Research Article: Contrast-to-noise ratios and thickness-normalized, ventilation-dependent signal levels in dark-field and conventional in vivo thorax radiographs of two pigs

Date Published: June 3, 2019

Publisher: Public Library of Science

Author(s): Fabio De Marco, Konstantin Willer, Lukas B. Gromann, Jana Andrejewski, Katharina Hellbach, Andrea Bähr, Michaela Dmochewitz, Thomas Koehler, Hanns-Ingo Maack, Franz Pfeiffer, Julia Herzen, Martin Bech.


Lung tissue causes significant small-angle X-ray scattering, which can be visualized with grating-based X-ray dark-field imaging. Structural lung diseases alter alveolar microstructure, which often causes a dark-field signal decrease. The imaging method provides benefits for diagnosis of such diseases in small-animal models, and was successfully used on porcine and human lungs in a fringe-scanning setup. Micro- and macroscopic changes occur in the lung during breathing, but their individual effects on the dark-field signal are unknown. However, this information is important for quantitative medical evaluation of dark-field thorax radiographs. To estimate the effect of these changes on the dark-field signal during a clinical examination, we acquired in vivo dark-field chest radiographs of two pigs at three ventilation pressures. Pigs were used due to the high degree of similarity between porcine and human lungs. To analyze lung expansion separately, we acquired CT scans of both pigs at comparable posture and ventilation pressures. Segmentation, masking, and forward-projection of the CT datasets yielded maps of lung thickness and logarithmic lung attenuation signal in registration with the dark-field radiographs. Upon correlating this data, we discovered approximately linear relationships between the logarithmic dark-field signal and both projected quantities for all scans. Increasing ventilation pressure strongly decreased dark-field extinction coefficients, whereas the ratio of lung dark-field and attenuation signal changed only slightly. Furthermore, we investigated ratios of dark-field and attenuation noise levels at realistic signal levels via calculations and phantom measurements. Dark-field contrast-to-noise ratio (CNR) per lung height was 5 to 10% of the same quantity in attenuation. We conclude that better CNR performance in the dark-field modality is typically due to greater anatomical noise in the conventional radiograph. Given the high physiological similarity of human and porcine lungs, the presented thickness-normalized, ventilation-dependent values allow estimation of dark-field activity of human lungs of variable size and inspiration, which facilitates the design of suitable clinical imaging setups.

Partial Text

Grating-based X-ray phase-contrast and dark-field imaging typically exploits the occurrence of periodic intensity patterns at certain positions downstream of a grating, which is introduced in the beam before or after a sample. In addition to the conventional attenuation image, analyzing the distortion of these intensity patterns allows retrieval of information about X-ray refraction and small-angle scattering by the sample [1–5]. In particular, the three-grating Talbot-Lau interferometer enables the use of lab-based high-flux, low-coherence X-ray sources [6].

The goal of the calculation steps presented here is to combine the volumetric data obtained from the CT scans with the dark-field projection data acquired in the radiographic fringe-scanning acquisition, and to compare noise and CNR for the conventional and dark-field radiographs. The relationship between individual calculation steps and procedures, as well as their data output are summarized in Fig 1. Individual procedures or calculations are shown as rectangles, whereas data exchanged between them are shown as ellipses.

In this work, we have combined imaging data from dark-field chest radiography and thorax CT of two living pigs at three different ventilation pressures. Furthermore, we acquired dark-field radiographs of a simple phantom and performed theoretical calculations to evaluate noise levels in the dark-field and attenuation modalities. The main findings are as follows:




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