Radiotherapy Monte Carlo simulation using cloud computing technology

Area of Science:

• Medical Physics
• Computational Science
• Radiotherapy

Background:

• Cloud computing provides scalable computational power on demand.
• Monte Carlo methods are crucial for accurate radiotherapy dose calculations.
• GEANT4 is a toolkit for simulating particle transport through matter.

Purpose of the Study:

• To present a technique for performing Monte Carlo radiotherapy dose calculations in the cloud using GEANT4.
• To evaluate the impact of machine count on simulation cost and completion time.
• To demonstrate the feasibility of cloud-based Monte Carlo simulations for radiotherapy.

Main Methods:

• Utilized cloud computing infrastructure for GEANT4 simulations.
• Performed Monte Carlo radiotherapy dose calculations.
• Analyzed simulation completion time and relative cost as a function of parallel machine count (n).

Main Results:

• Simulation completion time showed a decrease proportional to 1/n with n parallel machines.
• Relative simulation cost was found to be optimal when n was a factor of the total simulation time in hours.
• Successfully executed Monte Carlo simulations in the cloud.

Conclusions:

• Cloud computing is a viable solution for rapid Monte Carlo simulations in radiotherapy.
• This technique eliminates the need for dedicated local hardware for complex dose calculations.
• The findings support the use of cloud resources for efficient radiotherapy planning.