An evaluation of automated chest radiography reading software for tuberculosis screening among public- and private-sector patients
Open accessAbstract
Computer-aided reading (CAR) of medical images is becoming increasingly common, but few studies exist for CAR in tuberculosis (TB). We designed a prospective study evaluating CAR for chest radiography (CXR) as a triage tool before Xpert MTB/RIF (Xpert). Consecutively enrolled adults in Dhaka, Bangladesh, with TB symptoms received CXR and Xpert. Each image was scored by CAR and graded by a radiologist. We compared CAR with the radiologist for sensitivity and specificity, area under the receiver operating characteristic curve (AUC), and calculated the potential Xpert tests saved. A total of 18 036 individuals were enrolled. TB prevalence by Xpert was 15%. The radiologist graded 49% of CXRs as abnormal, resulting in 91% sensitivity and 58% specificity. At a similar sensitivity, CAR had a lower specificity (41%), saving fewer (36%) Xpert tests. The AUC for CAR was 0.74 (95% CI 0.73–0.75). CAR performance declined with increasing age. The radiologist grading was superior across all sub-analyses. Using CAR can save Xpert tests, but the radiologist's specificity was superior. Differentiated CAR thresholds may be required for different populations. Access to, and costs of, human readers must be considered when deciding to use CAR software. More studies are needed to evaluate CAR using different screening approaches.
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The majority of studies reporting on CAD threshold determination only included individuals who met criteria for microbiological testing.
“The majority of studies reporting on CAD threshold determination only included individuals who met some criteria for microbiological testing, such as having symptoms and/or abnormal chest radiographs [8, 16–27].”
From Computer-aided detection thresholds for digital chest radiography interpretation in tuberculosis diagnostic algorithms. (2024) · cites this paper as [24]
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- Authors
- Rahman, M. T., Codlin, A. J., Rahman, M. M., Nahar, A., Reja, M., Islam, T., Qin, Z. Z., Khan, M. A. S., Banu, S., & Creswell, J.
- Affiliations
- International Centre for Diarrhoeal Disease Research (BD)
- National Institute of Neurosciences & Hospital (BD)
- National Institute of Diseases of the Chest and Hospital (BD)
- Corresponding author
- Creswell, Jacob
- Venue
- European Respiratory Journal
- Publisher
- European Respiratory Society (ERS)
- Published
- 2017-05
- Volume
- 49
- Issue
- 5
- Pages
- 1602159
- ISSN
- 0903-1936 (ISSN-L)
- 1399-3003
- PMC
- PMC5460641
- OpenAlex
- W2615068833
- Cited by
- 66
- References
- 1
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 9 · 2023: 10 · 2022: 5 · 2021: 8 · 2020: 9 · 2019: 8 · 2018: 8 · 2017: 1
- FWCI
- 5.47
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- European Respiratory Journal (publishedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- Global Affairs Canada
- UNITAID
- Topics
- Health Sciences › Medicine › Infectious Diseases › Tuberculosis Research and Epidemiology
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › COVID-19 diagnosis using AI
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- tuberculosis screening, chest radiography, Xpert MTB/RIF, triage, diagnostic accuracy, radiologist comparison, age-related performance decline
- MeSH terms
- Adult, Aged, Algorithms, Bangladesh, Diagnosis, Computer-Assisted, Female, Humans, Male, Mass Screening, Middle Aged, Prospective Studies, Radiographic Image Interpretation, Computer-Assisted, ROC Curve, Sensitivity and Specificity, Software, Radiography, Thoracic, Tomography, X-Ray Computed, Tuberculosis, Pulmonary, Private Sector, Tuberculosis, Multidrug-Resistant, Area Under Curve, Extensively Drug-Resistant Tuberculosis
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