Views: 30 Author: Site Editor Publish Time: 2024-03-24 Origin: Site
Tuberculosis, often abbreviated as TB, is a contagious bacterial infection that primarily affects the lungs. It remains one of the top infectious disease killers globally, despite being curable and preventable. In response to the ongoing TB epidemic, the World Health Organization (WHO) has launched various initiatives to combat the disease. One key initiative is the End TB Strategy, which aims to reduce TB deaths by 95% and cut new cases by 90% between 2015 and 2035.
However, there is a large, persistent gap in global TB case detection. In 2019, an estimated 10 million people fell ill with TB globally, but only 7.1 million of these people were diagnosed and notified. Chest X-ray (CXR) is a recommended and commonly used tool for case detection, but its effectiveness in resource-constrained settings is hampered by limited specificity, significant inter- and intra-reader variability and lack of reproducibility, as well as a lack of access to sufficiently trained radiologists.
Computer-aided detection (CAD) presents an opportunity to improve the detection of TB by circumventing inefficiencies in the interpretation of CXR images, automating and standardizing X-ray interpretation, and supplementing existing human health workers. When used in combination with ultra-portable X-ray systems, the promise of CAD technology can be extended to hard-to-reach key populations. In WHO consolidated guidelines on tuberculosis 2021, Computer-aided detection (CAD) is being recommended for the first time as an alternative to human interpretation of digital chest X-ray (CXR) for TB screening and triage in individuals aged 15 years or older. The WHO recommends that CAD can replace a human reader in two broad contexts: for screening, and for triage. In both, the end goal is the same, namely, that CAD be used to establish whether or not an individual should receive confirmatory diagnostic tests.
CAD technology involves using computer algorithms to assist in the interpretation of medical imaging, such as chest X-rays, for TB detection. Evaluations indicates that CAD software programmes are accurate and their performance compares well with human interpretation of CXR for detection of TB disease. CAD systems can also analyze large volumes of images rapidly, facilitating mass screening and timely diagnosis and intervention. Moreover, CAD technology can reduce reliance on highly trained medical personnel for interpretation, has the potential to standardize interpretation, reducing intra- and inter-reader variability.
Sensitivity and specificity ranges of CAD softwareand human readers interpreting digital CXR
The global market for CAD technology in TB detection is witnessing significant growth, driven by increasing awareness of the importance of mass screening and early diagnosis and advancements in medical imaging technology. Major players in the market are investing in research and development to further enhance the capabilities of CAD systems for TB detection. Additionally, collaborations between healthcare institutions, technology companies, and government agencies are fostering innovation and driving market expansion.
In conclusion, the fight against tuberculosis requires a multi-faceted approach, including early detection, prompt treatment, and innovative technologies. WHO's initiatives to end TB and promote widespread screening are crucial steps in this direction. Utilizing CAD technology for TB detection holds great promise in improving diagnostic accuracy, efficiency, and accessibility, ultimately contributing to the global efforts to eradicate tuberculosis.
Reference:
1. https://www.who.int/health-topics/tuberculosis#tab=tab_1
