19
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

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

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          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.

          Related collections

          Most cited references33

          • Record: found
          • Abstract: found
          • Article: not found

          An innovative digital imaging set-up allowing a low-dose approach to phase contrast applications in the medical field.

          Recently, new imaging modalities based on the detection of weak phase perturbations effects, among which are phase contrast and diffraction imaging, have been developed by several researchers. Due to their high sensitivity to weakly absorbing details, these techniques seem to be very promising for applications in the medical field. On the other hand, digital radiology is undergoing a wide diffusion, and its benefits are presently very well understood. Up to now, however, the strong pixel size constraints associated with phase contrast pattern detection limited the possibility of exploiting the advantages of phase contrast in digital radiology applications. In this paper, an innovative setup capable of removing the pixel size constraints, and thus opening the way to low dose digital phase contrast imaging, is described. Furthermore, we introduce an imaging technique based on the detection of radiation scattered at small angles: the information extracted from the sample is increased at no dose expense. We believe that several radiological fields, mammography being the first important example, may benefit from the herein described innovative imaging techniques.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Clinical Presentation of Patients With Tension Pneumothorax: A Systematic Review.

            To determine whether the reported clinical presentation of tension pneumothorax differs between patients who are breathing unassisted versus receiving assisted ventilation.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              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.
                Bookmark

                Author and article information

                Contributors
                katharina.hellbach@med.uni-muenchen.de
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                8 February 2018
                8 February 2018
                2018
                : 8
                : 2602
                Affiliations
                [1 ]Department of Radiology, University Hospital, LMU Munich, 81377 Munich, Germany
                [2 ]ISNI 0000 0004 1936 973X, GRID grid.5252.0, Chair for Molecular Animal Breeding and Biotechnology, , Ludwig-Maximilians-University Munich, ; Munich, 85764 Oberschleißheim Germany
                [3 ]ISNI 0000000123222966, GRID grid.6936.a, Chair of Biomedical Physics & Munich School of BioEngineering, , Technical University of Munich, ; Munich, 85748 Garching Germany
                [4 ]ISNI 0000000123222966, GRID grid.6936.a, Department of Diagnostic and Interventional Radiology, , Technical University of Munich, ; 81675 Munich, Germany
                [5 ]Philips Medical Systems DMC GmbH, 22335 Hamburg, Germany
                [6 ]ISNI 0000 0004 0373 4886, GRID grid.418621.8, Philips GmbH Innovative Technologies, Research Laboratories, ; 22335 Hamburg, Germany
                [7 ]ISNI 0000000123222966, GRID grid.6936.a, Institute for Advanced Study, , Technical University of Munich, ; 85748 Garching, Germany
                [8 ]ISNI 0000 0001 0075 5874, GRID grid.7892.4, Institute of Microstructure Technology, , Karlsruhe Institute of Technology (KIT), ; 76344 Eggenstein-Leopoldshafen, Germany
                [9 ]German Center for Lung Research (DZL), Comprehensive Pneumology Center (CPC-M), Helmholtz Zentrum Munich, 81377 Munich, Germany
                Author information
                http://orcid.org/0000-0002-3561-7305
                http://orcid.org/0000-0003-1097-9323
                http://orcid.org/0000-0002-9456-1591
                http://orcid.org/0000-0002-4991-4933
                Article
                20985
                10.1038/s41598-018-20985-y
                5805747
                29422512
                c47ea596-1ced-4750-be35-97c25975ea71
                © The Author(s) 2018

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 21 July 2017
                : 29 January 2018
                Categories
                Article
                Custom metadata
                © The Author(s) 2018

                Uncategorized
                Uncategorized

                Comments

                Comment on this article

                scite_
                0
                0
                0
                0
                Smart Citations
                0
                0
                0
                0
                Citing PublicationsSupportingMentioningContrasting
                View Citations

                See how this article has been cited at scite.ai

                scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

                Similar content137

                Cited by14

                Most referenced authors304