Estimation of saline-mixed tissue conductivity and ablation lesion size
- Authors
- Park, Joong Yull; Park, Chan Young; Lee, Jeong Min
- Issue Date
- Jun-2013
- Publisher
- PERGAMON-ELSEVIER SCIENCE LTD
- Keywords
- Radiofrequency ablation; Effective conductivity; Electrical conductivity; Thermal conductivity
- Citation
- COMPUTERS IN BIOLOGY AND MEDICINE, v.43, no.5, pp 504 - 512
- Pages
- 9
- Journal Title
- COMPUTERS IN BIOLOGY AND MEDICINE
- Volume
- 43
- Number
- 5
- Start Page
- 504
- End Page
- 512
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/14550
- DOI
- 10.1016/j.compbiomed.2013.02.012
- ISSN
- 0010-4825
1879-0534
- Abstract
- In radiofrequency ablation (RFA), saline infusion is beneficial for enhancing electrical conductivity, which allows more energy dissipation into target tissue, resulting in increased lesion size. Computational simulation has been a popular method to estimate lesion size from RFA treatment, but it has not been used effectively for saline-infused RFA, for lack of methods to address the conductivity properties of saline-tissue mixtures. To fill this gap, we propose a microscopic mixture model to derive the effective temperature-dependent conductivities of a saline-tissue mixture. We modeled a small block of 6% hypertonic saline-infused liver tissue as a 1 x 1 x 1 cm cube, which was divided into 64-1000 elements, with each element representing either liver tissue or saline. A 1:1 mixing of saline and liver tissue was assumed to calculate the effective conductivities at 30, 50, 70, and 90 degrees C. Different mixing conditions (2:1 and 1:2 of saline to liver tissue) were also tested to observe the effect of mixing ratio on the resulting data. Then, the derived conductivities were applied for 3D hypertonic saline-infused RFA simulation. The results matched our previous experimental measurements within 13%. The proposed model is customizable in constructing mixtures of multiple components, and can thus be expanded to include the effects of various anatomical microstructures and materials. (C) 2013 Elsevier Ltd. All rights reserved.
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Collections - College of Engineering > School of Mechanical Engineering > 1. Journal Articles
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