Photon-counting, energy-resolving and super-resolution phase contrast X-ray imaging using an integrating detector.

This work demonstrates the use of a scientific-CMOS (sCMOS) energy-integrating detector as a photon-counting detector, thereby eliminating dark current and read-out noise issues, that simultaneously provides both energy resolution and sub-pixel spatial resolution for X-ray imaging. These capabilities are obtained by analyzing visible light photon clouds that result when X-ray photons produce fluorescence from a scintillator in front of the visible light sensor. Using low-fluence monochromatic X-ray projections to avoid overlapping photon clouds, the centroid of individual X-ray photon interactions was identified. This enabled a tripling of the spatial resolution of the detector to 6.71 ± 0.04 µm. By calculating the total charge deposited by this interaction, an energy resolution of 61.2 ± 0.1% at 17 keV was obtained. When combined with propagation-based phase contrast imaging and phase retrieval, a signal-to-noise ratio of up to 15 ± 3 was achieved for an X-ray fluence of less than 3 photons/mm2.

Quantifying lung aeration in neonatal lambs at birth using lung ultrasound.

Background: Lung ultrasound (LUS) is a safe and non-invasive tool that can potentially assess regional lung aeration in newborn infants and reduce the need for X-ray imaging. LUS produces images with characteristic artifacts caused by the presence of air in the lung, but it is unknown if LUS can accurately detect changes in lung air volumes after birth. This study compared LUS images with lung volume measurements from high-resolution computed tomography (CT) scans to determine if LUS can accurately provide relative measures of lung aeration. Methods: Deceased near-term newborn lambs (139 days gestation, term ∼148 days) were intubated and the chest imaged using LUS (bilaterally) and phase contrast x-ray CT scans at increasing static airway pressures (0-50 cmH2O). CT scans were analyzed to calculate regional air volumes and correlated with measures from LUS images. These measures included (i) LUS grade; (ii) brightness (mean and coefficient of variation); and (iii) area under the Fourier power spectra within defined frequency ranges. Results: All LUS image analysis techniques correlated strongly with air volumes measured by CT (p < 0.01). When imaging statistics were combined in a multivariate linear regression model, LUS predicted the proportion of air in the underlying lung with moderate accuracy (95% prediction interval ± 22.15%, r 2 = 0.71). Conclusion: LUS can provide relative measures of lung aeration after birth in neonatal lambs. Future studies are needed to determine if LUS can also provide a simple means to assess air volumes and individualize aeration strategies for critically ill newborns in real time.