ArticleAnnals of translational medicine2020
Temporal changes of COVID-19 pneumonia by mass evaluation using CT: a retrospective multi-center study.
Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- High resolution chest computed tomography findings in patients with clinically suspected COVID-19 pneumonia in Uganda: a cross-sectional study.African health sciences · 2023Article
- Clinical utilization of artificial intelligence-based COVID-19 pneumonia quantification using chest computed tomography - a multicenter retrospective cohort study in Japan.Respiratory research · 2023Article
- Phase 1 clinical trial for intravenous administration of mesenchymal stem cells derived from umbilical cord and placenta in patients with moderate COVID-19 virus pneumonia: results of stage 1 of the study.American journal of stem cells · 2022Article
- Dynamic change of COVID-19 lung infection evaluated using co-registration of serial chest CT images.Frontiers in public health · 2022Article
- COVID-19: Histopathological correlates of imaging patterns on chest computed tomography.Respirology (Carlton, Vic.) · 2021Article
- Article
- 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
- Should CT be used for the diagnosis of RT-PCR-negative suspected COVID-19 patients?The clinical respiratory journal · 2021Article
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24 authors.
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Abstract
backgroundCoronavirus disease 2019 (COVID-19) has widely spread worldwide and caused a pandemic. Chest CT has been found to play an important role in the diagnosis and management of COVID-19. However, quantitatively assessing temporal changes of COVID-19 pneumonia over time using CT has still not been fully elucidated. The purpose of this study was to perform a longitudinal study to quantitatively assess temporal changes of COVID-19 pneumonia.
methodsThis retrospective and multi-center study included patients with laboratory-confirmed COVID-19 infection from 16 hospitals between January 19 and March 27, 2020. Mass was used as an approach to quantitatively measure dynamic changes of pulmonary involvement in patients with COVID-19. Artificial intelligence (AI) was employed as image segmentation and analysis tool for calculating the mass of pulmonary involvement.
resultsA total of 581 confirmed patients with 1,309 chest CT examinations were included in this study. The median age was 46 years (IQR, 35-55; range, 4-87 years), and 311 (53.5%) patients were male. The mass of pulmonary involvement peaked on day 10 after the onset of initial symptoms. Furthermore, the mass of pulmonary involvement of older patients (>45 years) was significantly severer (P<0.001) and peaked later (day 11
conclusionsPulmonary involvement peaked on day 10 after the onset of initial symptoms in patients with COVID-19. Further, pulmonary involvement of older patients was severer and peaked later than that of younger patients. These findings suggest that AI-based quantitative mass evaluation of COVID-19 pneumonia hold great potential for monitoring the disease progression.
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