Background: Dark-field chest radiography allows the assessment of the structural integrity of the alveoli by exploiting the wave properties of x-rays.
Purpose: To compare the qualitative and quantitative features of dark-field chest radiography in patients with COVID-19 pneumonia with conventional CT imaging.
Materials And Methods: In this prospective study conducted from May 2020 to December 2020, patients aged at least 18 years who underwent chest CT for clinically suspected COVID-19 infection were screened for participation. Inclusion criteria were a CO-RADS score ≥4, the ability to consent to the procedure and to stand upright without help. Participants were examined with a clinical dark-field chest radiography prototype. For comparison, a healthy control cohort of 40 subjects was evaluated. Using Spearman's correlation coefficient, correlation was tested between dark-field coefficient and CT-based COVID-19 index and visual total CT score as well as between the visual total dark-field score and the visual total CT score.
Results: A total of 98 participants [mean age 58 ± 14 (standard deviation) years; 59 men] were studied. The areas of signal intensity reduction observed in dark-field images showed a strong correlation with infiltrates identified on CT scans. The dark-field coefficient had a negative correlation with both the quantitative CT-based COVID-19 index ( = -.34, = .001) and the overall CT score used for visual grading of COVID-19 severity ( = -.44, < .001). The total visual dark-field score for the presence of COVID-19 was positively correlated to the total CT score for visual COVID-19 severity grading ( = .85, < .001).
Conclusion: COVID-19 pneumonia-induced signal intensity losses in dark-field chest radiographs are consistent with CT-based findings, showing the technique's potential for COVID-19 assessment.
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http://dx.doi.org/10.3389/fradi.2024.1487895 | DOI Listing |
Front Radiol
January 2025
Department of Diagnostic and Interventional Radiology, School of Medicine & Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Background: Dark-field chest radiography allows the assessment of the structural integrity of the alveoli by exploiting the wave properties of x-rays.
Purpose: To compare the qualitative and quantitative features of dark-field chest radiography in patients with COVID-19 pneumonia with conventional CT imaging.
Materials And Methods: In this prospective study conducted from May 2020 to December 2020, patients aged at least 18 years who underwent chest CT for clinically suspected COVID-19 infection were screened for participation.
Med Phys
January 2025
Department of Engineering Physics, Tsinghua University, Beijing, China.
Background: X-ray grating-based dark-field imaging can sense the small angle scattering caused by object's micro-structures. This technique is sensitive to the porous microstructure of lung alveoli and has the potential to detect lung diseases at an early stage. Up to now, a human-scale dark-field CT (DF-CT) prototype has been built for lung imaging.
View Article and Find Full Text PDFPLoS One
December 2024
Chair of Biomedical Physics, Department of Physics & School of Natural Sciences, Technical University of Munich, Garching bei München, Germany.
Background: Dark-field radiography has been proven to be a promising tool for the assessment of various lung diseases.
Purpose: To evaluate the potential of dose reduction in dark-field chest radiography for the detection of the Coronavirus SARS-CoV-2 (COVID-19) pneumonia.
Materials And Methods: Patients aged at least 18 years with a medically indicated chest computed tomography scan (CT scan) were screened for participation in a prospective study between October 2018 and December 2020.
Background: X-ray dark-field imaging (XDFI) has been explored to provide superior performance over the conventional X-ray imaging for the diagnosis of many pathologic conditions. A simulation tool to reliably predict clinical XDFI images at a human scale, however, is currently missing.
Purpose: In this paper, we demonstrate XDFI simulation at a human scale for the first time to the best of our knowledge.
X-ray computed tomography (CT) is a crucial tool for non-invasive medical diagnosis that uses differences in materials' attenuation coefficients to generate contrast and provide 3D information. Grating-based dark-field-contrast X-ray imaging is an innovative technique that utilizes small-angle scattering to generate additional co-registered images with additional microstructural information. While it is already possible to perform human chest dark-field radiography, it is assumed that its diagnostic value increases when performed in a tomographic setup.
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