Planning lung radiotherapy using 4D CT data and a motion model.

This work is a feasibility study to use a four-dimensional computed tomography (4D CT) dataset generated by a continuous motion model for treatment planning in lung radiotherapy. The model-based 4D CT data were derived from multiple breathing cycles. Four patients were included in this retrospective study. Treatment plans were optimized at end-exhale for each patient and the effect of respiratory motion on the dose delivery investigated. The accuracy of the delivered dose as determined by the number of intermediate respiratory phases used for the calculation was considered. The time-averaged geometry of the anatomy representing the mid-ventilation phase of the breathing cycle was generated using the motion model and a treatment plan was optimized for this phase for one patient. With respiratory motion included, the mid-ventilation plan achieved better target coverage than the plan optimized at end-exhale when standard margins were used to expand the clinical target volume (CTV) to planning target volume (PTV). Using a margin to account for set-up uncertainty only, resulted in poorer target coverage and healthy tissue sparing. For this patient cohort, the results suggest that conventional three-dimensional treatment planning was sufficient to maintain target coverage despite respiratory motion. The motion model has proved a useful tool in 4D treatment planning.