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Adaptive Radiotherapy

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Jan-jakob Sonke – One of the best experts on this subject based on the ideXlab platform.

  • LDeform: Longitudinal deformation analysis for Adaptive Radiotherapy of lung cancer
    Medical physics, 2019
    Co-Authors: Saad Nadeem, Jan-jakob Sonke, Joseph O Deasy, Pengpeng Zhang, Andreas Rimner, Allen Tannenbaum

    Abstract:

    Purpose Conventional Radiotherapy for large lung tumors is given over several weeks, during which the tumor typically regresses in a highly nonuniform and variable manner. Adaptive Radiotherapy would ideally follow these shape changes, but we need an accurate method to extrapolate tumor shape changes. We propose a computationally efficient algorithm to quantitate tumor surface shape changes that makes minimal assumptions, identifies fixed points, and can be used to predict future tumor geometrical response. Methods A novel combination of nonrigid iterative closest point (ICP) and local shape-preserving map algorithms, LDeform, is developed to enable visualization, prediction, and categorization of both diffeomorphic and nondiffeomorphic tumor deformations during an extended course of Radiotherapy. Results We tested and validated our technique on 31 longitudinal CT/MRI subjects, with five to nine time points each. Based on this tumor deformation analysis, regions of local growth, shrinkage, and anchoring are identified and tracked across multiple time points. This categorization in turn represents a rational biomarker of local response. Results demonstrate useful predictive power, with an averaged Dice coefficient and surface mean-squared error of 0.85 and 2.8 mm, respectively, over all images. Conclusions We conclude that the LDeform algorithm can facilitate the Adaptive decision-making process during lung cancer Radiotherapy.

  • Adaptive Radiotherapy for anatomical changes
    Seminars in radiation oncology, 2019
    Co-Authors: Jan-jakob Sonke, Marianne C. Aznar, Coen R. N. Rasch

    Abstract:

    The anatomy of cancer patients changes between radiation treatment planning and delivery as well as over the course of Radiotherapy. Adaptive Radiotherapy (ART) aims to deliver radiation accurately and precisely in the presence of such changes. To that end, ART uses an imaging feedback loop to quantify these changes and modify the treatment plan accordingly. This paper provides an overview of anatomical changes occurring over the course of therapy and various Adaptive strategies developed to account for those. Moreover, residual uncertainties present in Adaptive Radiotherapy are discussed as well as required tools, potential pitfalls and remaining challenges.

  • magnetic resonance guided Adaptive Radiotherapy a solution to the future
    Seminars in Radiation Oncology, 2014
    Co-Authors: Patrick A Kupelian, Jan-jakob Sonke

    Abstract:

    Magnetic resonance imaging–guided Adaptive Radiotherapy would make available the best in anatomical and functional imaging during the course of radiation therapy. The possible methodology of magnetic resonance imaging–guided adapted Radiotherapy and possible clinical applications are discussed.

Hans Theodor Eich – One of the best experts on this subject based on the ideXlab platform.

  • Primary Cardiac Angiosarcoma Treated With Positron Emission Tomography/Magnetic Resonance Imaging-Guided Adaptive Radiotherapy.
    The Canadian journal of cardiology, 2015
    Co-Authors: Khaled Elsayad, Philipp Lehrich, Heidi Yppaerilae-wolters, Chantal Dieckmann, Jan Kriz, Uwe Haverkamp, Hans Theodor Eich

    Abstract:

    Radiotherapy (RT) for inoperable patients with primary cardiac sarcomas or residual tumor is often limited by the sensitivity of the heart and lung to radiation injury. We describe a novel treatment modality with Adaptive Radiotherapy (ART) using tumor volume tracking in a 37-year-old woman who presented with unresectable primary cardiac angiosarcoma. The patient was treated using positron emission tomography/magnetic resonance imaging-guided ART with 55.8 Gy concomitant with paclitaxel chemotherapy. In conclusion, the treatment was well tolerated, and a significant tumor volume reduction of ∼ 57% was achieved during Radiotherapy, suggesting the effectiveness and tolerability of ART in combination with paclitaxel-based chemotherapy.

  • Primary Cardiac Angiosarcoma Treated With Positron Emission Tomography/Magnetic Resonance Imaging–Guided Adaptive Radiotherapy
    Canadian Journal of Cardiology, 2015
    Co-Authors: Khaled Elsayad, Philipp Lehrich, Heidi Yppaerilae-wolters, Chantal Dieckmann, Jan Kriz, Uwe Haverkamp, Hans Theodor Eich

    Abstract:

    Radiotherapy (RT) for inoperable patients with primary cardiac sarcomas or residual tumor is often limited by the sensitivity of the heart and lung to radiation injury. We describe a novel treatment modality with Adaptive Radiotherapy (ART) using tumor volume tracking in a 37-year-old woman who presented with unresectable primary cardiac angiosarcoma. The patient was treated using positron emission tomography/magnetic resonance imaging-guided ART with 55.8 Gy concomitant with paclitaxel chemotherapy. In conclusion, the treatment was well tolerated, and a significant tumor volume reduction of ∼ 57% was achieved during Radiotherapy, suggesting the effectiveness and tolerability of ART in combination with paclitaxel-based chemotherapy.

D Yang – One of the best experts on this subject based on the ideXlab platform.

  • A practical implementation of physics quality assurance for photon Adaptive Radiotherapy.
    Zeitschrift fur medizinische Physik, 2018
    Co-Authors: Bin Cai, S Mutic, Olga Green, Rojano Kashani, Vivian Rodriguez, D Yang

    Abstract:

    Abstract The fast evolution of technology in Radiotherapy (RT) enabled the realization of Adaptive Radiotherapy (ART). However, the new characteristics of ART pose unique challenges for efficiencies and effectiveness of quality assurance (QA) strategies. In this paper, we discuss the necessary QAs for ART and introduce a practical implementation. A previously published work on failure modes and effects analysis (FMEA) of ART is introduced first to explain the risks associated with ART sub-processes. After a brief discussion of QA challenges, we review the existing QA strategies and tools that might be suitable for each ART step. By introducing the MR-guided online ART QA processes developed at our institute, we demonstrate a practical implementation. The limitations and future works to develop more robust and efficient QA strategies are discussed at the end.

  • technical note dirart a software suite for deformable image registration and Adaptive Radiotherapy research
    Medical Physics, 2010
    Co-Authors: D Yang, Issam El Naqa, S Brame, Apte Aditya, Murty S Goddu, S Mutic, Joseph O Deasy, D Low

    Abstract:

    Purpose: Recent years have witnessed tremendous progress in image guide Radiotherapy technology and a growing interest in the possibilities for adapting treatment planning and delivery over the course of treatment. One obstacle faced by the research community has been the lack of a comprehensive open-source software toolkit dedicated for Adaptive Radiotherapy (ART). To address this need, the authors have developed a software suite called the Deformable Image Registration and Adaptive Radiotherapy Toolkit (DIRART). Methods: DIRART is an open-source toolkit developed in MATLAB. It is designed in an object-oriented style with focus on user-friendliness, features, and flexibility. It contains four classes of DIR algorithms, including the newer inverse consistency algorithms to provide consistent displacement vector field in both directions. It also contains common ART functions, an integrated graphical user interface, a variety of visualization and image-processing features, dose metric analysis functions, and interface routines. These interface routines make DIRART a powerful complement to the Computational Environment for Radiotherapy Research (CERR) and popular image-processing toolkits such as ITK. Results :DIRART provides a set of image processing/registration algorithms and postprocessing functions to facilitate the development and testing of DIR algorithms. It also offers a good amount of options for DIR results visualization, evaluation, and validation. Conclusions : By exchanging data with treatment planning systems via DICOM-RT files andCERR, and by bringing image registration algorithms closer to Radiotherapy applications, DIRART is potentially a convenient and flexible platform that may facilitate ART and DIR research.

  • Technical Note: DIRART – A software suite for deformable image registration and Adaptive Radiotherapy research
    Medical physics, 2010
    Co-Authors: D Yang, Issam El Naqa, S Brame, Apte Aditya, S Mutic, Joseph O Deasy, S. Murty Goddu, Daniel A. Low

    Abstract:

    Purpose: Recent years have witnessed tremendous progress in image guide Radiotherapy technology and a growing interest in the possibilities for adapting treatment planning and delivery over the course of treatment. One obstacle faced by the research community has been the lack of a comprehensive open-source software toolkit dedicated for Adaptive Radiotherapy (ART). To address this need, the authors have developed a software suite called the Deformable Image Registration and Adaptive Radiotherapy Toolkit (DIRART). Methods: DIRART is an open-source toolkit developed in MATLAB. It is designed in an object-oriented style with focus on user-friendliness, features, and flexibility. It contains four classes of DIR algorithms, including the newer inverse consistency algorithms to provide consistent displacement vector field in both directions. It also contains common ART functions, an integrated graphical user interface, a variety of visualization and image-processing features, dose metric analysis functions, and interface routines. These interface routines make DIRART a powerful complement to the Computational Environment for Radiotherapy Research (CERR) and popular image-processing toolkits such as ITK. Results :DIRART provides a set of image processing/registration algorithms and postprocessing functions to facilitate the development and testing of DIR algorithms. It also offers a good amount of options for DIR results visualization, evaluation, and validation. Conclusions : By exchanging data with treatment planning systems via DICOM-RT files andCERR, and by bringing image registration algorithms closer to Radiotherapy applications, DIRART is potentially a convenient and flexible platform that may facilitate ART and DIR research.