Towards Real Time Radiotherapy Simulation

Nils Voss*, Peter Ziegenhein, Lukas Vermond, Joost Hoozemans, Oskar Mencer, Uwe Oelfke, Wayne Luk, Georgi Gaydadjiev

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)
22 Downloads (Pure)


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.

Original languageEnglish
Pages (from-to)949-963
Number of pages15
JournalJournal of Signal Processing Systems
Issue number9
Publication statusPublished - 2020


  • Dataflow
  • Dose calculation
  • FPGA acceleration
  • Monte Carlo simulation
  • Radiotherapy


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