Radiographic and fluoroscopic X-ray systems: Quality control of the X-ray tube and automatic exposure control using theoretical spectra to determine air kerma and dose to a homogenous phantom

Purpose To develop a method to perform quality control (QC) of X-ray tubes and automatic exposure control (AEC) as a part of the QC of the radiographic and fluoroscopic X-ray system. Our aim is to verify the output from the X-ray tube by comparing the measured radiation output, or air kerma, to the theoretical output given the applied exposure settings and geometry, in addition to comparing the measured kV to the nominal kV. The AEC system for fluoroscopic and conventional X-ray systems is assessed by determining the absorbed dose to a homogenous phantom with different thicknesses. Method This study presents a model to verify the X-ray tube measurement results and a method to determine the dose to a homogenous phantom (Dphantom). The following input is needed: a parameterized model of the X-ray spectrum, the X-ray tube measurements using a multifunctional X-ray meter, the exposure parameters recorded via imaging of polymethyl methacrylate (PMMA) slabs of different thickness that simulate the patient using AEC, and a parameterized model for calculating the dose to water from Monte Carlo simulations. The output is the entrance surface dose (ESD) and absorbed dose in the phantom, Dphantom (µGy). In addition, the parameterized X-ray spectrum is used to compare theoretical and measured air kerma as a part of the QC of the X-ray tube. To verify the proposed method, the X-ray spectrum provided in this study, SPECTRUM, was compared to two commercially available spectra, SpekCalc and Institute of Physics and Engineering in Medicine (IPEM) 78. The fraction of energy imparted to the homogenous phantom was compared to the imparted fraction calculated by PCXMC. Results The spectrum provided in this study was in good agreement with two previously published X-ray spectra. The absolute percentage differences of the spectra varied from 0.05% to 3.9%, with an average of 1.4%, compared to SpekCalc. Similarly, the deviation from IPEM report 78 varied from 0.02% to 2.3%, with an average of 0.74%. The SPECTRUM was parameterized for calculation of the imparted fraction for target angles of 10°, 12°, and 15°, kV (50–150 kV) with the materials Al (2.2–8 mm), Cu (0–1 mm), and any combination of the filters, PMMA and water. The deviation of energy imparted from the results by PCXMC was less than 8% for all measurements across different kV, filtration, and vendors, obtained by using PMMA to record the exposure parameters, while the dose was calculated based on water with same thicknesses as the PMMA. Conclusion This study presents an accurate and suitable method to perform a part of the QC of fluoroscopic and conventional X-ray systems with respect to the X-ray tube and the associated AEC system. The method is suitable for comparing protocols within and between systems via the absorbed dos

Novel method to determine recursive filtration and noise reduction in fluoroscopic imaging - a comparison of four different vendors

Purpose: This study attempted to develop a method to measure the applied recursive filtration and to determine the noise reduction of four different fluoroscopic systems. The study also attempted to elucidate the importance of considering the recursive filter for quality control tests concerning signal-to-noise ratio (SNR) or image quality. The vendor's settings for recursive filtration factor (β) are, unfortunately, often not available. Hence, a method to determine the recursive filtration and associated noise reduction would be useful. Method: The recursive filter was determined by using a single fluoroscopic series and the method presented in this study. The theoretical noise reduction based on the choice of β was presented. In addition, the corresponding noise reduction, evaluated as the ratio of the standard deviation of the pixel value between a series with β equal to zero (recursive filtration off) and β > 0, was determined for different pulse rates given by pulses per second (pps), doses (mAs) and recursive filter. The images were acquired using clinically relevant radiation quality and quantity. Results: The presented method to measure the recursive filter exhibited high accuracy (1.08%) and precision (1.48%). The recursive filtration and noise reduction were measured for several settings for each vendor. The recursive filtration settings and associated recursive filtration factors for four different vendors were presented. Conclusions: This study presented an accurate method to determine applied recursive filtration, which was easy to determine. Hence, for all quality control purposes, including noise evaluation, it was possible to consider the essential noise reduction given by the settings for recursive filtration. It was also possible to compare the recursive filtration settings and associated recursive filtration within and between vendors