Abstract
Current issues in tuberculosis detection and the potential of computer-aided chest radiography interpretation
In 2015, there were an estimated 10.4 million new tuberculosis (TB) cases, but only 6.1 million (59%) were detected, and notified to national TB programmes (NTPs) [1]. The World Health Organization (WHO) emphasises that more proactive efforts are needed to close this case detection gap to move towards TB elimination [2, 3]. Progress has been made in improving laboratory services in recent decades. New tests for TB diagnosis have become available, and their use is being scaled up [4]. Efforts have been made to improve the evaluation of people who seek care and have symptoms consistent with TB. However, many people with TB remain undiagnosed or are diagnosed and treated only after long delays [1].
A large proportion of persons with active TB do not have classical TB symptoms, while TB abnormalities can be detected early in the disease course with the help of chest radiography (CXR) [5]. However, access to high-quality radiography with expert interpretation is limited in many settings, and high hardware costs as well as infrastructure requirements make it challenging to decentralise the technology [6]. For this reason, as well as concerns due to low specificity of CXR-based TB diagnosis and high intra- and inter-reader variability, previous WHO recommendations for resource-limited settings emphasised CXR to be used primarily when pulmonary TB cannot be confirmed bacteriologically, thus at the end of diagnostic algorithms.
Recently, however, CXR has been promoted as a useful tool that can be placed early in systematic screening (i.e. for patients who do not actively seek medical care but are at risk of having TB), and in triaging algorithms (i.e. among patients who present to care with symptoms) to identify those who need confirmatory laboratory testing (figure 1) [7]. An important reason for re-evaluating the role of CXR is the increased availability of digital radiography which presents numerous advantages over conventional radiography, such as lower running costs, better image quality, and better safety [8].