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Image-Guided High-Precision Radiotherapy Esther G. C. Troost Editor 123 Image-Guided High-Precision Radiotherapy Esther G. C. Troost Editor Image-Guided High-Precision Radiotherapy Editor Esther G. C. Troost, MD, PhD Department of Radiotherapy and Radiation Oncology Faculty of Medicine and University Hospital Carl Gustav Carus Dresden, Sachsen, Germany ISBN 978-3-031-08600-7 ISBN 978-3-031-08601-4 (eBook) https://doi.org/10.1007/978-3-031-08601-4 © Springer Nature Switzerland AG 2022 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. 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This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Preface Radiation therapy is one of the pillars of oncological treatment. As opposed to sur- gery, external beam radiation therapy requires the indirect depiction of the tumour and its surrounding structures both during the phase of treatment planning and during fractionated treatment. Historically, only pretreatment imaging was available and served as basis for the entire course of treatment, irrespective of anatomical changes caused, e.g. by tumour response or by patient’s weight loss. During the last 15 years, advances in the field of image-guided radiotherapy have been dramatic. Anatomical and functional imaging is available prior to and during the course of treatment, occasionally even during the treatment fraction. Novel, tumour type-specific radionuclides have been developed for positron emission tomography (PET) and enable depiction of small tumour deposits, which would otherwise have been overlooked. Fast, highly precise radiation therapy techniques enable the treatment of small lesions. Linear accelerators integrated with magnetic resonance imaging (MRI) have revolutionized the field since they facilitate online real-time image-guided radiation dose delivery of moving soft-tissue targets. Herewith, safety margins compensating for repeat patient positioning and target motion can be reduced or even abolished, thus reducing dose to normal tissues and hopefully subsequent side effects. This book provides the reader with an overview of the value of PET with widely available as well as more exclusive, tumour-specific for radiation treatment planning. In-room equipment for online positioning on the linear accelerator is summa- rized and radiation treatment techniques relying on those imaging possibilities are explained to experts outside the field of radiotherapy. Moreover, the value of MRI for soft-tissue tumours both during the phase of target volume delineation for treatment planning as well as during MR-LINAC treatments is focused on. Brachytherapy of several tumours, such as prostate and gynaecological tumours, heavily depends on MRI, also this is exemplified in one of the chapters. The ample possibilities of ultrasonography for image-guidance are furthermore referred to. In those tumours not well visible on imaging, the use of fiducial markers may play a role—this is described for oesophageal and prostate cancer. Lastly, the use of artificial intelligence, multimodal imaging for prediction of tumour control as well as of normal- tissue side effects are topics of the remaining three chapters. v vi Preface Together with the authors of the different chapters, I hope that this book will be of value to residents and senior physicians in the fields of radiotherapy, radiology, and nuclear, as well as to the physicists and radiation technologists of the respective disciplines. Dresden, Sachsen, Germany Esther G. C. Troost April 2022 Contents Part I Target Volume Definition 1 Use of [18F]FDG PET/CT for Target Volume Definition in Radiotherapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Hanneke E. E. Pouw, Dennis Vriens, Floris H. P. van Velden, and Lioe-Fee de Geus-Oei 2 Specific PET Tracers for Solid Tumors and for Definition of the Biological Target Volume . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Constantin Lapa, Ken Herrmann, and Esther G. C. Troost 3 Use of Anatomical and Functional MRI in Radiation Treatment Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 Angela Romano, Luca Boldrini, Antonio Piras, and Vincenzo Valentini Part II Image-Guided Radiation Therapy Techniques 4 In-Room Systems for Patient Positioning and Motion Control . . . . . . 91 Patrick Wohlfahrt and Sonja Schellhammer 5 IMRT/VMAT-SABR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Pablo Carrasco de Fez and Núria Jornet 6 Magnetic Resonance-Guided Adaptive Radiotherapy: Technical Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 Sara Hackett, Bram van Asselen, Marielle Philippens, Simon Woodings, and Jochem Wolthaus 7 MR-Integrated Linear Accelerators: First Clinical Results . . . . . . . . . 159 Olga Pen, Borna Maraghechi, Lauren Henke, and Olga Green 8 Image-Guided Adaptive Brachytherapy . . . . . . . . . . . . . . . . . . . . . . . . . 179 Bradley Pieters and Taran Paulsen-Hellebust vii viii Contents 9 Ultrasonography in Image-Guided Radiotherapy: Current Status and Future Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . 201 Davide Fontanarosa, Emma Harris, Alex Grimwood, Saskia Camps, Maria Antico, Erika Cavanagh, and Chris Edwards 10 Means for Target Volume Delineation and Stabilisation: Fiducial Markers, Balloons and Others . . . . . . . . . . . . . . . . . . . . . . . . . 221 Ben G. L. Vanneste, Oleksandr Boychak, Marianne Nordsmark, and Lone Hoffmann 11 Artificial Intelligence in Radiation Oncology: A Rapidly Evolving Picture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249 Harini Veeraraghavan and Joseph O. Deasy Part III Outcome Evaluation 12 Multi-Modality Imaging for Prediction of Tumor Control Following Radiotherapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271 Daniela Thorwarth 13 Modelling for Radiation Treatment Outcome . . . . . . . . . . . . . . . . . . . . 285 Almut Dutz, Alex Zwanenburg, Johannes A. Langendijk, and Steffen Löck Part I Target Volume Definition Use of [18F]FDG PET/CT for Target 1 Volume Definition in Radiotherapy Hanneke E. E. Pouw, Dennis Vriens, Floris H. P. van Velden, and Lioe-Fee de Geus-Oei Abbreviations ATLAAS Automatic decision Tree-based Learning Algorithm for Advanced Segmentation ATP Adenosine-5′-TriPhosphate CT X-ray Computed Tomography CTAC (low dose) CT performed for Attenuation- and scatter Correction of the PET-image H. E. E. Pouw (*) Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center (LUMC), Leiden, The Netherlands HollandPTC, Delft, The Netherlands Department of Medical Oncology, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands e-mail: [email protected] D. Vriens Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center (LUMC), Leiden, The Netherlands HollandPTC, Delft, The Netherlands e-mail: [email protected] F. H. P. van Velden Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center (LUMC), Leiden, The Netherlands e-mail: [email protected] L.-F. de Geus-Oei Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center (LUMC), Leiden, The Netherlands Biomedical Photonic Imaging Group, University of Twente, Enschede, The Netherlands e-mail: [email protected] © Springer Nature Switzerland AG 2022 3 E. G. C. Troost (ed.), Image-Guided High-Precision Radiotherapy, https://doi.org/10.1007/978-3-031-08601-4_1