Evaluation of the diagnostic accuracy of Computer-Aided Detection of tuberculosis on Chest radiography among private sector patients in Pakistan

Abstract

The introduction of digital CXR with automated computer-aided interpretation, has given impetus to the role of CXR in TB screening, particularly in low resource, high-burden settings. The aim of this study was to evaluate the diagnostic accuracy of CAD4TB as a screening tool, implemented in the private sector in Karachi, Pakistan. This study analyzed retrospective data from CAD4TB and Xpert MTB/RIF testing carried out at two private TB treatment and diagnostic centers in Karachi. Sensitivity, specificity, potential Xperts saved, were computed and the receiver operator characteristic curves were constructed for four different models of CAD4TB. A total of 6,845 individuals with presumptive TB were enrolled in the study, 15.2% of which had MTB + ve result on Xpert. A high sensitivity (range 65.8–97.3%) and NPV (range 93.1–98.4%) were recorded for CAD4TB. The Area under the ROC curve (AUC) for CAD4TB was 0.79. CAD4TB with patient demographics (age and gender) gave an AUC of 0.83. CAD4TB offered high diagnostic accuracy. In low resource settings, CAD4TB, as a triage tool could minimize use of Xpert. Using CAD4TB in combination with age and gender data enhanced the performance of the software. Variations in demographic information generate different individual risk probabilities for the same CAD4TB scores.

Evaluation of computer aided detection of tuberculosis on chest radiography among people with diabetes in Karachi Pakistan

“…Our study findings indicate that CAD4TB offers good diagnostic accuracy as a triage test for TB screening among PWD using Xpert MTB/RIF as the reference standard. However, in comparison with the CAD4TB evaluation conducted in Pakistan among individuals with an unknown diabetes status that reported sensitivities in the range 91.0-97.3%, our current study shows lower sensitivities (range 48.6-90.5%) for the corresponding CAD4TB cut-offs on the same version of CAD4TB software on the same version of CAD4TB software 5 . A recent study from Indonesia evaluating CAD4TB among PWD reported an AUC of 0.89 using against the reference standard of bacteriologically and clinically confirmed TB (7 bacteriologically confirmed TB cases and 2 clinically diagnosed) 12 .…”

“…In addition, the association of glycemic control with CAD4TB scores and MTB positivity was not evaluated in this study. Another limitation of this study is that the symptoms data was not recorded which can be an important factor in risk assessment for CAD scores and enhance the performance of the software 5 .…”

“…Recently, there has been renewed interest in the use of chest X-rays (CXR) as a screening tool for TB, particularly in active case finding programs. Computer-Aided Detection for TB (CAD4TB) software provides automatic readings of CXR with a higher score suggestive of TB and has the potential of being used as a triage tool in low-resource settings to pre-screen individuals for Xpert MTB/RIF testing 5 . Pragmatic use of screening through CAD4TB can result in significant savings through reduced Xpert testing specially in lower middle-income countries where high costs of Xpert testing has limited its use.…”

“…It also reduces the need for an onsite radiologist for immediate readings, which is difficult in low resource settings. Evaluations of the software, using Xpert MTB/ RIF as the reference standard have been conducted in Zambia, Bangladesh, Pakistan and most recently in Nepal and Cameroon, reporting a diagnostic accuracy in the range 0.71-0.92 [5][6][7][8] . Studies of radiographic manifestations of pulmonary TB in PWD report an increased frequency of lower lung field lesions, a higher frequency of cavitation, and more advanced disease 9,10 yet there is almost no data on use of automated reading software for TB among PWD.…”

Contact Investigation of Multidrug-Resistant Tuberculosis Patients: A Mixed-Methods Study from Myanmar

“…However, this alone will not obviate the need for visiting health facility, as contacts also have to undergo chest radiography. To address this, we recommend exploring the possibility of using new technologies such as digital chest radiography with automated computer-aided detection of tuberculosis, which can be mounted in a mobile van for greater outreach [24].…”