Automatic Iceball Segmentation with Adapted Shape Priors for MRI-guided Cryoablation.


Xinyang Liu, Kemal Tuncali, William M Wells III, and Gary P. Zientara. 2015. “Automatic Iceball Segmentation with Adapted Shape Priors for MRI-guided Cryoablation.” J Magn Reson Imaging, 41, 2, Pp. 517-24. Copy at


PURPOSE: To develop and evaluate an automatic segmentation method that extracts the 3D configuration of the ablation zone, the iceball, from images acquired during the freezing phase of MRI-guided cryoablation. MATERIALS AND METHODS: Intraprocedural images at 63 timepoints from 13 kidney tumor cryoablation procedures were examined retrospectively. The images were obtained using a 3 Tesla wide-bore MRI scanner and axial HASTE sequence. Initialized with semiautomatically localized cryoprobes, the iceball was segmented automatically at each timepoint using the graph cut (GC) technique with adapted shape priors. RESULTS: The average Dice Similarity Coefficients (DSC), compared with manual segmentations, were 0.88, 0.92, 0.92, 0.93, and 0.93 at 3, 6, 9, 12, and 15 min timepoints, respectively, and the average DSC of the total 63 segmentations was 0.92 ± 0.03. The proposed method improved the accuracy significantly compared with the approach without shape prior adaptation (P = 0.026). The number of probes involved in the procedure had no apparent influence on the segmentation results using our technique. The average computation time was 20 s, which was compatible with an intraprocedural setting. CONCLUSION: Our automatic iceball segmentation method demonstrated high accuracy and robustness for practical use in monitoring the progress of MRI-guided cryoablation.

Last updated on 11/02/2017