Quantitative differentiation of minimal-fat angiomyolipomas from renal cell carcinomas using grating-based x-ray phase-contrast computed tomography: An ex vivo study.

BACKGROUND: The differentiation of minimal-fat-or low-fat-angiomyolipomas from other renal lesions is clinically challenging in conventional computed tomography. In this work, we have assessed the potential of grating-based x-ray phase-contrast computed tomography (GBPC-CT) for visualization and quantitative differentiation of minimal-fat angiomyolipomas (mfAMLs) and oncocytomas from renal cell carcinomas (RCCs) on ex vivo renal samples. MATERIALS AND METHODS: Laboratory GBPC-CT was performed at 40 kVp on 28 ex vivo kidney specimens including five angiomyolipomas with three minimal-fat (mfAMLs) and two high-fat (hfAMLs) subtypes as well as three oncocytomas and 20 RCCs with eight clear cell (ccRCCs), seven papillary (pRCCs) and five chromophobe RCC (chrRCC) subtypes. Quantitative values of conventional Hounsfield units (HU) and phase-contrast Hounsfield units (HUp) were determined and histogram analysis was performed on GBPC-CT and grating-based attenuation-contrast computed tomography (GBAC-CT) slices for each specimen. For comparison, the same specimens were imaged at a 3T magnetic resonance imaging (MRI) scanner. RESULTS: We have successfully matched GBPC-CT images with clinical MRI and histology, as GBPC-CT presented with increased soft tissue contrast compared to absorption-based images. GBPC-CT images revealed a qualitative and quantitative difference between mfAML samples (58±4 HUp) and oncocytomas (44±10 HUp, p = 0.057) and RCCs (ccRCCs: 40±12 HUp, p = 0.012; pRCCs: 43±9 HUp, p = 0.017; chrRCCs: 40±7 HUp, p = 0.057) in contrast to corresponding laboratory attenuation-contrast CT and clinical MRI, although not all differences were statistically significant. Due to the heterogeneity and lower signal of oncocytomas, quantitative differentiation of the samples based on HUp or in combination with HUs was not possible. CONCLUSIONS: GBPC-CT allows quantitative differentiation of minimal-fat angiomyolipomas from pRCCs and ccRCCs in contrast to absorption-based imaging and clinical MRI.

COVID-19 pneumonia and its lookalikes: How radiologists perform in differentiating atypical pneumonias.

PURPOSE: To examine the performance of radiologists in differentiating COVID-19 from non-COVID-19 atypical pneumonia and to perform an analysis of CT patterns in a study cohort including viral, fungal and atypical bacterial pathogens. METHODS: Patients with positive RT-PCR tests for COVID-19 pneumonia (n = 90) and non-COVID-19 atypical pneumonia (n = 294) were retrospectively included. Five radiologists, blinded to the pathogen test results, assessed the CT scans and classified them as COVID-19 or non-COVID-19 pneumonia. For both groups specific CT features were recorded and a multivariate logistic regression model was used to calculate their ability to predict COVID-19 pneumonia. RESULTS: The radiologists differentiated between COVID-19 and non-COVID-19 pneumonia with an overall accuracy, sensitivity, and specificity of 88% ± 4 (SD), 79% ± 6 (SD), and 90% ± 6 (SD), respectively. The percentage of correct ratings was lower in the early and late stage of COVID-19 pneumonia compared to the progressive and peak stage (68 and 71% vs 85 and 89%). The variables associated with the most increased risk of COVID-19 pneumonia were band like subpleural opacities (OR 5.55, p < 0.001), vascular enlargement (OR 2.63, p = 0.071), and subpleural curvilinear lines (OR 2.52, p = 0.021). Bronchial wall thickening and centrilobular nodules were associated with decreased risk of COVID-19 pneumonia with OR of 0.30 (p = 0.013) and 0.10 (p < 0.001), respectively. CONCLUSIONS: Radiologists can differentiate between COVID-19 and non-COVID-19 atypical pneumonias at chest CT with high overall accuracy, although a lower performance was observed in the early and late stage of COVID 19 pneumonia. Specific CT features might help to make the correct diagnosis.

[Modern tumor therapy and its pulmonary side effects]. / Moderne Tumortherapien und ihre pulmonalen Nebenwirkungen.

Radiation therapy and more recently, drug-based molecular therapy in particular, are a central component of modern oncology. Both forms of therapy are suitable for effectively treating tumors with comparatively low systemic side effects. Nevertheless, even these treatment approaches have side effects, which are triggered by the toxicity of the radiation and by the immunomodulatory effects of the administered drugs. The pneumotoxic potential of these forms of therapy is reflected in the development of interstitial pneumonitis, which can transition into fibrotic changes in the lung structure. The clinical diagnosis of the disease is made more difficult as the symptoms are nonspecific. Computed tomography (CT) is an excellent means of diagnosing the corresponding consolidations and to monitor them over time. Therefore, in the interdisciplinary context the radiologist plays a central role in the diagnostics of this disease.

Simultaneous presence of the "bullseye" and "reversed halo" sign at CT of COVID-19 pneumonia: A case report.

The "bullseye" sign has been exclusively reported in patients suffering from coronavirus disease 2019 (COVID-19) pneumonia. It is theorized that this newly recognized computed tomography (CT) feature represents a sign of organizing pneumonia. Well established signs of organizing pneumonia also reported in COVID-19 patients include linear opacities, the "reversed halo" sign (or "atoll" sign), and a perilobular distribution of abnormalities. These findings are usually present on imaging in the intermediate and late stage of the disease. This is a case of simultaneous presence of the "bullseye" and the "reversed halo" sign on chest CT images of a COVID-19 patient examined 22 days after symptom onset.

Diagnostic accuracy of magnetic resonance imaging for the detection of pulmonary nodules simulated in a dedicated porcine chest phantom.

OBJECTIVE: CT serves as gold standard for the evaluation of pulmonary nodules. However, CT exposes patients to ionizing radiation, a concern especially in screening scenarios with repeated examinations. Due to recent technological advances, MRI emerges as a potential alternative for lung imaging using 3D steady state free precession and ultra-short echo-time sequences. Therefore, in this study we assessed the performance of three state-of-the-art MRI sequences for the evaluation of pulmonary nodules. METHODS: Lesions of variable sizes were simulated in porcine lungs placed in a dedicated chest phantom mimicking a human thorax, followed by CT and MRI examinations. Two blinded readers evaluated the acquired MR-images locating and measuring every suspect lesion. Using the CT-images as reference, logistic regression was performed to investigate the sensitivity of the tested MRI-sequences for the detection of pulmonary nodules. RESULTS: For nodules with a diameter of 6 mm, all three sequences achieved high sensitivity values above 0.91. However, the sensitivity dropped for smaller nodules, yielding an average of 0.83 for lesions with 4 mm in diameter and less than 0.69 for lesions with 2 mm in diameter. The positive predictive values ranged between 0.91 and 0.96, indicating a low amount of false positive findings. Furthermore, the size measurements done on the MR-images were subject to a bias ranging from 0.83 mm to -1.77 mm with standard deviations ranging from 1.40 mm to 2.11 mm. There was no statistically significant difference between the three tested sequences. CONCLUSION: While showing promising sensitivity values for lesions larger than 4 mm, MRI appears to be not yet suited for lung cancer screening. Nonetheless, the three tested MRI sequences yielded high positive predictive values and accurate size measurements; therefore, MRI could potentially figure as imaging method of the chest in selected follow-up scenarios, e.g. of incidental findings subject to the Fleischner Criteria.

A proof-of principal study using phase-contrast imaging for the detection of large airway pathologies after lung transplantation.

In this study we aim to evaluate the assessment of bronchial pathologies in a murine model of lung transplantation with grating-based X-ray interferometry in vivo. Imaging was performed using a dedicated grating-based small-animal X-ray dark-field and phase-contrast scanner. While the contrast modality of the dark-field signal already showed several promising applications for diagnosing various types of pulmonary diseases, the phase-shifting contrast mechanism of the phase contrast has not yet been evaluated in vivo. For this purpose, qualitative analysis of phase-contrast images was performed and revealed pathologies due to previous lung transplantation, such as unilateral bronchial stenosis or bronchial truncation. Dependent lung parenchyma showed a strong loss in dark-field and absorption signal intensity, possibly caused by several post transplantational pathologies such as atelectasis, pleural effusion, or pulmonary infiltrates. With this study, we are able to show that bronchial pathologies can be visualized in vivo using conventional X-ray imaging when phase-contrast information is analysed. Absorption and dark-field images can be used to quantify the severity of lack of ventilation in the affected lung.

Imaging characteristics of intravascular spherical contrast agents for grating-based x-ray dark-field imaging - effects of concentrations, spherical sizes and applied voltage.

This study investigates the x-ray scattering characteristics of microsphere particles in x-ray-grating-based interferometric imaging at different concentrations, bubble sizes and tube voltages (kV). Attenuation (ATI), dark-field (DFI) and phase-contrast (PCI) images were acquired. Signal-to-noise (SNR) and contrast-to-noise ratios with water (CNRw) and air as reference (CNRa) were determined. In all modalities, a linear relationship between SNR and microbubbles concentration, respectively, microsphere size was found. A significant gain of SNR was found when varying kV. SNR was significantly higher in DFI and PCI than ATI. The highest gain of SNR was shown at 60 kV for all media in ATI and DFI, at 80 kV for PCI. SNR for all media was significantly higher compared to air and was slightly lower compared to water. A linear relationship was found between CNRa, CNRw, concentration and size. With increasing concentration and decreasing size, CNRa and CNRw increased in DFI, but decreased in PCI. Best CNRa and CNRw was found at specific combination of kV and concentration/size. Highest average CNRa and CNRw was found for microspheres in ATI and PCI, for microbubbles in DFI. Microspheres are a promising contrast-media for grating-based-interferometry, if kV, microsphere size and concentration are appropriately combined.

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

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.

Exploration of different x-ray Talbot-Lau setups for dark-field lung imaging examined in a porcine lung.

X-ray dark-field imaging is a promising technique for lung diagnosis. Due to the alveolar structure of lung tissue, a higher contrast is obtained by the dark-field image compared to the attenuation image. Animal studies indicate an enhancement regarding the detection of lung diseases in early stages. In this publication, we focus on the influence of different Talbot-Lau interferometer specifications while maintaining the x-ray source, sample magnification and detector system. By imaging the same porcine lung with three different grating sets, we analyze the contrast-to-noise ratio of the obtained dark-field images with respect to visibility and correlation length. We demonstrate that relatively large grating periods of the phase and of the analyzer grating are sufficient for high quality lung imaging at reasonable dose levels.

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.

Single-shot Talbot-Lau x-ray dark-field imaging of a porcine lung applying the moiré imaging approach.

Talbot-Lau x-ray imaging provides additionally to the conventional attenuation image, two further images: the differential phase-contrast image which is especially sensitive to differences in refractive properties and the dark-field image which is showing the x-ray scattering properties of the object. Thus, in the dark-field image sub-pixeled object information can be observed. As it has been shown in recent studies, this is of special interest for lung imaging. Changes in the alveoli structure, which are in the size of one detector pixel, can be seen in the dark-field images. A fast acquisition process is crucial to avoid motion artifacts due to heartbeat and breathing of the patient. Using moiré imaging the images can be acquired with a single-shot exposure. Nevertheless, the spatial resolution is reduced compared to the phase-stepping acquisition. We evaluate the results of both imaging techniques towards their feasibility in clinical routine. Furthermore, we analyse the influence of artificial linear object movement on the image quality, in order to simulate the heartbeat of a patient.

Enhanced reconstruction algorithm for moiré artifact suppression in Talbot-Lau x-ray imaging.

Talbot-Lau x-ray imaging (TLXI) is an innovative and promising imaging technique providing information about the x-ray attenuation, scattering, and refraction features of objects. However, the method is susceptible to vibrations and system component imprecisions, which are inevitable in clinical and industrial practice. Those influences provoke grating displacements and hence errors in the acquired raw data, which cause moiré artifacts in the reconstructed images. We developed an enhanced reconstruction algorithm capable of compensating these errors by adjusting the grating positions and thus suppressing the occurrence of moiré artifacts. The algorithm has been developed with regard to a future application in medical practice. The capability of the algorithm is demonstrated on a medical data set of a human hand (post-mortem) acquired under clinical conditions using a pre-clinical TXLI prototype. It is shown that the algorithm reliably suppresses moiré artifacts, preserves image contrast, does not blur anatomical structures or prevent quantitative imaging, and is executable on low-dose data sets. In addition, the algorithm runs autonomously without the need of interaction or rework of the final results. In conclusion, the proposed reconstruction algorithm facilitates the use of TLXI in clinical practice and allows the exploitation of the method's full diagnostic potential in future medical applications.

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 to Depict Acute Lung Inflammation in Mice.

The aim of this study was to evaluate the feasibility of early stage imaging of acute lung inflammation in mice using grating-based X-ray dark-field imaging in vivo. Acute lung inflammation was induced in mice by orotracheal instillation of porcine pancreatic elastase. Control mice received orotracheal instillation of PBS. Mice were imaged immediately before and 1 day after the application of elastase or PBS to assess acute changes in pulmonary structure due to lung inflammation. Subsequently, 6 mice from each group were sacrificed and their lungs were lavaged and explanted for histological analysis. A further 7, 14 and 21 days later the remaining mice were imaged again. All images were acquired with a prototype grating-based small-animal scanner to generate dark-field and transmission radiographs. Lavage confirmed that mice in the experimental group had developed acute lung inflammation one day after administration of elastase. Acute lung inflammation was visible as a striking decrease in signal intensity of the pulmonary parenchyma on dark-field images at day 1. Quantitative analysis confirmed that dark-field signal intensity at day 1 was significantly lower than signal intensities measured at the remaining timepoints, confirming that acute lung inflammation can be depicted in vivo with dark-field radiography.

Improved Detection of Foreign Bodies on Radiographs Using X-ray Dark-Field and Phase-Contrast Imaging.

PURPOSE: The aim of this study was to investigate whether the detection of foreign bodies can be improved using dark-field and phase-contrast radiography compared with conventional (transmission) radiographs. MATERIALS AND METHODS: Experiments were performed using ex vivo pig paws, which were prepared with differently sized foreign bodies of metal, wood, and glass (n = 10 each). Paws without foreign bodies served as controls (n = 30). All images were acquired using an experimental grating-based large object radiography system. Five blinded readers (second- to fourth-year radiology residents) were asked to assess the presence or absence of any foreign body. Sensitivity and specificity for the detection of metal, wood, glass, and any foreign body were calculated and compared using McNemar test and generalized linear mixed models. RESULTS: Sensitivity for the detection of metal foreign bodies was 100% for all readers and image combinations. The sensitivity for the detection of wooden foreign bodies increased from 2% for transmission images to 78% when dark-field images were added (P < 0.0001). For glass foreign bodies, sensitivity increased from 84% for transmission images to 96% when adding phase-contrast images (P = 0.041). Sensitivity for the detection of any foreign body was 91% when transmission, dark-field, and phase-contrast images were viewed simultaneously, compared with 62% for transmission images alone (P < 0.0001). Specificity was 99% to 100% across all readers and radiography modalities. CONCLUSIONS: Adding dark-field images substantially improves the detection of wooden foreign bodies compared with the analysis of conventional (transmission) radiographs alone. Detection of glass foreign bodies was moderately improved when adding phase-contrast images.

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.

Qualitative and Quantitative Imaging Evaluation of Renal Cell Carcinoma Subtypes with Grating-based X-ray Phase-contrast CT.

Current clinical imaging methods face limitations in the detection and correct characterization of different subtypes of renal cell carcinoma (RCC), while these are important for therapy and prognosis. The present study evaluates the potential of grating-based X-ray phase-contrast computed tomography (gbPC-CT) for visualization and characterization of human RCC subtypes. The imaging results for 23 ex vivo formalin-fixed human kidney specimens obtained with phase-contrast CT were compared to the results of the absorption-based CT (gbCT), clinical CT and a 3T MRI and validated using histology. Regions of interest were placed on each specimen for quantitative evaluation. Qualitative and quantitative gbPC-CT imaging could significantly discriminate between normal kidney cortex (54 ± 4 HUp) and clear cell (42 ± 10), papillary (43 ± 6) and chromophobe RCCs (39 ± 7), p < 0.05 respectively. The sensitivity for detection of tumor areas was 100%, 50% and 40% for gbPC-CT, gbCT and clinical CT, respectively. RCC architecture like fibrous strands, pseudocapsules, necrosis or hyalinization was depicted clearly in gbPC-CT and was not equally well visualized in gbCT, clinical CT and MRI. The results show that gbPC-CT enables improved discrimination of normal kidney parenchyma and tumorous tissues as well as different soft-tissue components of RCCs without the use of contrast media.

X-ray Dark-field Radiography - In-Vivo Diagnosis of Lung Cancer in Mice.

Accounting for about 1.5 million deaths annually, lung cancer is the prevailing cause of cancer deaths worldwide, mostly associated with long-term smoking effects. Numerous small-animal studies are performed currently in order to better understand the pathogenesis of the disease and to develop treatment strategies. Within this letter, we propose to exploit X-ray dark-field imaging as a novel diagnostic tool for the detection of lung cancer on projection radiographs. Here, we demonstrate in living mice bearing lung tumors, that X-ray dark-field radiography provides significantly improved lung tumor detection rates without increasing the number of false-positives, especially in the case of small and superimposed nodules, when compared to conventional absorption-based imaging. While this method still needs to be adapted to larger mammals and finally humans, the technique presented here can already serve as a valuable tool in evaluating novel lung cancer therapies, tested in mice and other small animal models.

X-ray dark-field radiography facilitates the diagnosis of pulmonary fibrosis in a mouse model.

The aim of this study was to evaluate whether diagnosing pulmonary fibrosis with projection radiography can be improved by using X-ray dark-field radiograms. Pulmonary X-ray transmission and dark-field images of C57Bl/6N mice, either treated with bleomycin to induce pulmonary fibrosis or PBS to serve as controls, were acquired with a prototype grating-based small-animal scanner. Two blinded readers, both experienced radiologists and familiar with dark-field imaging, had to assess dark-field and transmission images for the absence or presence of fibrosis. Furthermore readers were asked to grade their stage of diagnostic confidence. Histological evaluation of the lungs served as the standard of reference in this study. Both readers showed a notably higher diagnostic confidence when analyzing the dark-field radiographs (p < 0.001). Diagnostic accuracy improved significantly when evaluating the lungs in dark-field images alone (p = 0.02) or in combination with transmission images (p = 0.01) compared to sole analysis of absorption images. Interreader agreement improved from good when assessing only transmission images to excellent when analyzing dark-field images alone or in combination with transmission images. Adding dark-field images to conventional transmission images in a murine model of pulmonary fibrosis leads to an improved diagnosis of this disease on chest radiographs.

Facilitated Diagnosis of Pneumothoraces in Newborn Mice Using X-ray Dark-Field Radiography.

OBJECTIVE: The aim of this study was to evaluate the diagnostic value of x-ray dark-field imaging in projection radiography-based depiction of pneumothoraces in the neonatal murine lung, a potentially life-threatening medical condition that requires a timely and correct diagnosis. MATERIALS AND METHODS: By the use of a unique preclinical model, 7-day-old C57Bl/6N mice received mechanical ventilation for 2 or 8 hours with oxygen-rich gas (FIO2 = 0.4; n = 24). Unventilated mice either spontaneously breathed oxygen-rich gas (FIO2 = 0.4) for 2 or 8 hours or room air (n = 22). At the end of the experiment, lungs were inflated with a standardized volume of air after a lethal dose of pentobarbital was administered to the pups. All lungs were imaged with a prototype grating-based small-animal scanner to acquire x-ray transmission and dark-field radiographs. Image contrast between the air-filled pleural space and lung tissue was quantified for both transmission and dark-field radiograms. After the independent expert's assessment, 2 blinded readers evaluated all dark-field and transmission images for the presence or absence of pneumothoraces. Contrast ratios, diagnostic accuracy, as well as reader's confidence and interreader agreement were recorded for both imaging modalities. RESULTS: Evaluation of both x-ray transmission and dark-field radiographs by independent experts revealed the development of a total of 10 pneumothoraces in 8 mice. Here, the contrast ratio between the air-filled pleural space of the pneumothoraces and the lung tissue was significantly higher in the dark field (8.4 ± 3.5) when compared with the transmission images (5.1 ± 2.8; P < 0.05). Accordingly, the readers' diagnostic confidence for the diagnosis of pneumothoraces was significantly higher for dark-field compared with transmission images (P = 0.001). Interreader agreement improved from moderate for the analysis of transmission images alone (κ = 0.41) to very good when analyzing dark-field images alone (κ = 0.90) or in combination with transmission images (κ = 0.88). Diagnostic accuracy significantly improved for the analysis of dark-field images alone (P = 0.04) or in combination with transmission images (P = 0.02), compared with the analysis of transmission radiographs only. CONCLUSIONS: The significant improvement in contrast ratios between lung parenchyma and free air in the dark-field images allows the facilitated detection of pneumothoraces in the newborn mouse. These preclinical experiments indicate the potential of the technique for future clinical applications.