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. 2017 May 21;49(5):1602159.
doi: 10.1183/13993003.02159-2016. Print 2017 May.

An evaluation of automated chest radiography reading software for tuberculosis screening among public- and private-sector patients

Md Toufiq Rahman  1 , Andrew J Codlin  2 , Md Mahfuzur Rahman  1 , Ayenun Nahar  1 , Mehdi Reja  1 , Tariqul Islam  3 , Zhi Zhen Qin  2 , Md Abdus Shakur Khan  4 , Sayera Banu  1 , Jacob Creswell  5
Affiliations

An evaluation of automated chest radiography reading software for tuberculosis screening among public- and private-sector patients

Md Toufiq Rahman et al. Eur Respir J. .

Abstract

Computer-aided reading (CAR) of medical images is becoming increasingly common, but few studies exist for CAR in tuberculosis (TB). We designed a prospective study evaluating CAR for chest radiography (CXR) as a triage tool before Xpert MTB/RIF (Xpert).Consecutively enrolled adults in Dhaka, Bangladesh, with TB symptoms received CXR and Xpert. Each image was scored by CAR and graded by a radiologist. We compared CAR with the radiologist for sensitivity and specificity, area under the receiver operating characteristic curve (AUC), and calculated the potential Xpert tests saved.A total of 18 036 individuals were enrolled. TB prevalence by Xpert was 15%. The radiologist graded 49% of CXRs as abnormal, resulting in 91% sensitivity and 58% specificity. At a similar sensitivity, CAR had a lower specificity (41%), saving fewer (36%) Xpert tests. The AUC for CAR was 0.74 (95% CI 0.73-0.75). CAR performance declined with increasing age. The radiologist grading was superior across all sub-analyses.Using CAR can save Xpert tests, but the radiologist's specificity was superior. Differentiated CAR thresholds may be required for different populations. Access to, and costs of, human readers must be considered when deciding to use CAR software. More studies are needed to evaluate CAR using different screening approaches.

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Conflict of interest statement

Conflict of interest: Disclosures can be found alongside this article at erj.ersjournals.com

Figures

FIGURE 1
FIGURE 1
Receiver operating characteristic analysis for the detection of Mycobacterium tuberculosis stratified by referral type.
FIGURE 2
FIGURE 2
Receiver operating characteristic analysis for the detection of Mycobacterium tuberculosis stratified by age group.
See this image and copyright information in PMC

Comment in

References

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