Hanns-Ingo Maack

In-vivo X-ray Dark-Field Chest Radiography of a Pig

X-ray chest radiography is an inexpensive and broadly available tool for initial assessment of the lung in clinical routine, but typically lacks diagnostic sensitivity for detection of pulmonary diseases in their early stages. Recent X-ray dark-field (XDF) imaging studies on mice have shown significant improvements in imaging-based lung diagnostics. Especially in the case of early diagnosis of chronic obstructive pulmonary disease (COPD), XDF imaging clearly outperforms conventional radiography. However, a translation of this technique towards the investigation of larger mammals and finally humans has not yet been achieved. In this letter, we present the first in-vivo XDF full-field chest radiographs (32 × 35 cm2) of a living pig, acquired with clinically compatible parameters (40 s scan time, approx. 80 µSv dose). For imaging, we developed a novel high-energy XDF system that overcomes the limitations of currently established setups. Our XDF radiographs yield sufficiently high image quality to enable radiographic evaluation of the lungs. We consider this a milestone in the bench-to-bedside translation of XDF imaging and expect XDF imaging to become an invaluable tool in clinical practice, both as a general chest X-ray modality and as a dedicated tool for high-risk patients affected by smoking, industrial work and indoor cooking.

Depiction of pneumothoraces in a large animal model using x-ray dark-field radiography

The aim of this study was to assess the diagnostic value of x-ray dark-field radiography to detect pneumothoraces in a pig model. Eight pigs were imaged with an experimental grating-based large-animal dark-field scanner before and after induction of a unilateral pneumothorax. Image contrast-to-noise ratios between lung tissue and the air-filled pleural cavity were quantified for transmission and dark-field radiograms. The projected area in the object plane of the inflated lung was measured in dark-field images to quantify the collapse of lung parenchyma due to a pneumothorax. Means and standard deviations for lung sizes and signal intensities from dark-field and transmission images were tested for statistical significance using Student’s two-tailed t-test for paired samples. The contrast-to-noise ratio between the air-filled pleural space of lateral pneumothoraces and lung tissue was significantly higher in the dark-field (3.65 ± 0.9) than in the transmission images (1.13 ± 1.1; p = 0.002). In case of dorsally located pneumothoraces, a significant decrease (−20.5%; p > 0.0001) in the projected area of inflated lung parenchyma was found after a pneumothorax was induced. Therefore, the detection of pneumothoraces in x-ray dark-field radiography was facilitated compared to transmission imaging in a large animal model.

X-ray dark-field imaging of the human lung—A feasibility study on a deceased body

Disorders of the lungs such as chronic obstructive pulmonary disease (COPD) are a major cause of chronic morbidity and mortality and the third leading cause of death in the world. The absence of sensitive diagnostic tests for early disease stages of COPD results in under-diagnosis of this treatable disease in an estimated 60–85% of the patients. In recent years a grating-based approach to X-ray dark-field contrast imaging has shown to be very sensitive for the detection and quantification of pulmonary emphysema in small animal models. However, translation of this technique to imaging systems suitable for humans remains challenging and has not yet been reported. In this manuscript, we present the first X-ray dark-field images of in-situ human lungs in a deceased body, demonstrating the feasibility of X-ray dark-field chest radiography on a human scale. Results were correlated with findings of computed tomography imaging and autopsy. The performance of the experimental radiography setup allows acquisition of multi-contrast chest X-ray images within clinical boundary conditions, including radiation dose. Upcoming clinical studies will have to demonstrate that this technology has the potential to improve early diagnosis of COPD and pulmonary diseases in general.

First experience with x-ray dark-field radiography for human chest imaging (Conference Presentation)

Purpose: To evaluate the performance of an experimental X-ray dark-field radiography system for chest imaging in humans and to compare with conventional diagnostic imaging. Materials and Methods: The study was institutional review board (IRB) approved. A single human cadaver (52 years, female, height: 173 cm, weight: 84 kg, chest circumference: 97 cm) was imaged within 24 hours post mortem on the experimental x-ray dark-field system. In addition, the cadaver was imaged on a clinical CT system to obtain a reference scan. The grating-based dark-field radiography setup was equipped with a set of three gratings to enable grating-based dark-field contrast x-ray imaging. The prototype operates at an acceleration voltage of up to 70 kVp and with a field-of-view large enough for clinical chest x-ray (>35 x 35 cm2). Results: It was feasible to extract x-ray dark-field signal of the whole human thorax, clearly demonstrating that human x-ray dark-field chest radiography is feasible. Lung tissue produced strong scattering, reflected in a pronounced x-ray dark-field signal. The ribcage and the backbone are less prominent than the lung but are also distinguishable. Finally, the soft tissue is not present in the dark-field radiography. The regions of the lungs affected by edema, as verified by CT, showed less dark-field signal compared to healthy lung tissue. Conclusion: Our results reveal the current status of translating dark-field imaging from a micro (small animal) scale to a macro (patient) scale. The performance of the experimental x-ray dark-field radiography setup offers, for the first time, obtaining multi-contrast chest x-ray images (attenuation and dark-field signal) from a human cadaver.

Energy weighting improves the image quality of spectral mammograms: Implementation on a photon-counting mammography system

In x-ray imaging, contrast information content varies with photon energy. It is therefore possible to improve image quality by weighting photons according to energy. We have implemented and evaluated so-called energy weighting on a commercially available spectral photon-counting mammography system. A practical formula for calculating the optimal weight from pixel values was derived. Computer simulations and phantom measurements revealed that the contrast-tonoise ratio was improved by 3%–5%, and automatic image analysis showed that the improvement was detectable in a set of screening mammograms.

A method for lesion visibility prediction in mammograms by local analysis of spectral anatomical noise

Detection of mass lesions in mammograms via visual readings is a challenging task, and the radiographic density of the breast tissue or its strong anatomical structure may render lesions completely invisible. In order to assess visibility of lesions of a certain size in a given mammogram, we propose a measure for prediction of lesion visibility that complements established approaches for breast density assessment by taking also local structure into account. This measure is based on the analysis of spectral anatomical noise in terms of local standard deviation values for several frequency bands of the mammogram. The resulting values are used to generate two dimensional visibility maps for different lesion sizes. Phantoms of structured tissue equivalent materials were imaged using a full-field digital mammography (FFDM) system, and spherical lesions of different sizes were artificially added to the images. In an observer study with ten observers visibility thresholds were determined from a total of 290 simulated lesions. The resulting nonlinear threshold curve was verified in a second observer study, where 66 lesions were artificially added in clinical mammograms of varying breast density according to BI-RADS classification. A prediction accuracy of 92% was obtained, suffering mostly from different image characteristics in the breast tissue regions near the skinline or the pectoral muscle.