French Imaging Database Against Coronavirus (FIDAC): A large COVID-19 multi-center chest CT database.


Journal

Diagnostic and interventional imaging
ISSN: 2211-5684
Titre abrégé: Diagn Interv Imaging
Pays: France
ID NLM: 101568499

Informations de publication

Date de publication:
Oct 2022
Historique:
received: 01 04 2022
revised: 18 05 2022
accepted: 18 05 2022
pubmed: 18 6 2022
medline: 5 10 2022
entrez: 17 6 2022
Statut: ppublish

Résumé

During the first wave of the COVID-19 pandemic, the French Society of Radiology and the French College of Radiology, in partnership with NEHS Digital, have set up a system to collect chest computed tomography (CT) examinations with clinical, virological and radiological metadata, from patients clinically suspected of COVID-19 pneumonia. This allowed the constitution of an anonymized multicenter database, named FIDAC (French Imaging Database Against Coronavirus). The aim of this report was to describe the content of this public database. Twenty-two French radiology centers participated to the data collection. The data collected were chest CT examinations in DICOM format associated with the following metadata: patient age and sex, originating facility identifier, originating facility region, time from symptom onset to CT examination, indication for CT examination, reverse transcription-polymerase chain reaction (RT-PCR) results and normalized CT report performed by a senior radiologist. All the data were anonymized and sent through a NEHS Digital system to a centralized data center. A total of 5944 patients were included from the 22 centers aggregated into 8 regions with a mean number of patients of 743 ± 603.3 [SD] per region (range: 102-1577 patients). Reasons for CT examination and normalized CT reports were provided for all patients. RT-PCR results were provided in 5574 patients (93.77%) with a positive result of RT-PCR in 44.6% of patients. The FIDAC project allowed the creation of a large database of chest CT images and metadata available, under conditions, in open access through the CERF-SFR website.

Identifiants

pubmed: 35715328
pii: S2211-5684(22)00096-1
doi: 10.1016/j.diii.2022.05.006
pmc: PMC9194873
pii:
doi:

Types de publication

Journal Article Multicenter Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

460-463

Informations de copyright

Copyright © 2022 Société française de radiologie. Published by Elsevier Masson SAS. All rights reserved.

Auteurs

Loic Boussel (L)

Department of Radiology, Croix-Rousse Hospital, Hospices Civils de Lyon, 69004 Lyon, France; Univ Lyon, INSA Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1294, 69100 Villeurbanne, France. Electronic address: loic.boussel@chu-lyon.fr.

Jean-Michel Bartoli (JM)

Department of Radiology, Aix-Marseille University, University Hospital La Timone, AP-HM, 13385 Marseille, France.

Samy Adnane (S)

Department of Radiology, Croix-Rousse Hospital, Hospices Civils de Lyon, 69004 Lyon, France.

Jean-François Meder (JF)

Department of Neuroimaging, Sainte-Anne Hospital, 75013 Paris, France; Université Paris Cité, 75006 Paris, France.

Patrick Malléa (P)

NEHS DIGITAL, 92240 Malakoff, France.

Jeremy Clech (J)

NEHS DIGITAL, 92240 Malakoff, France.

Marc Zins (M)

Department of Radiology, Paris Saint-Joseph Hospitals, 75014 Paris, France.

Jean-Paul Bérégi (JP)

Department of Medical Imaging, University Hospital of Nîmes, 30900 Nîmes, France.

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Classifications MeSH