SU‐E‐J‐63: Estimating the Effects of Respiratory Motion On Dose Heterogeneity for ITV‐Based Treatments

Abstract

Purpose:To quantify the relationship between the amount of dose heterogeneity in a treatment plan that uses an internal target volume (ITV) to account for respiratory motion and the true amount of heterogeneity in the dose delivered to the tumor contained within that ITV.Methods:We develop a convolution‐based framework for calculating dose delivered to a tumor moving inside an ITV according to a common sinusoid‐based breathing model including asymmetry. We model the planned ITV dose distribution as a centrally peaked analytic function approximating the profile of clinical stereotactic body radiotherapy treatments. Expressions for the minimum and maximum dose received by the tumor are derived and evaluated for a range of clinically relevant parameters. Results of the model are validated with phantom measurements using an ion chamber array.Results:An analytic expression is presented for the maximum and minimum doses received by the tumor relative to the planned ITV dose. The tumor dose heterogeneity depends solely on the ratio of tumor size to ITV size, the peak dose in the planned ITV dose distribution, and the respiratory asymmetry parameter. Under the assumptions of this model, using a typical breathing asymmetry parameter and a dose distribution with a fixed size ITV covered by the 100% line and with a 130% hotspot, the maximum dose to the tumor varies between 113%–130%, and the minimum dose varies between 100%–116% depending on the amount of tumor motion.Conclusion:This modeling exercise demonstrates the interplay between motion and dose heterogeneity. Tumors that exhibit large amounts of respiratory motion relative to their size will receive a more homogeneous dose and a larger minimum dose than would be inferred from the ITV dose distribution. This effect is not captured in current clinical treatment planning methods unless 4D dose calculation techniques are used.This work was partially supported by a Varian Medical Systems research grant