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Büttgen LE, Werner R, Gauer T. Stability analysis of patient-specific 4DCT- and 4DCBCT-based correspondence models. Med Phys 2024. [PMID: 39032078 DOI: 10.1002/mp.17304] [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: 02/09/2024] [Revised: 06/26/2024] [Accepted: 06/29/2024] [Indexed: 07/22/2024] Open
Abstract
BACKGROUND Surrogate-based motion compensation in stereotactic body radiation therapy (SBRT) strongly relies on a constant relationship between an external breathing signal and the internal tumor motion over the course of treatment, that is, a stable patient-specific correspondence model. PURPOSE This study aims to develop methods for analyzing the stability of correspondence models by integrating planning 4DCT and pretreatment 4D cone-beam computed tomography (4DCBCT) data and assessing the relation to patient-specific clinical parameters. METHODS For correspondence modeling, a regression-based approach is applied, correlating patient-specific internal motion (vector fields computed by deformable image registration) and external breathing signals (recorded by Varian's RPM and RGSC system). To analyze correspondence model stability, two complementary methods are proposed. (1) Target volume-based analysis: 4DCBCT-based correspondence models predict clinical target volumes (GTV and internal target volume [ITV]) within the planning 4DCT, which are evaluated by overlap and distance measures (Dice similarity coefficient [DSC]/average symmetric surface distance [ASSD]). (2) System matrix-based analysis: 4DCBCT-based regression models are compared to 4DCT-based models using mean squared difference (MSD) and principal component analysis of the system matrices. Stability analysis results are correlated with clinical parameters. Both methods are applied to a dataset of 214 pretreatment 4DCBCT scans (Varian TrueBeam) from a cohort of 46 lung tumor patients treated with ITV-based SBRT (planning 4DCTs acquired with Siemens AS Open and SOMATOM go.OPEN Pro CT scanners). RESULTS Consistent results across the two complementary analysis approaches (Spearman correlation coefficient of0.6 / 0.7 $0.6/ 0.7$ between system matrix-based MSD and GTV-based DSC/ASSD) were observed. Analysis showed that stability was not predominant, with 114/214 fraction-wise models not surpassing a threshold ofD S C > 0.7 $DSC > 0.7$ for the GTV, and only 14/46 patients demonstrating aD S C > 0.7 $DSC > 0.7$ in all fractions. Model stability did not degrade over the course of treatment. The mean GTV-based DSC is0.59 ± 0.26 $0.59\pm 0.26$ (mean ASSD of2.83 ± 3.37 $2.83\pm 3.37$ ) and the respective ITV-based DSC is0.69 ± 0.20 $0.69\pm 0.20$ (mean ASSD of2.35 ± 1.81 $2.35\pm 1.81$ ). The clinical parameters showed a strong correlation between smaller tumor motion ranges and increased stability. CONCLUSIONS The proposed methods identify patients with unstable correspondence models prior to each treatment fraction, serving as direct indicators for the necessity of replanning and adaptive treatment approaches to account for internal-external motion variations throughout the course of treatment.
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Affiliation(s)
- Laura Esther Büttgen
- Department of Radiotherapy and Radio-Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Institute for Applied Medical Informatics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - René Werner
- Institute for Applied Medical Informatics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Institute of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Tobias Gauer
- Department of Radiotherapy and Radio-Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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Li G, Wang G, Wei W, Li Z, Xiao Q, He H, Luo D, Chen L, Li J, Zhang X, Song Y, Bai S. Cardiorespiratory motion characteristics and their dosimetric impact on cardiac stereotactic body radiotherapy. Med Phys 2024. [PMID: 38994881 DOI: 10.1002/mp.17284] [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: 02/05/2024] [Revised: 06/19/2024] [Accepted: 06/20/2024] [Indexed: 07/13/2024] Open
Abstract
BACKGROUND Cardiac stereotactic body radiotherapy (CSBRT) is an emerging and promising noninvasive technique for treating refractory arrhythmias utilizing highly precise, single or limited-fraction high-dose irradiations. This method promises to revolutionize the treatment of cardiac conditions by delivering targeted therapy with minimal exposure to surrounding healthy tissues. However, the dynamic nature of cardiorespiratory motion poses significant challenges to the precise delivery of dose in CSBRT, introducing potential variabilities that can impact treatment efficacy. The complexities of the influence of cardiorespiratory motion on dose distribution are compounded by interplay and blurring effects, introducing additional layers of dose uncertainty. These effects, critical to the understanding and improvement of the accuracy of CSBRT, remain unexplored, presenting a gap in current clinical literature. PURPOSE To investigate the cardiorespiratory motion characteristics in arrhythmia patients and the dosimetric impact of interplay and blurring effects induced by cardiorespiratory motion on CSBRT plan quality. METHODS The position and volume variations in the substrate target and cardiac substructures were evaluated in 12 arrhythmia patients using displacement maximum (DMX) and volume metrics. Moreover, a four-dimensional (4D) dose reconstruction approach was employed to examine the dose uncertainty of the cardiorespiratory motion. RESULTS Cardiac pulsation induced lower DMX than respiratory motion but increased the coefficient of variation and relative range in cardiac substructure volumes. The mean DMX of the substrate target was 0.52 cm (range: 0.26-0.80 cm) for cardiac pulsation and 0.82 cm (range: 0.32-2.05 cm) for respiratory motion. The mean DMX of the cardiac structure ranged from 0.15 to 1.56 cm during cardiac pulsation and from 0.35 to 1.89 cm during respiratory motion. Cardiac pulsation resulted in an average deviation of -0.73% (range: -4.01%-4.47%) in V25 between the 3D and 4D doses. The mean deviations in the homogeneity index (HI) and gradient index (GI) were 1.70% (range: -3.10%-4.36%) and 0.03 (range: -0.14-0.11), respectively. For cardiac substructures, the deviations in D50 due to cardiac pulsation ranged from -1.88% to 1.44%, whereas the deviations in Dmax ranged from -2.96% to 0.88% of the prescription dose. By contrast, the respiratory motion led to a mean deviation of -1.50% (range: -10.73%-4.23%) in V25. The mean deviations in HI and GI due to respiratory motion were 4.43% (range: -3.89%-13.98%) and 0.18 (range: -0.01-0.47) (p < 0.05), respectively. Furthermore, the deviations in D50 and Dmax in cardiac substructures for the respiratory motion ranged from -0.28% to 4.24% and -4.12% to 1.16%, respectively. CONCLUSIONS Cardiorespiratory motion characteristics vary among patients, with the respiratory motion being more significant. The intricate cardiorespiratory motion characteristics and CSBRT plan complexity can induce substantial dose uncertainty. Therefore, assessing individual motion characteristics and 4D dose reconstruction techniques is critical for implementing CSBRT without compromising efficacy and safety.
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Affiliation(s)
- Guangjun Li
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Guangyu Wang
- State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Weige Wei
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zhibin Li
- Department of Radiotherapy & Oncology, The First Affiliated Hospital of Soochow University, Institute of Radiotherapy & Oncology, Soochow University, Suzhou, China
| | - Qing Xiao
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Haiping He
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Dashuang Luo
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Li Chen
- Department of Radiotherapy & Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Jing Li
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiangyu Zhang
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ying Song
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Sen Bai
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Department of Radiotherapy Physics & Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
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Madesta F, Sentker T, Gauer T, Werner R. Deep learning-based conditional inpainting for restoration of artifact-affected 4D CT images. Med Phys 2024; 51:3437-3454. [PMID: 38055336 DOI: 10.1002/mp.16851] [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: 06/02/2023] [Revised: 10/12/2023] [Accepted: 10/16/2023] [Indexed: 12/08/2023] Open
Abstract
BACKGROUND 4D CT imaging is an essential component of radiotherapy of thoracic and abdominal tumors. 4D CT images are, however, often affected by artifacts that compromise treatment planning quality and image information reliability. PURPOSE In this work, deep learning (DL)-based conditional inpainting is proposed to restore anatomically correct image information of artifact-affected areas. METHODS The restoration approach consists of a two-stage process: DL-based detection of common interpolation (INT) and double structure (DS) artifacts, followed by conditional inpainting applied to the artifact areas. In this context, conditional refers to a guidance of the inpainting process by patient-specific image data to ensure anatomically reliable results. The study is based on 65 in-house 4D CT images of lung cancer patients (48 with only slight artifacts, 17 with pronounced artifacts) and two publicly available 4D CT data sets that serve as independent external test sets. RESULTS Automated artifact detection revealed a ROC-AUC of 0.99 for INT and of 0.97 for DS artifacts (in-house data). The proposed inpainting method decreased the average root mean squared error (RMSE) by 52 % (INT) and 59 % (DS) for the in-house data. For the external test data sets, the RMSE improvement is similar (50 % and 59 %, respectively). Applied to 4D CT data with pronounced artifacts (not part of the training set), 72 % of the detectable artifacts were removed. CONCLUSIONS The results highlight the potential of DL-based inpainting for restoration of artifact-affected 4D CT data. Compared to recent 4D CT inpainting and restoration approaches, the proposed methodology illustrates the advantages of exploiting patient-specific prior image information.
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Affiliation(s)
- Frederic Madesta
- Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Institute for Applied Medical Informatics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Center for Biomedical Artificial Intelligence (bAIome), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Thilo Sentker
- Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Institute for Applied Medical Informatics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Center for Biomedical Artificial Intelligence (bAIome), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Tobias Gauer
- Department of Radiotherapy and Radiation Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - René Werner
- Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Institute for Applied Medical Informatics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Center for Biomedical Artificial Intelligence (bAIome), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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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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Tascón-Vidarte JD, Stick LB, Josipovic M, Risum S, Jomier J, Erleben K, Vogelius IR, Darkner S. Accuracy and consistency of intensity-based deformable image registration in 4DCT for tumor motion estimation in liver radiotherapy planning. PLoS One 2022; 17:e0271064. [PMID: 35802593 PMCID: PMC9269460 DOI: 10.1371/journal.pone.0271064] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 06/23/2022] [Indexed: 11/29/2022] Open
Abstract
We investigate the accuracy of intensity-based deformable image registration (DIR) for tumor localization in liver stereotactic body radiotherapy (SBRT). We included 4DCT scans to capture the breathing motion of eight patients receiving SBRT for liver metastases within a retrospective clinical study. Each patient had three fiducial markers implanted. The liver and the tumor were delineated in the mid-ventilation phase, and their positions in the other phases were estimated with deformable image registration. We tested referenced and sequential registrations strategies. The fiducial markers were the gold standard to evaluate registration accuracy. The registration errors related to measured versus estimated fiducial markers showed a mean value less than 1.6mm. The positions of some fiducial markers appeared not stable on the 4DCT throughout the respiratory phases. Markers’ center of mass tends to be a more reliable measurement. Distance errors of tumor location based on registration versus markers center of mass were less than 2mm. There were no statistically significant differences between the reference and the sequential registration, i.e., consistency and errors were comparable to resolution errors. We demonstrated that intensity-based DIR is accurate up to resolution level for locating the tumor in the liver during breathing motion.
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Affiliation(s)
| | | | | | | | | | - Kenny Erleben
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | | | - Sune Darkner
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
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Xie X, Song Y, Ye F, Yan H, Wang S, Zhao X, Dai J. Improving deformable image registration with point metric and masking technique for postoperative breast cancer radiotherapy. Quant Imaging Med Surg 2021; 11:1196-1208. [PMID: 33816160 DOI: 10.21037/qims-20-705] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Background Deformable image registration (DIR) is increasingly used for target volume definition in radiotherapy. However, this method is challenging for postoperative breast cancer patients due to the large deformations and non-correspondence caused by tumor resection and clip insertion. In this study, an improved B-splines based DIR method was developed to address this issue for higher registration accuracy. Methods The conventional B-splines based DIR method was improved with the introduction of point metric and masking technique. The point metric minimizes the distance between 2 point sets with known correspondence for regularization of intensity-based B-splines registration. The masking technique reduces the influence of non-corresponding regions in breast computed tomography (CT) images. Two sets of CT images before and after breast surgery were used for image registration. One set was the diagnostic CT image acquired before surgery, and another set was the planning CT image acquired after surgery for breast cancer radiotherapy. A total of 26 sets of CT images from 13 patients were collected retrospectively for the test. The improved DIR method's registration accuracy was evaluated by target registration error (TRE), the Jacobian determinant, and visual assessment. Results For soft tissue, the difference in the median TRE between the improved DIR method and the conventional DIR method was statistically significant (2.27 vs. 5.88, P<0.05). The Jacobian determinant of the deformation field was positive for all patients. For visual assessment, the improved DIR method with point metric achieved better matching for soft tissue. Conclusions The improved DIR method's registration accuracy was higher than the conventional DIR method based on the preliminary results. With point metric and masking technique, the influence of large deformations and non-correspondence on registration between pre- and post-operative CT images can be effectively reduced. Therefore, this method provides a feasible way for target volume definition in postoperative breast cancer radiotherapy treatment planning.
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Affiliation(s)
- Xin Xie
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yuchun Song
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Feng Ye
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hui Yan
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shulian Wang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xinming Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jianrong Dai
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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7
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A review on 3D deformable image registration and its application in dose warping. RADIATION MEDICINE AND PROTECTION 2020. [DOI: 10.1016/j.radmp.2020.11.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
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Madesta F, Sentker T, Gauer T, Werner R. Self‐contained deep learning‐based boosting of 4D cone‐beam CT reconstruction. Med Phys 2020; 47:5619-5631. [DOI: 10.1002/mp.14441] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Revised: 06/02/2020] [Accepted: 07/16/2020] [Indexed: 12/25/2022] Open
Affiliation(s)
- Frederic Madesta
- Department of Computational Neuroscience University Medical Center Hamburg‐Eppendorf Hamburg20246 Germany
| | - Thilo Sentker
- Department of Computational Neuroscience University Medical Center Hamburg‐Eppendorf Hamburg20246 Germany
- Department of Radiotherapy and Radio‐Oncology University Medical Center Hamburg‐Eppendorf Hamburg20246 Germany
| | - Tobias Gauer
- Department of Radiotherapy and Radio‐Oncology University Medical Center Hamburg‐Eppendorf Hamburg20246 Germany
| | - René Werner
- Department of Computational Neuroscience University Medical Center Hamburg‐Eppendorf Hamburg20246 Germany
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Nenoff L, Ribeiro CO, Matter M, Hafner L, Josipovic M, Langendijk JA, Persson GF, Walser M, Weber DC, Lomax AJ, Knopf AC, Albertini F, Zhang Y. Deformable image registration uncertainty for inter-fractional dose accumulation of lung cancer proton therapy. Radiother Oncol 2020; 147:178-185. [DOI: 10.1016/j.radonc.2020.04.046] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Revised: 04/22/2020] [Accepted: 04/25/2020] [Indexed: 12/25/2022]
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Schmitt D, Blanck O, Gauer T, Fix MK, Brunner TB, Fleckenstein J, Loutfi-Krauss B, Manser P, Werner R, Wilhelm ML, Baus WW, Moustakis C. Technological quality requirements for stereotactic radiotherapy : Expert review group consensus from the DGMP Working Group for Physics and Technology in Stereotactic Radiotherapy. Strahlenther Onkol 2020; 196:421-443. [PMID: 32211939 PMCID: PMC7182540 DOI: 10.1007/s00066-020-01583-2] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2020] [Accepted: 01/13/2020] [Indexed: 12/25/2022]
Abstract
This review details and discusses the technological quality requirements to ensure the desired quality for stereotactic radiotherapy using photon external beam radiotherapy as defined by the DEGRO Working Group Radiosurgery and Stereotactic Radiotherapy and the DGMP Working Group for Physics and Technology in Stereotactic Radiotherapy. The covered aspects of this review are 1) imaging for target volume definition, 2) patient positioning and target volume localization, 3) motion management, 4) collimation of the irradiation and beam directions, 5) dose calculation, 6) treatment unit accuracy, and 7) dedicated quality assurance measures. For each part, an expert review for current state-of-the-art techniques and their particular technological quality requirement to reach the necessary accuracy for stereotactic radiotherapy divided into intracranial stereotactic radiosurgery in one single fraction (SRS), intracranial fractionated stereotactic radiotherapy (FSRT), and extracranial stereotactic body radiotherapy (SBRT) is presented. All recommendations and suggestions for all mentioned aspects of stereotactic radiotherapy are formulated and related uncertainties and potential sources of error discussed. Additionally, further research and development needs in terms of insufficient data and unsolved problems for stereotactic radiotherapy are identified, which will serve as a basis for the future assignments of the DGMP Working Group for Physics and Technology in Stereotactic Radiotherapy. The review was group peer-reviewed, and consensus was obtained through multiple working group meetings.
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Affiliation(s)
- Daniela Schmitt
- Klinik für Radioonkologie und Strahlentherapie, National Center for Radiation Research in Oncology (NCRO), Heidelberger Institut für Radioonkologie (HIRO), Universitätsklinikum Heidelberg, Heidelberg, Germany.
| | - Oliver Blanck
- Klinik für Strahlentherapie, Universitätsklinikum Schleswig-Holstein, Kiel, Germany
| | - Tobias Gauer
- Klinik für Strahlentherapie und Radioonkologie, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Michael K Fix
- Abteilung für Medizinische Strahlenphysik und Universitätsklinik für Radio-Onkologie, Inselspital-Universitätsspital Bern, Universität Bern, Bern, Switzerland
| | - Thomas B Brunner
- Universitätsklinik für Strahlentherapie, Universitätsklinikum Magdeburg, Magdeburg, Germany
| | - Jens Fleckenstein
- Klinik für Strahlentherapie und Radioonkologie, Universitätsmedizin Mannheim, Universität Heidelberg, Mannheim, Germany
| | - Britta Loutfi-Krauss
- Klinik für Strahlentherapie und Onkologie, Universitätsklinikum Frankfurt, Frankfurt am Main, Germany
| | - Peter Manser
- Abteilung für Medizinische Strahlenphysik und Universitätsklinik für Radio-Onkologie, Inselspital-Universitätsspital Bern, Universität Bern, Bern, Switzerland
| | - Rene Werner
- Institut für Computational Neuroscience, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Maria-Lisa Wilhelm
- Klinik für Strahlentherapie, Universitätsmedizin Rostock, Rostock, Germany
| | - Wolfgang W Baus
- Klinik für Radioonkologie, CyberKnife- und Strahlentherapie, Universitätsklinikum Köln, Cologne, Germany
| | - Christos Moustakis
- Klinik für Strahlentherapie-Radioonkologie, Universitätsklinikum Münster, Münster, Germany
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Shintani T, Nakamura M, Matsuo Y, Miyabe Y, Mukumoto N, Mitsuyoshi T, Iizuka Y, Mizowaki T. Investigation of 4D dose in volumetric modulated arc therapy-based stereotactic body radiation therapy: does fractional dose or number of arcs matter? JOURNAL OF RADIATION RESEARCH 2020; 61:325-334. [PMID: 32030408 PMCID: PMC7246072 DOI: 10.1093/jrr/rrz103] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 12/05/2019] [Accepted: 01/09/2020] [Indexed: 06/10/2023]
Abstract
The aim of this study was to assess the impact of fractional dose and the number of arcs on interplay effects when volumetric modulated arc therapy (VMAT) is used to treat lung tumors with large respiratory motions. A three (fractional dose of 4, 7.5 or 12.5 Gy) by two (number of arcs, one or two) VMAT plan was created for 10 lung cancer cases. The median 3D tumor motion was 17.9 mm (range: 8.2-27.2 mm). Ten phase-specific subplans were generated by calculating the dose on each respiratory phase computed tomography (CT) scan using temporally assigned VMAT arcs. We performed temporal assignment of VMAT arcs using respiratory information obtained from infrared markers placed on the abdomens of the patients during CT simulations. Each phase-specific dose distribution was deformed onto exhale phase CT scans using contour-based deformable image registration, and a 4D plan was created by dose accumulation. The gross tumor volume dose of each 4D plan (4D GTV dose) was compared with the internal target volume dose of the original plan (3D ITV dose). The near-minimum 4D GTV dose (D99%) was higher than the near-minimum 3D internal target volume (ITV) dose, whereas the near-maximum 4D GTV dose (D1%) was lower than the near-maximum 3D ITV dose. However, the difference was negligible, and thus the 4D GTV dose corresponded well with the 3D ITV dose, regardless of the fractional dose and number of arcs. Therefore, interplay effects were negligible in VMAT-based stereotactic body radiation therapy for lung tumors with large respiratory motions.
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Affiliation(s)
- Takashi Shintani
- Department of Radiation Oncology and Image-applied Therapy, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Mitsuhiro Nakamura
- Department of Radiation Oncology and Image-applied Therapy, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
- Division of Medical Physics, Department of Information Technology and Medical Engineering, Human Health Sciences, Graduate School of Medicine, Kyoto University, 53 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan
| | - Yukinori Matsuo
- Department of Radiation Oncology and Image-applied Therapy, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Yuki Miyabe
- Department of Radiation Oncology and Image-applied Therapy, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Nobutaka Mukumoto
- Department of Radiation Oncology and Image-applied Therapy, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Takamasa Mitsuyoshi
- Department of Radiation Oncology and Image-applied Therapy, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Yusuke Iizuka
- Department of Radiation Oncology and Image-applied Therapy, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
| | - Takashi Mizowaki
- Department of Radiation Oncology and Image-applied Therapy, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto 606-8507, Japan
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12
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Evaluation of Intensity- and Contour-Based Deformable Image Registration Accuracy in Pancreatic Cancer Patients. Cancers (Basel) 2019; 11:cancers11101447. [PMID: 31569617 PMCID: PMC6826682 DOI: 10.3390/cancers11101447] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 09/25/2019] [Accepted: 09/26/2019] [Indexed: 12/15/2022] Open
Abstract
We aimed to clarify the accuracy of rigid image registration and deformable image registration (DIR) in carbon-ion radiotherapy (CIRT) for pancreatic cancer. Six patients with pancreatic cancer who were treated with passive irradiation CIRT were enrolled. Three registration patterns were evaluated: treatment planning computed tomography images (TPCT) to CT images acquired in the treatment room (IRCT) in the supine position, TPCT to IRCT in the prone position, and TPCT in the supine position to the prone position. After warping the contours of the original CT images to the destination CT images using deformation matrices from the registration, the warped delineated contours on the destination CT images were compared with the original ones using mean displacement to agreement (MDA). Four contours (clinical target volume (CTV), gross tumor volume (GTV), stomach, duodenum) and four registration algorithms (rigid image registration [RIR], intensity-based DIR [iDIR], contour-based DIR [cDIR], and a hybrid iDIR-cDIR ([hDIR]) were evaluated. The means ± standard deviation of the MDAs of all contours for RIR, iDIR, cDIR, and hDIR were 3.40 ± 3.30, 2.2 1± 2.48, 1.46 ± 1.49, and 1.46 ± 1.37 mm, respectively. There were significant differences between RIR and iDIR, and between RIR/iDIR and cDIR/hDIR. For the pancreatic cancer patient images, cDIR and hDIR had better accuracy than RIR and iDIR.
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13
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Meschini G, Seregni M, Molinelli S, Vai A, Phillips J, Sharp GC, Pella A, Valvo F, Ciocca M, Riboldi M, Paganetti H, Baroni G. Validation of a model for physical dose variations in irregularly moving targets treated with carbon ion beams. Med Phys 2019; 46:3663-3673. [PMID: 31206718 DOI: 10.1002/mp.13662] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Revised: 06/07/2019] [Accepted: 06/07/2019] [Indexed: 12/14/2022] Open
Abstract
PURPOSE In particle therapy, conventional treatment planning systems rely on an imaging representation of the irradiated region to compute the dose. For irregular breathing, when an imaging dataset describing the actual motion is not available, a different approach for dose estimation is needed. To this aim, we validate a method for the estimation of physical dose variations in gated carbon ion treatments, providing also a demonstration of the feasibility of physical dose metrics to assess the method performance. Finally, we describe a sample use case, in which this method is used to assess plan robustness with respect to undetected irregular tumor motion. METHODS The method entails the definition of a patient- and beam-specific water equivalent depth (WED) space, the simulation of motion as a translation equal to tumor displacement, and the reconstruction of the altered dose. We validated the approach using four-dimensional computed tomographies (4DCTs) and clinical plans in 12 patients, treated with respiratory gated carbon ion beams at the National Centre for Oncological Hadrontherapy (Pavia, Italy). Using the end-exhale CT and dose distribution as a reference, the physical dose delivered at the end-inhale tumor position was estimated and compared to the ground-truth dose recalculation on the end-inhale CT. Biologically effective and physical dose variations between the plan and the recalculation were compared as well. As a use case, we evaluated dose changes caused by simulated irregular tumor motion, that is, linear and nonlinear baseline shifts and/or amplitude variations with hysteresis. RESULTS The ratio between biologically effective and physical equivalent uniform dose (EUD) variations due to end-exhale to end-inhale motion was less than one for 96% of investigated structures. In the validation study, we found a median error corresponding to a 14% EUD overestimation for the tumor and 4% EUD underestimation for a subgroup of organs at risk, together with a high EUD variation due to motion [median 352% EUD variation between end-exhale and end-inhale doses in the planning tumor volume (PTV)]. Considering relevant dose-volume histogram (DVH) metrics, the median difference between estimated and ground truth doses was ≤ 4%. Gamma analysis between estimated and recalculated dose distributions resulted in a pass rate > 80% for 83% of the target volumes. For the two patients selected for the sample use case, a patient-specific assessment of the method performance was performed on the 4DCT and it was possible to relate EUD variations of both tumor and organs at risk to the simulated target motion. CONCLUSIONS The physical dose distribution was found to be more sensitive to motion with respect to the biologically effective one, suggesting the suitability of the physical dose metrics for the WED-space method validation. We showed that the method can compensate for intra-fractional tumor motion with proper accuracy in the selected patient group, although its use is recommended when limited deformations are expected. In conclusion, the WED-space method can provide simulations of dose alteration due to irregular breathing when imaging data are lacking, and, once integrated with relative biological effectiveness (RBE) modeling, it would be useful in evaluating the robustness of carbon ion treatment plans.
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Affiliation(s)
| | | | | | - Alessandro Vai
- Centro Nazionale Adroterapia Oncologica, Pavia, 27100, Italy
| | - Justin Phillips
- Alexian Brothers Medical Center, Elk Grove Village, IL, 60007, USA
| | | | - Andrea Pella
- Centro Nazionale Adroterapia Oncologica, Pavia, 27100, Italy
| | - Francesca Valvo
- Centro Nazionale Adroterapia Oncologica, Pavia, 27100, Italy
| | - Mario Ciocca
- Centro Nazionale Adroterapia Oncologica, Pavia, 27100, Italy
| | - Marco Riboldi
- Ludwig-Maximilians-Universität, Munich, 80539, Germany
| | | | - Guido Baroni
- Politecnico di Milano, Milan, 20133, Italy.,Centro Nazionale Adroterapia Oncologica, Pavia, 27100, Italy
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14
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Werner R, Sentker T, Madesta F, Gauer T, Hofmann C. Intelligent 4D CT sequence scanning (i4DCT): Concept and performance evaluation. Med Phys 2019; 46:3462-3474. [DOI: 10.1002/mp.13632] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Revised: 04/30/2019] [Accepted: 05/22/2019] [Indexed: 12/20/2022] Open
Affiliation(s)
- René Werner
- Department of Computational Neuroscience University Medical Center Hamburg‐Eppendorf 20246Hamburg Germany
| | - Thilo Sentker
- Department of Computational Neuroscience University Medical Center Hamburg‐Eppendorf 20246Hamburg Germany
- Department of Radiotherapy and Radio‐Oncology University Medical Center Hamburg‐Eppendorf 20246Hamburg Germany
| | - Frederic Madesta
- Department of Computational Neuroscience University Medical Center Hamburg‐Eppendorf 20246Hamburg Germany
| | - Tobias Gauer
- Department of Radiotherapy and Radio‐Oncology University Medical Center Hamburg‐Eppendorf 20246Hamburg Germany
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15
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Rigaud B, Simon A, Castelli J, Lafond C, Acosta O, Haigron P, Cazoulat G, de Crevoisier R. Deformable image registration for radiation therapy: principle, methods, applications and evaluation. Acta Oncol 2019; 58:1225-1237. [PMID: 31155990 DOI: 10.1080/0284186x.2019.1620331] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Background: Deformable image registration (DIR) is increasingly used in the field of radiation therapy (RT) to account for anatomical deformations. The aims of this paper are to describe the main applications of DIR in RT and discuss current DIR evaluation methods. Methods: Articles on DIR published from January 2000 to October 2018 were extracted from PubMed and Science Direct. Our search was restricted to articles that report data obtained from humans, were written in English, and address DIR methods for RT. A total of 207 articles were selected from among 2506 identified in the search process. Results: At planning, DIR is used for organ delineation using atlas-based segmentation, deformation-based planning target volume definition, functional planning and magnetic resonance imaging-based dose calculation. In image-guided RT, DIR is used for contour propagation and dose calculation on per-treatment imaging. DIR is also used to determine the accumulated dose from fraction to fraction in external beam RT and brachytherapy, both for dose reporting and adaptive RT. In the case of re-irradiation, DIR can be used to estimate the cumulated dose of the two irradiations. Finally, DIR can be used to predict toxicity in voxel-wise population analysis. However, the evaluation of DIR remains an open issue, especially when dealing with complex cases such as the disappearance of matter. To quantify DIR uncertainties, most evaluation methods are limited to geometry-based metrics. Software companies have now integrated DIR tools into treatment planning systems for clinical use, such as contour propagation and fraction dose accumulation. Conclusions: DIR is increasingly important in RT applications, from planning to toxicity prediction. DIR is routinely used to reduce the workload of contour propagation. However, its use for complex dosimetric applications must be carefully evaluated by combining quantitative and qualitative analyses.
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Affiliation(s)
- Bastien Rigaud
- CLCC Eugène Marquis, University of Rennes, Inserm , Rennes , France
| | - Antoine Simon
- CLCC Eugène Marquis, University of Rennes, Inserm , Rennes , France
| | - Joël Castelli
- CLCC Eugène Marquis, University of Rennes, Inserm , Rennes , France
| | - Caroline Lafond
- CLCC Eugène Marquis, University of Rennes, Inserm , Rennes , France
| | - Oscar Acosta
- CLCC Eugène Marquis, University of Rennes, Inserm , Rennes , France
| | - Pascal Haigron
- CLCC Eugène Marquis, University of Rennes, Inserm , Rennes , France
| | - Guillaume Cazoulat
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center , Houston , TX , USA
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16
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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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