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Fast Monte Carlo dose calculation in proton therapy.

Jason HolmesHongying FengLian ZhangMichael K FixSteve B JiangWei Liu
Published in: Physics in medicine and biology (2024)
This article examines the critical role of fast Monte Carlo dose calculations in advancing proton therapy techniques, particularly in the context of increasing treatment customization and precision. As adaptive radiotherapy and other patient-specific approaches evolve, the need for accurate and precise dose calculations, essential for techniques like proton-based stereotactic radiosurgery, becomes more prominent. These calculations, however, are time-intensive, with the treatment planning/optimization process constrained by the achievable speed of dose computations. Thus, enhancing the speed of Monte Carlo methods is vital, as it not only facilitates the implementation of novel treatment modalities but also leads to more optimal treatment plans. Today, the state-of-the-art in Monte Carlo dose calculation speeds is 10<sup>6<sup> - 10 7 protons per second. This review highlights the latest advancements in fast Monte Carlo dose calculations that have led to such speeds, including emerging artificial intelligence-based techniques, and discusses their application in both current and emerging proton therapy strategies.
Keyphrases
  • monte carlo
  • artificial intelligence
  • primary care
  • healthcare
  • deep learning
  • squamous cell carcinoma
  • combination therapy
  • radiation induced
  • replacement therapy
  • molecular dynamics
  • rectal cancer
  • electron transfer