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The first step that is required to extract the correct information from a two-dimensional (2D) diffraction signature is to remove the background accurately. However, direct background subtraction inevitably overcorrects the signal as it does not take into account the attenuation by the sample. Other traditional background removal methods, such as the rolling ball technique, can separate sharp diffraction peaks of crystalline materials from their background. These methods are unsuitable for biological tissue, which is amorphous and does not have sharp diffraction peaks. This technical note proposes a novel method that combines peak fitting and experimental results to estimate the background for 2D XRD signals.

A system using energy-dispersive X-ray diffraction (EDXRD) has been developed and tested using multivariate calibration for the quantitative analysis of tablet-form mixtures of common pharmaceutical ingredients. A principal advantage of EDXRD over the more traditional and common angular dispersive X-ray diffraction technique (ADXRD) is the potential of EDXRD to analyse tablets within their packaging, due to the higher energy X-rays used. In the experiment, a series of caffeine, paracetamol and microcrystalline cellulose mixtures were prepared and pressed into tablets. EDXRD profiles were recorded on each sample and a principal component analysis (PCA) was carried out in both unpackaged and packaged scenarios. In both cases the first two principal components explained >98% of the between-sample variance. The PCA projected the sample profiles into two dimensional principal component space in close accordance to their ternary mixture design, demonstrating the discriminating potential of the EDXRD system. A partial least squares regression (PLSR) model was built with the samples and was validated using leave-one-out cross-validation. Low prediction errors of between 2% and 4% for both unpackaged and packaged tablets were obtained for all three chemical compounds. The prediction capability through packaging demonstrates a truly non-destructive method for quantifying tablet composition and demonstrates good potential for EDXRD to be applied in the field of counterfeit medicine screening and pharmaceutical quality control., (Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.)

In this note we present the first proof-of-concept results on the potential effectiveness of the edge-illumination x-ray phase contrast method (in its 'coded-aperture' based lab implementation) combined with tomosynthesis. We believe that, albeit admittedly preliminary (e.g. we only present phantom work), these results deserve early publication in a note primarily for four reasons. First, we fully modelled the imaging acquisition method, and validated the simulation directly with experimental results. This shows that the implementation of the method in the new geometry is understood, and thus that it will be possible to use the model to simulate more complex scenarios in the future. Secondly, we show that a strong phase contrast signal is preserved in the reconstructed tomosynthesis slices: this was a concern, as the high spatial frequency nature of the signal makes it sensitive to any filtration-related procedure. Third, we show that, despite the non-optimized nature of the imaging prototype used, we can perform a full angular scan at acceptable dose levels and with exposure times not excessively distant from what is required by clinical practice. Finally, we discuss how the proposed phase contrast method, unlike other approaches apart from free-space propagation (which however requires a smaller focal spot, thus reducing the flux and increasing exposure times), can be easily implemented in a tomosynthesis geometry suitable for clinical use. In summary, we find that these technical results indicate a high potential for the combination of the two methods. Combining slice separation with detail enhancement provided by phase effects would substantially increase the detectability of small lesions and/or calcifications, which we aim to demonstrate in the next steps of this study.

X-ray phase contrast imaging has overcome the limitations of X-ray absorption imaging in many fields. Particular effort has been directed towards developing phase retrieval methods: These reveal quantitative information about a sample, which is a requirement for performing X-ray phase tomography, allows material identification and better distinction between tissue types, etc. Phase retrieval seems impossible with conventional X-ray sources due to their low spatial coherence. In the only previous example where conventional sources have been used, collimators were employed to produce spatially coherent secondary sources. We present a truly incoherent phase retrieval method, which removes the spatial coherence constraints and employs a conventional source without aperturing, collimation, or filtering. This is possible because our technique, based on the pixel edge illumination principle, is neither interferometric nor crystal based. Beams created by an X-ray mask to image the sample are smeared due to the incoherence of the source, yet we show that their displacements can still be measured accurately, obtaining strong phase contrast. Quantitative information is extracted from only two images rather than a sequence as required by several coherent methods. Our technique makes quantitative phase imaging and phase tomography possible in applications where exposure time and radiation dose are critical. The technique employs masks which are currently commercially available with linear dimensions in the tens of centimeters thus allowing for a large field of view. The technique works at high photon energy and thus promises to deliver much safer quantitative phase imaging and phase tomography in the future.

There is currently much interest in developing X-ray Phase Contrast Imaging (XPCI) systems which employ laboratory sources in order to deploy the technique in real world applications. The challenge faced by nearly all XPCI techniques is that of efficiently utilising the x-ray flux emitted by an x-ray tube which is polychromatic and possesses only partial spatial coherence. Techniques have, however, been developed which overcome these limitations. Such a technique, known as coded aperture XPCI, has been under development in our laboratories in recent years for application principally in medical imaging and security screening. In this paper we derive limitations imposed upon source polychromaticity and spatial extent by the coded aperture system. We also show that although other grating XPCI techniques employ a different physical principle, they satisfy design constraints similar to those of the coded aperture XPCI.

This paper describes the potential application of an active pixel sensor-based x-ray diffraction (APXRD) system in the field of breast cancer diagnosis. The design and initial testing of the system was reported previously (Bohndiek et al 2008b Phys. Med. Biol. 53 655-72). The system has potential both as a 'diffraction enhanced breast imager' (DEBI) and as a probe for quantitative analysis of breast biopsy samples. The resolution of the system in a DEBI arrangement is 1 mm and the contrast available using a material-specific x-ray diffraction image was found to be up to seven times greater than that of a transmission image. Scatter signatures from a series of biopsy-equivalent samples, ranging in composition from 100% fat to 100% fibrous tissue, were acquired with the APXRD system. Multivariate data analysis was used to produce a partial least squares (PLS) model sensitive to sample fat content. The final model is able to accurately predict the fat content of a series of unknown samples and is robust to significant added noise. This suggests that the APXRD system could provide a simple, semi-automated, quantitative measurement system for analysis of breast biopsy samples. Training on a range of scatter signatures from real breast biopsy samples covering various stages of disease is now needed to test this hypothesis.

X-ray diffraction studies give material-specific information about biological tissue. Ideally, a large area, low noise, wide dynamic range digital x-ray detector is required for laboratory-based x-ray diffraction studies. The goal of this work is to introduce a novel imaging technology, the CMOS active pixel sensor (APS) that has the potential to fulfil all these requirements, and demonstrate its feasibility for coherent scatter imaging. A prototype CMOS APS has been included in an x-ray diffraction demonstration system. An industrial x-ray source with appropriate beam filtration is used to perform angle dispersive x-ray diffraction (ADXRD). Optimization of the experimental set-up is detailed including collimator options and detector operating parameters. Scatter signatures are measured for 11 different materials, covering three medical applications: breast cancer diagnosis, kidney stone identification and bone mineral density calculations. Scatter signatures are also recorded for three mixed samples of known composition. Results are verified using two independent models for predicting the APS scatter signature: (1) a linear systems model of the APS and (2) a linear superposition integral combining known monochromatic scatter signatures with the input polychromatic spectrum used in this case. Cross validation of experimental, modelled and literature results proves that APS are able to record biologically relevant scatter signatures. Coherent scatter signatures are sensitive to multiple materials present in a sample and provide a means to quantify composition. In the future, production of a bespoke APS imager for x-ray diffraction studies could enable simultaneous collection of the transmitted beam and scattered radiation in a laboratory-based coherent scatter system, making clinical transfer of the technique attainable.

Energy dispersive X-ray diffraction is proposed as a suitable non-destructive method to rapidly identify illicit drugs in parcels. A preliminary data set of 7 illicit drug samples and a possible cutting agent has been collected with a range of count times using a tungsten target X-ray source, a high resolution HpGe detector and a variable geometry diffraction cell. These results have been used to calibrate and train multivariate analysis software to predict the drug content in previously unseen spectra.

Energy dispersive X‐ray diffraction (EDXRD) and maximum likelihood principal component analysis multivariate curve resolution‐alternating least squares (MLPCA‐MCR‐ALS) with correlation constraint were used to quantify the composition of packaged pharmaceutical formulations. Recorded EDXRD profiles from unpackaged and packaged samples of ternary mixtures were modelled together in order to recover the concentrations as well as the pure profiles of the constituent compounds. MLPCA was used as a data pretreatment step to MCR‐ALS, accounting for the high noise and nonconstant variance observed in the EDXRD profiles and was shown to improve the resolution accuracy of MCR‐ALS for the data set. Local correlation constraints were applied in the MCR‐ALS procedure in order to model unpackaged and packaged samples simultaneously while accounting for the matrix effect of the packaging materials. The composition of the formulations was estimated with root‐mean‐square error of prediction for each component, including paracetamol, being approximately 2.5 %w/w for unpackaged and packaged samples. Paracetamol concentration was resolved simultaneously for the unpackaged and packaged samples to a greater degree of accuracy than achieved by partial least squares regression (PLSR) when modelling the contexts separately. By modelling the effects of the packaging and incorporating accurate reference information of unpackaged samples into the resolution of packaged samples, the potential of EDXRD and MLPCA‐MCR‐ALS for the identification and quantification of packaged solid‐dosage medicine in nondestructive screening and counterfeit medicine detection has been raised. Energy dispersive X‐ray diffraction (EDXRD) and maximum likelihood principal component analysis multivariate curve resolution‐alternating least squares (MLPCA‐MCR‐ALS) with correlation constraint were used to quantify the composition of packaged pharmaceutical formulations. A multiset data structure was used to model and resolve concentrations and pure signals of unpackaged and packaged samples simultaneously. MLPCA enabled greater accuracy of resolution. The potential application of EDXRD and MLPCA‐MCR‐ALS in counterfeit medicine screening is demonstrated. [ABSTRACT FROM AUTHOR]

Preliminary studies have shown the effectiveness of multivariate analysis (MVA) for drug identification from energy-dispersive X-ray diffraction patterns. A statistical model to predict drug content from the diffraction profile of a sample of mixed composition was developed by applying MVA to both experimental and simulated data. Separate data-sets were used for building and testing the models. Both experimental and simulated data were used and the MVA predictions compared. Experimental data included diffraction patterns from small (5 mm diameter) drug samples with various cutting agents, acquired with a HPGe detector; simulated data included diffraction patterns of samples including materials simulating drugs (i.e., materials featuring sharp diffraction peaks in the relevant momentum transfer range) and typical packaging materials. Both a HPGe detector (energy resolution 0.7 keV at 59.5 keV) and a CZT detector (energy resolution 4 keV at all energies) were simulated. MVA was used to predict the drug content. In all cases different statistics were applied to assess the detection limits of the models. Multivariate analysis has proved effective in both identifying the presence of a drug and its concentration. Due to the large contribution to peak broadening given by angular resolution, no significant decrease in accuracy has been found when using CZT with respect to HPGe data. [ABSTRACT FROM AUTHOR]

A system for drug detection using X-ray diffraction is currently being developed by the DILAX collaboration. A simulation program for modelling the response of an energy-dispersive X-ray diffraction system has been developed, with the two-fold aim of selecting possible configurations prior to experimental tests and of generating data for statistical models for prediction of drug content. Simulated data showed a good agreement with experimental results. The data showed that the main factor affecting the shape of the diffraction pattern is the thickness of the sample. Scatter angle and detector energy resolution have a smaller effect on the diffraction pattern. This suggests that cheaper, room-temperature detectors can be used for a drug detection system without any loss in sensitivity and specificity. [ABSTRACT FROM AUTHOR]