Thermal analysis of induced damage to the healthy cell during RFA of breast tumor. (May 2016)

• Record Type: Journal Article
• Authors: Singh, Sundeep; Bhowmik, Arka; Repaka, Ramjee
• Is Part Of: Journal of thermal biology. Volume 58(2015)
• Page Start: 80
• Page End: 90
• Publication Date: 2016-05
• Subjects: Pre-clinical modeling -- Radiofrequency ablation -- Breast cancer -- Finite element analysis -- Bioheat equation; Thermobiology -- Periodicals; Temperature -- Periodicals; Biology -- Periodicals; Thermobiologie -- Périodiques; Thermobiology; Periodicals; 571.46
• DOI: 10.1016/j.jtherbio.2016.04.002
• Languages: English
• ISSNs: 0306-4565

Abstract

Abstract: Effective pre-clinical computational modeling strategies have been demonstrated in this article to enable risk free clinical application of radiofrequency ablation (RFA) of breast tumor. The present study (a) determines various optimal regulating parameters required for RFA of tumor and (b) introduces an essential clinical monitoring scheme to minimize the extent of damage to the healthy cell during RFA of tumor. The therapeutic capabilities offered by RFA of breast tumor, viz., the rise in local temperature and induced thermal damage have been predicted by integrating the bioheat transfer model, the electric field distribution model and the thermal damage model. The mathematical model has been validated with the experimental results available in the literature. The results revealed that, the effective damage of tumor volume sparing healthy tissue essentially depends on the voltage, the exposure time, the local heat distribution, the tumor stage and the electrode geometric configuration. It has been confirmed that, the assessment of damage front can accurately determine the extent of damage as compared to the thermal front. The study further evaluates the damaged healthy and tumor volumes due to RFA of different stages of breast cancer. The assessment of cell survival and damage fractions discloses the propensity of reappearance/healing of tumor cells after treatment. Graphical abstract: Highlights: Pre-clinical computational modeling strategies are proposed to enable risk free RFA of breast tumor. Essential regulating parameters are optimized and its effect on the extent of damage is predicted. Introduced measurable monitoring parameters for better control of in-vivo damages. Likelihood of healing of damaged tumor after the treatment is quantified.