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Towards machine learning aided real-time range imaging in proton therapy.

Jorge Lerendegui-Marco1, Javier Balibrea-Correa2, Víctor Babiano-Suárez2

  • 1Instituto de Física Corpuscular, CSIC-University of Valencia, Valencia, Spain. jorge.lerendegui@ific.uv.es.

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Summary

The i-TED detector shows promise for proton therapy range verification, offering improved signal-to-background ratios and efficient real-time monitoring. Its design enhances accuracy in hadron therapy by reducing neutron sensitivity and leveraging machine learning.

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Area of Science:

  • Medical Physics
  • Nuclear Instrumentation
  • Radiation Detection

Background:

  • Proton therapy requires precise range verification for effective cancer treatment.
  • Compton imaging is a developing technique for monitoring proton range.
  • Existing detectors face challenges with high-energy photons and neutron backgrounds.

Purpose of the Study:

  • To evaluate the i-TED detector's suitability for proton range monitoring in hadron therapy.
  • To assess the i-TED detector's performance using Monte Carlo simulations.
  • To investigate improvements in signal-to-background ratios and efficiency for real-time monitoring.

Main Methods:

  • Monte Carlo simulations were used to model the i-TED detector's response.
  • The i-TED detector's design, featuring LaCl[Formula: see text] crystals and a two-plane configuration, was analyzed.
  • Performance metrics including signal-to-background ratio, time resolution, and coincidence efficiency were calculated.
  • Machine-learning algorithms were employed to enhance signal processing for high-energy photons.

Main Results:

  • The i-TED detector demonstrated improved signal-to-background ratios compared to LYSO, CdZnTe, and LaBr[Formula: see text] systems.
  • High time resolution (CRT < 500 ps) aids background suppression in pulsed hadron therapy.
  • A coincidence efficiency of 0.2% for a 1 MeV gamma-ray source was achieved with four i-TED modules.
  • Machine learning enhanced the signal-to-total ratio by a factor of 2 for high-energy photons.

Conclusions:

  • The i-TED detector is a promising tool for real-time proton range verification in hadron therapy.
  • Its design offers advantages in efficiency, neutron background reduction, and high-energy photon detection.
  • Further development and application in clinical settings are warranted.