The fluence rate on a CT detector reaches 3 ⋅ 10(8) - 6 ⋅ 10(8) mm(-2) s(-1) in standard imaging protocols, with the highest rates occurring for ECG gated chest and miscentered head scans. These results will be useful to developers of CT detectors, in particular photon counting detectors.

The aim of the guideline presented in this article is to unify the test parameters for image quality evaluation and radiation output in all types of cone-beam computed tomography (CBCT) systems. The applications of CBCT spread over dental and interventional radiology, guided surgery and radiotherapy. The chosen tests provide the means to objectively evaluate the performance and monitor the constancy of the imaging chain. Experience from all involved associations has been collected to achieve a consensus that is rigorous and helpful for the practice. The guideline recommends to assess image quality in terms of uniformity, geometrical precision, voxel density values (or Hounsfield units where available), noise, low contrast resolution and spatial resolution measurements. These tests usually require the use of a phantom and evaluation software. Radiation output can be determined with a kerma-area product meter attached to the tube case. Alternatively, a solid state dosimeter attached to the flat panel and a simple geometric relationship can be used to calculate the dose to the isocentre. Summary tables including action levels and recommended frequencies for each test, as well as relevant references, are provided. If the radiation output or image quality deviates from expected values, or exceeds documented action levels for a given system, a more in depth system analysis (using conventional tests) and corrective maintenance work may be required.

A method to correct for the general recombination losses for liquid ionization chambers in continuous beams has been developed. The proposed method has been derived from Greening's theory for continuous beams and is based on measuring the signal from a liquid ionization chamber and an air filled monitor ionization chamber at two different dose rates. The method has been tested with two plane parallel liquid ionization chambers in a continuous radiation x-ray beam with a tube voltage of 120 kV and with dose rates between 2 and 13 Gy min(-1). The liquids used as sensitive media in the chambers were isooctane (C(8)H(18)) and tetramethylsilane (Si(CH(3))(4)). The general recombination effect was studied using chamber polarizing voltages of 100, 300, 500, 700 and 900 V for both liquids. The relative standard deviation of the results for the collection efficiency with respect to general recombination was found to be a maximum of 0.7% for isooctane and 2.4% for tetramethylsilane. The results are in excellent agreement with Greening's theory for collection efficiencies over 90%. The measured and corrected signals from the liquid ionization chambers used in this work are in very good agreement with the air filled monitor chamber with respect to signal to dose linearity.

We show that the proportion of double Auger decay following creation of single 1s core holes in molecules containing C, N and O atoms is greater than usually assumed, amounting to about 10% of single Auger decay in many cases. It varies from molecule to molecule, where the size of the molecule has a positive correlation to the amount of double Auger decay. In neon, examined as a related benchmark, the proportion of double Auger decay is similar to that in methane, and is in the order of 5%.

Purpose The purpose of this work was to assess a proof of concept for a novel method for predicting proton stopping power ratios (SPRs) based on a pair of dual‐energy CT generated virtual monoenergetic (VM) images. Materials and methods A rapid kV‐switching dual‐energy CT scanner was used to acquire Gemstone Spectral Imaging (GSI) and 120 kV conventional single‐energy CT (SECT) image data of the CIRS 062M phantom. The proposed method was applied to every possible pairing of VM images between 40 and 140 keV to find the optimal energy pairs for SPR prediction in lung tissue, soft tissue, and bone. The predicted SPRs were compared against SPRs predicted from the SECT data using the conventional SECT‐based method. The impact of different scan and reconstruction parameters was also investigated. Results The SPR residual root mean square errors (RMSE) yielded by the optimal pairs were 7.2% for lung tissue, 0.4% for soft tissue, and 0.8% for bone. While no direct comparison could be made to other DECT‐based methods for SPR prediction, as these methods could not be directly implemented on a fast kV‐switching system, the SPR RMSEs for soft tissue and bone in Table 4 are comparable to RMSEs reported in the literature. For the conventional SECT‐based method, the SPR RMSEs were 5.9% for lung tissue, 0.9% for soft tissue, and 5.1% for bone. Conclusions The proposed method is a valid alternative to, and has the potential to improve upon, the conventional SECT‐based method for predicting SPRs. The formalism used in the method is applied directly, with no approximations made on our part, and requires neither prior knowledge of the spectra nor calibration with a phantom. This work presents a way of optimizing the proposed method for a specific scanner by determining the optimal energy pairs to use as input and demonstrates the method's robustness to different levels of ASiR‐V, reconstruction kernels, and dose levels.