Detection of Post-COVID-19 Lung Abnormalities: Photon-counting CT versus Same-Day Energy-integrating Detector CT
Authors
Prayer, FlorianKienast, Patric
Strassl, Andreas
Moser, Philipp T
Bernitzky, Dominik
Milacek, Christopher
Gyöngyösi, Mariann
Kifjak, Daria
Röhrich, Sebastian
Beer, Lucian
Watzenböck, Martin L
Milos, Ruxandra I
Wassipaul, Christian
Gompelmann, Daniela
Herold, Christian J
Prosch, Helmut
Heidinger, Benedikt H
UMass Chan Affiliations
RadiologyDocument Type
Journal ArticlePublication Date
2022-11-29Keywords
Photon-counting detector CTpost-COVID-19 lung abnormalities
pulmonary fibrosis
energy-integrating detector CT
Metadata
Show full item recordAbstract
Background Photon-counting detector (PCD) CT enables ultra-high-resolution lung imaging and may shed light on morphologic correlates of persistent symptoms after COVID-19. Purpose To compare PCD CT with energy-integrating detector (EID) CT for noninvasive assessment of post-COVID-19 lung abnormalities. Materials and Methods For this prospective study, adult participants with one or more COVID-19-related persisting symptoms (resting or exertional dyspnea, cough, fatigue) underwent same-day EID and PCD CT between April 2022 and June 2022. The 1.0-mm EID CT images and, subsequently, 1.0-, 0.4-, and 0.2-mm PCD CT images were reviewed for the presence of lung abnormalities. Subjective and objective EID and PCD CT image quality were evaluated using a five-point Likert scale (-2 to 2) and lung signal-to-noise ratios (SNRs). Results Twenty participants (mean age, 54 years ± 16 [SD]; 10 men) were included. EID CT showed post-COVID-19 lung abnormalities in 15 of 20 (75%) participants, with a median involvement of 10% of lung volume [IQR, 0%-45%] and 3.5 lobes [IQR, 0-5]. Ground-glass opacities and linear bands (10 of 20 participants [50%] for both) were the most frequent findings at EID CT. PCD CT revealed additional lung abnormalities in 10 of 20 (50%) participants, with the most common being bronchiectasis (10 of 20 [50%]). Subjective image quality was improved for 1.0-mm PCD versus 1.0-mm EID CT images (median, 1; IQR, 1-2; P < .001) and 0.4-mm versus 1.0-mm PCD CT images (median, 1; IQR, 1-1; P < .001) but not for 0.4-mm versus 0.2-mm PCD CT images (median, 0; IQR, 0-0.5; P = .26). PCD CT delivered higher lung SNR versus EID CT for 1.0-mm images (mean difference, 0.53 ± 0.96; P = .03) but lower SNR for 0.4-mm versus 1.0-mm images and 0.2-mm vs 0.4-mm images (-1.52 ± 0.68 [P < .001] and -1.15 ± 0.43 [P < .001], respectively). Conclusion Photon-counting detector CT outperformed energy-integrating detector CT in the visualization of subtle post-COVID-19 lung abnormalities and image quality. © RSNA, 2023 Supplemental material is available for this article.Source
Prayer F, Kienast P, Strassl A, Moser PT, Bernitzky D, Milacek C, Gyöngyösi M, Kifjak D, Röhrich S, Beer L, Watzenböck ML, Milos RI, Wassipaul C, Gompelmann D, Herold CJ, Prosch H, Heidinger BH. Detection of Post-COVID-19 Lung Abnormalities: Photon-counting CT versus Same-Day Energy-integrating Detector CT. Radiology. 2023 Apr;307(1):e222087. doi: 10.1148/radiol.222087. Epub 2022 Nov 29. PMID: 36445225; PMCID: PMC9718279.DOI
10.1148/radiol.222087Permanent Link to this Item
http://hdl.handle.net/20.500.14038/52096PubMed ID
36445225Rights
Copyright © 2022 by the Radiological Society of North America, Inc. Publisher's version posted after 6 months with a Creative Commons Attribution-NonCommerical-NoDerivatives 4.0 International License (CC BY-NC-ND) as allowed by the publisher's open access policy at https://pubs.rsna.org/page/openaccess.Distribution License
https://creativecommons.org/licenses/by-nc-nd/4.0/ae974a485f413a2113503eed53cd6c53
10.1148/radiol.222087
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Except where otherwise noted, this item's license is described as Copyright © 2022 by the Radiological Society of North America, Inc. Publisher's version posted after 6 months with a Creative Commons Attribution-NonCommerical-NoDerivatives 4.0 International License (CC BY-NC-ND) as allowed by the publisher's open access policy at https://pubs.rsna.org/page/openaccess.