Model predictive filtering MR thermometry: Effects of model inaccuracies, k‐space reduction factor, and temperature increase rate. Issue 1 (25th February 2015) - Odéen, Henrik; Todd, Nick; Dillon, Christopher; Payne, Allison; Parker, Dennis L.
Abstract : 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.