Detection of tuberculosis using digital chest radiography: automated reading vs. interpretation by clinical officers

Abstract

SETTING: A busy urban health centre in Lusaka, Zambia. OBJECTIVE: To compare the accuracy of automated reading (CAD4TB) with the interpretation of digital chest radiograph (CXR) by clinical officers for the detection of tuberculosis (TB). DESIGN: A retrospective analysis was performed on 161 subjects enrolled in a TB specimen bank study. CXRs were analysed using CAD4TB, which computed an image abnormality score (0-100). Four clinical officers scored the CXRs for abnormalities consistent with TB. We compared the automated readings and the readings by clinical officers against the bacteriological and radiological results used as reference. We report here the area under the receiver operating characteristic curve (AUC) and kappa (κ) statistics. RESULTS: Of 161 enrolled subjects, 97 had bacteriologically confirmed TB and 120 had abnormal CXR. The AUCs for CAD4TB and the clinical officers were respectively 0.73 and 0.65-0.75 in comparison with the bacteriological reference, and 0.91 and 0.89-0.94 in comparison with the radiological reference. P values indicated no significant differences, except for one clinical officer who performed significantly worse than CAD4TB (P < 0.05) using the bacteriological reference. κ values for CAD4TB and clinical officers with radiological reference were respectively 0.61 and 0.49-0.67. CONCLUSION: CXR assessment using CAD4TB and by clinical officers is comparable. CAD4TB has potential as a point-of-care test and for the automated identification of subjects who require further examinations.