Determining Threshold for Computer-Aided Detection (CAD) in Pre-Diagnostic Pulmonary TB Screening for Targeted Community TB Case Finding Using Portable Digital X-Ray in Nigeria

Introduction: Computer-Aided Detection technologies for TB detection were considered by the WHO as part of an update to TB screening guidelines and recommendations. However, no universal guidelines exist for selecting a decision threshold. Most CAD software products do not come with a pre-set manufacturer-recommended threshold. Several studies suggested countries and setting specific threshold. This study seeks to calibrate CAD4TB to local settings and population groups in Nigeria. Methods: A retrospective review of data was done for all eligible participants identified from E. presumptive Register. Data was entered into a standardized CSV spreadsheet and uploaded to the online CAD for TB detection calibration tool developed by WHO for analysis of CAD data calibration studies. CAD score threshold cut-off point was based on Area Under Curve (AUC) in relation to other test modalities. Mean CAD scores were compared using Student T test at p < 0.005. Result: The Mean CAD4 score was 43.13 (Range 0 to 99.3). Those located at health facility have highest mean 55.05 followed by those in slums 49.53 with p < 0.001. There were similar mean scores (between 41.0 and 49.0) with p < 0.001. Mean values were males 46.05 and females 44.96 with p = 0.118. Mean value for that previous TB treatment was 48.38 and no previous TB treatment 45.32. (p = 0.004). Mean value for those with TB was 67.92 versus 40.10 for those without TB p < 0.001. The AUC was 0.810 [CI 0.799 to 0.822]. The chosen CAD4 Threshold cut off is 37 (Sen 90.20%, Spec 39.50%). Conclusion: Findings provide valuable insights into calibration of CAD4TB for the entire population. Integrating CAD4TB into routine TB detection programs can help bridge gaps in TB case detection, leading to better health outcomes globally.