LETd Optimization Verification With an SOI Microdosimeter

V. A. Pan, L. T. Tran, T. Madden, B. Clasie, H. Kooy, A. B. Rosenfeld, N. Depauw

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: A first of its kind experimental verification of dose-averaged linear energy transfer (LETd) optimized treatment plans for proton therapy has been carried out using a silicon-on-insulator microdosimeter at the Massachusetts General Hospital (MGH), Boston, USA. Methods and Materials: Three clinical treatment plans of a typical ependymoma structure set were designed using the standard clinical approach, the proposed protocol approach, and a one-field approach. The plans were then reoptimized to reduce the LETd-weighted dose in the brain stem. All six plans were delivered in a solid water phantom and the experimental yD‾ measured. Results: After LETd optimization, a reduction in yD‾ was found within the brain stem by an average of 12%, 19%, and 4% for the clinical, protocol, and one-field plans, respectively, while maintaining adequate coverage of the tumor structure. The experimental LETd-weighted doses were in agreement with the treatment planning system calculations and Monte Carlo simulations and reinforced the improvement of the optimization. Conclusions: This work demonstrates the first experimental verification of the clinical implementation of LETd optimization for patient treatment with proton therapy.

Original languageEnglish
JournalInternational Journal of Radiation Oncology Biology Physics
Early online date31 Jan 2024
DOIs
StatePublished - 1 Jul 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2024 Elsevier Inc.

Funding

Funding: NHMRC Ideas Grant GNT2012330 from the National Health and Medical Research Council, Australia . Career Development Fellowship 2021/CDF1112 from the Cancer Institute of NSW. Acknowledgments—The authors would like to acknowledge the help provided by the Australian Government Research Training Program Scholarship and the Post Graduate Research Award (PGRA) from the Australian Institute of Nuclear Science and Engineering (AINSE).

FundersFunder number
National Health and Medical Research CouncilGNT2012330, 2021/CDF1112
Australian Institute of Nuclear Science and Engineering
Cancer Institute NSW

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