Single proton LET characterization with the Timepix detector and artificial intelligence for advanced proton therapy treatment planning
Language English Country Great Britain, England Media electronic
Document type Journal Article, Research Support, Non-U.S. Gov't
- Keywords
- Monte Carlo simulations, Timepix, artificial neural networks, linear energy transfer, particle tracking, proton therapy, relative biological effectiveness,
- MeSH
- Radiotherapy Dosage MeSH
- Humans MeSH
- Linear Energy Transfer MeSH
- Monte Carlo Method MeSH
- Proton Therapy * methods MeSH
- Protons MeSH
- Radiometry MeSH
- Artificial Intelligence MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- Protons MeSH
Objective.Protons have advantageous dose distributions and are increasingly used in cancer therapy. At the depth of the Bragg peak range, protons produce a mixed radiation field consisting of low- and high-linear energy transfer (LET) components, the latter of which is characterized by an increased ionization density on the microscopic scale associated with increased biological effectiveness. Prediction of the yield and LET of primary and secondary charged particles at a certain depth in the patient is performed by Monte Carlo simulations but is difficult to verify experimentally.Approach.Here, the results of measurements performed with Timepix detector in the mixed radiation field produced by a therapeutic proton beam in water are presented and compared to Monte Carlo simulations. The unique capability of the detector to perform high-resolution single particle tracking and identification enhanced by artificial intelligence allowed to resolve the particle type and measure the deposited energy of each particle comprising the mixed radiation field. Based on the collected data, biologically important physics parameters, the LET of single protons and dose-averaged LET, were computed.Main results.An accuracy over 95% was achieved for proton recognition with a developed neural network model. For recognized protons, the measured LET spectra generally agree with the results of Monte Carlo simulations. The mean difference between dose-averaged LET values obtained from measurements and simulations is 17%. We observed a broad spectrum of LET values ranging from a fraction of keVμm-1to about 10 keVμm-1for most of the measurements performed in the mixed radiation fields.Significance.It has been demonstrated that the introduced measurement method provides experimental data for validation of LETDor LET spectra in any treatment planning system. The simplicity and accessibility of the presented methodology make it easy to be translated into a clinical routine in any proton therapy facility.
ADVACAM Prague 17000 Czech Republic
Baylor University Waco TX 76706 Texas United States of America
Faculty of Mathematics and Physics Charles University Prague 18000 Czech Republic
Institute of Nuclear Physics Polish Academy of Sciences PL 31342 Krakow Poland
Loma Linda University Loma Linda CA 92350 California United States of America
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