TH-EF-BRD-05: A New Intensity Modulation Radiation Therapy (IMRT) Optimizer Solution with Robust Fluence Maps for XXXX Segmentation.

@entity1 @entity3097 @entity343
PURPOSE: Converting theoretical fluence maps to deliverable @entity3097 segments while maintaining plan quality has posed a significant challenge for highly complex IMRT plans involving many fields. Rather than simplifying individual fluence maps, we have formulated the problem as a global dose domain fluence map optimization with anisotropic total variation regularization (FMOATVR) problem and then solve the large scale optimization problem. METHODS: The 4   planning platform was used to select and optimize 20 non-coplanar beams for 2 GBM, 2 head _ neck, and 2 lung @entity1 with varying prescription doses, including H_N case #2 that had 3 prescription dose levels of 54 Gy, 59.4 Gy, and 69.96 Gy. The plans were re-run using FMOATVR and the same 20 4   beams. The L2 norm of dose deviation from the ideal prescription with zero dose to OARs was used as the objective function, which was subjected to anisotropic total variation regularization to encourage piecewise smoothness in the fluence maps. The fluences were stratified into equal step sizes to create 300 @entity3097 segments. The dose distributions were normalized so the prescription dose covered cover 95% of the @entity343 . H_N case #2 was normalized to cover the 59.4 Gy @entity343 , which was included in the statistics. RESULTS: Compared to the directly stratified 4   plans (4   DS), the 4   FMOATVR method reduced the average mean and max dose to the OARs by 3.54% and 4.15%, respectively, of the prescription dose. Dose coverage was also improved, evidenced by an average D98 and D99 increase of 1.63% and 2.74% of the prescription dose, respectively. The average @entity343 homogeneity was increased from 0.833 to 0.905. CONCLUSION: The global dose domain fluence map optimization formula and its solver provides a straightforward yet potent method to attain high quality while remaining robust to @entity3097 segmentation for complex IMRT. This work is supported in part by Varian Medical Systems, Inc.
