Optimization of dynamic multi-leaf collimator based on multi-objective particle swarm optimization algorithm.

Abstract

Background: The dynamic multi-leaf collimator (DMLC) plays a crucial role in shaping X-rays, significantly enhancing the precision, efficiency, and quality of tumor radiotherapy.

Objective: To improve the shaping effect of X-rays by optimizing the end structure of the DMLC leaf, which significantly impacts the collimator's performance.

Methods: This study introduces the innovative application of the multi-objective particle swarm optimization (MOPSO) algorithm to optimize DMLC parameters, including leaf end radius, source-to-leaf distance, leaf height, and tangent angle between the leaf end and the central axis. The main optimization objectives are to minimize the width and variance of the penumbra, defined as the distance between the 80% and 20% dose of X-rays on the isocenter plane, which directly impacts treatment accuracy.

Results: Structural optimization across various scenarios showed significant improvements in the size and uniformity of the penumbra, ensuring a more precise radiation dose. Based on the optimized structure, a three-dimensional model of the MLC was designed and an experimental prototype was fabricated for performance testing. The results indicate that the optimized MLC exhibits a smaller penumbra.

Conclusion: The proposed optimization method significantly enhances the precision of radiotherapy while minimizing radiation exposure to healthy tissue, representing a notable advancement in radiotherapy technology.