Poster Poster Program Therapy Physics

Development of a Decision Support Tool for Optimizing the Configuration of the Static Angle Modulated Ports

Abstract
Purpose

To develop a decision support tool for optimizing the configuration of the static angle modulated ports (STAMPs), including the number of ports, gantry angles and collimator angles, using an Eclipse Scripting API (ESAPI) for RapidArc Dynamic (RAD), based on BEV geometric and mechanical constraints, and to evaluate its dosimetric superiority for sinonasal cancer compared with conventional VMAT.

Methods

Treatment plans for 10 patients with sinonasal cancer were retrospectively generated using 3-arcs coplanar VMAT and 1-2 arcs RAD. The prescribed dose was 70 Gy (D50% to PTV70) in 35 fractions. A custom script was developed using ESAPI to generate BEV-based cost map by combining a PTV-fitting term with an OAR-avoidance term for selected OARs. Preferred collimator angles at each gantry position were determined through cost minimization. The optimal configuration of STAMPs was automatically identified at high-cost inflection points where the required collimator rotation exceeded the dynamic limit relative to gantry speed. VMAT and RAD plans were optimized using identical objectives. Plan quality was evaluated using dose-volume metrics, optimization time, estimated delivery time, modulation complexity score (MCS). Statistical comparisons were performed using the Wilcoxon-signed rank test.

Results

The decision support tool automatically selected between 2 and 10 STAMPs per plan according to geometric complexity. Both techniques achieved comparable PTV coverage. Compared with VMAT, RAD plans demonstrated significant reductions in the eyes Dmax (-8%), lenses Dmax (-22%), oral cavity Dmean (-12%) and parotid Dmean (-14%) (p<0.05). The RAD approach also resulted in significant reduction in optimization time (-44%, p<0.001) and estimated delivery time (-34%, p<0.001). The MCS was significantly lower for RAD (0.29±0.02) than for VMAT (0.38±0.04, p<0.001).

Conclusion

The proposed decision support tool successfully determined optimal STAMP configurations without manual trial-and-error. This approach significantly improved OAR sparing and planning efficiency in sinonasal cancer cases, despite using fewer arcs than conventional VMAT.

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