Backgroundand Purpose: FLASH radiotherapy has aroused strong interest among researchers, but how to monitor dose in real time and lack of generally accepted ion correction model are one of the challenges. This study is based on previous research work, the dosimetric verification of FLASH ionization chamber was performed using a 200 keV electron beam irradiation platform at an ultra-high dose rate. At the same time, the finite element program is written to analyze and calculate the ion correction factor. In addition, the results are compared with the calculation results of Boag model. MethodsIn this study, the pressure of the sensitive volume in the detector was adjusted to 16 mbar for the purpose of dosimetry of dose rates in excess of 100 Gy/s. In order to monitor the response of the detector, the beam frequency and pulse width were adjusted accordingly. However, due to the saturation effect of the ionization chamber, the processes of electron ion pair drift, attachment, recombination and diffusion in the sensitive volume were modelled on the basis of the relevant physical principles. Finally, the correction factor was calculated by the finite element analysis. ResultsThe experimental results demonstrate that the FLASH ionization chamber is capable of meeting the requirements of dose measurement and beam monitoring of the electron beam at ultra-high dose rates. Furthermore, the analytical model is able to more accurately describe the saturation effect and calculate the correction factor. ConclusionIn this paper, the method of reducing air pressure is employed for the purpose of monitoring the dose of ultra-high dose rate. Simultaneously, the finite element method was employed to analyze the physical process of electron–ion pairs within the chamber and to calculate the ion correction factor analytically. A comparison with the Boag model indicates that the proposed approach is effective. However, the results exhibit a certain degree of divergence from experimental outcomes. This discrepancy may be attributed to the influence of the input parameters, which require further calibration to enhance the accuracy and the robustness of the model.
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