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Rationale and Objectives: Diffraction-enhanced imaging (DEI) is a type of phase contrast x-ray imaging that has improved image contrast at a lower dose than conventional radiography for many imaging applications, but no studies have been done to determine if DEI might be useful for diagnosing lung injury. The goals of this study were to determine if DEI could differentiate between healthy and injured lungs for a rat model of gastric aspiration and to compare diffraction-enhanced images with chest radiographs. Materials and Methods: Radiographs and diffraction-enhanced chest images of adult Sprague Dawley rats were obtained before and 4 hours after the aspiration of 0.4 mL/kg of 0.1 mol/L hydrochloric acid. Lung damage was confirmed with histopathology. Results: The radiographs and diffraction-enhanced peak images revealed regions of atelectasis in the injured rat lung. The diffraction-enhanced peak images revealed the full extent of the lung with improved clarity relative to the chest radiographs, especially in the portion of the lower lobe that extended behind the diaphragm on the anteroposterior projection. Conclusions: For a rat model of gastric acid aspiration, DEI is capable of distinguishing between a healthy and an injured lung and more clearly than radiography reveals the full extent of the lung and the lung damage. [ABSTRACT FROM AUTHOR]

In tissue engineering, non-invasive imaging of biomaterial scaffolds and tissues in living systems is essential to longitudinal animal studies for assessments without interrupting the repair process. Conventional X-ray imaging is inadequate for use in soft tissue engineering due to the limited absorption difference between the soft tissue and biomaterial scaffolds. X-ray phase-based imaging techniques that derive contrast from refraction or phase effects rather than absorption can provide the necessary contrast to see low-density biomaterial scaffolds and tissues in large living systems. This paper explores and compares three synchrotron phase-based X-ray imaging techniques—computed tomography (CT)-diffraction enhanced imaging (DEI), -analyzer based imaging (ABI), and -phase contrast imaging (PCI)—for visualization and characterization of low-density biomaterial scaffolds and tissues in situ for non-invasive soft tissue engineering assessments. Intact pig joints implanted with polycaprolactone scaffolds were used as the model to assess and compare the imaging techniques in terms of different qualitative and quantitative criteria. For long-term in vivo live animal imaging, different strategies for reducing the imaging radiation dose and scan time—reduced number of CT projections, region of interest, and low resolution imaging—were examined with the presented phase-based imaging techniques. The results demonstrated promising capabilities of the phase-based techniques for visualization of biomaterial scaffolds and soft tissues in situ . The low-dose imaging strategies were illustrated effective for reducing the radiation dose to levels appropriate for live animal imaging. The comparison among the imaging techniques suggested that CT-DEI has the highest efficiency in retaining image contrast at considerably low radiation doses. [ABSTRACT FROM AUTHOR]

Abstract: Moiré pattern noise in Scanning Transmission X-ray Microscopy (STXM) imaging introduces significant errors in qualitative and quantitative image analysis. Due to the complex origin of the noise, it is difficult to avoid Moiré pattern noise during the image data acquisition stage. In this paper, we introduce a post-processing method for filtering Moiré pattern noise from STXM images. This method includes a semi-automatic detection of the spectral peaks in the Fourier amplitude spectrum by using a local median filter, and elimination of the spectral noise peaks using a Gaussian notch filter. The proposed median-Gaussian filtering framework shows good results for STXM images with the size of power of two, if such parameters as threshold, sizes of the median and Gaussian filters, and size of the low frequency window, have been properly selected. [Copyright &y& Elsevier]