Robotic ultrasound image guidance for radiation therapy

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Abstract/Contents

Abstract
External Beam Radiation Therapy (EBRT) is used in the disease management of more than half of all cancer patients. In order to improve clinical EBRT outcomes, highly conformal, potent ablative doses must be delivered to maximize local tumor control and minimize toxicity to surrounding healthy tissue. Random and quasi-periodical anatomy motion during beam delivery poses a fundamental threat to realizing such conformality, and thus restricts the curative potential of EBRT. We address this problem in the development and evaluation of a novel robotic ultrasound guidance system that integrates with existing medical linear accelerators (LINACs), enabling real-time, volumetric, non-invasive, non-ionizing, markerless tracking of soft tissue targets during radiation delivery. Major challenges in the deployment of robotic ultrasound guidance for radiotherapy include image acquisition, image calibration, tissue tracking, and treatment planning. For image acquisition, we first present a novel robotic manipulator designed to perform two-dimensional (2D) prostate ultrasound imaging while minimizing interferences with the radiation delivery system. A second, more generalized robotic manipulator is then presented, designed for 3D ultrasound imaging of multiple abdominal sites. We demonstrate stable remote ultrasound image acquisition with each robot over extended time periods in volunteers. Ultrasound image calibration is required to reconstruct image data in the LINAC frame for treatment guidance. We develop a method for 3D ultrasound spatial calibration based on intra-modality image registration that can be performed using any ultrasound imaging phantom, and characterize the method using a novel validation metric. We also present a new method for temporal synchronization of ultrasound images that leverages ultrasound probe motions generated by the robotic manipulator. Using calibrated 2D ultrasound images, we next describe a technique for monitoring real-time prostate displacements. Two image-based parameters were used to detect in-plane and out-of-plane displacements relative to an initial target position. With 95% confidence, the proposed method detected in-vivo prostate displacements before they exceeded 2.3, 2.5, and 2.8 mm in anteroposterior, superoinferior, and mediolateral directions. Given that typical prostate treatment margins are 5 mm, this technique showed significant promise for margin reduction and reduced healthy tissue toxicity relative to existing guidance techniques. In certain imaging positions, the robotic manipulator and ultrasound probe can interfere with radiation beams. To account for this, we developed a software environment that enables 3D visualization of image guidance hardware and radiation beams during treatment planning. With aid from the software, we re-planned treatments for prostate and liver cancer patients while avoiding interfering beam directions, and showed that clinically-deployed plans and plans with restricted sectors are similar. With reduced dose margins, as enabled by real-time imaging, gross tumor volume coverage was nearly identical while notable reductions of healthy tissue volumes exposed to large doses were possible. Our work demonstrates the feasibility of robotic ultrasound guidance for radiation therapy, and shows promise for the delivery of highly conformal cancer treatments that are truly adaptive to the continuous changes of internal anatomy.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2013
Issuance monographic
Language English

Creators/Contributors

Associated with Schlosser, Jeffrey Steven
Associated with Stanford University, Department of Mechanical Engineering.
Primary advisor Hristov, Dimitre H, 1966-
Primary advisor Salisbury, J. Kenneth
Thesis advisor Hristov, Dimitre H, 1966-
Thesis advisor Salisbury, J. Kenneth
Thesis advisor Pelc, Norbert J
Advisor Pelc, Norbert J

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Jeffrey Steven Schlosser.
Note Submitted to the Department of Mechanical Engineering.
Thesis Thesis (Ph.D.)--Stanford University, 2013.
Location electronic resource

Access conditions

Copyright
© 2013 by Jeffrey Steven Schlosser
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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