ArticleQuantitative imaging in medicine and surgery2020
Chest lesion CT radiological features and quantitative analysis in RT-PCR turned negative and clinical symptoms resolved COVID-19 patients.
Article in Quantitative imaging in medicine and surgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed, 26 citations in OpenAlex.
- Predicting malignant potential of solitary pulmonary nodules in patients with COVID-19 infection: a comprehensive analysis of CT imaging and tumor markers.BMC infectious diseases · 2024Article
- Admission chest CT findings and risk assessment for stroke-associated pneumonia.Acta neurologica Belgica · 2023Article
- A prospective cohort study on radiological and physiological outcomes of recovered COVID-19 patients 6 months after discharge.Quantitative imaging in medicine and surgery · 2021Article
- Thin-section computed tomography findings and longitudinal variations of the residual pulmonary sequelae after discharge in patients with COVID-19: a short-term follow-up study.European radiology · 2021Article
- The relationship between lesion density change in chest computed tomography and clinical improvement in COVID-19 patients.International journal of clinical practice · 2021Article
- Chest CT findings in patients with coronavirus disease 2019 (COVID-19): a comprehensive review.Diagnostic and interventional radiology (Ankara, Turkey) · 2021Review
- Quantitative CT for detecting COVID‑19 pneumonia in suspected cases.BMC infectious diseases · 2021Article
- The Applications of Artificial Intelligence in Chest Imaging of COVID-19 Patients: A Literature Review.Diagnostics (Basel, Switzerland) · 2021Review
- Longitudinal trajectories of pneumonia lesions and lymphocyte counts associated with disease severity among convalescent COVID-19 patients: a group-based multi-trajectory analysis.BMC pulmonary medicine · 2021Article
- Progression to fibrosing diffuse alveolar damage in a series of 30 minimally invasive autopsies with COVID-19 pneumonia in Wuhan, China.Histopathology · 2021Article
- Role of Machine Learning Techniques to Tackle the COVID-19 Crisis: Systematic Review.JMIR medical informatics · 2021Review
- Optimization of imaging parameters in chest CT for COVID-19 patients: an experimental phantom study.Quantitative imaging in medicine and surgery · 2021Article
- CT suggests discharged Covid-19 patients who were retested RT-PCR positive again for SARS-CoV-2 more likely had false negative RT-PCR tests before discharging.Quantitative imaging in medicine and surgery · 2020Article
- AI-Based Quantitative CT Analysis of Temporal Changes According to Disease Severity in COVID-19 Pneumonia.Journal of computer assisted tomographyArticle
- Use of Conventional Chest Imaging and Artificial Intelligence in COVID-19 Infection. A Review of the Literature.Open respiratory archivesReview
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9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMany studies have described lung lesion computed tomography (CT) features of coronavirus disease 2019 (COVID-19) patients at the early and progressive stages. In this study, we aim to evaluate lung lesion CT radiological features along with quantitative analysis for the COVID-19 patients ready for discharge.
methodsFrom February 10 to March 10, 2020, 125 COVID-19 patients (age: 16-67 years, 63 males) ready for discharge, with two consecutive negative reverse transcription-polymerase chain reaction (RT-PCR) and no clinical symptoms for more than 3 days, were included. The pre-discharge CT was performed on all patients 1-3 days after the second negative RT-PCR test, and the follow-up CTs were performed on 44 patients 2-13 days later. The imaging features and quantitative analysis were evaluated on both the pre-discharge and the follow-up CTs, by both radiologists and an artificial intelligence (AI) software.
resultsOn the pre-discharge CT, the most common CT findings included ground-glass opacity (GGO) (99/125, 79.2%) with bilateral mixed distribution, and fibrosis (56/125, 44.8%) with bilateral subpleural distribution. Enlarged mediastinal lymph nodes were also commonly observed (45/125, 36.0%). AI enabled quantitative analysis showed the right lower lobe was mostly involved, and lesions most commonly had CT value of -570 to -470 HU consistent with GGO. Follow-up CT showed GGO decrease in size and density (40/40, 100%) and fibrosis reduction (17/26, 65.4%). Compared with the pre-discharge CT results, quantitative analysis shows the lung lesion volume regressed significantly at follow-up.
conclusionsFor COVID-19 patients ready for discharge, GGO and fibrosis are the main CT features and they further regress at follow-up.
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