Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/148545
Title: HYBRID CRYOSURGERY - RFA TREATMENT : A SIMULATION AND EXPERIMENTAL STUDY
Authors: SHAO YUNLIN
Keywords: Mathematical modeling, Cryosurgery, Radiofrequency ablation, Genetic algorithm, Immersive boundary method, Optimization planning
Issue Date: 28-May-2018
Citation: SHAO YUNLIN (2018-05-28). HYBRID CRYOSURGERY - RFA TREATMENT : A SIMULATION AND EXPERIMENTAL STUDY. ScholarBank@NUS Repository.
Abstract: Both cryosurgery and radiofrequency ablation (RFA) for solid liver tumor treatment are available as minimally invasive procedures that destroy cancer cells. However, one of the critical factors that impedes cryosurgery and RFA’s successful outcomes is the relatively high recurrence rate caused by the inability to ablate a large damaged tissue zone that envelopes targeted tumors, resulting in therapy failure. In this thesis, I am aimed at bringing these thermal therapies’ simulations closer to requirements for clinical use and enhancing its overall therapeutic efficacy. A hybrid cryo-RFA system under thermal stress control is proposed in this study. In addition, genetic algorithm is employed to optimize the position and orientation of the multiple probes required to treat a clinically extracted irregularly-shaped liver tumor. The obtained results can facilitate the understanding of the thermal therapy on liver tumor and provide potential methods to improve the efficacy of RFA/cryosurgery processes.
URI: http://scholarbank.nus.edu.sg/handle/10635/148545
Appears in Collections:Ph.D Theses (Open)

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