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.