In vivo validation of spatio-temporal liver motion prediction from motion tracked on MR thermometry images.

PURPOSE: Magnetic resonance-guided focused ultrasound (MRgFUS) of the liver during free-breathing requires spatio-temporal prediction of the liver motion from partial motion observations. The study purpose is to evaluate the prediction accuracy for a realistic MRgFUS therapy scenario, namely for human in vivo data, tracking based on MR images routinely acquired during MRgFUS and in vivo deformations caused by the FUS probe. METHODS: In vivo validation of the motion model was based on a 3D breath-hold image and an interleaved acquisition of two MR slices. Prediction accuracy was determined with respect to manually annotated landmarks. A statistical population liver motion model was used for predicting the liver motion for not tracked regions. This model was individualized by mapping it to end-exhale 3D breath-hold images. Spatial correspondence between tracking and model positions was established by affine 3D-to-2D image registration. For spatio-temporal prediction, MR tracking results were temporally extrapolated. RESULTS: Performance was evaluated for 10 volunteers, of which 5 had a dummy FUS probe put on their abdomen. MR tracking had a mean (95 %) accuracy of 1.1 (2.4) mm. The motion of the liver on the evaluation MR slice was spatio-temporally predicted with an accuracy of 1.9 (4.4) mm for a latency of 216 ms. A simple translation model performed similarly (2.1 (4.8) mm) as the two MR slices were relatively close (mean 38 mm). Temporal prediction was important (10 % error reduction), while registration effects could only partially be assessed and showed no benefits. On average, motion magnitude, motion amplitude and breathing frequency increased by 24, 16 and 8 %, respectively, for the cases with FUS probe placement. This motion increase could be reduced by the spatio-temporal prediction. CONCLUSION: The study shows that tracking liver vessels on MR images, which are also used for MR thermometry, is a viable approach.

Fast Estimation of the Vascular Cooling in RFA Based on Numerical Simulation.

We present a novel technique to predict the outcome of an RF ablation, including the vascular cooling effect. The main idea is to separate the problem into a patient independent part, which has to be performed only once for every applicator model and generator setting, and a patient dependent part, which can be performed very fast. The patient independent part fills a look-up table of the cooling effects of blood vessels, depending on the vessel radius and the distance of the RF applicator from the vessel, using a numerical simulation of the ablation process. The patient dependent part, on the other hand, only consists of a number of table look-up processes. The paper presents this main idea, along with the required steps for its implementation. First results of the computation and the related ex-vivo evaluation are presented and discussed. The paper concludes with future extensions and improvements of the approach.