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Proceedings Paper

A mechanically coupled reaction diffusion model of breast tumor response during neoadjuvant chemotherapy
Author(s): Jared A. Weis; Michael I. Miga; Xia Li; Lori R. Arlinghaus; A. Bapsi Chakravarthy; Vandana Abramson; Richard G. Abramson; Jaime Farley; Thomas E. Yankeelov
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Paper Abstract

There is currently a paucity of reliable techniques for predicting the response of breast tumors to neoadjuvant chemotherapy. The standard approach is to monitor gross changes in tumor size as measured by physical exam and/or conventional imaging, but these methods generally do not show whether a tumor is responding until the patient has completed therapy. One promising approach to address this clinical need is to integrate quantitative in vivo imaging data into biomathematical models of tumor growth in order to predict eventual response based on early measurements during therapy. Contrast enhanced and diffusion weighted magnetic resonance imaging data acquired before and after the first cycle of therapy to calibrate a patient-specific response model can be used to predict patient outcome at the conclusion of therapy. We have developed a mathematical modeling approach to optimize key model parameters for the calibration of a patient-specific mechanically coupled reaction-diffusion model of response. We apply the approach to patient data in which tumors were either responsive or non-responsive to neoajuvant chemotherapy and demonstrate changes to the patient-specific model which result in altered growth patterns. Additionally, we show that reconstructed parameter maps exhibit drastic differences between patients with different tumor burden outcomes at the conclusion of therapy, in this case, a 10-fold increase in proliferative capacity is found for a non-responding tumor versus its responsive counterpart. Finally, we show that the mechanically coupled reaction-diffusion growth model, when projected forward, more accurately predicts residual tumor burden than the uncoupled model.

Paper Details

Date Published: 29 March 2013
PDF: 7 pages
Proc. SPIE 8672, Medical Imaging 2013: Biomedical Applications in Molecular, Structural, and Functional Imaging, 86721G (29 March 2013); doi: 10.1117/12.2007961
Show Author Affiliations
Jared A. Weis, Vanderbilt Univ. (United States)
Michael I. Miga, Vanderbilt Univ. (United States)
Xia Li, Vanderbilt Univ. (United States)
Lori R. Arlinghaus, Vanderbilt Univ. (United States)
A. Bapsi Chakravarthy, Vanderbilt Univ. (United States)
Vandana Abramson, Vanderbilt Univ. (United States)
Richard G. Abramson, Vanderbilt Univ. (United States)
Jaime Farley, Vanderbilt Univ. (United States)
Thomas E. Yankeelov, Vanderbilt Univ. (United States)


Published in SPIE Proceedings Vol. 8672:
Medical Imaging 2013: Biomedical Applications in Molecular, Structural, and Functional Imaging
John B. Weaver; Robert C. Molthen, Editor(s)

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