Characterization of speckle in lung images acquired with a benchtop in-line x-ray phase-contrast system

Department of Biomedical Engineering, Washington University in St Louis, St Louis, MO 63130, USA.
Physics in Medicine and Biology (Impact Factor: 2.76). 05/2013; 58(12):4237-4253. DOI: 10.1088/0031-9155/58/12/4237
Source: PubMed


We investigate the manifestation of speckle in propagation-based x-ray phase-contrast imaging of mouse lungs in situ by use of a benchtop imager. The key contributions of the work are the demonstration that lung speckle can be observed by use of a benchtop imaging system employing a polychromatic tube-source and a systematic experimental investigation of how the texture of the speckle pattern depends on the parameters of the imaging system. Our analyses consists of image texture characterization based on the statistical properties of pixel intensity values.

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    ABSTRACT: Propagation-based phase contrast x-ray (PBX) imaging yields high contrast images of the lung where airways that overlap in projection coherently scatter the x-rays, giving rise to a speckled intensity due to interference effects. Our previous works have shown that total and regional changes in lung air volumes can be accurately measured from two-dimensional (2D) absorption or phase contrast images when the subject is immersed in a water-filled container. In this paper we demonstrate how the phase contrast speckle patterns can be used to directly measure absolute regional lung air volumes from 2D PBX images without the need for a water-filled container. We justify this technique analytically and via simulation using the transport-of-intensity equation and calibrate the technique using our existing methods for measuring lung air volume. Finally, we show the full capabilities of this technique for measuring regional differences in lung aeration.
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    ABSTRACT: Herein a propagation-based phase contrast x-ray imaging technique for measuring particle size and number is presented. This is achieved with an algorithm that utilizes the Fourier space signature of the speckle pattern associated with the images of particles. We validate this algorithm using soda-lime glass particles, demonstrating its effectiveness on random and non-randomly packed particles. This technique is then applied to characterise lung alveoli, which are difficult to measure dynamically in vivo with current imaging modalities due to inadequate temporal resolution and/or depth of penetration and field-of-view. We obtain an important result in that our algorithm is able to measure changes in alveolar size on the micron scale during ventilation and shows the presence of alveolar recruitment/de-recruitment in newborn rabbit kittens. This technique will be useful for ventilation management and lung diagnostic procedures.
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