Clinical hyperthermia refers to treatment of tumors by heating the lesions between 40 and 45° C. Several clinical trials have demonstrated that hyperthermia provides significant improvements in clinical outcomes for a variety of tumors, especially when combined with radiotherapy. However, its routine clinical application is still not optimal and major improvements are needed. The temperature distributions achieved are far from satisfactory and improved temperature control and monitoring are still in need of further development.
The use of gold nanoparticles (GNPs) has emerged as a good method to achieve local heat delivery when combined with near-infrared (NIR) laser. GNPs have a plasmon resonance frequency that can be tuned to absorb strongly in the NIR region where tissue absorption of laser light is minimal, allowing for less tissue heating and better penetration. For further development of the technique and appropriate clinical translation, it is essential to have a computational method by which the temperature distribution within the tumor and surrounding tissue can be estimated. Previously, our group developed a technique to estimate the temperature increase in a GNP-filled medium, by taking into account the heat generated from individual GNPs. This method involved a two-step approach combining the temperature rise due to GNPs and the solution to the heat equation using the laser light as heat source. The goal of this project was to develop a one-step approach that calculates the temperature distribution using the solution to the heat equation with multiple heat source terms, the laser light, and each individual GNP. This new method can be of great use in
developing a treatment planning technique for GNP-mediated thermal therapy including hyperthermia.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/45966 |
| Date | 18 November 2011 |
| Creators | Reynoso, Francisco J. |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Thesis |
Page generated in 0.002 seconds