Further investigation of 3D dose verification in proton therapy utilizing acoustic signal, wavelet decomposition and machine learning

Songhuan Yao, Zongsheng Hu, Qiang Xie, Yidong Yang, Hao Peng

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Online dose verification in proton therapy is a critical task for quality assurance. We further studied the feasibility of using a wavelet-based machine learning framework to accomplishing that goal in three dimensions, built upon our previous work in 1D. The wavelet decomposition was utilized to extract features of acoustic signals and a bidirectional long-short-term memory (Bi-LSTM) recurrent neural network (RNN) was used. The 3D dose distributions of mono-energetic proton beams (multiple beam energies) inside a 3D CT phantom, were generated using Monte-Carlo simulation. The 3D propagation of acoustic signal was modeled using the k-Wave toolbox. Three different beamlets (i.e. acoustic pathways) were tested, one with its own model. The performance was quantitatively evaluated in terms of mean relative error (MRE) of dose distribution and positioning error of Bragg peak (Δ {BP}), for two signal-to-noise ratios (SNRs). Due to the lack of experimental data for the time being, two SNR conditions were modeled (SNR = 1 and 5). The model is found to yield good accuracy and noise immunity for all three beamlets. The results exhibit an MRE below 0.6% (without noise) and 1.2% (SNR = 5), and Δ BP below 1.2 mm (without noise) and 1.3 mm (SNR = 5). For the worst-case scenario (SNR = 1), the MRE and Δ BP are below 2.3% and 1.9 mm, respectively. It is encouraging to find out that our model is able to identify the correlation between acoustic waveforms and dose distributions in 3D heterogeneous tissues, as in the 1D case. The work lays a good foundation for us to advance the study and fully validate the feasibility with experimental results.

Original languageEnglish (US)
Article number015008
JournalBiomedical Physics and Engineering Express
Volume8
Issue number1
DOIs
StatePublished - Jan 2022
Externally publishedYes

Keywords

  • acoustic signal
  • dose verification
  • machine learning
  • proton therapy
  • wavelet

ASJC Scopus subject areas

  • Biophysics
  • Bioengineering
  • Biomaterials
  • Physiology
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications
  • Health Informatics

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