Ebook: 4D Modeling and Estimation of Respiratory Motion for Radiation Therapy

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.

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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.

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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.
Content:
Front Matter....Pages i-xx
Front Matter....Pages 23-23
Helical 4D CT and Comparison with Cine 4D CT....Pages 25-41
Acquiring 4D Thoracic CT Scans Using Cin? CT Acquisition....Pages 43-58
Front Matter....Pages 59-59
Biophysical Modeling of Respiratory Organ Motion....Pages 61-84
Feature-Based Registration Techniques....Pages 85-102
Intensity-Based Deformable Registration: Introduction and Overview....Pages 103-124
Intensity-Based Registration for Lung Motion Estimation....Pages 125-158
Validation and Comparison of Approaches to Respiratory Motion Estimation....Pages 159-183
Front Matter....Pages 185-185
Estimating Internal Respiratory Motion from Respiratory Surrogate Signals Using Correspondence Models....Pages 187-213
Computational Motion Phantoms and Statistical Models of Respiratory Motion....Pages 215-247
Front Matter....Pages 249-249
4-Dimensional Imaging for Radiation Oncology: A Clinical Perspective....Pages 251-284
Respiratory Motion Prediction in Radiation Therapy....Pages 285-296
Estimation of Lung Ventilation....Pages 297-317
Respiratory Motion Correction in Cone-Beam CT for Image-Guided Radiotherapy....Pages 319-334
Introduction to 4D Motion Modeling and 4D Radiotherapy....Pages 1-21
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.
Content:
Front Matter....Pages i-xx
Front Matter....Pages 23-23
Helical 4D CT and Comparison with Cine 4D CT....Pages 25-41
Acquiring 4D Thoracic CT Scans Using Cin? CT Acquisition....Pages 43-58
Front Matter....Pages 59-59
Biophysical Modeling of Respiratory Organ Motion....Pages 61-84
Feature-Based Registration Techniques....Pages 85-102
Intensity-Based Deformable Registration: Introduction and Overview....Pages 103-124
Intensity-Based Registration for Lung Motion Estimation....Pages 125-158
Validation and Comparison of Approaches to Respiratory Motion Estimation....Pages 159-183
Front Matter....Pages 185-185
Estimating Internal Respiratory Motion from Respiratory Surrogate Signals Using Correspondence Models....Pages 187-213
Computational Motion Phantoms and Statistical Models of Respiratory Motion....Pages 215-247
Front Matter....Pages 249-249
4-Dimensional Imaging for Radiation Oncology: A Clinical Perspective....Pages 251-284
Respiratory Motion Prediction in Radiation Therapy....Pages 285-296
Estimation of Lung Ventilation....Pages 297-317
Respiratory Motion Correction in Cone-Beam CT for Image-Guided Radiotherapy....Pages 319-334
Introduction to 4D Motion Modeling and 4D Radiotherapy....Pages 1-21
Back Matter....Pages 335-341
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