Date Approved
8-4-2023
Graduate Degree Type
Project
Degree Name
Medical Dosimetry (M.S.)
Degree Program
Health Professions
First Advisor
Karen Snyder
Academic Year
2022/2023
Abstract
Introduction
MRI-guided radiation therapy has proven to provide many benefits such as real-time tracking, dose escalation, and the ability to perform online adaptive therapy. The objective of this study is to compare curative treatment plans for glioblastoma tumors on a low-field MR-guided linac vs a C-Arm linac and evaluate if they are comparable in terms of coverage, organ at risk sparing, delivery time, and deliverability.
Methods
This is a retrospective study that consisted of 15 previously treated patients who received radiation therapy for glioblastoma on a C-Arm linac. The CT simulation data that was used for the original treated plans was imported into a MR-linac treatment planning system (TPS) where MR-linac plans were generated. The plans were analyzed utilizing the dose volumetric histogram (DVH) and isodose lines and compared in terms of plan quality consisting of PTV coverage, dose distributions, and OAR constraints between the two delivery platforms. QA was performed on a sub-set of the plans to verify deliverability.
Results
Data was collected on all 15 patients for both the C-Arm linac and MR-linac plans and statistical analysis was performed. Wilcoxon signed-rank tests were performed, and the Effect size was found using Cohen’s D to compare differences between the two plans. Results are given for PTV values, organs at risk, homogeneity indexes, total MU’s, and normal brain values.
Conclusion
It was concluded that both treatment techniques resulted in appropriate PTV coverage and acceptable max doses to OARs. There was a statistically significant difference in the homogeneity index (HI) values (p value
ScholarWorks Citation
Moats, Emily J., "Dosimetric comparison of Glioblastoma Radiotherapy treatment plans on a low-field MRI-guided linear accelerator compared to conventional C-Arm linear accelerator" (2023). Culminating Experience Projects. 357.
https://scholarworks.gvsu.edu/gradprojects/357