Date Approved

7-29-2026

Graduate Degree Type

Project

Degree Name

Medical Dosimetry (M.S.)

Degree Program

School of Interdisciplinary Health

First Advisor

Kristen Vu

Second Advisor

Tahsa Potts

Third Advisor

Dennis Stanley

Fourth Advisor

Carlos Cardenas

Academic Year

2025/2026

Abstract

Adaptive radiotherapy (ART) and knowledge-based planning (KBP) have independently improved treatment planning quality and efficiency; however, limited evidence exists regarding their combined use within the Varian Ethos planning system. This retrospective study evaluated whether an institution-specific Ethos-trained RapidPlan model improved dosimetric plan quality compared with Intelligent Optimization Engine (IOE) optimization alone and a publicly available Eclipse-trained RapidPlan model for right-sided non-small cell lung cancer. Ten patients previously treated with adaptive radiotherapy were replanned using three planning approaches: IOE optimization alone, IOE with a generic RapidPlan model, and IOE with an institutional Ethos-trained RapidPlan model. Target coverage, homogeneity, and organ-at-risk (OAR) dose metrics were compared using Friedman tests with Holm-adjusted Wilcoxon signed-rank tests for pairwise analysis. All three approaches achieved clinically acceptable target coverage, although small statistical differences were observed for selected planning target volume metrics. Both RapidPlan-assisted approaches significantly reduced heart and esophageal dose compared with IOE optimization alone, while the institutional Ethos-trained model consistently produced the lowest lung, heart, and esophageal doses. No significant differences were observed for spinal cord maximum dose. These findings demonstrate that integrating knowledge-based planning into the Ethos adaptive workflow can improve OAR sparing while maintaining clinically acceptable target coverage. Institution-specific RapidPlan models trained on Ethos-generated plans may better complement the Ethos optimization engine than generic Eclipse-derived models, supporting their use to enhance adaptive radiotherapy planning.

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