A radiotherapy community data-driven approach to determine which complexity metrics best predict the impact of atypical TPS beam modeling on clinical dose calculation accuracy

Our plain-English summary of A radiotherapy community data-driven approach to determine which complexity metrics best predict the impact of atypical TPS beam modeling on clinical dose calculation accuracy, by F.M.D. Brooks, M.C. Glenn, V. Hernandez, et al (Journal of Applied Clinical Medical Physics, 2024).

The study

• Authors: F.M.D. Brooks, M.C. Glenn, V. Hernandez, J. Saez, H. Mehrens, J.M. Pollard-Larkin, R.M. Howell, C.B. Peterson, C.L. Nelson, C.H. Clark, S.F. Kry
• Journal: Journal of Applied Clinical Medical Physics
• Published: 2024;25(5):e14318
• Cited by: 17 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

Abstract

Purpose: To quantify the impact of treatment planning system beam model parameters, based on the actual spread in radiotherapy community data, on clinical treatment plans and determine which complexity metrics best describe the impact beam modeling errors have on dose accuracy.

Methods: Ten beam modeling parameters for a Varian accelerator were modified in RayStation to match radiotherapy community data at the 2.5, 25, 50, 75, and 97.5 percentile levels. These modifications were evaluated on 25 patient cases, including prostate, non-small cell lung, H&N, brain, and mesothelioma, generating 1,000 plan perturbations. Differences in the mean planned dose to clinical target volumes (CTV) and organs at risk (OAR) were evaluated with respect to the planned dose using the reference (50th-percentile) parameter values. Correlation between CTV dose differences, and 18 different complexity metrics were evaluated using linear regression; R-squared values were used to determine the best metric.

Results: Perturbations to MLC offset and transmission parameters demonstrated the greatest changes in dose: up to 5.7% in CTVs and 16.7% for OARs. More complex clinical plans showed greater dose perturbation with atypical beam model parameters. The mean MLC Gap and Tongue & Groove index (TGi) complexity metrics best described the impact of TPS beam modeling variations on clinical dose delivery across all anatomical sites; similar, though not identical, trends between complexity and dose perturbation were observed among all sites.

Conclusion: Extreme values for MLC offset and MLC transmission beam modeling parameters were found to most substantially impact the dose distribution of clinical plans and careful attention should be given to these beam modeling parameters. The mean MLC Gap and TGi complexity metrics were best suited to identifying clinical plans most sensitive to beam modeling errors; this could help provide focus for clinical QA in identifying unacceptable plans.

© 2024 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.

In plain English

This was a computer-based radiotherapy physics study, not a study of asbestos exposure. Mesothelioma appeared only as one of five cancer types whose treatment plans were used. The authors recalculated 25 existing radiation treatment plans (five each for prostate, non-small cell lung, head and neck, mesothelioma and brain). Each time, they changed one of ten beam-modeling settings to a value used across radiotherapy clinics, giving 1,000 recalculations. Settings for the multi-leaf collimator (MLC) offset and transmission changed the calculated dose the most. With the MLC offset at the 97.5th percentile, dose to the target rose on average 3.0% (maximum 5.7%) and dose to organs at risk rose 6.2% (maximum 16.7%). Head and neck and mesothelioma targets were the most sensitive to MLC offset. The authors compared 18 plan complexity measures with the target dose changes caused by three settings: MLC offset, MLC transmission and leaf tip width. Mean MLC gap and tongue-and-groove index matched these changes best. The authors concluded that MLC offset and transmission need careful attention. They noted the findings may apply only to the RayStation and Varian systems studied.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Computer-based treatment-planning simulation study using retrospectively selected clinical radiotherapy plans, each recalculated under altered beam-model settings
• Who was studied: 25 standard fractionated IMRT and VMAT clinical treatment plans, five each for prostate, non-small cell lung, head and neck (oropharynx), mesothelioma and brain, retrospectively selected at the authors' institution (MD Anderson, Houston); 1,000 plan perturbations in total
• Exposure: No asbestos exposure was studied. The variables changed were ten treatment planning system beam-model parameters for a Varian accelerator: MLC offset, MLC transmission, MLC gain, MLC curvature, source size, leaf tip width, tongue and groove, percent depth dose, output factors and off-axis factors. Each was set to radiotherapy community values at the 2.5, 25, 75 and 97.5 percentile levels and compared with a 50th-percentile reference model.
• Main results:
  • MLC offset at the community 97.5 percentile level overdosed target volumes (CTVs) on average by 3.0% (maximum 5.7%)
  • MLC offset at the 97.5 percentile level overdosed organ-at-risk structures on average by 6.2% (maximum 16.7%)
  • MLC offset at the 2.5 percentile level underdosed CTVs on average by 1.7% (maximum 3.2%)
  • MLC transmission at the 2.5 percentile value underdosed CTVs by 2.4% (maximum 5.0%)
  • In the 200 head and neck plan perturbations, 25 gave the parotid glands more than 26 Gy and 41 gave the mandible more than 70 Gy
  • CTVs in head and neck and mesothelioma cases had the greatest sensitivity to MLC offset, followed by prostate, brain and non-small cell lung cases
  • 186 of the 1,000 plan perturbations caused CTV dose deviations greater than 1%
  • Complexity metrics were tested by linear regression against the maximum percent dose deviation in the CTV, for three modeling parameters only: MLC offset, MLC transmission and leaf-tip width
  • Of 18 complexity metrics, mean MLC gap (meanGap) and tongue and groove index (TGi) best described the dose impact of beam-modeling variations across all sites
  • The authors reported that dose errors could be limited to less than approximately 2% if meanGap is greater than 34.0 mm and TGi is less than 0.224, as long as parameters are not outside the 97.5 percentile
• The authors' conclusion: The authors concluded that MLC offset and MLC transmission modeling had a substantial impact on dose to targets and critical structures. They found these dose changes were related to plan complexity, with mean MLC gap and tongue and groove index best suited to identifying plans sensitive to beam-modeling errors. They stated that use of atypical modeling values requires careful attention by clinical physicists.
• Limitations the authors state:
  • The metrics are likely specific to the RayStation and Varian platform evaluated, and it is unclear how other platforms may behave
  • Only five anatomical sites were studied, and other sources of error were not evaluated
  • The study addressed dose calculation accuracy, not deliverability accuracy

Topics

Medical terms in this study, explained in our Lexicon: Mesothelioma.

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