Date Approved
8-9-2026
Graduate Degree Type
Project
Degree Name
Medical Dosimetry (M.S.)
Degree Program
School of Interdisciplinary Health
First Advisor
Kristen Vu
Second Advisor
Tasha Potts
Academic Year
2025/2026
Abstract
Proton therapy is more commonly being utilized for head and neck cancer treatment due to its ability to reduce dose to the surrounding normal tissue. However, one of the biggest challenges in proton treatment is its sensitivity to changes in tissue density, often necessitating adaptive replanning. This study evaluated if incorporating additional synthetic CTs (sCT) datasets during robust optimization can create treatment plans that maintain target coverage and organ sparing despite anatomical changes better than the original nominal plan, thereby reducing the need for adaptive planning in head and neck proton treatment. Ten head and neck cancer patients who underwent adaptive replanning during treatment were retrospectively evaluated. Five CBCT’s were taken during different points in the patient’s treatment and converted into synthetic CTs that show the anatomical changes that a patient undergoes throughout treatment. Three separate robustly optimized plans were generated from each nominal treatment plan using different sCT datasets and compared using dosimetric endpoints. The first plan, Robust_vsCT5, was created by robustly optimizing the nominal plan on the sCT #5 dataset. The second plan, Robust_vsCT4 was created by robustly optimizing the nominal plan on sCT #4. Lastly, Robust_Comp plan was generated by robustly optimizing the nominal plan on sCT #2-5. Robustness was evaluated with a 3.5% density uncertainty and 3 mm isotropic setup uncertainty. No statistically significance differences were shown for CTV high-risk D99 target coverage or the OAR metrics. Statistical significance was shown for the CTV standard-risk D99 when comparing the Nominal Plan with Robust_vsCT5 and Robust_Comp with a P value of .01 and .002 respectively. All robust optimization plans maintained similar target coverage and OAR sparing despite the influence of anatomical changes added during robust optimization
ScholarWorks Citation
Rodriguez, Ryan Michael, "Robustness Assessment of Head and Neck Proton Therapy Plans Using Composite Synthetic CTs: A Preliminary Step Toward AI Driven Anatomy Prediction Planning: A Retrospective Dosimetric Study." (2026). Masters Projects. 754.
https://scholarworks.gvsu.edu/gradprojects/754
