-risk for radiotherapy treatment planning and is a necessity for image guidance of moving tumors treated on an MRI-linac. Essential for 4D-MRI generation is a robust respiratory surrogate signal. We investigated the feasibility of the noise navigator as respiratory surrogate signal for 4D-MRI generation. The noise navigator is based on the respiratory-induced modulation of the thermal noise variance measured by the receive coils during MR acquisition and thus is inherently present and synchronized with MRI data acquisition. Additionally, the noise navigator can be combined with any rectilinear readout strategy (e.g. radial and cartesian) and is independent of MR image contrast and imaging orientation. For radiotherapy applications, the noise navigator provides a robust respiratory signal for patients scanned with an elevated coil setup. This is particularly attractive for widely used cartesian sequences where currently a non-interfering self-navigation means is lacking for MRI-based simulation and MRI-guided radiotherapy. The feasibility of 4D-MRI generation with the noise navigator as respiratory surrogate signal was demonstrated for both cartesian and radial readout strategies in radiotherapy setup on four healthy volunteers and two radiotherapy patients on a dedicated 1.5 T MRI scanner and two radiotherapy patients on a 1.5 T MRI-linac system. Moreover, the respiratory-correlated 4D-MR images showed liver motion comparable to a reference 2D cine MRI series for the volunteers. For 2D cartesian cine MRI acquisitions, both the noise navigator and respiratory bellows were benchmarked against an image navigator. Respiratory phase detection based on the noise navigator agreed 1.4 times better with the image navigator than the respiratory bellows did. For a 3D Stack-of-Stars acquisitions, the noise navigator was compared to radial self-navigation and a 1.7 times higher respiratory phase detection agreement was observed than for the respiratory bellows compared to radial self-navigation.
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Affiliation(s)
- R J M Navest
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands. Computational Imaging Group for MRI Diagnostics & Therapy, Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands. Author to whom any correspondence should be addressed
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Vicente E, Modiri A, Yu KC, Wibowo H, Yan Y, Timmerman R, Sawant A. Accounting for respiratory motion in small serial structures during radiotherapy planning: proof of concept in virtual bronchoscopy-guided lung functional avoidance radiotherapy. Phys Med Biol 2019; 64:225011. [PMID: 31665703 DOI: 10.1088/1361-6560/ab52a1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Respiratory motion management techniques in radiotherapy (RT) planning are primarily focused on maintaining tumor target coverage. An inadequately addressed need is accounting for motion in dosimetric estimations in smaller serial structures. Accurate dose estimations in such structures are more sensitive to motion because respiration can cause them to move completely in or out of a high dose-gradient field. In this work, we study three motion management strategies (m1-m3) to find an accurate method to estimate the dosimetry in airways. To validate these methods, we generated a 'ground truth' digital breathing model based on a 4DCT scan from a lung stereotactic ablative radiotherapy (SAbR) patient. We simulated 225 breathing cycles with ±10% perturbations in amplitude, respiratory period, and time per respiratory phase. A high-resolution breath-hold CT (BHCT) was also acquired and used with a research virtual bronchoscopy software to autosegment 239 airways. Contours for planning target volume (PTV) and organs at risk (OARs) were defined on the maximum intensity projection of the 4DCT (CTMIP) and transferred to the average of the 10 4DCT phases (CTAVG). To design the motion management methods, the RT plan was recreated using different images and structure definitions. Methods m1 and m2 recreated the plan using the CTAVG image. In method m1, airways were deformed to the CTAVG. In m2, airways were deformed to each of the 4DCT phases, and union structures were transferred onto the CTAVG. In m3, the RT plan was recreated on each of the 10 phases, and the dose distribution from each phase was deformed to the BHCT and summed. Dose errors (mean [min, max]) in airways were: m1: 21% (0.001%, 93%); m2: 45% (0.1%, 179%); and m3: 4% (0.006%, 14%). Our work suggests that accurate dose estimation in moving small serial structures requires customized motion management techniques (like m3 in this work) rather than current clinical and investigational approaches.
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Affiliation(s)
- Esther Vicente
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD 21201, United States of America. Author to whom correspondence should be addressed
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Freislederer P, von Münchow A, Kamp F, Heinz C, Gerum S, Corradini S, Söhn M, Reiner M, Roeder F, Floca R, Alber M, Belka C, Parodi K. Comparison of planned dose on different CT image sets to four-dimensional Monte Carlo dose recalculation using the patient's actual breathing trace for lung stereotactic body radiation therapy. Med Phys 2019; 46:3268-3277. [PMID: 31074510 DOI: 10.1002/mp.13579] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 04/17/2019] [Accepted: 04/18/2019] [Indexed: 12/25/2022] Open
Abstract
PURPOSE The need for four-dimensional (4D) treatment planning becomes indispensable when it comes to radiation therapy for moving tumors in the thoracic and abdominal regions. The primary purpose of this study is to combine the actual breathing trace during each individual treatment fraction with the Linac's log file information and Monte Carlo 4D dose calculations. We investigated this workflow on multiple computed tomography (CT) datasets in a clinical environment for stereotactic body radiation therapy (SBRT) treatment planning. METHODS We have developed a workflow, which allows us to recalculate absorbed dose to a 4DCT dataset using Monte Carlo calculation methods and accumulate all 4D doses in order to compare them to the planned dose using the Linac's log file, a 4DCT dataset, and the patient's actual breathing curve for each individual fraction. For five lung patients, three-dimensional-conformal radiation therapy (3D-CRT) and volumetric modulated arc treatment (VMAT) treatment plans were generated on four different CT image datasets: a native free-breathing 3DCT, an average intensity projection (AIP) and a maximum intensity projection (MIP) CT both obtained from a 4DCT, and a 3DCT with density overrides based on the 3DCT (DO). The Monte Carlo 4D dose has been calculated on each 4DCT phase using the Linac's log file and the patient's breathing trace as a surrogate for tumor motion and dose was accumulated to the gross tumor volume (GTV) at the 50% breathing phase (end of exhale) using deformable image registration. RESULTS Δ D 98 % and Δ D 2 % between 4D dose and planned dose differed largely for 3DCT-based planning and also for DO in three patients. Least dose differences between planned and recalculated dose have been found for AIP and MIP treatment planning which both tend to be superior to DO, but the results indicate a dependency on the breathing variability, tumor motion, and size. An interplay effect has not been observed in the small patient cohort. CONCLUSIONS We have developed a workflow which, to our best knowledge, is the first incorporation of the patient breathing trace over the course of all individual treatment fractions with the Linac's log file information and 4D Monte Carlo recalculations of the actual treated dose. Due to the small patient cohort, no clear recommendation on which CT can be used for SBRT treatment planning can be given, but the developed workflow, after adaption for clinical use, could be used to enhance a priori 4D Monte Carlo treatment planning in the future and help with the decision on which CT dataset treatment planning should be carried out.
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Affiliation(s)
- Philipp Freislederer
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Asmus von Münchow
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Florian Kamp
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Christian Heinz
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Sabine Gerum
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Stefanie Corradini
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Matthias Söhn
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Michael Reiner
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Falk Roeder
- Department of Radiotherapy and Radiation Oncology, Paracelsus Medical University, Landeskrankenhaus, Salzburg, Austria.,CCU Molecular Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Ralf Floca
- Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Research in Oncology (NCRO), Heidelberg, Germany.,Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Markus Alber
- Heidelberg Institute of Radiation Oncology (HIRO), National Center for Radiation Research in Oncology (NCRO), Heidelberg, Germany.,Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Claus Belka
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany.,German Cancer Consortium (DKTK), Munich, Germany.,Member of the German Center for Lung Research (DZL), Comprehensive Pneumology Center Munich (CPC-M), Munich, Germany
| | - Katia Parodi
- Department of Experimental Physics - Medical Physics, LMU Munich, Munich, Germany
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Abstract
As deformable image registration makes its way into the clinical routine, the summation of doses from fractionated treatment regimens to evaluate cumulative doses to targets and healthy tissues is also becoming a frequently utilized tool in the context of image-guided adaptive radiotherapy. Accounting for daily geometric changes using deformable image registration and dose accumulation potentially enables a better understanding of dose-volume-effect relationships, with the goal of translation of this knowledge to personalization of treatment, to further enhance treatment outcomes. Treatment adaptation involving image deformation requires patient-specific quality assurance of the image registration and dose accumulation processes, to ensure that uncertainties in the 3D dose distributions are identified and appreciated from a clinical relevance perspective. While much research has been devoted to identifying and managing the uncertainties associated with deformable image registration and dose accumulation approaches, there are still many unanswered questions. Here, we provide a review of current deformable image registration and dose accumulation techniques, and related clinical application. We also discuss salient issues that need to be deliberated when applying deformable algorithms for dose mapping and accumulation in the context of adaptive radiotherapy and response assessment.
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Paganelli C, Whelan B, Peroni M, Summers P, Fast M, van de Lindt T, McClelland J, Eiben B, Keall P, Lomax T, Riboldi M, Baroni G. MRI-guidance for motion management in external beam radiotherapy: current status and future challenges. Phys Med Biol 2018; 63:22TR03. [PMID: 30457121 DOI: 10.1088/1361-6560/aaebcf] [Citation(s) in RCA: 83] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
High precision conformal radiotherapy requires sophisticated imaging techniques to aid in target localisation for planning and treatment, particularly when organ motion due to respiration is involved. X-ray based imaging is a well-established standard for radiotherapy treatments. Over the last few years, the ability of magnetic resonance imaging (MRI) to provide radiation-free images with high-resolution and superb soft tissue contrast has highlighted the potential of this imaging modality for radiotherapy treatment planning and motion management. In addition, these advantageous properties motivated several recent developments towards combined MRI radiation therapy treatment units, enabling in-room MRI-guidance and treatment adaptation. The aim of this review is to provide an overview of the state-of-the-art in MRI-based image guidance for organ motion management in external beam radiotherapy. Methodological aspects of MRI for organ motion management are reviewed and their application in treatment planning, in-room guidance and adaptive radiotherapy described. Finally, a roadmap for an optimal use of MRI-guidance is highlighted and future challenges are discussed.
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Affiliation(s)
- C Paganelli
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy. Author to whom any correspondence should be addressed. www.cartcas.polimi.it
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15
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Pepin MD, Tryggestad E, Wan Chan Tseung HS, Johnson JE, Herman MG, Beltran C. A Monte-Carlo-based and GPU-accelerated 4D-dose calculator for a pencil beam scanning proton therapy system. Med Phys 2018; 45:5293-5304. [PMID: 30203550 DOI: 10.1002/mp.13182] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Revised: 08/30/2018] [Accepted: 08/31/2018] [Indexed: 01/16/2023] Open
Abstract
PURPOSE The presence of respiratory motion during radiation treatment leads to degradation of the expected dose distribution, both for target coverage and healthy tissue sparing, particularly for techniques like pencil beam scanning proton therapy which have dynamic delivery systems. While tools exist to estimate this degraded four-dimensional (4D) dose, they typically have one or more deficiencies such as not including the particular effects from a dynamic delivery, using analytical dose calculations, and/or using nonphysical dose-accumulation methods. This work presents a clinically useful 4D-dose calculator that addresses each of these shortcomings. METHODS To quickly compute the 4D dose, the three main tasks of the calculator were run on graphics processing units (GPUs). These tasks were (a) simulating the delivery of the plan using measured delivery parameters to distribute the plan amongst 4DCT phases characterizing the patient breathing, (b) using an in-house Monte Carlo simulation (MC) dose calculator to determine the dose delivered to each breathing phase, and (c) accumulating the doses from the various breathing phases onto a single phase for evaluation. The accumulation was performed by individually transferring the energy and mass of dose-grid subvoxels, a technique that models the transfer of dose in a more physically realistic manner. The calculator was run on three test cases, with lung, esophagus, and liver targets, respectively, to assess the various uncertainties in the beam delivery simulation as well as to characterize the dose-accumulation technique. RESULTS Four-dimensional doses were successfully computed for the three test cases with computation times ranging from 4-6 min on a server with eight NVIDIA Titan X graphics cards; the most time-consuming component was the MC dose engine. The subvoxel-based dose-accumulation technique produced stable 4D-dose distributions at subvoxel scales of 0.5-1.0 mm without impairing the total computation time. The uncertainties in the beam delivery simulation led to moderate variations of the dose-volume histograms for these cases; the variations were reduced by implementing repainting or phase-gating motion mitigation techniques in the calculator. CONCLUSIONS A MC-based and GPU-accelerated 4D-dose calculator was developed to estimate the effects of respiratory motion on pencil beam scanning proton therapy treatments. After future validation, the calculator could be used to assess treatment plans and its quick runtime would make it easily usable in a future 4D-robust optimization system.
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Affiliation(s)
- Mark D Pepin
- Department of Radiation Oncology, Mayo Clinic, 200 1st Street Southwest, Rochester, MN, 55905, USA
| | - Erik Tryggestad
- Department of Radiation Oncology, Mayo Clinic, 200 1st Street Southwest, Rochester, MN, 55905, USA
| | - Hok Seum Wan Chan Tseung
- Department of Radiation Oncology, Mayo Clinic, 200 1st Street Southwest, Rochester, MN, 55905, USA
| | - Jedediah E Johnson
- Department of Radiation Oncology, Mayo Clinic, 200 1st Street Southwest, Rochester, MN, 55905, USA
| | - Michael G Herman
- Department of Radiation Oncology, Mayo Clinic, 200 1st Street Southwest, Rochester, MN, 55905, USA
| | - Chris Beltran
- Department of Radiation Oncology, Mayo Clinic, 200 1st Street Southwest, Rochester, MN, 55905, USA
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Paganelli C, Meschini G, Molinelli S, Riboldi M, Baroni G. “Patient-specific validation of deformable image registration in radiation therapy: Overview and caveats”. Med Phys 2018; 45:e908-e922. [DOI: 10.1002/mp.13162] [Citation(s) in RCA: 58] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Revised: 07/30/2018] [Accepted: 08/24/2018] [Indexed: 12/26/2022] Open
Affiliation(s)
- Chiara Paganelli
- Dipartimento di Elettronica, Informazione e Bioingegneria; Politecnico di Milano; Milano 20133 Italy
| | - Giorgia Meschini
- Dipartimento di Elettronica, Informazione e Bioingegneria; Politecnico di Milano; Milano 20133 Italy
| | | | - Marco Riboldi
- Department of Medical Physics; Ludwig-Maximilians-Universitat Munchen; Munich 80539 Germany
| | - Guido Baroni
- Dipartimento di Elettronica, Informazione e Bioingegneria; Politecnico di Milano; Milano 20133 Italy
- Centro Nazionale di Adroterapia Oncologica; Pavia 27100 Italy
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Tong Y, Yin Y, Cheng P, Gong G. Impact of deformable image registration on dose accumulation applied electrocardiograph-gated 4DCT in the heart and left ventricular myocardium during esophageal cancer radiotherapy. Radiat Oncol 2018; 13:145. [PMID: 30097045 PMCID: PMC6086020 DOI: 10.1186/s13014-018-1093-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Accepted: 08/02/2018] [Indexed: 11/16/2022] Open
Abstract
Background The deformable image registration (DIR) technique has the potential to realize the dose accumulation during radiotherapy. This study will analyze the feasibility of evaluating dose-volume parameters for the heart and left ventricular myocardium (LVM) by applying DIR. Methods The electrocardiograph-gated four-dimensional CT (ECG-gated 4DCT) data of 21 patients were analyzed retrospectively. The heart and LVM were contoured on 20 phases of 4DCT (0%, 5%,…,95%). The heart and LVM in the minimum volume/dice similarity coefficient (DSC) phase (Volume min/DSC min) were deformed to the maximum volume/DSC phase (Volume max/ DSC max), which used the intensity-based free-form DIR algorithm of MIM software. The dose was deformed according to the deformation vector. The variations in volume, mean dose (Dmean), V20, V30 and V40 for the heart and LVM before and after DIR were compared, and the reference phase was the Volume max/DSC max phase. Results For the heart, the difference between the pre- and post-registration Volume min and Volume max were reduced from 13.87 to 1.72%; the DSC was increased from 0.899 to 0.950 between the pre- and post-registration DSC min phase relative to the DSC max phase. The post-registration Dmean, V20, V30 and V40 of the heart were statistically significant compared to those in the Volume max/DSC max phase (p < 0.05). For the LVM, the difference between the pre- and post-registration Volume min and Volume max were only reduced from 18.77 to 17.38%; the DSC reached only 0.733 in the post-registration DSC min phase relative to the DSC max phase. The pre- and post-registration volume, Dmean, V20, V30 and V40 of the LVM were all statistically significant compared to those in the Volume max/DSC max phase (p < 0.05). Conclusions There was no significant relationship between the variation in dose-volume parameters and the variation in the volume and morphology for the heart; however, the inconsistency of the variation in the volume and morphology for the LVM was a major factor that led to uncertainty in the dose-volume evaluation. In addition, the individualized local deformation registration technology should be applied in dose accumulation for the heart and LVM.
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Affiliation(s)
- Ying Tong
- Radiation Physics Department of Shandong Cancer Hospital Affiliated to Shandong University, Jinan, China
| | - Yong Yin
- Radiation Physics Department of Shandong Cancer Hospital Affiliated to Shandong University, Jinan, China
| | - Pinjing Cheng
- School of Nuclear Science and Technology, University of South China, Hengyang, China
| | - Guanzhong Gong
- Radiation Physics Department of Shandong Cancer Hospital Affiliated to Shandong University, Jinan, China.
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Mogadas N, Sothmann T, Knopp T, Gauer T, Petersen C, Werner R. Influence of deformable image registration on 4D dose simulation for extracranial SBRT: A multi-registration framework study. Radiother Oncol 2018; 127:225-232. [PMID: 29606523 DOI: 10.1016/j.radonc.2018.03.015] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 03/14/2018] [Accepted: 03/14/2018] [Indexed: 12/25/2022]
Abstract
BACKGROUND AND PURPOSE To evaluate the influence of deformable image registration approaches on correspondence model-based 4D dose simulation in extracranial SBRT by means of open source deformable image registration (DIR) frameworks. MATERIAL AND METHODS Established DIR algorithms of six different open source DIR frameworks were considered and registration accuracy evaluated using freely available 4D image data. Furthermore, correspondence models (regression-based correlation of external breathing signal measurements and internal structure motion field) were built and model accuracy evaluated. Finally, the DIR algorithms were applied for motion field estimation in radiotherapy planning 4D CT data of five lung and five liver lesion patients, correspondence model formation, and model-based 4D dose simulation. Deviations between the original, statically planned and the 4D-simulated VMAT dose distributions were analyzed and correlated to DIR accuracy differences. RESULTS Registration errors varied among the DIR approaches, with lower DIR accuracy translating into lower correspondence modeling accuracy. Yet, for lung metastases, indices of 4D-simulated dose distributions widely agreed, irrespective of DIR accuracy differences. In contrast, liver metastases 4D dose simulation results strongly vary for the different DIR approaches. CONCLUSIONS Especially in treatment areas with low image contrast (e.g. the liver), DIR-based 4D dose simulation results strongly depend on the applied DIR algorithm, drawing resulting dose simulations and indices questionable.
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Affiliation(s)
- Nik Mogadas
- Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Germany
| | - Thilo Sothmann
- Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Germany; Department of Radiotherapy and Radio-Oncology, University Medical Center Hamburg-Eppendorf, Germany.
| | - Tobias Knopp
- Section for Biomedical Imaging, University Medical Center Hamburg-Eppendorf, Germany
| | - Tobias Gauer
- Department of Radiotherapy and Radio-Oncology, University Medical Center Hamburg-Eppendorf, Germany
| | - Cordula Petersen
- Department of Radiotherapy and Radio-Oncology, University Medical Center Hamburg-Eppendorf, Germany
| | - René Werner
- Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Germany
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Sentker T, Madesta F, Werner R. GDL-FIRE$$^\text {4D}$$: Deep Learning-Based Fast 4D CT Image Registration. MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION – MICCAI 2018 2018. [DOI: 10.1007/978-3-030-00928-1_86] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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Kostiukhina N, Georg D, Rollet S, Kuess P, Sipaj A, Andrzejewski P, Furtado H, Rausch I, Lechner W, Steiner E, Kertész H, Knäusl B. Advanced Radiation DOSimetry phantom (ARDOS): a versatile breathing phantom for 4D radiation therapy and medical imaging. Phys Med Biol 2017; 62:8136-8153. [PMID: 28817381 DOI: 10.1088/1361-6560/aa86ea] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
A novel breathing phantom was designed for being used in conventional and ion-beam radiotherapy as well as for medical imaging. Accurate dose delivery and patient safety are aimed to be verified for four-dimensional (4D) treatment techniques compensating for breathing-induced tumor motion. The phantom includes anthropomorphic components representing an average human thorax. It consists of real tissue equivalent materials to fulfill the requirements for dosimetric experiments and imaging purposes. The different parts of the torso (lungs, chest wall, and ribs) and the tumor can move independently. Simple regular movements, as well as more advanced patient-specific breathing cycles are feasible while a reproducible setup can be guaranteed. The phantom provides the flexibility to use different types of dosimetric devices and was designed in a way that it is robust, transportable and easy to handle. Tolerance levels and the reliability of the phantom setup were determined in combination with tests on motion accuracy and reproducibility by using infrared optical tracking technology. Different imaging was performed including positron emission tomography imaging, 4D computed tomography as well as real-time in-room imaging. The initial dosimetric benchmarking studies were performed in a photon beam where dose parameters are predictable and the dosimetric procedures well established.
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Affiliation(s)
- Natalia Kostiukhina
- Division Medical Radiation Physics, Department of Radiation Oncology, Medical University of Vienna/AKH Vienna, Vienna, Austria. Christian Doppler Laboratory for Medical Radiation Research for Radiation Oncology, Medical University of Vienna, Vienna, Austria. Health & Environment Department, Biomedical Systems, AIT Austrian Institute of Technology GmbH, Vienna, Austria
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Werner R, Hofmann C, Mücke E, Gauer T. Reduction of breathing irregularity-related motion artifacts in low-pitch spiral 4D CT by optimized projection binning. Radiat Oncol 2017. [PMID: 28629434 PMCID: PMC5477247 DOI: 10.1186/s13014-017-0835-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Background Respiration-correlated CT (4D CT) is the basis of radiotherapy treatment planning of thoracic and abdominal tumors. Current clinical 4D CT images suffer, however, from artifacts due to unfulfilled assumptions concerning breathing pattern regularity. We propose and evaluate modifications to existing low-pitch spiral 4D CT reconstruction protocols to counteract respective artifacts. Methods The proposed advanced reconstruction (AR) approach consists of two steps that build on each other: (1) statistical analysis of the breathing signal recorded during CT data acquisition and extraction of a patient-specific reference breathing cycle for projection binning; (2) incorporation of an artifact measure into the reconstruction. 4D CT data of 30 patients were reconstructed by standard phase- and local amplitude-based reconstruction (PB, LAB) and compared with images obtained by AR. The number of artifacts was evaluated and artifact statistics correlated to breathing curve characteristics. Results AR reduced the number of 4D CT artifacts by 31% and 27% compared to PB and LAB; the reduction was most pronounced for irregular breathing curves. Conclusions We described a two-step optimization of low-pitch spiral 4D CT reconstruction to reduce artifacts in the presence of breathing irregularity and illustrated that the modifications to existing reconstruction solutions are effective in terms of artifact reduction. Electronic supplementary material The online version of this article (doi:10.1186/s13014-017-0835-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- René Werner
- University Medical Center Hamburg-Eppendorf, Martinistr. 52, Hamburg, 20246, Germany.
| | | | - Eike Mücke
- University Medical Center Hamburg-Eppendorf, Martinistr. 52, Hamburg, 20246, Germany
| | - Tobias Gauer
- University Medical Center Hamburg-Eppendorf, Martinistr. 52, Hamburg, 20246, Germany
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22
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Evaluation of mesh- and binary-based contour propagation methods in 4D thoracic radiotherapy treatments using patient 4D CT images. Phys Med 2017; 36:46-53. [DOI: 10.1016/j.ejmp.2017.03.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Revised: 03/08/2017] [Accepted: 03/10/2017] [Indexed: 12/28/2022] Open
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Santoso AP, Song KH, Qin Y, Gardner SJ, Liu C, Chetty IJ, Movsas B, Ajlouni M, Wen N. Evaluation of gantry speed on image quality and imaging dose for 4D cone-beam CT acquisition. Radiat Oncol 2016; 11:98. [PMID: 27473367 PMCID: PMC4966562 DOI: 10.1186/s13014-016-0677-8] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2016] [Accepted: 07/22/2016] [Indexed: 11/10/2022] Open
Abstract
Background This study investigates the effect of gantry speed on 4DCBCT image quality and dose for the Varian On-Board Imager®. Methods A thoracic 4DCBCT protocol was designed using a 125 kVp spectrum. Image quality parameters were evaluated for 4DCBCT acquisition using Catphan® phantom with real-time position management™ system for gantry speeds varying between 1.0 to 6.0°/s. Superior-inferior motion of the phantom was executed using a sinusoidal waveform with five second period. Scans were retrospectively sorted into 4 phases (CBCT-4 ph) and 10 phases (CBCT-10 ph); average 4DCBCT (CBCT-ave), using all image data from the 4DCBCT acquisitions was also evaluated. The 4DCBCT images were evaluated using the following image quality metrics: spatial resolution, contrast-to-noise ratio (CNR), and uniformity index (UI). Additionally, Hounsfield unit (HU) sensitivity compared to a baseline CBCT and percent differences and RMS errors (RMSE) of excursion were also determined. Imaging dose was evaluated using an IBA CC13 ion chamber placed within CIRS Thorax phantom using the same sinusoidal motion and image acquisition settings as mentioned above. Results Spatial resolution decreased linearly from 5.93 to 3.82 lp/cm as gantry speed increased from 1.0 to 6.0°/s. CNR decreased linearly from 4.80 to 1.82 with gantry speed increasing from 1.0 to 6.0°/s, respectively. No noteworthy variations in UI, HU sensitivity, or excursion metrics were observed with changes in gantry speed. Ion chamber dose rates measured ranged from 2.30 (lung) to 5.18 (bone) E-3 cGy/mAs. Conclusions A quantitative analysis of the Varian OBI’s 4DCBCT capabilities was explored. Changing gantry speed changes the number of projections used for reconstruction, affecting both image quality and imaging dose if x-ray tube current is held constant. From the results of this study, a gantry speed between 2 and 3°/s was optimal when considering image quality, dose, and reconstruction time. The future of 4DCBCT clinical utility relies on further investigation of image acquisition and reconstruction optimization.
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Affiliation(s)
- Andrew P Santoso
- Department of Radiation Oncology, Wayne State University School of Medicine, Detroit, MI, 48201, USA
| | - Kwang H Song
- Texas Oncology, Fort Worth, TX, 76104, USA.,Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, 48202, USA
| | - Yujiao Qin
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, 48202, USA
| | - Stephen J Gardner
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, 48202, USA
| | - Chang Liu
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, 48202, USA
| | - Indrin J Chetty
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, 48202, USA
| | - Benjamin Movsas
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, 48202, USA
| | - Munther Ajlouni
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, 48202, USA
| | - Ning Wen
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, 48202, USA.
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Sothmann T, Blanck O, Poels K, Werner R, Gauer T. Real time tracking in liver SBRT: comparison of CyberKnife and Vero by planning structure-based γ-evaluation and dose-area-histograms. Phys Med Biol 2016; 61:1677-91. [PMID: 26836488 DOI: 10.1088/0031-9155/61/4/1677] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
The purpose of this study was to evaluate and compare two clinical tracking systems for radiosurgery with regard to their dosimetric and geometrical accuracy in liver SBRT: the robot-based CyberKnife and the gimbal-based Vero. Both systems perform real-time tumour tracking by correlating internal tumour and external surrogate motion. CyberKnife treatment plans were delivered to a high resolution 2D detector array mounted on a 4D motion platform, with the platform simulating (a) tumour motion trajectories extracted from the corresponding CyberKnife predictor log files and (b) the tumour motion trajectories with superimposed baseline-drift. Static reference and tracked dose measurements were compared and dosimetric as well as geometrical uncertainties analyzed by a planning structure-based evaluation. For (a), γ-passing rates inside the CTV (γ-criteria of 1% / 1 mm) ranged from 95% to 100% (CyberKnife) and 98% to 100% (Vero). However, dosimetric accuracy decreases in the presence of the baseline-drift. γ-passing rates for (b) ranged from 26% to 92% and 94% to 99%, respectively; i.e. the effect was more pronounced for CyberKnife. In contrast, the Vero system led to maximum dose deviations in the OAR between +1.5 Gy to +6.0 Gy (CyberKnife: +0.5 Gy to +3.5 Gy). Potential dose shifts were interpreted as motion-induced geometrical tracking errors. Maximum observed shift ranges were -1.0 mm to +0.7 mm (lateral) /-0.6 mm to +0.1 mm (superior-inferior) for CyberKnife and -0.8 mm to +0.2 mm /-0.8 mm to +0.4 mm for Vero. These values illustrate that CyberKnife and Vero provide high precision tracking of regular breathing patterns. Even for the modified motion trajectory, the obtained dose distributions appear to be clinical acceptable with regard to literature QA γ-criteria of 3% / 3 mm.
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Affiliation(s)
- T Sothmann
- Department of Radiotherapy and Radio-Oncology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany. Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany
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Cooper BJ, O’Brien RT, Kipritidis J, Shieh CC, Keall PJ. Quantifying the image quality and dose reduction of respiratory triggered 4D cone-beam computed tomography with patient-measured breathing. Phys Med Biol 2015; 60:9493-513. [DOI: 10.1088/0031-9155/60/24/9493] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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Grohmann C, Frenzel T, Werner R, Cremers F. Design, performance characteristics and application examples of a new 4D motion platform. Z Med Phys 2015; 25:156-67. [DOI: 10.1016/j.zemedi.2014.09.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2014] [Revised: 08/22/2014] [Accepted: 09/09/2014] [Indexed: 12/25/2022]
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Zeng C, Plastaras JP, Tochner ZA, White BM, Hill-Kayser CE, Hahn SM, Both S. Proton pencil beam scanning for mediastinal lymphoma: the impact of interplay between target motion and beam scanning. Phys Med Biol 2015; 60:3013-29. [DOI: 10.1088/0031-9155/60/7/3013] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Wujcicki A, Corteville D, Materka A, Schad LR. Perfusion and ventilation filters for Fourier-decomposition MR lung imaging. Z Med Phys 2015; 25:66-76. [DOI: 10.1016/j.zemedi.2014.10.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2013] [Revised: 10/15/2014] [Accepted: 10/30/2014] [Indexed: 11/26/2022]
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Bert C, Graeff C, Riboldi M, Nill S, Baroni G, Knopf AC. Advances in 4D treatment planning for scanned particle beam therapy - report of dedicated workshops. Technol Cancer Res Treat 2014; 13:485-95. [PMID: 24354749 PMCID: PMC4527425 DOI: 10.7785/tcrtexpress.2013.600274] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2013] [Revised: 09/27/2013] [Accepted: 10/01/2013] [Indexed: 11/25/2022] Open
Abstract
We report on recent progress in the field of mobile tumor treatment with scanned particle beams, as discussed in the latest editions of the 4D treatment planning workshop. The workshop series started in 2009, with about 20 people from 4 research institutes involved, all actively working on particle therapy delivery and development. The first workshop resulted in a summary of recommendations for the treatment of mobile targets, along with a list of requirements to apply these guidelines clinically. The increased interest in the treatment of mobile tumors led to a continuously growing number of attendees: the 2012 edition counted more than 60 participants from 20 institutions and commercial vendors. The focus of research discussions among workshop participants progressively moved from 4D treatment planning to complete 4D treatments, aiming at effective and safe treatment delivery. Current research perspectives on 4D treatments include all critical aspects of time resolved delivery, such as in-room imaging, motion detection, beam application, and quality assurance techniques. This was motivated by the start of first clinical treatments of hepato cellular tumors with a scanned particle beam, relying on gating or abdominal compression for motion mitigation. Up to date research activities emphasize significant efforts in investigating advanced motion mitigation techniques, with a specific interest in the development of dedicated tools for experimental validation. Potential improvements will be made possible in the near future through 4D optimized treatment plans that require upgrades of the currently established therapy control systems for time resolved delivery. But since also these novel optimization techniques rely on the validity of the 4DCT, research focusing on alternative 4D imaging technique, such as MRI based 4DCT generation will continue.
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Affiliation(s)
- Christoph Bert
- University Clinic Erlangen, Radiation Oncology, Universitatsstrasse 27, 91054 Erlangen, Germany.
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Milz S, Wilkens JJ, Ullrich W. A dose error evaluation study for 4D dose calculations. Phys Med Biol 2014; 59:6401-15. [DOI: 10.1088/0022-3727/59/21/6401] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Fan Q, Nanduri A, Yang J, Yamamoto T, Loo B, Graves E, Zhu L, Mazin S. Toward a planning scheme for emission guided radiation therapy (EGRT): FDG based tumor tracking in a metastatic breast cancer patient. Med Phys 2014; 40:081708. [PMID: 23927305 DOI: 10.1118/1.4812427] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
PURPOSE Emission guided radiation therapy (EGRT) is a new modality that uses PET emissions in real-time for direct tumor tracking during radiation delivery. Radiation beamlets are delivered along positron emission tomography (PET) lines of response (LORs) by a fast rotating ring therapy unit consisting of a linear accelerator (Linac) and PET detectors. The feasibility of tumor tracking and a primitive modulation method to compensate for attenuation have been demonstrated using a 4D digital phantom in our prior work. However, the essential capability of achieving dose modulation as in conventional intensity modulated radiation therapy (IMRT) treatments remains absent. In this work, the authors develop a planning scheme for EGRT to accomplish sophisticated intensity modulation based on an IMRT plan while preserving tumor tracking. METHODS The planning scheme utilizes a precomputed LOR response probability distribution to achieve desired IMRT planning modulation with effects of inhomogeneous attenuation and nonuniform background activity distribution accounted for. Evaluation studies are performed on a 4D digital patient with a simulated lung tumor and a clinical patient who has a moving breast cancer metastasis in the lung. The Linac dose delivery is simulated using a voxel-based Monte Carlo algorithm. The IMRT plan is optimized for a planning target volume (PTV) that encompasses the tumor motion using the MOSEK package and a Pinnacle3™ workstation (Philips Healthcare, Fitchburg, WI) for digital and clinical patients, respectively. To obtain the emission data for both patients, the Geant4 application for tomographic emission (GATE) package and a commercial PET scanner are used. As a comparison, 3D and helical IMRT treatments covering the same PTV based on the same IMRT plan are simulated. RESULTS 3D and helical IMRT treatments show similar dose distribution. In the digital patient case, compared with the 3D IMRT treatment, EGRT achieves a 15.1% relative increase in dose to 95% of the gross tumor volume (GTV) and a 31.8% increase to 50% of the GTV. In the patient case, EGRT yields a 15.2% relative increase in dose to 95% of the GTV and a 20.7% increase to 50% of the GTV. The organs at risk (OARs) doses are kept similar or lower for EGRT in both cases. Tumor tracking is observed in the presence of planning modulation in all EGRT treatments. CONCLUSIONS As compared to conventional IMRT treatments, the proposed EGRT planning scheme allows an escalated target dose while keeping dose to the OARs within the same planning limits. With the capabilities of incorporating planning modulation and accurate tumor tracking, EGRT has the potential to greatly improve targeting in radiation therapy and enable a practical and effective implementation of 4D radiation therapy for planning and delivery.
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Affiliation(s)
- Qiyong Fan
- Nuclear and Radiological Engineering Program, The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
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Simulation of spatiotemporal CT data sets using a 4D MRI-based lung motion model. Int J Comput Assist Radiol Surg 2013; 9:401-9. [DOI: 10.1007/s11548-013-0963-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2013] [Accepted: 11/12/2013] [Indexed: 11/24/2022]
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