4D Modeling and Estimation of Respiratory Motion for Radiation Therapy

1. Front Matter

   Pages i-xx

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2. Introduction to 4D Motion Modeling and 4D Radiotherapy

   • Paul Keall, Tokihiro Yamamoto, Yelin Suh

   Pages 1-21

3. 4D Image Acquisition

   1. Front Matter

      Pages 23-23

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   2. Helical 4D CT and Comparison with Cine 4D CT

      • Tinsu Pan

      Pages 25-41

   3. Acquiring 4D Thoracic CT Scans Using Ciné CT Acquisition

      • Daniel Low

      Pages 43-58

4. Motion Estimation and Modeling

   1. Front Matter

      Pages 59-59

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   2. Biophysical Modeling of Respiratory Organ Motion

      • René Werner

      Pages 61-84

   3. Feature-Based Registration Techniques

      • Cristian Lorenz, Tobias Klinder, Jens von Berg

      Pages 85-102

   4. Intensity-Based Deformable Registration: Introduction and Overview

      • David Sarrut, Jef Vandemeulebroucke, Simon Rit

      Pages 103-124

   5. Intensity-Based Registration for Lung Motion Estimation

      • Kunlin Cao, Kai Ding, Ryan E. Amelon, Kaifang Du, Joseph M. Reinhardt, Madhavan L. Raghavan et al.

      Pages 125-158

   6. Validation and Comparison of Approaches to Respiratory Motion Estimation

      • Sven Kabus, Tobias Klinder, Keelin Murphy, René Werner, David Sarrut

      Pages 159-183

5. Modeling of Motion Variability

   1. Front Matter

      Pages 185-185

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   2. Estimating Internal Respiratory Motion from Respiratory Surrogate Signals Using Correspondence Models

      • Jamie McClelland

      Pages 187-213

   3. Computational Motion Phantoms and Statistical Models of Respiratory Motion

      • Jan Ehrhardt, Tobias Klinder, Cristian Lorenz

      Pages 215-247

6. Applications of Motion Estimation Algorithms

   1. Front Matter

      Pages 249-249

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   2. 4-Dimensional Imaging for Radiation Oncology: A Clinical Perspective

      • Max Dahele, Suresh Senan

      Pages 251-284

   3. Respiratory Motion Prediction in Radiation Therapy

      • Sastry Vedam

      Pages 285-296

   4. Estimation of Lung Ventilation

      • Kai Ding, Kunlin Cao, Kaifang Du, Ryan Amelon, Gary E. Christensen, Madhavan Raghavan et al.

      Pages 297-317

   5. Respiratory Motion Correction in Cone-Beam CT for Image-Guided Radiotherapy

      • Simon Rit, David Sarrut, Jan-Jakob Sonke

      Pages 319-334

7. Back Matter

   Pages 335-341

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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.

• 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

From the reviews:

“This book provides a very welcome one-stop reference on the subject. … each chapter is painstakingly referenced and the end-of-chapter reference sections are extensive. … The book seems predominantly aimed at engineers, physicists and researchers. … The book is most useful as a reference for many different staff groups, and as such would be a valuable addition to any medical physics and engineering departmental bookshelf.” (Mark Worrall, Scope, Vol. 23 (2), June, 2014)

“This is an in-depth review of advanced topics in 4D imaging and modeling of respiratory motion. … The equation derivations are particularly helpful to researchers and students trying to understand the basic principles. … The authors demonstrate a thorough knowledge of 4D imaging and modeling of respiratory motion. The chapters are well structured and contain a wealth of detailed and timely information.” (Jing Cai, Doody’s Book Reviews, March, 2014)

• , Institut für Medizinische Informatik, Universität Lübeck, Lübeck, Germany

  Jan Ehrhardt

• Forschungslaboratorien, Digital Imaging 24, Philips Technologie GmbH, Hamburg, Germany

  Cristian Lorenz

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