Incorporating biological modeling into patient-specific plan verification

Ara N. Alexandrian, Panayiotis Mavroidis, Ganesh Narayanasamy, Kristen A. McConnell, Christopher N. Kabat, Renil B. George, Dewayne L. Defoor, Neil Kirby, Nikos Papanikolaou, Sotirios Stathakis

Research output: Contribution to journalArticle

Abstract

Purpose: Dose–volume histogram (DVH) measurements have been integrated into commercially available quality assurance systems to provide a metric for evaluating accuracy of delivery in addition to gamma analysis. We hypothesize that tumor control probability and normal tissue complication probability calculations can provide additional insight beyond conventional dose delivery verification methods. Methods: A commercial quality assurance system was used to generate DVHs of treatment plan using the planning CT images and patient-specific QA measurements on a phantom. Biological modeling was performed on the DVHs produced by both the treatment planning system and the quality assurance system. Results: The complication-free tumor control probability, P+, has been calculated for previously treated intensity modulated radiotherapy (IMRT) patients with diseases in the following sites: brain (−3.9% ± 5.8%), head-neck (+4.8% ± 8.5%), lung (+7.8% ± 1.3%), pelvis (+7.1% ± 12.1%), and prostate (+0.5% ± 3.6%). Conclusion: Dose measurements on a phantom can be used for pretreatment estimation of tumor control and normal tissue complication probabilities. Results in this study show how biological modeling can be used to provide additional insight about accuracy of delivery during pretreatment verification.

Original languageEnglish (US)
Pages (from-to)94-107
Number of pages14
JournalJournal of Applied Clinical Medical Physics
Volume21
Issue number3
DOIs
StatePublished - Mar 1 2020

Keywords

  • IMRT QA
  • radiobiological QA
  • radiobiological verification
  • radiobiology

ASJC Scopus subject areas

  • Radiation
  • Instrumentation
  • Radiology Nuclear Medicine and imaging

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  • Cite this

    Alexandrian, A. N., Mavroidis, P., Narayanasamy, G., McConnell, K. A., Kabat, C. N., George, R. B., Defoor, D. L., Kirby, N., Papanikolaou, N., & Stathakis, S. (2020). Incorporating biological modeling into patient-specific plan verification. Journal of Applied Clinical Medical Physics, 21(3), 94-107. https://doi.org/10.1002/acm2.12831