Agility MLC transmission optimization in the Monaco treatment planning system

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Dosimetry

Background:

• The Monaco Monte Carlo treatment planning system (TPS) relies on components like virtual source models (VSM) and transmission probability filters (TPFs) for accurate dose calculations.
• Accurate dose calculation is critical for effective radiation therapy planning and patient outcomes.

Purpose of the Study:

• To assess and optimize the transmission probability filter (TPF) component of the Monaco TPS.
• To improve the accuracy of dose calculations using an Elekta linear accelerator with an Agility™ multileaf collimator (MLC).

Main Methods:

• Systematic optimization of TPF parameters using measurements from an Elekta linear accelerator and Agility™ MLC.
• Characterization of individual TPF parameters against vendor-provided and additional test fields.
• Validation using point dose measurements and 3D gamma analysis with Octavius 4D.

Main Results:

• Optimized TPF parameters significantly improved point dose measurements, reducing average differences in low-dose regions from 4.4% to 0.9%.
• 3D gamma analysis pass rates increased to over 95% (2%/2mm criteria) with the optimized model, compared to as low as 88.4% with default parameters.
• The optimization process demonstrated a rigorous method for characterizing TPF transmission.

Conclusions:

• Adjustment of TPF parameters in the Monaco TPS leads to enhanced dose calculation accuracy.
• The study provides a step-by-step guide for optimizing TPF parameters, recommending this systematic approach over random selection for reliable clinical results.