Extract
One of the interventions in tuberculosis (TB) control is to screen people at high risk for TB with chest radiography [1]. Chest radiography in TB screening programmes are usually read by a radiographer or a pulmonologist specialised in TB. In recent years, computer-aided detection (CAD) software has become available for automated reading of CXRs and identifying people with presumptive TB [2, 3] and for TB screening [4, 5]. A systematic review published in 2016 concluded that the evidence of diagnostic accuracy of CAD was limited by the small number of studies, co-authored by owners of the only CAD software on the market at that time, and not generalisable to low TB and HIV settings [6]. The application of CAD software for TB detection has to our knowledge not been assessed in Europe.
Abstract
Automated reading of chest radiographs in a tuberculosis screening programme can reduce human reading to less than 20% of the chest radiographs, avoiding unnecessary TB examinations while maintaining high sensitivity https://bit.ly/3kCFWmq
Acknowledgement
The authors gratefully acknowledge the E-DETECT TB (709624) project which has received funding from the European Union's Health Programme (2014–2020). The views expressed here are the authors only and are their sole responsibility; it cannot be considered to reflect the views of the European Commission and/or the Consumers, Health, Agriculture and Food Executive Agency or any other body of the EU.
Footnotes
Conflict of interest: G. de Vries has nothing to disclose.
Conflict of interest: D. Gainaru has nothing to disclose.
Conflict of interest: S. Keizer has nothing to disclose.
Conflict of interest: B. Mahler has nothing to disclose.
Conflict of interest: I. Radulescu has nothing to disclose.
Conflict of interest: M. Zamfirescu has nothing to disclose.
Conflict of interest: I. Abubakar reports grants from European Commission (E-DETECT TB grant co-funding to UCL from the European Commission) and UK National Institute for Health Research (SRF-2011-04-001 and NF-SI-0616-10037), during the conduct of the study.
Support statement: The E-DETECT TB project has received funding from the European Commission Consumers, Health, Agriculture and Food Executive Agency (grant number: 709624). I. Abubakar acknowledges support from the UK National Institute for Health Research (SRF-2011-04-001) and (NF-SI-0616-10037), and grants from European Commission to undertake the project reported in this manuscript. Delft Imaging was a co-applicant on the EU grant that supported the project which required all partners to co-fund their contribution. The company was not involved in this study. Funding information for this article has been deposited with the Crossref Funder Registry.
- Received December 24, 2020.
- Accepted February 24, 2021.
- Copyright ©The authors 2021. For reproduction rights and permissions contact permissions{at}ersnet.org
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