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A computational theoretical model for radiofrequency ablation of tumor with complex vascularization.

Authors :
Shao YL
Arjun B
Leo HL
Chua KJ
Source :
Computers in biology and medicine [Comput Biol Med] 2017 Oct 01; Vol. 89, pp. 282-292. Date of Electronic Publication: 2017 Aug 24.
Publication Year :
2017

Abstract

Radiofrequency ablation (RFA) for liver tumors is a minimally invasive procedure that uses electrical energy and heat to destroy cancer cells. One of the critical factors that impedes its successful outcome is the thermal heat sink effects from complex vascular systems that give rise to incomplete destruction of the target tumor tissue, resulting in therapy failure. To better understand the thermal influence of the complex vascular system during RFA, this work proposes the employment of two 3D fractal tree-like branched networks to investigate which key factors of the tree-like vascular system impact heating process. A three-dimensional finite difference analysis is employed to simulate the RFA treatment. Based on the data acquired from the measured experiments, the simulated results derived from combining the Pennes bioheat model and the boundary condition-enforced immersed boundary method (IBM) have demonstrated close agreement with experimental data with a maximum discrepancy of ±8.3%. We employed the orthogonal design approach to analyze 3 factors, namely, the blood vessel's volume, the average distance between probe center and the blood vessel system and the number of the selected part's branches at three different levels. Results have revealed that the distance between RFA probe and blood vessel plays a major role during the heating process compared with the other two factors. In addition, both the ablating rates and the volume of damaged tissue are slightly reduced with increasing number of blood vessel branches.<br /> (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Details

Language :
English
ISSN :
1879-0534
Volume :
89
Database :
MEDLINE
Journal :
Computers in biology and medicine
Publication Type :
Academic Journal
Accession number :
28858644
Full Text :
https://doi.org/10.1016/j.compbiomed.2017.08.025