Scientists at Stellenbosch University (SU) are at the forefront of innovation with their pioneering mobile application aimed at distinguishing coughs caused by tuberculosis (TB) from non-TB-related coughs. This revolutionary project, known as the Cough Audio Triage for TB (Cage-TB) project, holds immense promise as a key screening tool to expedite TB diagnosis and optimize resource allocation.

Led by Grant Theron from SU's Clinical Mycobacteriology and Epidemiology (Clime) group within the division of molecular biology and human genetics, the Cage-TB project represents a collaborative effort involving partners from Europe and Africa. Theron expressed optimism about the project's potential, stating, "Mobile-based cough audio classification represents a potential holy grail for triage testing, with no specimens collected and negligible cost."

TB remains a significant global health challenge, particularly in low-income communities where many cases go undiagnosed. The Cage-TB project aims to address this diagnostic gap by harnessing smartphone technology to accurately identify individuals in need of further testing.

Daphne Naidoo, the project coordinator, underscored the significance of Cage-TB in tackling critical diagnostic challenges in TB. "Cage-TB aims to systematically identify individuals requiring confirmatory testing for TB, thereby streamlining the management of potential TB patients upon clinic entry," Naidoo explained.

Recently, the project received a substantial funding boost of R20 million from the European and Developing Countries Clinical Trials Partnership (EDCTP), highlighting its importance in combating poverty-related diseases in developing nations.

Initiated in 2021, the Cage-TB project builds upon earlier proof-of-concept work, demonstrating that TB patients exhibit distinctive cough sounds compared to healthy individuals and those with other respiratory conditions.

Naidoo clarified that the Cage-TB app is not meant to diagnose TB but to serve as a triage tool, identifying individuals at high risk for TB and prioritizing them for further testing. "We want to speed up TB diagnosis by creating a tool that uses the sound of a cough to classify potential TB quickly and inexpensively," she elaborated.

The research process involves collecting cough sound bites from trial participants in South Africa and Uganda. Advanced machine learning algorithms will then analyze these soundbites to distinguish between TB and non-TB-related coughs.

Currently in its discovery and validation phases, the project sees researchers refining the cough audio signal specific to TB and validating the technology in diverse populations.

With over 30 skilled professionals from institutions including SU, Makerere University (Uganda), and the University of Gottingen (Germany) collaborating on the project, Cage-TB represents a pioneering effort to leverage technology for the early detection and management of TB globally. As the project progresses, it holds the promise of revolutionizing TB diagnosis and significantly reducing the disease burden worldwide.

 

Article by RB Reporter

Photo/Mint

http://www.sun.ac.za/english/Lists/news/DispForm.aspx?ID=10520