Estimations of lung structural properties from a single propagation-based dark-field x-ray image

Abstract Objective. To employ a single-projection dark-field imaging approach to obtain statistical information on alveolar size and number as key structural indicators of lung health. Approach. The algorithm employed here retrieves the projected thickness of the sample from a propagation-based phase contrast image using the transport-of-intensity equation. The first Born approximation is then used to isolate the dark-field signal associated with edge scattering, which increases the visibility of microstructure boundaries. Poly(methyl methacrylate) spheres of known sizes were imaged first as an idealised alveolar model. The dark-field signal was then recovered from propagation-based phase-contrast x-ray images of the lungs of small mammals using this method. Main results. The retrieved dark-field signal was found to be proportional to both the alveolar size ( R 2 = 0.85 ) and the number in projection ( R 2 = 0.69 ), and these measurements could be combined to provide an estimate of the total surface area of the alveolar interfaces ( R 2 = 0.78 ). Significance. This demonstrates the approach’s ability to potentially indicate lung health using the dark-field signal retrieved from a single-phase-contrast x-ray image.