David Fuentes1, Yusheng Feng2, Andrew Elliott1, Anil Shetty1, Roger McNichols3, J Tinsley Oden4, R Jason Stafford1
1Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States; 2The University of Texas at San Antonio; 3BioTex Inc; 4ICES, The University of Texas at Austin
Treatment times of computationally assisted MR guided LITT are determined by the convergence behavior of PDE constrained optimization problems. This work investigates the feasibility of applying real-time bioheat transfer constrained model calibration to patient specific data and rigorously validates model calibrations against MR temperature imaging data. The calibration techniques attempt to adaptively recover the patient specific bio-thermal heterogeneities within the tissue and result in a formidable real time PDE constrained optimization problem. The calibrations are critical to the predictive power of the simulation during therapy which may be further exploited for treatment optimization to maximize the efficiency of the therapy control loop.