Model predictive filtering MR thermometry: Effects of model inaccuracies, k-space reduction factor, and temperature increase rate

Purpose Evaluate effects of model parameter inaccuracies (thermal conductivity, k, and ultrasound power deposition density, Q), k‐space reduction factor (R), and rate of temperature increase ( T˙) in a thermal model‐based reconstruction for MR‐thermometry during focused‐ultrasound heating. Methods Simulations and ex vivo experiments were performed to investigate the accuracy of the thermal model and the model predictive filtering (MPF) algorithm for varying R and T˙, and their sensitivity to errors in k and Q. Ex vivo data was acquired with a segmented EPI pulse sequence to achieve large field‐of‐view (192 × 162 × 96 mm) four‐dimensional temperature maps with high spatiotemporal resolution (1.5 × 1.5 × 2.0 mm, 1.7 s). Results In the simulations, 50% errors in k and Q resulted in maximum temperature root mean square errors (RMSE) of 6°C for model only and 3°C for MPF. Using recently developed methods, estimates of k and Q were accurate to within 3%. The RMSE between MPF and true temperature increased with R and T˙. In the ex vivo study the RMSE remained below 0.7°C for R ranging from 4 to 12 and T˙ of 0.28–0.75°C/s. Conclusion Errors in MPF temperatures occur due to errors in k and Q. These MPF temperature errors increase with increase in R and T˙, but are smaller than those obtained using the thermal model alone. Magn Reson Med 75:207–216, 2016. © 2015 Wiley Periodicals, Inc.