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Title: Online Adaptive Radiation Therapy

Abstract

The current paradigm of radiation therapy has the treatment planned on a snapshot dataset of the patient's anatomy taken at the time of simulation. Throughout the course of treatment, this snapshot may vary from initial simulation. Although there is the ability to image patients within the treatment room with technologies such as cone beam computed tomography, the current state of the art is largely limited to rigid-body matching and not accounting for any geometric deformations in the patient's anatomy. A plan that was once attuned to the initial simulation can become suboptimal as the treatment progresses unless improved technologies are brought to bear. Adaptive radiation therapy (ART) is an evolving paradigm that seeks to address this deficiency by accounting for ongoing changes in the patient's anatomy and/or physiology during the course of treatment, affording an increasingly more accurate targeting of disease. ART relies on several components working in concert, namely in-room treatment image guidance, deformable image registration, automatic recontouring, plan evaluation and reoptimization, dose calculation, and quality assurance. Various studies have explored how a putative ART solution would improve the current state of the art of radiation therapy—some centers have even clinically implemented online adaptation. These explorations are reviewed heremore » for a variety of sites.« less

Authors:
 [1];  [1];  [2];  [1];  [1];  [2];  [1];  [2]
  1. Sunnybrook Health Sciences Centre/Odette Cancer Centre, Toronto, Ontario (Canada)
  2. (Canada)
Publication Date:
OSTI Identifier:
22723047
Resource Type:
Journal Article
Journal Name:
International Journal of Radiation Oncology, Biology and Physics
Additional Journal Information:
Journal Volume: 99; Journal Issue: 4; Other Information: Copyright (c) 2017 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0360-3016
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; COMPUTERIZED TOMOGRAPHY; IMAGE PROCESSING; PATIENTS; RADIATION DOSES; RADIOTHERAPY; SIMULATION

Citation Formats

Lim-Reinders, Stephanie, Keller, Brian M., Department of Radiation Oncology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Al-Ward, Shahad, Sahgal, Arjun, Department of Radiation Oncology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Kim, Anthony, and Department of Radiation Oncology, Faculty of Medicine, University of Toronto, Toronto, Ontario. Online Adaptive Radiation Therapy. United States: N. p., 2017. Web. doi:10.1016/J.IJROBP.2017.04.023.
Lim-Reinders, Stephanie, Keller, Brian M., Department of Radiation Oncology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Al-Ward, Shahad, Sahgal, Arjun, Department of Radiation Oncology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Kim, Anthony, & Department of Radiation Oncology, Faculty of Medicine, University of Toronto, Toronto, Ontario. Online Adaptive Radiation Therapy. United States. doi:10.1016/J.IJROBP.2017.04.023.
Lim-Reinders, Stephanie, Keller, Brian M., Department of Radiation Oncology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Al-Ward, Shahad, Sahgal, Arjun, Department of Radiation Oncology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Kim, Anthony, and Department of Radiation Oncology, Faculty of Medicine, University of Toronto, Toronto, Ontario. Wed . "Online Adaptive Radiation Therapy". United States. doi:10.1016/J.IJROBP.2017.04.023.
@article{osti_22723047,
title = {Online Adaptive Radiation Therapy},
author = {Lim-Reinders, Stephanie and Keller, Brian M. and Department of Radiation Oncology, Faculty of Medicine, University of Toronto, Toronto, Ontario and Al-Ward, Shahad and Sahgal, Arjun and Department of Radiation Oncology, Faculty of Medicine, University of Toronto, Toronto, Ontario and Kim, Anthony and Department of Radiation Oncology, Faculty of Medicine, University of Toronto, Toronto, Ontario},
abstractNote = {The current paradigm of radiation therapy has the treatment planned on a snapshot dataset of the patient's anatomy taken at the time of simulation. Throughout the course of treatment, this snapshot may vary from initial simulation. Although there is the ability to image patients within the treatment room with technologies such as cone beam computed tomography, the current state of the art is largely limited to rigid-body matching and not accounting for any geometric deformations in the patient's anatomy. A plan that was once attuned to the initial simulation can become suboptimal as the treatment progresses unless improved technologies are brought to bear. Adaptive radiation therapy (ART) is an evolving paradigm that seeks to address this deficiency by accounting for ongoing changes in the patient's anatomy and/or physiology during the course of treatment, affording an increasingly more accurate targeting of disease. ART relies on several components working in concert, namely in-room treatment image guidance, deformable image registration, automatic recontouring, plan evaluation and reoptimization, dose calculation, and quality assurance. Various studies have explored how a putative ART solution would improve the current state of the art of radiation therapy—some centers have even clinically implemented online adaptation. These explorations are reviewed here for a variety of sites.},
doi = {10.1016/J.IJROBP.2017.04.023},
journal = {International Journal of Radiation Oncology, Biology and Physics},
issn = {0360-3016},
number = 4,
volume = 99,
place = {United States},
year = {2017},
month = {11}
}