Companies: Qure.ai, Lunit Products: qXR, Lunit INSIGHT CXR
Detection of other pathologies when utilising computer-assisted digital solutions for TB screening
IJTLD Open, 2024
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 DrAIDTM 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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