A comparison of two methodologies for radiotherapy treatment plan optimization and QA for clinical trials.

Journal Article (Journal Article)

BACKGROUND AND PURPOSE: The efficacy of clinical trials and the outcome of patient treatment are dependent on the quality assurance (QA) of radiation therapy (RT) plans. There are two widely utilized approaches that include plan optimization guidance created based on patient-specific anatomy. This study examined these two techniques for dose-volume histogram predictions, RT plan optimizations, and prospective QA processes, namely the knowledge-based planning (KBP) technique and another first principle (FP) technique. METHODS: This analysis included 60, 44, and 10 RT plans from three Radiation Therapy Oncology Group (RTOG) multi-institutional trials: RTOG 0631 (Spine SRS), RTOG 1308 (NSCLC), and RTOG 0522 (H&N), respectively. Both approaches were compared in terms of dose prediction and plan optimization. The dose predictions were also compared to the original plan submitted to the trials for the QA procedure. RESULTS: For the RTOG 0631 (Spine SRS) and RTOG 0522 (H&N) plans, the dose predictions from both techniques have correlation coefficients of >0.9. The RT plans that were re-optimized based on the predictions from both techniques showed similar quality, with no statistically significant differences in target coverage or organ-at-risk sparing. The predictions of mean lung and heart doses from both methods for RTOG1308 patients, on the other hand, have a discrepancy of up to 14 Gy. CONCLUSIONS: Both methods are valuable tools for optimization guidance of RT plans for Spine SRS and Head and Neck cases, as well as for QA purposes. On the other hand, the findings suggest that KBP may be more feasible in the case of inoperable lung cancer patients who are treated with IMRT plans that have spatially unevenly distributed beam angles.

Full Text

Duke Authors

Cited Authors

  • Geng, H; Giaddui, T; Cheng, C; Zhong, H; Ryu, S; Liao, Z; Yin, F-F; Gillin, M; Mohan, R; Xiao, Y

Published Date

  • October 2021

Published In

Volume / Issue

  • 22 / 10

Start / End Page

  • 329 - 337

PubMed ID

  • 34432946

Pubmed Central ID

  • PMC8504592

Electronic International Standard Serial Number (EISSN)

  • 1526-9914

Digital Object Identifier (DOI)

  • 10.1002/acm2.13401

Language

  • eng

Conference Location

  • United States