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Advancing RBE Models for High LET Particles Beyond the Linear-Quadratic Model

O Vassiliev*, C Peterson, D Grosshans, R Mohan, UT MD Anderson Cancer Center, Houston, TX

Presentations

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

Room: AAPM ePoster Library

Purpose:

Experimental data show that cell survival curves attain a constant slope as the dose increases. Several models of this property have been proposed. None offers an insight into the mechanism. Instead, a constant slope is set rather artificially. The Non-Poisson Multi-Hit model (NPMH) is an exception. It predicts a constant slope and attributes it to the statistics of energy depositions in a subcellular target volume. We tested a simple version of the model for consistency with experimental data for high LET ions.

Methods:

We used published experimental cell survival data to test a version of the NPMH model, in which the microdosimetric quantity yF is replaced with LET. The data was for ions: ²H, ³He, 4He, ¹²C, ¹6O, ¹?F; the LET range was 40 to 600 keV/µm. We fitted the model to nine cell survival curves simultaneously. We used an innovative optimization technique, in which the hard constraint S(0)=1 was removed to account for uncertainties in the plating efficiency. The correct normalization was restored after an optimal solution was found.

Results:

The model agreed with experimental data. The formula for cell survival in this version of the model was as follows: S(D)=[1+ab×exp(-b)]×exp[-a+a×exp(-b)], where a=DA/LET, b=LET/L0. It has two parameters, A and L0. The best fit values were A=575 keV/µm/Gy, L0=148 keV/µm. Although very simple, the formula predicted correctly how the shape of a survival curve changes with increasing LET: the shoulder gradually disappears, and at very high LETs the slope starts to decrease. The RBE versus LET curve had the well known shape that for low doses has a maximum around 200 keV/µm.

Conclusion:

With only two parameters, the NPMH model achieved agreement with experimental data for several ions, over a broad LET range. It predicted correctly the shape of cell survival curves and how it changes with LET.

Download ePoster [PDF]

Funding Support, Disclosures, and Conflict of Interest: The study was supported by NIH/NCI grant R01 CA225961

Keywords

Heavy Ions, Radiobiology

Taxonomy

TH- Radiobiology(RBio)/Biology(Bio): RBio- Particle therapy- other

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