ArticleJapanese journal of radiology2020
Ultra-high-resolution computed tomography can demonstrate alveolar collapse in novel coronavirus (COVID-19) pneumonia.
Article in Japanese journal of radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 47 papers, 3 of them syntheses that pooled it.
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Who cites it
47 citing papers in PubMed, 3 syntheses or guidelines pooled it, 71 citations in OpenAlex.
- Do COVID-19 CT features vary between patients from within and outside mainland China? Findings from a meta-analysis.Frontiers in public health · 2022Pooled it
- CT in coronavirus disease 2019 (COVID-19): a systematic review of chest CT findings in 4410 adult patients.European radiology · 2020Pooled it
- Diagnostic Performance of CT and Reverse Transcriptase Polymerase Chain Reaction for Coronavirus Disease 2019: A Meta-Analysis.Radiology · 2020Pooled it
- Corticosteroids for hospitalized patients with mild to critically-ill COVID-19: a multicenter, retrospective, propensity score-matched study.Scientific reports · 2021Trial
- Performance of a deep-learning-based lung nodule detection system using 0.25-mm thick ultra-high-resolution CT images.Japanese journal of radiology · 2025Article
- Improvement of Quantification of Myocardial Synthetic ECV with Second-Generation Deep Learning Reconstruction.Journal of cardiovascular development and disease · 2024Article
- Super-resolution deep-learning reconstruction for cardiac CT: impact of radiation dose and focal spot size on task-based image quality.Physical and engineering sciences in medicine · 2024Article
- Evaluation of four computed tomography reconstruction algorithms using a coronary artery phantom.Quantitative imaging in medicine and surgery · 2024Article
- Effectiveness of deep learning reconstruction on standard to ultra-low-dose high-definition chest CT images.Japanese journal of radiology · 2023Article
- Gradually Progressive Interstitial Pneumonia Following COVID-19 in an Older Patient: A Case Report.Cureus · 2023Article
- Quantitative Analysis for Lung Disease on Thin-Section CT.Diagnostics (Basel, Switzerland) · 2023Review
- Quantitative Assessment of Lung Volumes and Enhancement in Patients with COVID-19: Role of Dual-Energy CT.Diagnostics (Basel, Switzerland) · 2023Article
- Pathological Roles of Pulmonary Cells in Acute Lung Injury: Lessons from Clinical Practice.International journal of molecular sciences · 2022Review
- Imaging Pulmonary Blood Vessels and Ventilation-Perfusion Mismatch in COVID-19.Molecular imaging and biology · 2022Review
- Evaluation of the models generated from clinical features and deep learning-based segmentations: Can thoracic CT on admission help us to predict hospitalized COVID-19 patients who will require intensive care?BMC medical imaging · 2022Article
- Role of the renin-angiotensin system in NETosis in the coronavirus disease 2019 (COVID-19).Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2022Review
- Comparison of visibility of in-stent restenosis between conventional- and ultra-high spatial resolution computed tomography: coronary arterial phantom study.Japanese journal of radiology · 2022Article
- ECG-BiCoNet: An ECG-based pipeline for COVID-19 diagnosis using Bi-Layers of deep features integration.Computers in biology and medicine · 2022Article
- Visual classification of three computed tomography lung patterns to predict prognosis of COVID-19: a retrospective study.BMC pulmonary medicine · 2022Article
- A novel strategy to develop deep learning for image super-resolution using original ultra-high-resolution computed tomography images of lung as training dataset.Japanese journal of radiology · 2022Article
Corrections and comments
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- Erratum issued
Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo 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
methodsIn 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.
resultsAll 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.
conclusionU-HRCT can evaluate not only the distribution and hallmarks of COVID-19 pneumonia but also visualize local lung volume loss.
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