Date of Graduation

12-2016

Document Type

Dissertation (PhD)

Program Affiliation

Medical Physics

Degree Name

Doctor of Philosophy (PhD)

Advisor/Committee Chair

R. Jason Stafford

Committee Member

James A. Bankson

Committee Member

John D. Hazle

Committee Member

Marites Melancon

Committee Member

Arvind Rao

Abstract

Magnetic Resonance Temperature Imaging (MRTI) is a powerful technique for noninvasively monitoring temperature during minimally invasive thermal therapy procedures. When coupled with thermal dose models, MRTI feedback provides the clinician with a real-time estimate of tissue damage by functioning as a surrogate for post-treatment verification imaging. This aids in maximizing the safety and efficacy of treatment by facilitating adaptive control of the damaged volume during therapy. The underlying thermal dose parameters are derived from laboratory experiments that do not necessarily reflect the surrogate imaging endpoints used for treatment verification. Thus, there is interest and opportunity in deriving model parameters from clinical procedures that are tailored to radiologic endpoints.

The objective of this work is to develop and investigate the feasibility of a methodology for extracting thermal dose model parameters from MR data acquired during ablation procedures. To this end, two approaches are investigated. One is to optimize model parameters using post-treatment imaging outcomes. Another is to use a multi-parametric pulse sequence designed for simultaneous monitoring of temperature and damage dependent MR parameters. These methodologies were developed and investigated in phantom and feasibility established using retrospective analysis of in vivo thermal therapy treatments. This technique represents an opportunity to exploit experimental data to obtain thermal dose parameters that are highly specific for clinically relevant endpoints.

Keywords

Magnetic Resonance Imaging, Thermal Dose Modeling, Thermal Ablation, Laser Ablation, Arrhenius Parameters, Thermal Damage

Available for download on Saturday, November 18, 2017

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