Computer-Aided Analysis of Photographed Chest X-Ray Films Performs Well Compared With Trained Radiologists

Objective: To assess whether computer-aided detection (CAD) chest X-ray (CXR) software may aid physicians in low-resource, high tuberculosis (TB) endemic settings where radiologists are scarce. Patients and Methods: A retrospective pilot study was conducted on CXR films taken between January 1, 2017, and March 30, 2018, in Guinea-Bissau and Ethiopia to compare the interpretation of CXRs regarding pulmonary TB (PTB) by CAD (qXR; Qure.ai) with that of 2 experienced Ethiopian radiologists (A and B). To improve the applicability of this method in low-resource settings, an analysis was performed on images of CXRs taken by mobile phones. Two reference standards were applied: final PTB diagnosis by clinical or laboratory findings (ie, Xpert MTB/RIF [Xpert]-confirmed PTB). Results: We included 498 CXRs from patients seeking help for TB indicative symptoms. Radiologist A identified 50, radiologist B identified 99, and the software identified 81 as indicative of TB. The overall area under the curve for the receiver-operating characteristic curve of the software was 0.84 for Xpert-confirmed cases. At the prechosen cutoff value of 0.5, the sensitivity of CAD CXR was 76.5%, and the specificity was 85.9%. Radiologist A’s assessments were 64.7% sensitive and 91.9% specific, whereas radiologist B’s assessments were 76.5% sensitive and 82.3% specific for Xpert-confirmed cases. The agreement regarding TB-related findings between the radiologists combined (κ=0.45) and each radiologist and the software (κ=0.56) was moderate. Conclusion: Our study revealed that CAD CXR performs comparably with experienced radiologists when it is applied to CXR films, photographed by mobile phones and a digital camera with similar sensor resolutions. Trial registration: PACTR201611001838365.