A treatment planning algorithm optimizing TCP based on a dose rate dependent LQ-model.

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     Planning objectives in the Gamma Knife® Radio Surgery are in general to have a high coverage and selectivity of the planning iso-dose to the target as well as low dose to surrounding tissue and organs at risk (OARs). The basic assumption is that there is a strong correlation between the clinical outcome and the physical prescribed dose. As has been pointed out by several authors the radiobiological effect may also be dependent on overall treatment time, a function of both the dose-rate in tissue and the number of iso-centers used, for which models that have been developed that take these variables into account.
     The purpose of this study is to discuss planning based on radiobiological models rather than physical dosimetric based objectives.
     A prototype version of the inverse planning software in Leksell Gamma Plan® has been developed that optimizes the tumor control probability (TCP) calculated with a modified LQ-model suggested by J. Hopewell, B. Millar et al. This model depends explicitly on the dose rate as a function of time during the treatment delivery. Penalty functions for OARs are also incorporated in the optimization. For several clinical indications TCP-optimized plans have been derived and compared to plans based on dose metrics (coverage, selectivity and dose gradients). Plans with similar dose metrics but with different number of iso-centers have been generated to see the influence of dose-rate on TCP. To the test the sensitivity on the outcome the parameter ? and ? as well as the half-times repair of sublethal radiation damage have been varied.
     The suggested method makes it possible to create plans optimized with regards to TCP determined by models incorporating dose-rate. TCP optimized plans will in general be different to plans based on optimized dose metrics.
     A framework has been created that makes it possible to include radiobiological objectives into dose plan optimization.
     This concept may help to define a new dose planning approach.


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