Magnetic resonance imaging and model prediction for thermal ablation of tissue.

PURPOSE: To monitor and predict tissue temperature distributions and lesion boundaries during thermal ablation by combining MRI and thermal modeling methods.

MATERIALS AND METHODS: Radiofrequency (RF) ablation was conducted in the paraspinal muscles of rabbits with MRI monitoring. A gradient-recalled echo (GRE) sequence via a 1.5T MRI system provided tissue temperature distribution from the phase images and lesion progression from changes in magnitude images. Post-ablation GRE estimates of lesion size were compared with post-ablation T2-weighted turbo-spin-echo (TSE) images and hematoxylin and eosin (H&E)-stained histological slices. A three-dimensional (3D) thermal model was used to simulate and predict tissue temperature and lesion size dynamics.

RESULTS: The lesion area estimated from repeated GRE images remained constant during the post-heating period when the temperature of the lesion boundary was less than a critical temperature. The final lesion areas estimated from multi-slice (M/S) GRE, TSE, and histological slices were not statistically different. The model-simulated tissue temperature distribution and lesion area closely corresponded to the GRE-based MR measurements throughout the imaging experiment.

CONCLUSION: For normal tissue in vivo, the dynamics of tissue temperature distribution and lesion size during RF thermal ablation can be 1) monitored with GRE phase and magnitude images, and 2) simulated for prediction with a thermal model.