AbstractID: 7989 Title: Gated Motion Adaptive Therapy (GMAT): Average Tumor Trajectory for Lung
Patients
In order to improve the effectiveness and efficiency of IMRT for treating mobile tumors in thorax and
abdomen, we have proposed a technique called Gated Motion Adaptive Therapy (GMAT). GMAT is a
combination of respiratory gating and tumor tracking with dMLC. The original IMRT leaf sequence is
modified to compensate for tumor motion based on average tumor trajectory (ATT). In the present study, we
have developed a method to derive ATT for each patient and investigated its validity for lung tumor. The
tumor trajectory data for 20 patients with 22 lung tumors, obtained during gated radiotherapy using a real-time
tumor-tracking system, were used for this study. The velocity of the tumor as a function of time was calculated
to identify the phases in breathing cycle. The average period was calculated after discarding some outliers.
ATT was derived by averaging tumor position at each phase of remaining ‘good’ cycles. The derived ATT has
been validated by simulating the GMAT treatment. The radiation beam moves along ATT while the tumor
moves according to measured data. When phase shift between measured data and ATT was greater than a
tolerance, the treatment was on halt until two phases matched again. The error of using ATT for tumor tracking
was calculated during beam-on time. It is found that, for lung patients with regular breathing pattern, the ATT
concept is valid; the error in tumor tracking can be controlled to within a few millimeters while keeping
delivery efficiency greater than 80%.
Supported by the Whitaker Foundation.