ArticleScientific reports2022
Biomarkers extracted by fully automated body composition analysis from chest CT correlate with SARS-CoV-2 outcome severity.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Topogram-based anatomical labelling of CT series: anatomy-aware CT data processing using deep learning.European radiology · 2026Article
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- SALT: Introducing a framework for hierarchical segmentations in medical imaging using label trees.Scientific reports · 2025Article
- Machine learning survival prediction in esophageal cancer using radiomics and body composition from pretreatment and follow-up T12-level computed tomography.World journal of gastrointestinal oncology · 2025Article
- Impact of imaging biomarkers from body composition analysis on outcome of endovascularly treated acute ischemic stroke patients.Journal of neurointerventional surgery · 2025Article
- 3D deep learning-based muscle volume quantification from thoracic CT as a surrogate for DXA-Derived appendicular muscle mass in older adults.Aging clinical and experimental research · 2025Article
- Article
- Body Composition Changes in Hospitalized Patients with Community-Acquired Pneumonia.Journal of clinical medicine · 2025Article
- AI-based body composition analysis of CT data has the potential to predict disease course in patients with multiple myeloma.Scientific reports · 2025Article
- Article
- Exchange of Quantitative Computed Tomography Assessed Body Composition Data Using Fast Healthcare Interoperability Resources as a Necessary Step Toward Interoperable Integration of Opportunistic Screening Into Clinical Practice: Methodological Development Study.Journal of medical Internet research · 2025Article
- The Impact of Radiation Dose on CT-Based Body Composition Analysis: A Large-Animal Study.Journal of cachexia, sarcopenia and muscle · 2025Article
- Fully automatic quantification of pulmonary fat attenuation volume by CT: an exploratory pilot study.European radiology experimental · 2024Observational
- AI-derived body composition parameters as prognostic factors in patients with HCC undergoing TACE in a multicenter study.JHEP reports : innovation in hepatology · 2024Article
- SAROS: A dataset for whole-body region and organ segmentation in CT imaging.Scientific data · 2024Article
- Elexacaftor/tezacaftor/ivacaftor influences body composition in adults with cystic fibrosis: a fully automated CT-based analysis.Scientific reports · 2024Article
- Body composition impacts outcome of bronchoscopic lung volume reduction in patients with severe emphysema: a fully automated CT-based analysis.Scientific reports · 2024Article
- Sarcopenia and Mortality in Critically Ill COVID-19 Patients.Life (Basel, Switzerland) · 2023Review
- The role of diet and nutrition in the management of COPD.European respiratory review : an official journal of the European Respiratory Society · 2023Review
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Authors and funding
11 authors.
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No grant is acknowledged in the PubMed record.
Abstract
The complex process of manual biomarker extraction from body composition analysis (BCA) has far restricted the analysis of SARS-CoV-2 outcomes to small patient cohorts and a limited number of tissue types. We investigate the association of two BCA-based biomarkers with the development of severe SARS-CoV-2 infections for 918 patients (354 female, 564 male) regarding disease severity and mortality (186 deceased). Multiple tissues, such as muscle, bone, or adipose tissue are used and acquired with a deep-learning-based, fully-automated BCA from computed tomography images of the chest. The BCA features and markers were univariately analyzed with a Shapiro-Wilk and two-sided Mann-Whitney-U test. In a multivariate approach, obtained markers were adjusted by a defined set of laboratory parameters promoted by other studies. Subsequently, the relationship between the markers and two endpoints, namely severity and mortality, was investigated with regard to statistical significance. The univariate approach showed that the muscle volume was significant for female (p
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