Exploitation of the charge sharing effect in Timepix device to achieve sub-pixel resolution in imaging applications with alpha particles.

Teyssier, C.; Guerin, P.; Bergeron, G.; Dallaire, F.; Leroy, Claude; Pospı́šil, S.; Trudeau, Yves

doi:10.1142/9789814405072_0101

Cited by 2 publications

(1 citation statement)

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“…the geometric details of the gantry nozzle and the aluminum case of the detector were neglected. Also, the pixelated structure and charge-sharing effect (Campbell et al 2007, Bouchami et al 2011c, Teyssier et al 2012, Šolc et al 2022 occurring in the Timepix sensor were not included in the MC simulations. However, it is unlikely that these details have a substantial impact on the MC simulationʼs accuracy.…”

Section: Discussionmentioning

confidence: 99%

Single proton LET characterization with the Timepix detector and artificial intelligence for advanced proton therapy treatment planning

et al. 2023

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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 keV/um to about 10 keV/um for 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 LET_D or 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.

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Section: Discussionmentioning

confidence: 99%