Detection of other pathologies when utilising computer-assisted digital solutions for TB screening

利用计算机辅助数字解决方案进行结核病筛查时,其他病理的检出情况

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Abstract

BACKGROUND: Computer-aided detection (CAD) tools for TB detection have the potential to enable screening programmes and reduce the diagnostic gap in settings where access to radiologists is limited. However, there are concerns that other common chest X-ray (CXR) abnormalities not due to TB may be missed. METHODS: We assessed the performance of three commercialised CAD tools (qXR, INSIGHT CXR and DrAID(TM) TB XR) to detect common non-TB abnormalities against readings with a standardised annotation guide by an expert radiologist. More than 20 well-characterised diagnoses besides TB significant in TB high-burden countries were examined. RESULTS: The 517 CXRs included were deemed abnormal by the three CAD with a sensitivity of respectively 97% (95% CI 95-98), 94% (95% CI 91-95), and 87% (95% CI 84-90) for INSIGHT CXR, qXR, and DrAID. The CAD generally detected abnormalities in patients with critical diagnoses such as lung cancer or heart failure. Performance for detecting other abnormalities was variable. CONCLUSION: This study showed that the three CAD tools identified CXRs as abnormal when diseases other than TB were present. Our findings alleviate ethical concerns of missing abnormalities other than TB when using commercially available CAD for TB screening and show their potential broader applicability.

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