skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: SU-E-T-173: Clinical Comparison of Treatment Plans and Fallback Plans for Machine Downtime

Abstract

Purpose: The purpose of this study was to determine the clinical effectiveness and dosimetric quality of fallback planning in relation to machine downtime. Methods: Plans for a Varian Novalis TX were mimicked, and fallback plans using an Elekta VersaHD machine were generated using a dual arc template. Plans for thirty (n=30) patients of various treatment sites optimized and calculated using RayStation treatment planning system. For each plan, a fall back plan was created and compared to the original plan. A dosimetric evaluation was conducted using the homogeneity index, conformity index, as well as DVH analysis to determine the quality of the fallback plan on a different treatment machine. Fallback plans were optimized for 60 iterations using the imported dose constraints from the original plan DVH to give fallback plans enough opportunity to achieve the dose objectives. Results: The average conformity index and homogeneity index for the NovalisTX plans were 0.76 and 10.3, respectively, while fallback plan values were 0.73 and 11.4. (Homogeneity =1 and conformity=0 for ideal plan) The values to various organs at risk were lower in the fallback plans as compared to the imported plans across most organs at risk. Isodose difference comparisons between plans were also comparedmore » and the average dose difference across all plans was 0.12%. Conclusion: The clinical impact of fallback planning is an important aspect to effective treatment of patients. With the complexity of LINACS increasing every year, an option to continue treating during machine downtime remains an essential tool in streamlined treatment execution. Fallback planning allows the clinic to continue to run efficiently should a treatment machine become offline due to maintenance or repair without degrading the quality of the plan all while reducing strain on members of the radiation oncology team.« less

Authors:
 [1];  [1];  [2];  [3]
  1. University of Texas Health Science Center at San Antonio, San Antonio, TX (United States)
  2. University of North Carolina, Chapel Hill, NC (United States)
  3. Cancer Therapy and Research Center, San Antonio, TX (United States)
Publication Date:
OSTI Identifier:
22545298
Resource Type:
Journal Article
Journal Name:
Medical Physics
Additional Journal Information:
Journal Volume: 42; Journal Issue: 6; Other Information: (c) 2015 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0094-2405
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; HEALTH HAZARDS; LINEAR ACCELERATORS; ORGANS; PATIENTS; RADIATION DOSES

Citation Formats

Cruz, W, Cancer Therapy and Research Center, San Antonio, TX, Papanikolaou, P, Mavroidis, P, and Stathakis, S. SU-E-T-173: Clinical Comparison of Treatment Plans and Fallback Plans for Machine Downtime. United States: N. p., 2015. Web. doi:10.1118/1.4924535.
Cruz, W, Cancer Therapy and Research Center, San Antonio, TX, Papanikolaou, P, Mavroidis, P, & Stathakis, S. SU-E-T-173: Clinical Comparison of Treatment Plans and Fallback Plans for Machine Downtime. United States. https://doi.org/10.1118/1.4924535
Cruz, W, Cancer Therapy and Research Center, San Antonio, TX, Papanikolaou, P, Mavroidis, P, and Stathakis, S. 2015. "SU-E-T-173: Clinical Comparison of Treatment Plans and Fallback Plans for Machine Downtime". United States. https://doi.org/10.1118/1.4924535.
@article{osti_22545298,
title = {SU-E-T-173: Clinical Comparison of Treatment Plans and Fallback Plans for Machine Downtime},
author = {Cruz, W and Cancer Therapy and Research Center, San Antonio, TX and Papanikolaou, P and Mavroidis, P and Stathakis, S},
abstractNote = {Purpose: The purpose of this study was to determine the clinical effectiveness and dosimetric quality of fallback planning in relation to machine downtime. Methods: Plans for a Varian Novalis TX were mimicked, and fallback plans using an Elekta VersaHD machine were generated using a dual arc template. Plans for thirty (n=30) patients of various treatment sites optimized and calculated using RayStation treatment planning system. For each plan, a fall back plan was created and compared to the original plan. A dosimetric evaluation was conducted using the homogeneity index, conformity index, as well as DVH analysis to determine the quality of the fallback plan on a different treatment machine. Fallback plans were optimized for 60 iterations using the imported dose constraints from the original plan DVH to give fallback plans enough opportunity to achieve the dose objectives. Results: The average conformity index and homogeneity index for the NovalisTX plans were 0.76 and 10.3, respectively, while fallback plan values were 0.73 and 11.4. (Homogeneity =1 and conformity=0 for ideal plan) The values to various organs at risk were lower in the fallback plans as compared to the imported plans across most organs at risk. Isodose difference comparisons between plans were also compared and the average dose difference across all plans was 0.12%. Conclusion: The clinical impact of fallback planning is an important aspect to effective treatment of patients. With the complexity of LINACS increasing every year, an option to continue treating during machine downtime remains an essential tool in streamlined treatment execution. Fallback planning allows the clinic to continue to run efficiently should a treatment machine become offline due to maintenance or repair without degrading the quality of the plan all while reducing strain on members of the radiation oncology team.},
doi = {10.1118/1.4924535},
url = {https://www.osti.gov/biblio/22545298}, journal = {Medical Physics},
issn = {0094-2405},
number = 6,
volume = 42,
place = {United States},
year = {Mon Jun 15 00:00:00 EDT 2015},
month = {Mon Jun 15 00:00:00 EDT 2015}
}