SU‐E‐T‐651: A Novel Non‐Uniformly Distributed Control Points‐Based Algorithm for VMAT Treatment Plan Optimization

Abstract

Purpose: To develop a new method for adding control points to volumetric modulated arc therapy (VMAT) optimization in non‐uniformly distributed scheme that improves the delivery efficiency and dose distribution. Methods: The algorithm generates piecewise constant fluence maps using total‐variation regulation (TVR) for each beam direction. The optimized fluence maps of one fluence profile per the initial arc spacing of 6° are distributed as coarse sampling of control points over a single arc, 360°. From the initial control points having an aperture sequence {A(0), …, A(N)}, each association {A(0)‐A(1), …, A(N‐1)‐A(N)} of apertures is assigned a mutual information(MI) score. A new control point (B0) is added to the mid‐point of two apertures {A(0)‐B(0)‐A(1)} in which the {A(0)‐A(1)} association has the lowest MI score having the biggest aperture shape difference. A new shape of aperture at B(0) is created by the interpolation of the adjacent apertures. The aperture shape is then rectified to be a sequencing of arc using the manufacture constraints. The implemented plan optimization is evaluated using clinical cases of head neck, lung, and prostate previously treated with a Varian TrueBeam™STX linac. Results: The propose method with non‐uniformly distributed 120 control points reduced the dose delivery time approximately 32%, 26%, and 30% compared to the uniformly distributed 180 control points for head neck, lung, and prostate plans, respectively. The target dose coverage and critical structure sparing of plans obtained using the proposed method with non‐uniformly distributed 120 control points are almost identical to those obtained using the conventional method with 180 control points uniformly distributed. Conclusion: The results demonstrate that non‐uniformly distributed control points‐based VMAT plan optimization reduced the dose delivery time and slightly improved dose conformity. This new algorithm can substantially provide future station mediated planning parameters. This work was supported in part by Korean grants from the National Research Foundation of Korea (NRFK) of the Korea government (MEST) (No.K20901000001‐09E0100‐00110) and the National Cancer Institute (1R01 CA133474).