Multiple direction needle-path planning and inverse dose optimization for robotic low-dose rate brachytherapy

Area of Science:

• Medical Physics
• Radiation Oncology
• Robotics in Medicine

Background:

• Robotic systems offer potential for precise needle placement in brachytherapy.
• Current systems are limited by path planning around critical structures.
• Conformal dose planning requires advanced optimization algorithms.

Purpose of the Study:

• To develop and evaluate a treatment planning system (TPS) integrating multi-directional needle-path planning with inverse dose optimization for low-dose-rate brachytherapy.
• To enable conformal dose planning by overcoming limitations of path planning around risk structures.

Main Methods:

• Investigated a path planning algorithm to identify optimal needle trajectories avoiding critical structures.
• Developed a modular inverse radiation plan optimization algorithm including greedy, remove-seed, depth, and coverage optimizers.
• Benchmarked dose calculation and inverse optimization using a phantom liver metastasis model and compared with a commercial TPS via global gamma analysis.

Main Results:

• Path planning algorithm reduced potential injection points by 72.5%.
• Global gamma analysis (1%=2.9Gy, 1mm) achieved a 98.5% pass rate, indicating good agreement with commercial TPS.
• Achieved excellent dose coverage (V100=99.1±0.3%, D90=125.9±3.6Gy) with 10.7±1.3 needles and 34.0±0.8 seeds in a median TPS running time of 4.4 minutes.

Conclusions:

• The developed TPS generates clinically acceptable treatment plans efficiently.
• The system demonstrates good agreement with commercial TPS, validating its accuracy.
• This TPS leverages robotic navigation for precise, safe, and minimally invasive low-dose-rate brachytherapy.