Optimization of Radiation Therapy in Time-Dependent Anatomy
The objective of this dissertation is to develop treatment planning techniques that have the potential to improve radiation therapy of time-dependent (4D) anatomy. Specifically, this study examines dose estimation, dose evaluation, and decision making in the context of optimizing lung cancer radiat...
| Main Author: | |
|---|---|
| Format: | Others |
| Published: |
VCU Scholars Compass
2013
|
| Subjects: | |
| Online Access: | http://scholarscompass.vcu.edu/etd/3069 http://scholarscompass.vcu.edu/cgi/viewcontent.cgi?article=4068&context=etd |
| Summary: | The objective of this dissertation is to develop treatment planning techniques that have the potential to improve radiation therapy of time-dependent (4D) anatomy. Specifically, this study examines dose estimation, dose evaluation, and decision making in the context of optimizing lung cancer radiation therapy. Two methods of dose estimation are compared in patients with locally advanced and early stage lung cancer: dose computed on a single image (3D-dose) and deformably registered, accumulated dose (or 4D-dose). The results indicate that differences between 3D- and 4D- dose are not significant in organs at risk (OARs), however, 4D-dose to a moving lung cancer target can deviate from 3D-dose. These differences imply that optimization of the 4D-dose through multiple-anatomy optimization (MAO) can improve radiation therapy in 4D-anatomy. MAO incorporates time-dependent target and OAR geometry while enabling a simple, clinically realizable delivery. MAO has the potential to enhance the therapeutic ratio in terms of target coverage and OAR sparing in 4D-anatomy. In dose evaluation within 4D-anatomy; dose-to-mass is a more intuitive and precise metric in estimating the effects of radiation in tissues. Assuming physical density is proportional to functional tissue density, dose-to-mass has a 1-1 correspondence with radiation damage. Dose-to-mass optimization boosts dose in massive regions of lung cancer targets and can reduce integral dose to lung by preferentially treating through regions of low-density lung tissue. Finally, multi-criteria optimization (MCO) is implemented in order to clarify decision making during plan design for lung cancer treatment. An MCO basis set establishes a patient-specific decision space which reveals trade-offs in OAR-dose at a fixed, constrained target dose. By interpolating the MCO basis set and evaluating the plan on 4D-anatomy, patient- and organ- specific conservatism in plan design can be expressed in real time. Through improved methods of dose estimation, dose evaluation, and decision making, this dissertation will positively impact radiation therapy of time-dependent anatomy. |
|---|