LET-weighted doses effectively reduce biological variability in proton radiotherapy planning

Stephen McMahon, Harald Paganetti, Kevin Prise

Research output: Contribution to journalArticle

14 Citations (Scopus)
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Abstract

Variations in proton Relative Biological Effectiveness (RBE) with Linear Energy Transfer (LET) remain one of the largest sources of uncertainty in proton radiotherapy. This work seeks to identify metrics which can be applied to mitigate these effects in treatment optimisation, and quantify their effectiveness. Three different metrics – dose, dose × LET and an LET-weighted dose defined as Dose×(1+κ LET_D) were compared with in vitro experimental studies of proton RBE and clinical treatment plans incorporating RBE models. In each system the biological effects of protons were plotted against these metrics to quantify the degree of variation introduced by unaccounted-for RBE uncertainties. As expected, the LET-dependence of RBE introduces significant variability in the biological effects of protons when plotted against dose alone. Plotting biological effects against dose × LET significantly over-estimated the impact of LET on cell survival, and typically produced even larger spreads in biological effect. LET-weighted dose was shown to have superior correlation to biological effect in both experimental data and clinical plans. For prostate and medulloblastoma treatment plans, the average RBE-associated variability in biological effect is ±5% of the prescribed dose, but is reduced to less than 1% using LET-weighting. While not a replacement for full RBE models, simplified metrics such as this LET-weighted dose can be used to account for the majority of variability which arises from the LET-dependence of RBE with reduced need for biological parameterisation. These metrics may be used to identify regions in normal tissues which may see unexpectedly high effects due to end-of-range elevations of RBE, or as part of a more general tool for biological optimisation in proton therapy.
Original languageEnglish
JournalPhysics in Medicine and Biology
Early online date16 Oct 2018
DOIs
Publication statusPublished - 09 Nov 2018

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