AbstractID: 7910 Title: Non-linear image registration techniques to account for variable anatomy in
radiotherapy
In radiation therapy of cancer, uncertainties due to changes in patient anatomy during the course of treatment are a major
concern. These uncertainties may lead to differences between the planned dose distribution and the actual dose distribution delivered
to the patient and may have adverse impact on the treatment outcome. In current radiotherapy protocols, the dose distribution is
computed assuming one instance of the patient’s anatomy based on a CT image taken before treatment. This is not realistic since the
human anatomy changes from day to day. The goal of this research is to calculate the dose distribution received by the patient while
accounting for variable anatomy. We use non-linear image registration techniques to combine the dose distributions computed for
each serial CT image taken during treatment. The method involves using the thin-plate spline algorithm to “warp” the patient’s pretreatment image to each serial image. Then, since each volume element within the pre-treatment image can be tracked, the daily dose
distribution can be mapped back to the pre-treatment image. This re-mapping is necessary for display purposes and for accumulating
the dose distribution delivered to each tissue element. The dose distribution uncertainty is the difference between the dose
distributions with and without accounting for variable anatomy. We demonstrate that there are significant localized errors (>10%) in
the daily dose distribution due to changes in organ shape (5-10 mm) using a simulated prostate example. We believe that this work
will be important for enabling adaptive radiation treatments in radiotherapy and tomotherapy.