ArticleScientific reports2021
Quantitative and semi-quantitative CT assessments of lung lesion burden in COVID-19 pneumonia.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 22 citations in OpenAlex.
- Spatial Immune Model of Alveolar Lung Infection (SIMALI) Identifies Structural Determinants of Lung Inflammation.Research square · 2026Article
- Prognostic value of deep learning-based coronary artery calcium score and quantitative pneumonia burden in patients hospitalized with COVID-19.BMC medical imaging · 2026Article
- Severity assessment of COVID-19 disease: radiological visual score versus automated quantitative CT parameters using a pneumonia analysis algorithm.Frontiers in medicine · 2025Article
- The existence of adrenal insufficiency in patients with COVID-19 pneumonia.Frontiers in endocrinology · 2024Article
- CT semi-quantitative score used as risk factor for hyponatremia in patients with COVID-19: a cross-sectional study.Frontiers in endocrinology · 2024Article
- Artificial intelligence-assisted quantification of COVID-19 pneumonia burden from computed tomography improves prediction of adverse outcomes over visual scoring systems.The British journal of radiology · 2023Article
- The Real-World Clinical Outcomes of Favipiravir Treatment with Telemedicine Monitoring in Preventing Disease Progression in Mild to Moderate COVID-19 Patients; A Retrospective Cohort Study.Medicina (Kaunas, Lithuania) · 2023Observational
- Are the thorax Computed Tomography findings of ICU patients diagnosed with COVID-19 pneumonia related to the duration of hospital stay and mortality?Journal of infection and chemotherapy : official journal of the Japan Society of Chemotherapy · 2023Article
- Prognostic utility of cardiovascular indices in COVID-19 infection: A single-center prospective study in India.Journal of family medicine and primary care · 2022Article
- Machine learning techniques for CT imaging diagnosis of novel coronavirus pneumonia: a review.Neural computing & applications · 2022Review
- Deep learning-based lesion subtyping and prediction of clinical outcomes in COVID-19 pneumonia using chest CT.Scientific reports · 2022Article
- Predictors for COVID-19 Complete Remission with HRCT Pattern Evolution: A Monocentric, Prospective Study.Diagnostics (Basel, Switzerland) · 2022Article
- Respiratory Outcomes After 6 Months of Hospital Discharge in Patients Affected by COVID-19: A Prospective Cohort.Frontiers in medicine · 2022Article
- Automated Quantitative Lung CT Improves Prognostication in Non-ICU COVID-19 Patients beyond Conventional Biomarkers of Disease.Diagnostics (Basel, Switzerland) · 2021Article
- Time to hospitalisation, CT pulmonary involvement and in-hospital death in COVID-19 patients in an Emergency Medicine Unit.International journal of clinical practice · 2021Observational
- Patients with hypertension hospitalized with COVID-19 pneumonia using angiotensinconverting enzyme inhibitors and angiotensin II receptor blockers or other antihypertensives: retrospective analysis of 435 patients.Annals of Saudi medicineArticle
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Authors and funding
13 authors at 5 institutions in 1 country.
Funding
Abstract
This study aimed to clarify and provide clinical evidence for which computed tomography (CT) assessment method can more appropriately reflect lung lesion burden of the COVID-19 pneumonia. A total of 244 COVID-19 patients were recruited from three local hospitals. All the patients were assigned to mild, common and severe types. Semi-quantitative assessment methods, e.g., lobar-, segmental-based CT scores and opacity-weighted score, and quantitative assessment method, i.e., lesion volume quantification, were applied to quantify the lung lesions. All four assessment methods had high inter-rater agreements. At the group level, the lesion load in severe type patients was consistently observed to be significantly higher than that in common type in the applications of four assessment methods (all the p < 0.001). In discriminating severe from common patients at the individual level, results for lobe-based, segment-based and opacity-weighted assessments had high true positives while the quantitative lesion volume had high true negatives. In conclusion, both semi-quantitative and quantitative methods have excellent repeatability in measuring inflammatory lesions, and can well distinguish between common type and severe type patients. Lobe-based CT score is fast, readily clinically available, and has a high sensitivity in identifying severe type patients. It is suggested to be a prioritized method for assessing the burden of lung lesions in COVID-19 patients.
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