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Free Content Automated chest X-ray reading for tuberculosis in the Philippines to improve case detection: a cohort study

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BACKGROUND: DetecTB (Diagnostic Enhanced Tools for Extra Cases of TB), an intensified tuberculosis (TB) case-finding programme targeting prisons and high-risk communities was implemented on Palawan Island, the Philippines.

OBJECTIVE: To evaluate the performance of TB detection based on computerised chest radiography (CXR) readings.

DESIGN: Data from 14 094 subjects were analysed from September 2012 to June 2014. All CXRs were read by a physician and by software. Individuals with TB symptoms or CXR abnormalities according to the physician underwent Xpert® MTB/RIF testing, the remaining persons were considered TB-negative (screening reference). A subset of 200 CXRs was read by an independent human reader (radiological reference). This reader also re-read a subset of the most abnormal cases as identified using the software but read as normal by the physician (discordant cases).

RESULTS: A total of 10 755 individuals were included in the analysis, 2534 of whom had a positively assessed CXR; 298 cases were Xpert-positive. Using the screening reference, the area under the receiver operating characteristic curve for software readings was 0.93 (95%CI 0.92–0.94), with a sensitivity of 0.98 (95%CI 0.97–0.99) and a specificity of 0.69 (95%CI 0.40–0.98). Based on the radiological reference, the physician performed slightly worse than the software (sensitivity, 0.82, 95%CI 0.74–0.89 and specificity, 0.87, 95%CI 0.81–0.96 vs. sensitivity, 0.83, 95%CI 0.71–0.93 and specificity, 0.87, 95%CI 0.75–0.95), although this was not statistically significant. Of the 291 discordant cases, 70% were assessed as positive, resulting in a 22% increase in TB detection when extrapolated to the full cohort.

CONCLUSION: The performance of automated CXR reading is comparable to that of the attending physicians in DetecTB, and its use as a second reader could increase TB detection.
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Keywords: TB; chest radiography; computer-aided detection; computerised image analysis

Document Type: Research Article

Affiliations: 1: Diagnostic Image Analysis Group, Radboud University Medical Center, Nijmegen, The Netherlands 2: World Health Organization Representative Office in Mongolia, Ulaanbaatar, Mongolia

Publication date: July 1, 2019

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  • The International Journal of Tuberculosis and Lung Disease publishes articles on all aspects of lung health, including public health-related issues such as training programmes, cost-benefit analysis, legislation, epidemiology, intervention studies and health systems research. The IJTLD is dedicated to the continuing education of physicians and health personnel and the dissemination of information on lung health world-wide.

    To share scientific research of immediate concern as rapidly as possible, The Union is fast-tracking the publication of certain articles from the IJTLD and publishing them on The Union website, prior to their publication in the Journal. Read fast-track articles.

    Certain IJTLD articles are also selected for translation into French, Spanish, Chinese or Russian. These are available on the Union website.

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