The DOI matches its Crossref record.
Automated chest radiography and mass systematic screening for tuberculosis
Abstract
BACKGROUND: Systematic screening for TB using automated chest radiography (ACR) with computer-aided detection software (CAD4TB) has been implemented at scale in Karachi, Pakistan. Despite evidence supporting the use of ACR as a pre-screen prior to Xpert® MTB/RIF diagnostic testing in presumptive TB patients, there has been no data published on its use in mass screening in real-world settings.METHOD: Screening was undertaken using mobile digital X-ray vehicles at hospital facilities and community camps. Chest X-rays were offered to individuals aged ≥15 years, regardless of symptoms. Those with a CAD4TB score of ≥70 were offered Xpert testing. The association between Xpert positivity and CAD4TB scores was examined using data collected between 1 January and 30 June 2018 using a custom-built data collection tool.RESULTS: Of the 127 062 individuals screened, 97.2% had a valid CAD4TB score; 11 184 (9.1%) individuals had a CAD4TB score ≥70. Prevalence of Xpert positivity rose from 0.7% in the <50 category to 23.5% in the >90 category. The strong linear association between CAD4TB score and Xpert positivity was found in both community and hospital settings.CONCLUSION: The strong association between CAD4TB scores and Xpert positivity provide evidence that an ACR-based pre-screening performs well when implemented at scale in a high-burden setting.
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“yet context-specific determination is often not done due to logistical and financial constraints [8, 14, 15].”
From Computer-aided detection thresholds for digital chest radiography interpretation in tuberculosis diagnostic algorithms. (2024) · cites this paper as [14]
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Geric, C., Qin, Z. Z., Denkinger, C. M., Kik, S. V., Marais, B., Anjos, A., David, P.-M., Ahmad Khan, F., & Trajman, A. (2023) · The International Journal of Tuberculosis and Lung Disease · doi:10.5588/ijtld.22.0687 · Cited by 61
Vanobberghen, F., Keter, A. K., Jacobs, B. K. M., Glass, T. R., Lynen, L., Law, I., Murphy, K., van Ginneken, B., Ayakaka, I., van Heerden, A., et al. (2024) · ERJ Open Research · doi:10.1183/23120541.00508-2023 · Cited by 13
“…CAD4TB (Delft Imaging Systems, Netherlands), recommend scores tailored to each setting due to variation in CAD abnormality scores between different software and populations [5, 6, 8 – 13], yet context-specific determination is often not done due to logistical and financial constraints [8, 14, 15].”
Background
Metadata
- Authors
- Madhani, F., Maniar, R. A., Burfat, A., Ahmed, M., Farooq, S., Sabir, A., Domki, A. K., Page-Shipp, L., Khowaja, S., Safdar, N., Khan, A. J., & Khan, P. Y.
- Affiliations
- Indus Hospital (PK)
- Provincial TB Control Program, Department of Health, Government of Sindh, Hyderabad, Pakistan
- Interactive Research and Development, Singapore
- Interactive Research and Development (PK)
- London School of Hygiene & Tropical Medicine (GB)
- Venue
- The International Journal of Tuberculosis and Lung Disease
- Published
- 2020-07-01
- Volume
- 24
- Issue
- 7
- Pages
- 665-673
- ISSN
- 1027-3719 (ISSN-L)
- OpenAlex
- W3046196624
- Cited by
- 26
- References
- 0
- Citations by year
- 2025: 1 · 2024: 5 · 2023: 6 · 2022: 6 · 2021: 7 · 2020: 1
- FWCI
- 0.66
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The International Journal of Tuberculosis and Lung Disease (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Infectious Diseases › Tuberculosis Research and Epidemiology
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › COVID-19 diagnosis using AI
- Keywords
- tuberculosis screening, computer-aided detection, CAD4TB, Xpert MTB/RIF, mass screening, prescreening, tuberculosis prevalence, high-burden settings
- MeSH terms
- Aged, Humans, Mass Screening, Mycobacterium tuberculosis, Pakistan, Radiography, Sensitivity and Specificity, Tuberculosis, Tuberculosis, Pulmonary
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