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Automated decision support tool for static angle modulated ports configuration in VMAT with dynamic collimator
Hideaki Hirashima1, Takahiro Iwai1, Shinya Hiraoka1
1Department of Radiation Oncology and Image-Applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Background:
RapidArc Dynamic (RAD; Varian Medical Systems, Palo Alto, CA) is a novel volumetric modulated arc therapy (VMAT) technique that features dynamic collimator rotation synchronized with gantry rotation. RAD enables the use of static angle-modulated ports (STAMPs) defined by user selected gantry and collimator angles. However, the determination of STAMP configurations currently relies on manual trial-and-error procedures based on planner experience, which limits the efficient clinical implementation of this functionality.
Purpose:
This study aimed to develop an automated decision support tool using an Eclipse Scripting Application Programming Interface (ESAPI; Varian Medical Systems) to identify cost-optimized STAMP configurations and evaluate its clinical utility in complex head and neck cancer planning.
Methods:
Twenty patients with nasopharyngeal or sinonasal cancer who had previously received radiotherapy at our institution were retrospectively analyzed. Four treatment plans were generated for each patient: conventional VMAT using RapidArc (RA, Varian Medical Systems), RAD with manually defined STAMPs (RADm) by an expert radiation oncologist, RAD with a vendor-provided automatic collimator rotation algorithm (RADa), and RAD using the proposed decision support tool (RADdst). The developed algorithm determined the STAMP configurations in three phases: (1) generation of a two-dimensional geometric cost map across the gantry and collimator angles by integrating planning target volume-fit and organ-at-risk (OAR)-avoidance terms, (2) extraction of a cost-minimizing collimator trajectory, and (3) identification of cost-optimized STAMP positions in geometrically critical regions that require substantial collimator rotation while satisfying machine-specific rotation-speed constraints. The dosimetric indices of the targets and OARs, optimization calculation times, and estimated beam delivery times were evaluated.
Results:
The ESAPI-based tool successfully generated dosimetrically feasible RADdst plans for all patients, automatically selecting between two and ten STAMPs according to anatomical complexity. All planning techniques achieved clinically acceptable target coverage and OAR sparing. In nasopharyngeal cancer cases, all RAD approaches significantly reduced the oral cavity dose compared with RA (RADm, p = 0.02; RADa, p = 0.002; RADdst, p = 0.002), and RADdst additionally achieved a significant reduction in the left lens dose (p = 0.008). In sinonasal cancer cases, significant differences were observed among the techniques for seven OAR dosimetric metrics (p < 0.05), whereas the target coverage remained comparable across all techniques. The optimization calculation time was reduced by approximately 40% for all RAD approaches compared with RA (p < 0.01). Furthermore, all RAD techniques reduced the estimated beam delivery time by approximately 20% relative to RA (p < 0.01).
Conclusions:
An automated ESAPI-based decision support tool for STAMP configuration in RAD planning was successfully developed. The proposed geometric cost-based framework achieved a dosimetric performance comparable to both expert-defined manual STAMP planning and the vendor-provided automatic collimator rotation approach, while eliminating the need for manual STAMP determination. These findings support the feasibility of the automated STAMP configuration as a practical strategy for enabling an efficient and planner-independent implementation of RAD planning.

