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.
Highlights
The lung is comprised of bifurcating hollow branches that carry air to the terminal airways where gas exchange takes place
We present a non-invasive phase contrast x-ray (PCX) imaging technique to measure the size and population of alveoli in situ. To do this we exploit the image texture associated with the speckle pattern that results from propagation-based phase contrast x-ray (PB-PCX) imaging of the lungs [1]
The method developed by Leong et al [21] was applied, after accounting for the large distance error and detector point spread function (d-PSF), to measure the N and R of alveoli from the speckle patterns of PB-PCX ventilated chest images
Summary
The lung is comprised of bifurcating hollow branches that carry air to the terminal airways (alveoli) where gas exchange takes place. We present a non-invasive phase contrast x-ray (PCX) imaging technique to measure the size and population of alveoli in situ To do this we exploit the image texture associated with the speckle pattern that results from propagation-based phase contrast x-ray (PB-PCX) imaging of the lungs [1]. Repeating this measure over several time points during breathing provides functional information regarding the changing morphology of lung tissue. We show how the alveolar size and population can be determined from lung speckled PB-PCX chest images if the lung air volume is known This derivation follows closely to that developed in Leong et al [21], but in that derivation alveoli were assumed to be randomly distributed.
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