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A Novel Linear-Quadratic-Cubic Cell Survival Model for Proton Therapy Response Based On the Microdosimetric Quantity Specific Energy

M Newpower

M Newpower*, O Vassiliev , F Guan , D Grosshans , L Bronk , R Mohan , UT MD Anderson Cancer Center, Houston, TX


SU-K-108-2 (Sunday, July 30, 2017) 4:00 PM - 6:00 PM Room: 108

Purpose: Recent cell survival data show a high relative biological effectiveness (RBE) near the distal edge of the Bragg curve of proton beams. Current biological effect models underestimate RBE in this region. We propose and evaluate an enhancement of the microdosimetric kinetic model (MKM) to explain the observed phenomena.

Methods: In MKM the average number of DNA lesions L₂ a linear-quadratic (LQ) function of the microdosimetric quantity specific energy z (the stochastic form of absorbed dose) and cell surviving fraction S of the form S=exp (-L₂) A new function L₃ was derived by assuming a cubic z dependence. This was then added to L₂ to arrive at L₃₂. L₃₂ incorporates the α and β parameters of the LQ model (L₂) along with other microdosimetric quantities such as dose-averaged and track-averaged specific energy, the skewness of the LET spectrum, as well as a single fitting parameter k₂. L₃₂ was fit to cell survival data by varying k₂ using the following relationship: S=exp (-L₃₂). In this case, calculating L₃₂ results in a linear-quadratic-cubic cell survival response to z. Monte Carlo simulations were performed to obtain microdosimetric quantities for the cell irradiation setup and used as input parameters for L₃₂.

Results: By varying the fitting parameter k₂ we were able to obtain considerably improved fit of the cell survival data and much better agreement between RBE predictions and experimental results compared to the standard MKM model.

Conclusion: Modifying MKM to include a cubic dependency for specific energy better predicts cell survival and RBE in the high LET region near the Bragg peak when compared to the standard MKM formulation. Improved models of biological response to proton irradiation could be incorporated in the optimization of intensity-modulated proton therapy to maximize the therapeutic benefits of proton therapy.

Funding Support, Disclosures, and Conflict of Interest: This work was funded by National Cancer Institute Grant Nos. U19 CA021239-35 and R21 CA187484-01.

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