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[I185] MRI for radiotherapy treatment planning
Abstracts / Physica Medica 52 (2018) 1–98
monitoring should include morphological, functional, metabolic and targeted molecular imaging as an integrative part. Oncologic MR imaging is accordingly challenged to improve and further develop novel concepts for precise tumor delineation and characterization. Significant progress has been achieved in morphologic-functional MRI and PET/MR, which have the potential to improve the delineation of target volumes and to adapt the dose to selected subvolumes. But integration of multiparametric MR imaging data into individual radiotherapy planning, guidance and control is still challenging. Improved IT concepts for precise spatial coregistration of multimodal morphologic and functional imaging data as well as for integration of complex imaging data into the radiotherapy process including quality control are required. Concerning imaging, hardware integration of PET and MRI (PET/MR) has proved to improve spatial coregistration of morphologic and biologic/functional imaging information. For use of imaging to improve daily radiotherapy planning and guidance hardware integration of MRI and linear accelerators (MR/Linac) are currently under development. The presentation will outline the potentials, challenges and limitations of MR and PET/MR imaging for modern radiotherapy. https://doi.org/10.1016/j.ejmp.2018.06.256
[I185] MRI for radiotherapy treatment planning Uulke van der Heide * The Netherlands Cancer Institute, Amsterdam, Radiation Oncology, Amsterdam, Netherlands ⇑ Corresponding author. MRI is used increasingly in radiotherapy to improve the accuracy of target delineation and to characterize relevant properties of the cancer. For dose calculation however, electron density information is usually obtained from CT images. As a consequence, image registration of MRI and CT is necessary. This results in a complex workflow that is a burden for the patient and may introduce inaccuracies in the treatment. An MR-only workflow, based entirely on MRI is therefore advocated, where all images necessary for preparation of a treatment plan are generated in a single exam. Several methods have been published to derive the electron densities from MR images. One option is to aply deformable registration of a template CT scan to the MRI of the patient, to create a patient-specific map of the Hounsfield units. Alternatively, Hounsfield units are derived directly from a combination of MR images via some model. Hybrid methods, combining autosegmentation of structures and Dixon MRI images separating water and fat are also available. To obtain an entirely automatic workflow, the target volume needs to be segmented from the MRI. Autocontouring software for this purpose is increasingly available. To make full use of the differential capacity of radiotherapy, multiparametric images can be combined to form tumor probability maps. For prostate cancer, we showed that dose mapping functions can be used to convert tumor probability into a voxel by voxel dose prescription. This concept allows generation of a dose painting treatment plan. In this presentation, the potential and challenges to create a fully automated workflow based on MR images only, will be shown. https://doi.org/10.1016/j.ejmp.2018.06.257
[I186] New technologies for MR guided radiotherapy Cornelius van den Berg * Umc Utrecht, Center for Image Sciences, Utrecht, Netherlands
⇑
71
Corresponding author.
Purpose. Provide an overview of technological developments in MR guided Radiotherapy. The key concept in MR guided Radiotherapy (MRgRT) is that the soft tissue contrast allows direct visualization of the tumor and organs-at-risk [1]. In this way an optimal plan can be devised for the actual position, shape and motion characteristics of a patient for a given treatment fraction. In the last decade the engineering challenges for the integration of such complex systems have been overcome. Currently, a new phase in technology development is commencing where advances in rapid dose planning, computer vision and especially MRI technology are enabling new treatment options. In this talk will give an overview on the technological developments in MRgRT with a special focus on innovations on MRI technologies. High on the Wishlist has always been fast 3D volumetric imaging to capture respiratory induced motion. New generation radiolucent, dense receive arrays are under development that offer much greater imaging speed. In addition, they can be placed directly on the body for improved signal-to-noise with minimal skin dose. Another area of active development is image reconstruction. Techniques such as self-navigated golden angle radial scanning techniques in combination with compressed sensing are employed for motion characterization (4D MRI) and motion tracking. A disadvantage of compressed sensing reconstruction is the large computation time that hinders real-time usage. Therefore, the combination of motion models updated by multiple 2D imaging has been explored for real time 3D motion tracking. A more recent development is the use of deep learning based image reconstruction as an alternative to compressed sensing. Once trained in an offline setting, the forward evaluation of the trained deep neural network can be very fast (<300 ms). In general, deep learning applied to MR (functional) image information holds great promise for MRgRT with applications in synthetic CT generation for dose planning, auto-contouring and tumor response monitoring. Conclusion. MRgRT is an exciting field where MRI meets Radiotherapy. Recent advances in general MRI technology and computer vision are being adopted and adapted for MRgRT to enable new treatments options. Reference [1] Raaymakers et al.. Phys. Med. Biol. 2017;62(23):L41–50. https://doi.org/10.1016/j.ejmp.2018.06.258
[OA187] Transfer of minibeam radiation therapy into a costeffective equipment: A proof of concept Yolanda Prezado a,*, Morgane Dos Santos b, Wilfredo Gonzalez a, Gregory Jouvion c, Consuelo Guardiola a, Sophie Heinrich d, dalila Labiod d, Marjorie Juchaux a, Laurene Jourdain e, Catherine Sebrié e, Frederic Pouzoulet d a Centre National de la Recherche Scientifique, Imagerie et Modelisation Pour la Neurobiologie et la Cancerologie, New Approaches in Radiotherapy, Orsay, France b Irsn, Laboratoire de Radiobiologie des Expositions Accidentelles (Lracc), Fontanay Aux Roses, France c Institut Pasteur, Laboratoire D’histopathologie, Paris, France d Institut Curie, Experimental Radiotherapy Platform, Orsay, France e Imagerie Par Résonance Magnétique Médicale et Multi-Modalités (Umr8081) Ir4m, Cnrs-University Paris Sud, Orsay, France ⇑ Corresponding author.
monitoring should include morphological, functional, metabolic and targeted molecular imaging as an integrative part. Oncologic MR imaging is accordingly challenged to improve and further develop novel concepts for precise tumor delineation and characterization. Significant progress has been achieved in morphologic-functional MRI and PET/MR, which have the potential to improve the delineation of target volumes and to adapt the dose to selected subvolumes. But integration of multiparametric MR imaging data into individual radiotherapy planning, guidance and control is still challenging. Improved IT concepts for precise spatial coregistration of multimodal morphologic and functional imaging data as well as for integration of complex imaging data into the radiotherapy process including quality control are required. Concerning imaging, hardware integration of PET and MRI (PET/MR) has proved to improve spatial coregistration of morphologic and biologic/functional imaging information. For use of imaging to improve daily radiotherapy planning and guidance hardware integration of MRI and linear accelerators (MR/Linac) are currently under development. The presentation will outline the potentials, challenges and limitations of MR and PET/MR imaging for modern radiotherapy. https://doi.org/10.1016/j.ejmp.2018.06.256
[I185] MRI for radiotherapy treatment planning Uulke van der Heide * The Netherlands Cancer Institute, Amsterdam, Radiation Oncology, Amsterdam, Netherlands ⇑ Corresponding author. MRI is used increasingly in radiotherapy to improve the accuracy of target delineation and to characterize relevant properties of the cancer. For dose calculation however, electron density information is usually obtained from CT images. As a consequence, image registration of MRI and CT is necessary. This results in a complex workflow that is a burden for the patient and may introduce inaccuracies in the treatment. An MR-only workflow, based entirely on MRI is therefore advocated, where all images necessary for preparation of a treatment plan are generated in a single exam. Several methods have been published to derive the electron densities from MR images. One option is to aply deformable registration of a template CT scan to the MRI of the patient, to create a patient-specific map of the Hounsfield units. Alternatively, Hounsfield units are derived directly from a combination of MR images via some model. Hybrid methods, combining autosegmentation of structures and Dixon MRI images separating water and fat are also available. To obtain an entirely automatic workflow, the target volume needs to be segmented from the MRI. Autocontouring software for this purpose is increasingly available. To make full use of the differential capacity of radiotherapy, multiparametric images can be combined to form tumor probability maps. For prostate cancer, we showed that dose mapping functions can be used to convert tumor probability into a voxel by voxel dose prescription. This concept allows generation of a dose painting treatment plan. In this presentation, the potential and challenges to create a fully automated workflow based on MR images only, will be shown. https://doi.org/10.1016/j.ejmp.2018.06.257
[I186] New technologies for MR guided radiotherapy Cornelius van den Berg * Umc Utrecht, Center for Image Sciences, Utrecht, Netherlands
⇑
71
Corresponding author.
Purpose. Provide an overview of technological developments in MR guided Radiotherapy. The key concept in MR guided Radiotherapy (MRgRT) is that the soft tissue contrast allows direct visualization of the tumor and organs-at-risk [1]. In this way an optimal plan can be devised for the actual position, shape and motion characteristics of a patient for a given treatment fraction. In the last decade the engineering challenges for the integration of such complex systems have been overcome. Currently, a new phase in technology development is commencing where advances in rapid dose planning, computer vision and especially MRI technology are enabling new treatment options. In this talk will give an overview on the technological developments in MRgRT with a special focus on innovations on MRI technologies. High on the Wishlist has always been fast 3D volumetric imaging to capture respiratory induced motion. New generation radiolucent, dense receive arrays are under development that offer much greater imaging speed. In addition, they can be placed directly on the body for improved signal-to-noise with minimal skin dose. Another area of active development is image reconstruction. Techniques such as self-navigated golden angle radial scanning techniques in combination with compressed sensing are employed for motion characterization (4D MRI) and motion tracking. A disadvantage of compressed sensing reconstruction is the large computation time that hinders real-time usage. Therefore, the combination of motion models updated by multiple 2D imaging has been explored for real time 3D motion tracking. A more recent development is the use of deep learning based image reconstruction as an alternative to compressed sensing. Once trained in an offline setting, the forward evaluation of the trained deep neural network can be very fast (<300 ms). In general, deep learning applied to MR (functional) image information holds great promise for MRgRT with applications in synthetic CT generation for dose planning, auto-contouring and tumor response monitoring. Conclusion. MRgRT is an exciting field where MRI meets Radiotherapy. Recent advances in general MRI technology and computer vision are being adopted and adapted for MRgRT to enable new treatments options. Reference [1] Raaymakers et al.. Phys. Med. Biol. 2017;62(23):L41–50. https://doi.org/10.1016/j.ejmp.2018.06.258
[OA187] Transfer of minibeam radiation therapy into a costeffective equipment: A proof of concept Yolanda Prezado a,*, Morgane Dos Santos b, Wilfredo Gonzalez a, Gregory Jouvion c, Consuelo Guardiola a, Sophie Heinrich d, dalila Labiod d, Marjorie Juchaux a, Laurene Jourdain e, Catherine Sebrié e, Frederic Pouzoulet d a Centre National de la Recherche Scientifique, Imagerie et Modelisation Pour la Neurobiologie et la Cancerologie, New Approaches in Radiotherapy, Orsay, France b Irsn, Laboratoire de Radiobiologie des Expositions Accidentelles (Lracc), Fontanay Aux Roses, France c Institut Pasteur, Laboratoire D’histopathologie, Paris, France d Institut Curie, Experimental Radiotherapy Platform, Orsay, France e Imagerie Par Résonance Magnétique Médicale et Multi-Modalités (Umr8081) Ir4m, Cnrs-University Paris Sud, Orsay, France ⇑ Corresponding author.