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Proceedings Paper

Modeling and simulation of tumor-influenced high resolution real-time physics-based breast models for model-guided robotic interventions
Author(s): John Neylon; Katelyn Hasse; Ke Sheng; Anand P. Santhanam
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Paper Abstract

Breast radiation therapy is typically delivered to the patient in either supine or prone position. Each of these positioning systems has its limitations in terms of tumor localization, dose to the surrounding normal structures, and patient comfort. We envision developing a pneumatically controlled breast immobilization device that will enable the benefits of both supine and prone positioning. In this paper, we present a physics-based breast deformable model that aids in both the design of the breast immobilization device as well as a control module for the device during every day positioning. The model geometry is generated from a subject’s CT scan acquired during the treatment planning stage. A GPU based deformable model is then generated for the breast. A mass-spring-damper approach is then employed for the deformable model, with the spring modeled to represent a hyperelastic tissue behavior. Each voxel of the CT scan is then associated with a mass element, which gives the model its high resolution nature. The subject specific elasticity is then estimated from a CT scan in prone position. Our results show that the model can deform at >60 deformations per second, which satisfies the real-time requirement for robotic positioning. The model interacts with a computer designed immobilization device to position the breast and tumor anatomy in a reproducible location. The design of the immobilization device was also systematically varied based on the breast geometry, tumor location, elasticity distribution and the reproducibility of the desired tumor location.

Paper Details

Date Published: 18 March 2016
PDF: 10 pages
Proc. SPIE 9786, Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling, 97860X (18 March 2016); doi: 10.1117/12.2217028
Show Author Affiliations
John Neylon, Univ. of California, Los Angeles (United States)
Katelyn Hasse, Univ. of California, Los Angeles (United States)
Ke Sheng, Univ. of California, Los Angeles (United States)
Anand P. Santhanam, Univ. of California, Los Angeles (United States)

Published in SPIE Proceedings Vol. 9786:
Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling
Robert J. Webster III; Ziv R. Yaniv, Editor(s)

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