Dark-field chest X-ray imaging for the assessment of COVID-19-pneumonia

Manuela Frank, Florian T. Gassert, Theresa Urban, Konstantin Willer, Wolfgang Noichl, Rafael Schick, Manuel Schultheiss, Manuel Viermetz, Bernhard Gleich, Fabio De Marco, Julia Herzen, Thomas Koehler, Klaus Jürgen Engel, Bernhard Renger, Felix G. Gassert, Andreas Sauter, Alexander A. Fingerle, Bernhard Haller, Marcus R. Makowski, Daniela PfeifferFranz Pfeiffer

Publikation: Beitrag in FachzeitschriftArtikelBegutachtung

10 Zitate (Scopus)

Abstract

Background: Currently, alternative medical imaging methods for the assessment of pulmonary involvement in patients infected with COVID-19 are sought that combine a higher sensitivity than conventional (attenuation-based) chest radiography with a lower radiation dose than CT imaging. Methods: Sixty patients with COVID-19-associated lung changes in a CT scan and 40 subjects without pathologic lung changes visible in the CT scan were included (in total, 100, 59 male, mean age 58 ± 14 years). All patients gave written informed consent. We employed a clinical setup for grating-based dark-field chest radiography, obtaining both a dark-field and a conventional attenuation image in one image acquisition. Attenuation images alone, dark-field images alone, and both displayed simultaneously were assessed for the presence of COVID-19-associated lung changes on a scale from 1 to 6 (1 = surely not, 6 = surely) by four blinded radiologists. Statistical analysis was performed by evaluation of the area under the receiver–operator-characteristics curves (AUC) using Obuchowski’s method with a 0.05 level of significance. Results: We show that dark-field imaging has a higher sensitivity for COVID-19-pneumonia than attenuation-based imaging and that the combination of both is superior to one imaging modality alone. Furthermore, a quantitative image analysis shows a significant reduction of dark-field signals for COVID-19-patients. Conclusions: Dark-field imaging complements and improves conventional radiography for the visualisation and detection of COVID-19-pneumonia.

OriginalspracheEnglisch
Aufsatznummer147
FachzeitschriftCommunications Medicine
Jahrgang2
Ausgabenummer1
DOIs
PublikationsstatusVeröffentlicht - Dez. 2022

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