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Publication Date

2019-05-01

Availability

UM campus only

Embargo Period

2021-04-30

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PHD)

Department

Biomedical Engineering (Engineering)

Date of Defense

2019-04-08

First Committee Member

Fabrice Manns

Second Committee Member

Nelson Salas

Third Committee Member

Edward Dauer

Fourth Committee Member

Raymond Leveillee

Fifth Committee Member

Weizhao Zhao

Abstract

Microwave ablation (MWA) is an alternative treatment modality for small renal masses that uses electromagnetic energy to cause coagulative necrosis. MWA cannot be considered a standard of care until treatment outcomes are similar to partial nephrectomy. The objective of this dissertation was to characterize MWA in renal tissue in order to optimize MWA as a nephron-sparing treatment. To quantify the effects of system-specific treatment parameters in renal tissue, MWA of ex-vivo and in-vivo porcine kidneys was performed. There was no significant difference between ex-vivo and in-vivo ablation volumes when using the same system, indicating that ex-vivo studies are an acceptable alternative. Comparison of in-vivo ablations induced by two different MWA systems yielded significant differences in ablation results. Therefore, the output power, irradiation time, frequency, antenna design, and energy delivery algorithm all must be considered during MWA in renal tissue. Models of approximated commercial antenna designs were developed and results were compared to experimentally measured values. While the predicted absolute specific absorption rate (SAR) values were higher than measured values, normalized SAR distribution showed good agreement between the models and experiments. The models predicted ablation dimensions within 12% of experimentally measured values for all except one parameter setting. From the simulation results a prototype of a treatment planning algorithm that predicts treatment parameters was developed. This work has laid the foundation for the development of a therapeutic prediction tool that could be used to determine the optimal treatment parameters necessary for safe and reproducible ablations of small renal tumors.

Keywords

microwave ablation; kidney; minimally-invasive; numerical modeling

Available for download on Friday, April 30, 2021

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