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Uncertainty Analysis for Relative Biological Effectiveness Derived From Different Dose-Effect Curve Model Fits

M Ghafarian*, J Eley, Vanderbilt University School of Medicine, Nashville, TN

Presentations

(Sunday, 7/12/2020)   [Eastern Time (GMT-4)]

Room: AAPM ePoster Library

Purpose: To demonstrate the derivation of relative biological effectiveness (RBE) and its uncertainty for biologic dose response data using various curve fitting models.

Methods: The RBE is defined as the ratio of a reference radiation dose and a corresponding test radiation dose under the condition that both radiation types yield an equivalent biologic effect. The RBE and its uncertainty were analytically derived for three dose-effect curve models with increasing complexity: the Linear Model fit, the Linear Quadratic General Model fit, and the Modified Error Function Model fit as commonly used in Normal Tissue Complication Probability analysis. The uncertainty in the RBE value was estimated for each model as a function of the dose and the uncertainties in the corresponding fit parameters, which were estimated during the numerical curve fitting, and using error propagation methods.

Results: The derived solutions demonstrate the relation between curve fit parameters for dose-response data of three models, the analytical expression of RBE, and the estimation of uncertainty in RBE as a function of dose.

Conclusions: These methods allow for a general handling of confidence intervals and estimation of the uncertainties in RBE, for example for high LET radiations.

Keywords

Radiobiology, RBE

Taxonomy

TH- Radiobiology(RBio)/Biology(Bio): RBio- LQ/TCP/NTCP/outcome modeling

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