AbstractID: 7940 Title: The Use of Convolution for Modeling Patient Repositioning and Organ Motion for Radiation
Treatment Planning
The motion of the tumour or organs within the patient inevitably leads to uncertainty in the dose distribution received during radiation
therapy. One method of accounting for this is to incorporate the effect of geometric uncertainties directly into the dose calculation during treatment
planning. This may be accomplished by convolution of the intended static dose distribution with a probability density function (PDF) describing the
geometric uncertainties. Convolution of the static dose distribution with a PDF provides excellent results through the bulk of the patient volume,
although it is inaccurate near the surface. Uncorrected, this inaccuracy limits the use of Convolution for many clinical sites (e.g., head and neck). A
second problem is that Convolution assumes the entire patient anatomy moves uniformly. In this work, a correction method is described that
overcomes the surface error limitation. A method of using multiple convolutions is used to predict the dose distribution for multiple mobile organs is
also demonstrated. A clinical example is used to demonstrate the use of these methods during treatment planning. This example demonstrates the
significance of performing surface corrections (9% difference in CTV minimum dose). The independent mobility of the CTV is less significant in
this example. Comparison to conventional treatment planning with a static anatomy demonstrates the impact of using uncertainty information during
treatment planning, illustrating a 9% difference in the maximum dose to the larynx. This work demonstrates Convolution methods can be effective
for modeling the effect of patient repositioning and organ motion in radiation treatment planning.