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Updated: May 8, 2025

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
Published on: December 19, 2020
Simulated low-dose dark-field radiography for detection of COVID-19 pneumonia
Rafael C Schick1,2,3, Henriette Bast1,2,3, Manuela Frank1,2,3
1Chair 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. Patients were included if they had a CO-RADS (COVID-19 Reporting and Data System) score ≥ 4 (COVID-19 group) or if they had no pathologic lung changes (controls). A total of 89 participants with a median age of 60 years (interquartile range 48 to 68 yrs.) were included in this study. Dark-field and attenuation-based radiographs were simultaneously obtained by using a prototype system for dark-field radiography. By modifying the image reconstruction algorithm, low-dose radiographs were simulated based on real participant images. The simulated radiographs corresponded to 50%, 25%, and 13% of the full dose (41.9 μSv, median value). Four experienced radiologists served as blinded readers assessing both image modalities, displayed side by side in random order. The presence of COVID-19-associated lung changes was rated on a scale from 1 to 6. The readers' diagnostic performance was evaluated by analyzing the area under the receiver operating characteristic curves (AUC) using Obuchowski's method. Also, the dark-field images were analyzed quantitatively by comparing the dark-field coefficients within and between the COVID-19 and the control group.
Results:
The readers' diagnostic performance in the image evaluation, as described by the AUC value (where a value of 1 corresponds to perfect diagnostic accuracy), did not differ significantly between the full dose images (AUC = 0.86) and the simulated images at 50% (AUC = 0.86) and 25% of the full dose(AUC = 0.84) (p>0.050), but was slightly lower at 13% dose (AUC = 0.82) (p = 0.038). For all four radiation dose levels, the median dark-field coefficients within groups were identical but different significantly by 15% between the controls and the COVID-19 pneumonia group (p<0.001).
Conclusion:
Dark-field imaging can be used to diagnose the Coronavirus SARS-CoV-2 (COVID-19) pneumonia with a median dose of 10.5 μSv, which corresponds to 25% of the original dose used for dark-field chest imaging.
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