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Best Practice: International Multisociety Consensus Statement for Post-COVID-19 Residual Abnormalities on Chest CT Scans.

Publication ,  Journal Article
Yoon, SH; Kanne, JP; Ashizawa, K; Biederer, J; Castañer, E; Fan, L; Frauenfelder, T; Ghaye, B; Henry, TS; Huang, Y-S; Jeong, YJ; Kay, FU ...
Published in: Radiology
July 2025

Residual lung abnormalities on CT scans after COVID-19 respiratory infection may be associated with persistent or progressive respiratory symptoms and frequently correlate with abnormal pulmonary function testing results. These abnormalities have been described using varying terms in numerous publications. Chest CT lung abnormalities after COVID-19 infection tend to stabilize or regress over time, indicating that they are nonprogressive and postinfectious in nature. This multisociety consensus statement, developed by 21 thoracic radiologists from the European Society of Thoracic Imaging, the Society of Thoracic Radiology, and the Asian Society of Thoracic Radiology with a two-round survey process, aims to standardize the indication, acquisition, and reporting of post-COVID-19 residual lung abnormalities on CT scans. Key recommendations include performing chest CT in patients with persistent or progressive respiratory symptoms 3 months after infection, using low-dose CT protocols (range, 1-3 mSv) for follow-up chest CT examinations, using Fleischner Society glossary of terms for radiologic descriptors, and avoiding the term interstitial lung abnormality to describe post-COVID-19 abnormalities. Instead, to prevent misinterpreting post-COVID-19 abnormalities as an early manifestation of interstitial lung disease, use the term post-COVID-19 residual lung abnormality. This consensus statement will help harmonize radiology practice and research for the substantial number of affected patients.

Duke Scholars

Published In

Radiology

DOI

EISSN

1527-1315

Publication Date

July 2025

Volume

316

Issue

1

Start / End Page

e243374

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Societies, Medical
  • SARS-CoV-2
  • Radiography, Thoracic
  • Nuclear Medicine & Medical Imaging
  • Lung
  • Humans
  • Consensus
  • COVID-19
  • 3202 Clinical sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Yoon, S. H., Kanne, J. P., Ashizawa, K., Biederer, J., Castañer, E., Fan, L., … Larici, A. R. (2025). Best Practice: International Multisociety Consensus Statement for Post-COVID-19 Residual Abnormalities on Chest CT Scans. Radiology, 316(1), e243374. https://doi.org/10.1148/radiol.243374
Yoon, Soon Ho, Jeffrey P. Kanne, Kazuto Ashizawa, Jürgen Biederer, Eva Castañer, Li Fan, Thomas Frauenfelder, et al. “Best Practice: International Multisociety Consensus Statement for Post-COVID-19 Residual Abnormalities on Chest CT Scans.Radiology 316, no. 1 (July 2025): e243374. https://doi.org/10.1148/radiol.243374.
Yoon SH, Kanne JP, Ashizawa K, Biederer J, Castañer E, Fan L, et al. Best Practice: International Multisociety Consensus Statement for Post-COVID-19 Residual Abnormalities on Chest CT Scans. Radiology. 2025 Jul;316(1):e243374.
Yoon, Soon Ho, et al. “Best Practice: International Multisociety Consensus Statement for Post-COVID-19 Residual Abnormalities on Chest CT Scans.Radiology, vol. 316, no. 1, July 2025, p. e243374. Pubmed, doi:10.1148/radiol.243374.
Yoon SH, Kanne JP, Ashizawa K, Biederer J, Castañer E, Fan L, Frauenfelder T, Ghaye B, Henry TS, Huang Y-S, Jeong YJ, Kay FU, Kligerman S, Ko JP, Parkar AP, Piyavisetpat N, Prosch H, Raptis CA, Simpson S, Tanaka N, Brown KK, Inoue Y, Sandbo N, Richeldi L, Larici AR. Best Practice: International Multisociety Consensus Statement for Post-COVID-19 Residual Abnormalities on Chest CT Scans. Radiology. 2025 Jul;316(1):e243374.

Published In

Radiology

DOI

EISSN

1527-1315

Publication Date

July 2025

Volume

316

Issue

1

Start / End Page

e243374

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Societies, Medical
  • SARS-CoV-2
  • Radiography, Thoracic
  • Nuclear Medicine & Medical Imaging
  • Lung
  • Humans
  • Consensus
  • COVID-19
  • 3202 Clinical sciences