Computer-Aided Detection of Pulmonary Tuberculosis on Digital Chest Radiographs: a Systematic Review

🔗2016

🔗Journal/Publication: The International Journal of Tuberculosis and Lung Disease

🔗Read it in full version: https://doi.org/10.5588/ijtld.15.0926

Abstract 

OBJECTIVE: To systematically review the diagnostic accuracy of computer-aided detection (CAD) of pulmonary tuberculosis (PTB) on digital chest radiographs (CXR).

DESIGN: We searched four databases for articles published between January 2010 and December 2015 comparing CAD of PTB on CXR to a microbiologic reference standard (smear, culture or polymerase chain reaction). We collected and summarised data on study design, CAD software and diagnostic accuracy (sensitivity, specificity, area under the curve [AUC]).

RESULTS: We included 5 of 455 articles identified by searching databases. PTB prevalence ranged from 18% to 60%, and human immunodeficiency virus (HIV) prevalence from 33% to 68%. All articles evaluated CAD4TB, the only commercially available software. AUC ranged from 0.71 to 0.84. Software settings that increased sensitivity resulted in important reductions in specificity, and vice versa. Risk of bias was low in prospective studies (n = 2), and high in retrospective studies (n = 3).

CONCLUSION: Evidence assessing CAD’s diagnostic accuracy is limited by the small number of studies, most of which have important methodological limitations, the availability and evaluation of only one software programme, and limited generalisability to settings where PTB and HIV are less prevalent. Additional research is required.