Evaluation of nanodosimetric quantities for ion radiotherapy treatment planning based on the degree of association of survival with cluster dose.

To demonstrate potential for a close association between cell survival and cluster dose for ionization parameters (), and to investigate the means to quantify the degree of this association when calculating cluster dose using these nanodosimetric quantities.The definitions ofconsidered were the number of clusters ofor more ionizations per unit track length {= 1,…10}. For thisdefinition, cluster dose is the number of clusters ofor more ionizations per unit mass. Three sets of published cell survival data, covering a range of clinically relevant particle types and energies, normal and tumor human cells, and aerobic and hypoxic conditions, were used to assess these. Values ofwere previously calculated for this survival data and evaluated for their application in treatment planning. New to this study, the dependence of cell survival on cluster dose, calculated as local fluence times the mean mass, was used. The degree of association of cell survival with cluster dose was quantified using three statistical methods: the moving window method, the residuals of linear quadratic fit, and the Bayesian information criteria.all three methods identifiedas the most closely associated with cell survival under aerobic conditions, andunder hypoxic conditions, consistent with visual observations. Remarkably,preferred for their close association with cell survival for different particle types having the same fluence, compared to alternative definitions, resulted in a statistically significant closer association of cell survival with cluster dose, regardless of particle fluence.fluence is a critical property Cluster dose has the potential of supplementing or even replacing RBE-weighted dose in optimization of ion therapy treatment plans. The proposed methodology lays the groundwork for rigorous identification ofthat exhibit the highest degree of association of cell survival with cluster dose, a trait that greatly enhances the potential clinical impact of cluster dose.