Abstract
We propose a novel reconfigurable hardware architecture to implement Monte Carlo based simulation of physical dose accumulation for intensity-modulated adaptive radiotherapy. The long term goal of our effort is to provide accurate dose calculation in real-time during patient treatment. This will allow wider adoption of personalised patient therapies which has the potential to significantly reduce dose exposure to the patient as well as shorten treatment and greatly reduce costs. The proposed architecture exploits the inherent parallelism of Monte Carlo simulations to perform domain decomposition and provide high resolution simulation without being limited by on-chip memory capacity. We present our architecture in detail and provide a performance model to estimate execution time, hardware area and bandwidth utilisation. Finally, we evaluate our architecture on a Xilinx VU9P platform as well as the Xilinx Alveo U250 and show that three VU9P based cards or two Alevo U250s are sufficient to meet our real time target of 100 million randomly generated particle histories per second.
Highlights
Radiotherapy is a commonly used treatment for various cancer types
In our work we will focus on the Dose Planning Method (DPM) [18] implementation of a Monte Carlo technique that simulates the dosimetric effect of high energy photons in organic materials
We show FieldProgrammable Gate Arrays (FPGAs) and total runtime separately
Summary
Radiotherapy is a commonly used treatment for various cancer types. High doses of radiation are used to kill cancer cells. In order to validate and optimise such therapy plans, the expected spatial dose distribution within the patient has to be simulated before the actual treatment This is often implemented by Monte Carlo methods which simulate the pathway of millions of radiation particle. Using Monte Carlo simulations to calculate the dose distribution in radiotherapy is widely considered to be the most accurate method This process relies on simulating individual particles and their trajectories through material representing the patient. In our work we will focus on the Dose Planning Method (DPM) [18] implementation of a Monte Carlo technique that simulates the dosimetric effect of high energy photons in organic materials This algorithm is optimised for the radio therapy use case. The latter reduces the simulation time of electron interactions significantly
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