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Computational Bio-Heat Transfer and Image-Guided Real-Time Control in Thermotherapeutic Cancer Treatment

Yusheng Feng, Associate Professor
The University of Texas at San Antonio


Advances in computational science and engineering have shown unprecedented power and potential to assist cancer biologist, oncologist, radiologists, and surgeon by providing advanced computational tools for scientific exploration and clinical applications such as model-based treatment outcome prediction and image-guided control in real-time. We have demonstrated, in collaboration with M.D. Anderson Cancer Center and UT Austin, that MR temperature imaging (MRTI) guided laser therapy can be modulated by predictive real-time control on in vivo K-9 prostate with high precision. In this talk, I will address the main idea and general computational infrastructure, and discuss how this predictive computational tool can be used for investigating cellular and tissue response to thermal therapy, as well as applications in treatment planning and surgical control. I will also discuss our latest effort in tumor growing modeling for prognosis study. In addition, I will give an overview for newly developed bio-heat transfer formulation using mixture theory. \ \ About the Speaker: Prof. Feng received his Ph.D. in Computational Mechanics from the University of Texas at Austin in 1995. He has two Masters degrees in Mechanical Engineering and Applied Mathematics. After he obtained his Ph.D. degree, Dr. Feng worked in industry for seven years before he returned to academia in 2002. Since then, he was an Assistant professor of Mathematics at Concordia University and Research Fellow at the Institute for Computational Engineering and Sciences (ICES) at the University of Texas at Austin. His research work focuses on computational biomechanics and bioheat transfer, mathematical modeling of cell viability and heat shock protein expressions, computational algorithms for image-guided laser therapy for prostate cancer, treatment planning and real time control, and nano-particle mediated thermal therapy simulation. He joined the faculty of the University of Texas at San Antonio in 2007 as an Associate Professor and the Director of Computational Bioengineering and Control Lab, where expanded his research to computer simulations for RF ablation of liver cancer, immunotherapeutic treatments, and tumor growth. Dr. Feng is a recipient of the NIH/NCI K25 career award for his work on integrative modeling of image-guided cancer treatment simulation.

Thursday, January 27, 2011
11:00AM AP&M 2402