A method for converting microdosimetric spectra in diamond to tissue in proton therapy.

PURPOSE: Diamond has been regarded as a promising microdosimeter in radiation protection and radiotherapy due to its excellent properties. However, as the diamond is not tissue equivalent, a conversion of the measured spectra in the diamond microdosimeter to the tissue site is needed. In this work, we intend to deduce a method for converting the microdosimetric spectra from diamond to tissue in the proton therapy application based on the Chapman-Kolmogorov equation and investigate the validity of this method in spectral conversion. METHODS: The comparison of stopping power and energy deposition distribution of diamond and tissue shows that the conversion of the spectra in diamond to tissue can be performed by a simple scaling factor. Therefore, the equivalence of the energy deposition spectra in the diamond microdosimeter and a tissue site of the same size in the same radiation field was studied first to obtain the scaling factor. Then, the spectra conversion method was derived from the Chapman-Kolmogorov equation and the scaling factor. The Geant4 simulation was employed to settle this study. RESULTS: Theoretical and Geant4 simulation results indicate that the linear stopping power ratio of diamond to tissue is adequate to convert the microdosimetric spectra in diamond to tissue of identical dimension. The conversion results indicate that the energy deposition spectra converted from diamond to bone agree well with the spectra calculated by Geant4 along the Bragg curve. As for water, a good agreement of the converted and calculated spectra was found at the plateau of the Bragg curve and the distal part of the Bragg peak. At the proximal part of the Bragg peak, the converted and calculated spectrum is poorly coincident. CONCLUSIONS: The method of the energy deposition spectra conversion from the diamond microdosimeter to the tissue site of equal size shows relatively good results in most situations. But the deficiency was also found. Therefore, further investigation is needed to improve the reliability of this method.

Counting-loss correction for X-ray spectra using the pulse-repairing method.

Facing the technical problem of pulse distortion caused by frequent resetting in the latest high-performance silicon drift detectors, which work under high-counting-rate conditions, a method has been used to remove false peaks in order to obtain a precise X-ray spectrum, the essence of which eliminates distorted pulses. Aiming at solving the problem of counting-loss generated by eliminating distorted pulses, this paper proposes an improved method of pulse repairing. A 238Pu source with activity of 10 mCi was used as the measurement object, and the energy spectrum obtained by the pulse repairing method was compared with that obtained by the pulse elimination method. The ten-measurement results show that the pulse repairing method can correct the counting-loss caused by the pulse elimination method and increase peak area, which is of great significance for obtaining a precise X-ray energy spectrum.

A new method for removing false peaks to obtain a precise X-ray spectrum.

To get a precise X-ray energy spectrum from the latest high-performance silicon drift detector (fast SDD), a switch reset preamplifier circuit, which has a high signal to noise ratio and small ballistic loss, is used to amplify the weak signal transmitted by the detector. Aiming at the technical problem of fast SDD, which works at high-count rate conditions, we adopt a slow triangle shaping method and use switch reset type preamplifier, and a new method is put forward to remove the false peaks to obtain a precise X-ray spectrum, in essence, to eliminate the distorted pulses transmitted by the detector. 55Fe standard source and a certain kind of rock sample are regarded as measuring objects in the experiments. The spectral comparison figure, which contains the two measurement results of the pre and post elimination of the false peaks, respectively, shows that this method removes the false peaks located in the front of the full-energy peak in spectra and improves the peak-to-background ratio in a complex spectral analysis and the analytical precision of weak signals.