Durante, M.

Elsässer, T.

Friedrich, T.

Scholz, M.

Scholz, U.

GSI Repository

Systematic investigation of RBE using the particle irradiation data ensemble∗T. Friedrich1, U. Scholz1,2, T. Elsa¨sser†1, M. Durante1,2, and M. Scholz11GSI, Darmstadt, Germany; 2TUD, FKP, Darmstadt, GermanyIntroductionSurvival assays of cultured cells are frequently usedto investigate the response to both photon and ion radia-tion. Its dose dependence is commonly visualized as sur-vival curves. An enhanced efficacy of ion irradiation com-pared to photon irradiation is evident for many endpointsand is expressed by the relative biological effectiveness(RBE), which is the ratio of doses of ion and photon ra-diation needed to cause the same effect [1]. The experi-mental investigation of the systematics of RBE and dose re-sponse curves is complemented by predictive models suchas the Local Effect Model (LEM). To probe their accuracya global view on available data is needed. Therefore theParticle Irradiation Data Ensemble (PIDE) was set up [2],which is a collection of ion and photon survival curvesfrom the literature. Meanwhile it comprises 855 dose re-sponse experiments, parameterized by the linear-quadratic(LQ) model for photons and ions, from 77 publications [3].ResultsFor ion irradiation survival decreases usually linearlywith increasing dose. This makes it difficult to performreliable fits in particular for the quadratic parameter βI . Itis not clear up to now how βI evolves with LET. Here PIDEallows model comparisons with good statistics.Figure 1 presents βI normalized to the photon βγ pa-rameter vs LET for different particle types and cell lines.The spread of the data points is large, and it is unclear if βIsystematically exceeds βγ or falls off starting from smallLET. Hence a running average procedure was applied. Theemerging average curves suggest a small initial increase ofβI and a final falloff to zero. It may be explained by satu-ration effects, as for very large LET each hit cell is killedanyway, and hence only hit statistics matters, resulting in astraight survival curve.Experimental findings do not precisely reveal the natureof βI , and also RBE models reflect a huge variability in thepredictions. This can be seen in Fig. 2 where βI for threemodels is compared with data from two cell lines. The fig-ure indicates that neither experimental nor model data showa clear systematics, so some aspects of high LET cell sur-vival are still unclear. With respect to clinical applicationsthe accurate modelling of βI presumably becomes relevantin hypofractionation, whereas for more conventional frac-tionation schemes treatment plans are comparably robustagainst larger variation of βI .∗Work supported by Siemens Healthcare. Work is part of HGS Hire.† Now working at Siemens Healthcare.Figure 1: Ratio of the LQ parameter βI of ions to that ofphotons vs LET for monoenergetic ions for different ionspecies (p: red; He: blue; C: grey; Ne: orange; heavierions than Ne: green). The solid lines are running averageswith correlation length as indicated by the horizontal bar.Figure 2: As Fig. 1 for two individual cell lines (V79: red,HSG: green). Thick lines: running averages of the data.Dashed, dotted and dashed-dotted lines: model predictionsof the repair-misrepair-fixation model, the LEM, and themicrodosimetric-kinetic model, respectively.ConclusionsThe presented example demonstrates that the PIDE is ap-propriate to identify open points in the dose response sys-tematics. It is helpful for model evaluation and accessibleto the research community (http://www.gsi.de/bio-pide).References[1] ICRP Report 92, Elsevier (2003).[2] T. Friedrich, GSI Sci.-Rep. 2010, Health-22.[3] T. Friedrich et al., J Radiat Res 2012, in press.GSI SCIENTIFIC REPORT 2012 HEALTH-41465

Systematic investigation of RBE using the particle irradiation data ensemble

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Systematic investigation of RBE using the particle irradiation data ensemble

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