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Jpn J Radiol. Ultra-high-resolution computed tomography can demonstrate alveolar collapse in novel coronavirus (COVID-19) pneumonia

tetano

Editor, Senior Moderator
Jpn J Radiol. 2020 Mar 31. doi: 10.1007/s11604-020-00956-y. [Epub ahead of print]
Ultra-high-resolution computed tomography can demonstrate alveolar collapse in novel coronavirus (COVID-19) pneumonia.


Iwasawa T[SUP]1,[/SUP][SUP]2[/SUP], Sato M[SUP]3[/SUP], Yamaya T[SUP]3[/SUP], Sato Y[SUP]3[/SUP], Uchida Y[SUP]3[/SUP], Kitamura H[SUP]3[/SUP], Hagiwara E[SUP]3[/SUP], Komatsu S[SUP]3[/SUP], Utsunomiya D[SUP]4,[/SUP][SUP]5[/SUP], Ogura T[SUP]3[/SUP].

Author information




Abstract

PURPOSE:

To review the chest computed tomography (CT) findings on the ultra-high-resolution CT (U-HRCT) in patients with the Novel coronavirus disease 2019 (COVID-19).
MATERIALS AND METHODS:

In February 2020, six consecutive patients with COVID-19 pneumonia (median age, 69 years) underwent U-HR CT imaging. U-HR-CT has a larger matrix size of 1024 ? 1024 thinner slice thickness of 0.25 mm and can demonstrate terminal bronchioles in the normal lungs; as a result, Reid's secondary lobules and their abnormalities can be identified. The distribution and hallmarks (ground-glass opacity, consolidation with or without architectural distortion, linear opacity, crazy paving) of the lung opacities on U-HRCT were visually evaluated on a 1 K monitor by two experienced reviewers. The CT lung volume was measured, and the ratio of the measured lung volume to the predicted total lung capacity (predTLC) based on sex, age and height was calculated.
RESULTS:

All cases showed crazy paving pattern in U-HRCT. In these lesions, the secondary lobules were smaller than those in the un-affected lungs. CT lung volume decreased in two cases comparing predTLC.
CONCLUSION:

U-HRCT can evaluate not only the distribution and hallmarks of COVID-19 pneumonia but also visualize local lung volume loss.



KEYWORDS:

Crazy-paving pattern; Novel coronavirus; Pneumonia; Ultra-high-resolution computed tomography


PMID:32236856DOI:10.1007/s11604-020-00956-y
 
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