ArticleBMJ public health2026
Accuracy and operational performance of computer-aided detection software use cases for TB screening: a retrospective comparative evaluation in Ho Chi Minh City, Viet Nam.
Article in BMJ public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Human reader variability and workforce constraints limit the quality and scale of chest X-ray (CXR) screening for tuberculosis (TB) in many high-burden settings. Although the WHO endorses computer-aided detection (CAD) software, most evaluations have focused on the use case where CAD software entirely replaces human readers. Evidence on alternate CAD software deployment models for TB screening and head-to-head comparisons remains limited. Methods: A test library of 1466 CXR images was curated after an active case finding initiative in Ho Chi Minh City, Viet Nam. Images were processed by Lunit INSIGHT CXR CAD software and independently interpreted by 10 human readers across two rounds separated by a wash-out period. Five CXR interpretation methods were simulated: human-only reading, CAD-only reading, CAD-assisted human reading, independent double reading and sequential reading. Generalised estimating equations were used to estimate adjusted incidence rate ratios comparing the sensitivity and specificity of CAD-containing CXR interpretation methods with human-only reading, while operational performance metrics were summarised as percentage changes relative to human-only reading. Results: Human-only reading achieved mean sensitivity 79.0% and specificity 84.8%. CAD-only reading significantly increased sensitivity (91.4%, adjusted incidence rate ratio (aIRR) 1.16, 95% CI 1.06 to 1.27, p=0.002) and significantly reduced specificity (81.9%, aIRR 0.96, 95% CI 0.94 to 0.98, p<0.001). Independent double reading achieved the highest sensitivity (95.0%, aIRR 1.20, 95% CI 1.12 to 1.30, p<0.001), but the lowest specificity (74.5%, aIRR 0.87, 95% CI 0.86 to 0.89, p<0.001) and increased diagnostic testing by +59.2% and the number needed to test by +32.3%. Sequential reading maintained sensitivity comparable to human-only reading (78.8%, aIRR 1.00, 95% CI 0.99 to 1.00, p=0.326), while achieving the highest specificity (90.3%, aIRR 1.07, 95% CI 1.06 to 1.07, p<0.001), reducing human workload by -67.5%, and lowering the number needed to test by -29.9%. CAD-assisted human reading produced non-significant sensitivity gains (82.9%, aIRR 1.05, 95% CI 1.00 to 1.11, p=0.057) and reduced specificity (82.2%, aIRR 0.97, 95% CI 0.96 to 0.98, p<0.001), with substantial inter-reader variability. Sensitivity gains were greatest among participants without prior TB, and specificity improvements were most pronounced among less experienced readers. Conclusion: No single CAD software use case optimally balanced accuracy and operational efficiency. CAD-only and independent double reading maximised TB detection, while sequential reading improved efficiency and conserved resources. CAD software deployment should align with local workforce capacity, diagnostic infrastructure and programmatic priorities. Prospective evaluations of these use cases are warranted.
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