Strategizing Static Angle Modulated Ports (STAMPs) Configuration In Rapidarc Dynamic (RAD) Planning for Lung Radiation Therapy
Abstract
Purpose
The novel treatment delivery technique RapidArc Dynamic (RAD), which combines dynamic gantry motion with static angle–modulated ports (STAMPs), offers strong potential for advanced planning and improved plan quality. However, a major challenge in clinical implementation is determining the optimal configuration of STAMPs. This study aims to develop an automated framework for optimal STAMPs selection for lung radiation therapy.
Methods
A STAMP efficiency index (SEI) was defined for each target voxel as a function of voxel location and candidate beam direction. The SEI was computed by integrating dose contributions to the target volume, organs at risk (OARs), and surrounding normal tissues along the beam path. To account for the combined effects of multiple STAMPs, an additional constraint based on a spring-coupled mass model was introduced to quantify STAMP angular dispersion. By summing the voxel-level SEI and the dispersion term, a total efficiency index (TEI) was obtained for each multi-STAMP configuration. The optimal STAMP angle set was then determined by minimizing the TEI using a greedy optimization algorithm. Eight lung cancer patients treated with volumetric modulated arc therapy (VMAT, 7-case) or intensity modulated radiation therapy (IMRT, 1-case) were included under IRB approval. RAD plans were generated using a single full arc integrated with seven STAMPs corresponding to the optimized configurations for 2Gy/30Fx. Plan quality was evaluated against clinically approved plans at key dosimetric endpoints.
Results
RAD plans with optimized STAMP configurations demonstrated improved target conformity compared with clinical plans (conformity index: 1.02 vs. 1.06). In addition, RAD plans achieved comparable or improved OAR sparing, including reduced lung V20% (18.4% vs. 20.0%) and lower maximum spinal cord dose (30.3 Gy vs. 32.9 Gy).
Conclusion
An automated STAMP configuration framework for RAD lung planning is proposed. This approach streamlines the RAD planning workflow and demonstrates dosimetric improvement compared with conventional IMRT/VMAT plans.