Automatic model-based evaluation of magnetic resonance-guided radio frequency ablation lesions with histological correlation
✍ Scribed by Roee S. Lazebnik; Michael S. Breen; Jonathan S. Lewin; David L. Wilson
- Publisher
- John Wiley and Sons
- Year
- 2004
- Tongue
- English
- Weight
- 592 KB
- Volume
- 19
- Category
- Article
- ISSN
- 1053-1807
No coin nor oath required. For personal study only.
✦ Synopsis
Abstract
Purpose
To develop a model‐based method for automatic evaluation of radio frequency (RF) ablation treatment using magnetic resonance (MR) images.
Materials and Methods
RF current lesions were generated in a rabbit thigh model using MR imaging (MRI) guidance. We created a 12‐parameter, three‐dimensional, globally deformable model with quadric surfaces that delineates lesion boundaries and is automatically fitted to MR grayscale data. We applied this method to in vivo T~2~‐ and contrast‐enhanced (CE) T~1~‐weighted MR images acquired immediately post‐ablation and four days later. We then compared results to manually segmented MR and three‐dimensional registered corresponding histological boundaries of cellular damage.
Results
Resulting lesions featured a two‐boundary appearance with an inner region and an outer hyperintense margin on MR images. For automated vs. manual MR boundaries, the mean errors over all specimens were 0.19 ± 0.51 mm and 0.27 ± 0.52 mm for the inner surface, and −0.29 ± 0.40 mm and −0.12 ± 0.17 mm for the outer surface, for T~2~‐ and CE T~1~‐weighted images, respectively. For automated vs. histological boundaries, mean errors over all specimens were 0.07 ± 0.64 mm and 0.33 ± 0.71 mm for the inner surface, and −0.27 ± 0.69 mm and 0.02 ± 0.43 mm for the outer surface, for T~2~‐ and CE T~1~‐weighted images, respectively. All boundary errors compared favorably to MR voxel dimensions, which were 0.7 mm in‐plane and 3.0 mm thick.
Conclusion
The method is accurate both in describing MR‐apparent boundaries and in predicting histological response and has applications in lesion visualization, volume estimation, and treatment evaluation. J. Magn. Reson. Imaging 2004;19:245–254. © 2004 Wiley‐Liss, Inc.