ArticlePLOS global public health2022
Accuracy of computer-aided chest X-ray in community-based tuberculosis screening: Lessons from the 2016 Kenya National Tuberculosis Prevalence Survey.
Article in PLOS global public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 21 citations in OpenAlex.
- Evaluation of C-Reactive Protein and Computer-Aided Analysis of Chest X-rays as Tuberculosis Triage Tests at Health Facilities in Lesotho and South Africa.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024Trial
- Trade-offs in diagnostic algorithm, population coverage, and duration of community screening for tuberculosis: A modelling study.PLoS medicine · 2026Article
- Computer-aided detection pragmatic threshold calibration in TB active case finding: A mixed-methods study in Tondo, Manila.PLOS global public health · 2026Article
- A mixed-method evaluation of the impact of introducing 52 digital X-ray systems in Ghanaian health facilities on tuberculosis case finding and quality of care.PLOS global public health · 2026Article
- Performance of universal and stratified computer-aided detection thresholds for chest x-ray-based tuberculosis screening: a cross-sectional, diagnostic accuracy study.The Lancet. Digital health · 2025Article
- Diagnostic accuracy of screening and diagnostic tests used in a state-wide tuberculosis prevalence survey in India.Scientific reports · 2025Article
- Potential impact, costs, and benefits of population-wide screening interventions for tuberculosis in Viet Nam: A mathematical modelling study.PLOS global public health · 2025Article
- Evaluating InferVision's Computer-Aided Detection (CAD) algorithm for Tuberculosis (TB) screening, Lusaka, Zambia.PLOS global public health · 2025Article
- AI for Detection of Tuberculosis: Implications for Global Health.Radiology. Artificial intelligence · 2024Article
- Community-based active-case finding for tuberculosis: navigating a complex minefield.BMC global and public health · 2024Review
- Diagnostic Accuracy of Computer-Aided Detection During Active Case Finding for Pulmonary Tuberculosis in Africa: A Systematic Review and Meta-analysis.Open forum infectious diseases · 2024Article
- Article
- Accuracy of digital chest x-ray analysis with artificial intelligence software as a triage and screening tool in hospitalized patients being evaluated for tuberculosis in Lima, Peru.PLOS global public health · 2024Article
- Computer-aided detection thresholds for digital chest radiography interpretation in tuberculosis diagnostic algorithms.ERJ open research · 2024Article
- The Performance of Computer-Aided Detection Digital Chest X-ray Reading Technologies for Triage of Active Tuberculosis Among Persons With a History of Previous Tuberculosis.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Article
- Computer-aided diagnostic accuracy of pulmonary tuberculosis on chest radiography among lower respiratory tract symptoms patients.Frontiers in public health · 2023Article
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Authors and funding
16 authors at 6 institutions in 4 countries.
Funding
Abstract
Community-based screening for tuberculosis (TB) could improve detection but is resource intensive. We set out to evaluate the accuracy of computer-aided TB screening using digital chest X-ray (CXR) to determine if this approach met target product profiles (TPP) for community-based screening. CXR images from participants in the 2016 Kenya National TB Prevalence Survey were evaluated using CAD4TBv6 (Delft Imaging), giving a probabilistic score for pulmonary TB ranging from 0 (low probability) to 99 (high probability). We constructed a Bayesian latent class model to estimate the accuracy of CAD4TBv6 screening compared to bacteriologically-confirmed TB across CAD4TBv6 threshold cut-offs, incorporating data on Clinical Officer CXR interpretation, participant demographics (age, sex, TB symptoms, previous TB history), and sputum results. We compared model-estimated sensitivity and specificity of CAD4TBv6 to optimum and minimum TPPs. Of 63,050 prevalence survey participants, 61,848 (98%) had analysable CXR images, and 8,966 (14.5%) underwent sputum bacteriological testing; 298 had bacteriologically-confirmed pulmonary TB. Median CAD4TBv6 scores for participants with bacteriologically-confirmed TB were significantly higher (72, IQR: 58-82.75) compared to participants with bacteriologically-negative sputum results (49, IQR: 44-57, p<0.0001). CAD4TBv6 met the optimum TPP; with the threshold set to achieve a mean sensitivity of 95% (optimum TPP), specificity was 83.3%, (95% credible interval [CrI]: 83.0%-83.7%, CAD4TBv6 threshold: 55). There was considerable variation in accuracy by participant characteristics, with older individuals and those with previous TB having lowest specificity. CAD4TBv6 met the optimal TPP for TB community screening. To optimise screening accuracy and efficiency of confirmatory sputum testing, we recommend that an adaptive approach to threshold setting is adopted based on participant characteristics.
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Registered trials
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