Click here to


Are you sure ?

Yes, do it No, cancel

A Test of the Hypothesis That the Linear-Quadratic (LQ) Model Parameter Beta Decreases with Increasing Particle Linear Energy Transfer (LET)

D Wang*, R Stewart , University of Washington , Seattle, WA


(Tuesday, 7/16/2019) 1:15 PM - 1:45 PM

Room: Exhibit Hall | Forum 4

Purpose: A number of published studies suggest that the value of β in the LQ cell survival model tends to decrease with increasing particle LET. Other published studies, as well as some biophysical considerations, suggest that β may be independent of LET or even an increasing function of LET. The purpose of this study is to test hypothesized trends in β with particle LET.

Methods: Bayesian bootstrap sampling is used to construct confidence intervals on estimates of α and β from a regression analysis of cells irradiated by particles of varying LET under oxic and hypoxic conditions. Two scenarios are considered: (1) α and βbeta are independently adjusted (2 degrees of freedom) and (2) α is independently adjusted and β is set a priori to β(ref) (1 degree of freedom), i.e., β/β(ref)=1. Alternative hypotheses (fitting scenarios) are tested by comparing estimates of α and the measured and predicted cell survival fraction for the two scenarios.

Results: For 200-250kV x-rays (reference radiation), LQ parameters for human kidney T1 cells are α(ref)=2.28×10�¹Gy�¹ and β(ref)=2.43×10�²Gy�² for oxic cells and alphaREF=7.80×10�²Gy�¹ and β(ref)=7.12×10�³Gy�² for hypoxic cells. For oxic and hypoxic conditions, differences in the normalized α/α(ref) of �He²� ions (166keV/µm, 110keV/µm, 88keV/µm, 61keV/µm, 26keV/µm) are insignificant between the decreasing and constant β scenarios. Comparisons of the measured and predicted cell survival fraction with absorbed dose are also insignificant compared to the uncertainties in measured data, dosimetry and LQ parameters.

Conclusion: The presented results provide evidence disputing the widely held believe that β must decrease with increasing particle LET in order to explain the results of measurements. Additional work is needed to extend the analysis to other cell lines and higher LET particles.


LET, Linear Quadratic Model, Statistical Analysis


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

Contact Email