4D Modeling and Estimation of Respiratory Motion for Radiation Therapy

  • Jan Ehrhardt
  • Cristian Lorenz

Part of the Biological and Medical Physics, Biomedical Engineering book series (BIOMEDICAL)

Table of contents

  1. Front Matter
    Pages i-xx
  2. Paul Keall, Tokihiro Yamamoto, Yelin Suh
    Pages 1-21
  3. 4D Image Acquisition

    1. Front Matter
      Pages 23-23
  4. Motion Estimation and Modeling

    1. Front Matter
      Pages 59-59
    2. Cristian Lorenz, Tobias Klinder, Jens von Berg
      Pages 85-102
    3. David Sarrut, Jef Vandemeulebroucke, Simon Rit
      Pages 103-124
    4. Kunlin Cao, Kai Ding, Ryan E. Amelon, Kaifang Du, Joseph M. Reinhardt, Madhavan L. Raghavan et al.
      Pages 125-158
    5. Sven Kabus, Tobias Klinder, Keelin Murphy, René Werner, David Sarrut
      Pages 159-183
  5. Modeling of Motion Variability

    1. Front Matter
      Pages 185-185
    2. Jan Ehrhardt, Tobias Klinder, Cristian Lorenz
      Pages 215-247
  6. Applications of Motion Estimation Algorithms

    1. Front Matter
      Pages 249-249
    2. Kai Ding, Kunlin Cao, Kaifang Du, Ryan Amelon, Gary E. Christensen, Madhavan Raghavan et al.
      Pages 297-317
    3. Simon Rit, David Sarrut, Jan-Jakob Sonke
      Pages 319-334
  7. Back Matter
    Pages 335-341

About this book

Introduction

Respiratory motion causes an important uncertainty in radiotherapy planning of the thorax and upper abdomen. The main objective of radiation therapy is to eradicate or shrink tumor cells without damaging the surrounding tissue by delivering a high radiation dose to the tumor region and a dose as low as possible to healthy organ tissues. Meeting this demand remains a challenge especially in case of lung tumors due to breathing-induced tumor and organ motion where motion amplitudes can measure up to several centimeters. Therefore, modeling of respiratory motion has become increasingly important in radiation therapy. With 4D imaging techniques spatiotemporal image sequences can be acquired to investigate dynamic processes in the patient’s body. Furthermore, image registration enables the estimation of the breathing-induced motion and the description of the temporal change in position and shape of the structures of interest by establishing the correspondence between images acquired at different phases of the breathing cycle. In radiation therapy these motion estimations are used to define accurate treatment margins, e.g. to calculate dose distributions and to develop prediction models for gated or robotic radiotherapy. In this book, the increasing role of image registration and motion estimation algorithms for the interpretation of complex 4D medical image sequences is illustrated. Different 4D CT image acquisition techniques and conceptually different motion estimation algorithms are presented. The clinical relevance is demonstrated by means of example applications which are related to the radiation therapy of thoracic and abdominal tumors. The state of the art and perspectives are shown by an insight into the current field of research. The book is addressed to biomedical engineers, medical physicists, researchers and physicians working in the fields of medical image analysis, radiology and radiation therapy.

Keywords

4D CT image acquisition techniques 4D CT imaging 4D dose distributions 4D medical image sequences biophysical modeling of respiratory motion deformable registration image processing and computer vision lung and tumor motion modeling of respiratory motion motion estimation algorithms pulmonary motion respiratory motion estimation

Editors and affiliations

  • Jan Ehrhardt
    • 1
  • Cristian Lorenz
    • 2
  1. 1., Institut für Medizinische InformatikUniversität LübeckLübeckGermany
  2. 2.Forschungslaboratorien, Digital Imaging 24Philips Technologie GmbHHamburgGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-36441-9
  • Copyright Information Springer-Verlag Berlin Heidelberg 2013
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Physics and Astronomy
  • Print ISBN 978-3-642-36440-2
  • Online ISBN 978-3-642-36441-9
  • Series Print ISSN 1618-7210
  • About this book