Journal
INTERNATIONAL JOURNAL OF TUBERCULOSIS AND LUNG DISEASE
Volume 22, Issue 5, Pages 567-+Publisher
INT UNION AGAINST TUBERCULOSIS LUNG DISEASE (I U A T L D)
DOI: 10.5588/ijtld.17.0492
Keywords
TB; computer-aided detection; chest radiography; computerised image analysis
Categories
Funding
- European & Developing Countries Clinical Trials Partnership ('Evaluation of multiple novel and emerging technologies for TB diagnosis, in smear-negative and HIV-infected persons, in high burden countries' [the TB-NEAT] project)
- Wellcome Trust, London [206602/Z/17/Z]
- National Institute for Health Research (NIHR), London, UK
- NIHR Senior Research Fellowship
- Wellcome Trust [206602/Z/17/Z] Funding Source: Wellcome Trust
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SETTING: Tuberculosis (TB) screening programmes can be optimised by reducing the number of chest radiographs (CXRs) requiring interpretation by human experts. OBJECTIVE: To evaluate the performance of computerised detection software in triaging CXRs in a hight-hroughput digital mobile TB screening programme. DESIGN: A retrospective evaluation of the software was performed on a database of 38 961 postero-antcrior CXRs from unique individuals seen between 2005 and 2010, 87 of whom were diagnosed with TB. The software generated a TB likelihood score for each CXR. This score was compared with a reference standard for notified active pulmonary TB using receiver operating characteristic (ROC) curve and localisation ROC (LROC) curve analyses. RESULTS: On ROC curve analysis, software specificity was 55.71% (95%CI 55.21-56.20) and negative predictive value was 99.98% (95%CI 99.95-99.99), at a sensitivity of 95%. The area under the ROC curve was 0.90 (95%CI 0.86-0.93). Results of the LROC curve analysis were similar. CONCLUSION: The software could identify more than half of the normal images in a TB screening setting while maintaining high sensitivity, and may therefore be used for triage.
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