DOI
https://doi.org/10.25772/H5NQ-A050
Defense Date
2013
Document Type
Dissertation
Degree Name
Doctor of Philosophy
Department
Medical Physics
First Advisor
Andrei Pugachev
Abstract
Purpose: This dissertation focuses on establishment of pre-clinical methods facilitating the use of PET imaging for selective sub-volume dose escalation. Specifically the problems addressed are 1.) The difficulties associated with comparing multiple PET images, 2.) The need for further validation of novel PET tracers before their implementation in dose escalation schema and 3.) The lack of concrete pre-clinical data supporting the use of PET images for guidance of selective sub-volume dose escalations. Methods and materials: In order to compare multiple PET images the confounding effects of mispositioning and anatomical change between imaging sessions needed to be alleviated. To mitigate the effects of these sources of error, deformable image registration was employed. A deformable registration algorithm was selected and the registration error was evaluated via the introduction of external fiducials to the tumor. Once a method for image registration was established, a procedure for validating the use of novel PET tracers with FDG was developed. Nude mice were used to perform in-vivo comparisons of the spatial distributions of two PET tracers, FDG and FLT. The spatial distributions were also compared across two separate tumor lines to determine the effects of tumor morphology on spatial distribution. Finally, the research establishes a method for acquiring pre-clinical data supporting the use of PET for image-guidance in selective dose escalation. Nude mice were imaged using only FDG PET/CT and the resulting images were used to plan PET-guided dose escalations to a 5 mm sub-volume within the tumor that contained the highest PET tracer uptake. These plans were then delivered using the Small Animal Radiation Research Platform (SARRP) and the efficacy of the PET-guided plans was observed. Results and Conclusions: The analysis of deformable registration algorithms revealed that the BRAINSFit B-spline deformable registration algorithm available in SLICER3D was capable of registering small animal PET/CT data sets in less than 5 minutes with an average registration error of .3 mm. The methods used in chapter 3 allowed for the comparison of the spatial distributions of multiple PET tracers imaged at different times. A comparison of FDG and FLT showed that both are positively correlated but that tumor morphology does significantly affect the correlation between the two tracers. An overlap analysis of the high intensity PET regions of FDG and FLT showed that FLT offers additional spatial information to that seen with FDG. In chapter 4 the SARRP allowed for the delivery of planned PET-guided selective dose escalations to a pre-clinical tumor model. This will facilitate future research validating the use of PET for clinical selective dose escalation.
Rights
© The Author
Is Part Of
VCU University Archives
Is Part Of
VCU Theses and Dissertations
Date of Submission
September 2013