Can the mean linear energy transfer of organs be directly related to patient toxicities for current head and neck cancer intensity-modulated proton therapy practice?

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Abstract

BACKGROUND AND PURPOSE: The relative biological effectiveness (RBE) of proton therapy is predicted to vary with the dose-weighted average linear energy transfer (LETd). However, RBE values may substantially vary for different clinical endpoints. Therefore, the aim of this study was to assess the feasibility of relating mean D⋅LETd parameters to patient toxicity for HNC patients treated with proton therapy.

MATERIALS AND METHODS: The delivered physical dose (D) and the voxel-wise product of D and LETd (D⋅LETd) distributions were calculated for 100 head and neck cancer (HNC) proton therapy patients using our TPS (Raystation v6R). The means and covariance matrix of the accumulated D and D⋅LETd of all relevant organs-at-risk (OARs) were used to simulate 2.500 data sets of different sizes. For each dataset, an attempt was made to add mean D⋅LETd parameters to a multivariable NTCP model based on mean D parameters of the same OAR for xerostomia, tube feeding and dysphagia. The likelihood of creating an NTCP model with statistically significant parameters (i.e. power) was calculated as a function of the simulated sample size for various RBE models.

RESULTS: The sample size required to have a power of at least 80% to show an independent effect of mean D⋅LETd parameters on toxicity is over 15000 patients for all toxicities.

CONCLUSION: For current clinical practice, it is not feasible to directly model NTCP with both mean D and mean D⋅LETd of OARs. These findings should not be interpreted as a contradiction of previous evidence for the relationship between RBE and LETd.

Original languageEnglish
Pages (from-to)159-165
Number of pages7
JournalRadiotherapy and Oncology
Volume165
Early online date14-Sept-2021
DOIs
Publication statusPublished - Dec-2021

Keywords

  • Proton beam therapy
  • Biological modeling
  • Head and neck tumors
  • NTCP modeling
  • Relative biological effectiveness
  • RBE
  • Linear energy transfer
  • LET
  • EFFECTIVENESS RBE VALUES
  • BIOLOGICAL EFFECTIVENESS
  • CLINICAL-EVIDENCE
  • OPTIMIZATION
  • MODEL
  • SENSITIVITY

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