TY - JOUR
T1 - Optimization and real-time control for laser treatment of heterogeneous soft tissues
AU - Feng, Yusheng
AU - Fuentes, David
AU - Hawkins, Andrea
AU - Bass, Jon M.
AU - Rylander, Marissa Nichole
N1 - Funding Information:
As Prof. Oden’s current and former students, and former post-doctoral fellow, we are deeply grateful for his encouragement, guidance, leadership and active involvement in this new endeavor of computational cancer research. Also, we would like to acknowledge that the work reviewed in this article reflects a fruitful collaboration of a multidisciplinary team, which is led by Prof. Oden and consists of K.R. Diller, J. Hazle, J.C. Browne, I. Babuška, L. Bidaut, L. Demkowicz, C. Bajaj, A. Elliott, J. Zhang, S. Goswami, S. Khoshnevis, S. Prudhomme, R.J. Stafford,and A. Shetty, from the University of Texas at Austin and M.D. Anderson Cancer Center in Houston. Finally, the support of this work by the National Science Foundation under Grant CNS-0540033 and the National Institutes of Health under Grant 7K25CA116291-02 (YF) are gratefully acknowledged.
PY - 2009/5/1
Y1 - 2009/5/1
N2 - Predicting the outcome of thermotherapies in cancer treatment requires an accurate characterization of the bioheat transfer processes in soft tissues. Due to the biological and structural complexity of tumor (soft tissue) composition and vasculature, it is often very difficult to obtain reliable tissue properties that is one of the key factors for the accurate treatment outcome prediction. Efficient algorithms employing in vivo thermal measurements to determine heterogeneous thermal tissues properties in conjunction with a detailed sensitivity analysis can produce essential information for model development and optimal control. The goals of this paper are to present a general formulation of the bioheat transfer equation for heterogeneous soft tissues, review models and algorithms developed for cell damage, heat shock proteins, and soft tissues with nanoparticle inclusion, and demonstrate an overall computational strategy for developing a laser treatment framework with the ability to perform real-time robust calibrations and optimal control. This computational strategy can be applied to other thermotherapies using the heat source such as radio frequency or high intensity focused ultrasound.
AB - Predicting the outcome of thermotherapies in cancer treatment requires an accurate characterization of the bioheat transfer processes in soft tissues. Due to the biological and structural complexity of tumor (soft tissue) composition and vasculature, it is often very difficult to obtain reliable tissue properties that is one of the key factors for the accurate treatment outcome prediction. Efficient algorithms employing in vivo thermal measurements to determine heterogeneous thermal tissues properties in conjunction with a detailed sensitivity analysis can produce essential information for model development and optimal control. The goals of this paper are to present a general formulation of the bioheat transfer equation for heterogeneous soft tissues, review models and algorithms developed for cell damage, heat shock proteins, and soft tissues with nanoparticle inclusion, and demonstrate an overall computational strategy for developing a laser treatment framework with the ability to perform real-time robust calibrations and optimal control. This computational strategy can be applied to other thermotherapies using the heat source such as radio frequency or high intensity focused ultrasound.
KW - Bioheat transfer model
KW - Nanoparticle inclusion
KW - Nonlinearity
KW - Parallel computing
KW - Parameter estimation
KW - Soft tissue properties
UR - http://www.scopus.com/inward/record.url?scp=63249091312&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=63249091312&partnerID=8YFLogxK
U2 - 10.1016/j.cma.2008.12.027
DO - 10.1016/j.cma.2008.12.027
M3 - Article
C2 - 20485457
AN - SCOPUS:63249091312
SN - 0045-7825
VL - 198
SP - 1742
EP - 1750
JO - Computer Methods in Applied Mechanics and Engineering
JF - Computer Methods in Applied Mechanics and Engineering
IS - 21-26
ER -