Monte Carlo-based simulation of dynamic jaws tomotherapy.

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Modeling

Background:

• Original TomoTherapy systems face limitations in balancing treatment conformity and speed due to fixed slice widths.
• Implementing arbitrary field sizes, especially narrow ones (<1 cm), presents challenges for existing beam models.

Purpose of the Study:

• To incorporate dynamic jaws functionality into the TomoPen Monte Carlo (MC) model, enhancing its capabilities for radiation therapy.
• To validate the modified TomoPen model against established methods and experimental measurements.

Main Methods:

• Developed a simulation strategy using weight modifiers derived from a simplified FastStatic MC model to accommodate dynamic jaw settings efficiently.
• Implemented actual dynamic jaws simulation within the TomoPen model, based on the PENELOPE MC code.
• Validated the model by comparing simulations with convolution/superposition (C/S) methods and EDR2 film measurements in a 'cheese' phantom.

Main Results:

• FastStatic-derived weight modifiers showed equivalence to pure MC calculations within 0.5% statistical uncertainty.
• TomoPen with dynamic jaws demonstrated excellent agreement (<2%/2 mm) with C/S methods for both asymmetric and symmetric jaw optimizations.
• Experimental validation confirmed agreement within 2%/2 mm (95% of points) and 3%/3 mm (98% of points) using gamma analysis for the running start stop (RSS) procedure.

Conclusions:

• The integration of dynamic jaws and couch features into TomoPen was achieved efficiently using weight modifiers and interpolation.
• The enhanced TomoPen model provides accurate dose calculations for dynamic jaw configurations with minimal computational overhead.