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An overview of the National COVID-19 Chest Imaging Database: data quality and cohort analysis

Cushnan, D; Bennett, O; Berka, R; Bertolli, O; Chopra, A; Dorgham, S; Favaro, A; ... NCCID Collaborative, .; + view all (2021) An overview of the National COVID-19 Chest Imaging Database: data quality and cohort analysis. Gigascience , 10 (11) , Article giab076. 10.1093/gigascience/giab076. Green open access

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Abstract

Background: The National COVID-19 Chest Imaging Database (NCCID) is a centralized database containing mainly chest X-rays and computed tomography scans from patients across the UK. The objective of the initiative is to support a better understanding of the coronavirus SARS-CoV-2 disease (COVID-19) and the development of machine learning technologies that will improve care for patients hospitalized with a severe COVID-19 infection. This article introduces the training dataset, including a snapshot analysis covering the completeness of clinical data, and availability of image data for the various use-cases (diagnosis, prognosis, longitudinal risk). An additional cohort analysis measures how well the NCCID represents the wider COVID-19–affected UK population in terms of geographic, demographic, and temporal coverage. // Findings: The NCCID offers high-quality DICOM images acquired across a variety of imaging machinery; multiple time points including historical images are available for a subset of patients. This volume and variety make the database well suited to development of diagnostic/prognostic models for COVID-associated respiratory conditions. Historical images and clinical data may aid long-term risk stratification, particularly as availability of comorbidity data increases through linkage to other resources. The cohort analysis revealed good alignment to general UK COVID-19 statistics for some categories, e.g., sex, whilst identifying areas for improvements to data collection methods, particularly geographic coverage. // Conclusion: The NCCID is a growing resource that provides researchers with a large, high-quality database that can be leveraged both to support the response to the COVID-19 pandemic and as a test bed for building clinically viable medical imaging models.

Type: Article
Title: An overview of the National COVID-19 Chest Imaging Database: data quality and cohort analysis
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/gigascience/giab076
Publisher version: https://doi.org/10.1093/gigascience/giab076
Language: English
Additional information: © The Author(s) 2021. Published by Oxford University Press GigaScience. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: COVID-19, SARS-CoV2, machine learning, medical imaging, thoracic imaging
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Respiratory Medicine
URI: https://discovery.ucl.ac.uk/id/eprint/10140373
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