Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Jun 14;8(6):101292.
doi: 10.1016/j.adro.2023.101292. eCollection 2023 Nov-Dec.

Benchmarking Automated Machine Learning-Enhanced Planning With Ethos Against Manual and Knowledge-Based Planning for Locally Advanced Lung Cancer

Joel A Pogue  1 , Carlos E Cardenas  1 , Joseph Harms  1 , Michael H Soike  1 , Adam J Kole  1 , Craig S Schneider  1 , Christopher Veale  1 , Richard Popple  1 , Jean-Guy Belliveau  1 , Andrew M McDonald  1   2 , Dennis N Stanley  1
Affiliations

Benchmarking Automated Machine Learning-Enhanced Planning With Ethos Against Manual and Knowledge-Based Planning for Locally Advanced Lung Cancer

Joel A Pogue et al. Adv Radiat Oncol. .

Abstract

Purpose: Currently, there is insufficient guidance for standard fractionation lung planning using the Varian Ethos adaptive treatment planning system and its unique intelligent optimization engine. Here, we address this gap in knowledge by developing a methodology to automatically generate high-quality Ethos treatment plans for locally advanced lung cancer.

Methods and materials: Fifty patients previously treated with manually generated Eclipse plans for inoperable stage IIIA-IIIC non-small cell lung cancer were included in this institutional review board-approved retrospective study. Fifteen patient plans were used to iteratively optimize a planning template for the Daily Adaptive vs Non-Adaptive External Beam Radiation Therapy With Concurrent Chemotherapy for Locally Advanced Non-Small Cell Lung Cancer: A Prospective Randomized Trial of an Individualized Approach for Toxicity Reduction (ARTIA-Lung); the remaining 35 patients were automatically replanned without intervention. Ethos plan quality was benchmarked against clinical plans and reoptimized knowledge-based RapidPlan (RP) plans, then judged using standard dose-volume histogram metrics, adherence to clinical trial objectives, and qualitative review.

Results: Given equal prescription target coverage, Ethos-generated plans showed improved primary and nodal planning target volume V95% coverage (P < .001) and reduced lung gross tumor volume V5 Gy and esophagus D0.03 cc metrics (P ≤ .003) but increased mean esophagus and brachial plexus D0.03 cc metrics (P < .001) compared with RP plans. Eighty percent, 49%, and 51% of Ethos, clinical, and RP plans, respectively, were "per protocol" or met "variation acceptable" ARTIA-Lung planning metrics. Three radiation oncologists qualitatively scored Ethos plans, and 78% of plans were clinically acceptable to all reviewing physicians, with no plans receiving scores requiring major changes.

Conclusions: A standard Ethos template produced lung radiation therapy plans with similar quality to RP plans, elucidating a viable approach for automated plan generation in the Ethos adaptive workspace.

PubMed Disclaimer

Conflict of interest statement

Richard Popple reports that his institution, University of Alabama at Birmingham, has product evaluation agreements and research grants with Varian Medical Systems. He also reports that he has a patent licensed by UAB Research Foundation to Varian Medical Systems, has received honoraria for presentations on behalf of Varian Medical Systems, has received a stipend to speak at Sun Nuclear meetings, and that Varian Medical Systems provides equipment to UAB as a part of a product evaluation agreement. Andrew McDonald and his institution, University of Alabama at Birmingham, have received payment from Varian Medical Systems. Dennis N. Stanley and his institution, University of Alabama at Birmingham, have received payment from Varian Medical Systems.

Figures

Figure 1
Figure 1
Boxplots summarizing Ethos, clinical plans recalculated in AcurosXB, and RapidPlan cohort ARTIA-Lung planning metrics. Open and closed circles indicate outlier and mean values, respectively. Dashed and solid lines indicate per protocol and variation acceptable constraints. Significance values obtained via the Wilcoxon signed rank test are annotated as follows: ns: P > 0.004; *: P ≤ 0.004. Abbreviations: Clin = clinical; GTV = gross tumor volume; ns = not significant; PTV = planning target volume; RP = RapidPlan.
Figure 2
Figure 2
Validation cohort dose volume histogram comparison of Ethos, clinical plans recalculated in AcurosXB, and RapidPlan plans. Shaded areas illustrate the mean ± standard deviation and insets elucidate the difference between mean population dose volume histograms (ie, Ethos plan volume minus alternative plan volume). Abbreviations: GTV = gross tumor volume; PTV = planning target volume; PTVn = nodal planning target volume PTVp = primary planning target volume.
Figure 3
Figure 3
Likert qualitative plan review results by physician. The grading scale ranged from 1 to 5, but no scores below 3 were given.
See this image and copyright information in PMC

References

    1. Winkel D, Bol GH, Van Asselen B, et al. Development and clinical introduction of automated radiotherapy treatment planning for prostate cancer. Phys Med Biol. 2016;61:8587–8595. - PubMed
    1. Nelms BE, Robinson G, Markham J, et al. Variation in external beam treatment plan quality: An inter-institutional study of planners and planning systems. Pract Radiat Oncol. 2012;2:296–305. - PubMed
    1. Moore KL, Brame RS, Low DA, Mutic S. Quantitative metrics for assessing plan quality. Semin Radiat Oncol. 2012;22:62–69. - PubMed
    1. Batumalai V, Jameson MG, Forstner DF, Vial P, Holloway LC. How important is dosimetrist experience for intensity modulated radiation therapy? A comparative analysis of a head and neck case. Pract Radiat Oncol. 2013;3:e99–e106. - PubMed
    1. Moore KL, Appenzoller LM, Tan J, Michalski JM, Thorstad W, Mutic S. Clinical implementation of dose-volume histogram predictions for organs-at-risk in IMRT planning. J Phys Conf Ser. 2014;489 - PubMed

LinkOut - more resources