Towards real time radiotherapy simulation
Nils Voss (Imperial College London, Maxeler Technologies)
Peter Ziegenhein (Royal Marsden NHS Foundation Trust)
Lukas Vermond (Student TU Delft, Maxeler Technologies)
Joost Hoozemans (Maxeler Technologies)
Oskar Mencer (Maxeler Technologies)
Uwe Oelfke (Royal Marsden NHS Foundation Trust)
Wayne Luk (Imperial College London)
Georgi Gaydadjiev (Maxeler Technologies, TU Delft - Data-Intensive Systems, Imperial College London)
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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 online 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 and show that three cards are sufficient to meet our real time target of 100 million randomly generated particle histories per second.