Killing over 1.5 million people annually, tuberculosis is one of the world’s deadliest diseases. In 2022, TB killed more people than conflict, homicide, malaria, typhoid and cholera combined.
Despite it being treatable, curable and preventable, various factors have ensured that the majority world remains at risk. These include inaccessible healthcare, underfunded health programmes and lack of health awareness. This is where computer-aided detection solutions come in.
A software that leverages machine learning algorithms, CAD4TB analyses chest X-rays for signs of TB. Facilitating TB Screening in remote locations can boost the health system globally and promote health awareness. Here are some ways CAD4TB can help in scaling up TB screening in remote regions.
1. Quicker Screening leads to Accurate Diagnosis
By analysing chest X-rays quickly and accurately, CAD4TB allows health systems to identify potential TB cases before sending them for a GeneXpert test. This, in turn, allows for timely treatment. In remote areas, particularly rural communities, this strengthens existing health infrastructures.
2. Increased Screening Coverage
TB screening in densely packed remote regions can be daunting despite the best planning and project implementation. The AI-powered software allows health officials to increase medical imaging coverage by screening more people in a shorter duration. Mobile diagnostic units like OneStopTB, equipped with CAD4TB, are helping overcome the biggest hurdle in remote regions, particularly those impacted by conflict and displacement. “CAD/AI will be more sensitive diagnostic pathway to early detection of tuberculosis prioritising populations more at-risk for TB,” said Mr. Christopher Togara in our recent webinar. As the Procurement and Supply Management Officer, Middle East Response Project, IOM-Jordan, he discussed it at length. “We needed a technology that could be deployed and operated offline on image databases. At the moment, we have deployed it in four countries- Iraq, Jordan, Lebanon and Syria.”
3. Boosting TB Control and Strengthening Health Systems
Early TB detection can control the spread of disease, thereby reducing the TB burden in remote regions. It also aids in empowering community health workers, particularly radiographers. Upskilling allows them to support their fellow community members, share their experiences and learn with health officials. By incorporating digital health, health systems are strengthened from within. Chimezie Dimkpa, a radiographer working in WoW Clinic, said in his recent post, “My job takes me to all types of settings – cities, towns, rural areas, government houses, etc. – which avails me unfettered access to explore the real state of people’s livelihoods from a unique vantage point – ground zero. In the course of 5 years, I have spoken to various dignitaries in 4 different states within Nigeria, Ghana, and Uganda that I would never have met if I were domiciled in, say, a medical facility.”
4. Addresses the Healthcare gap
The implementation of CAD4TB saves on costs by rapidly reading X-rays to determine whether further testing is needed. A recent study found that AI could be a game-changer in the fight against TB. “We have effective drugs for treating TB, but large-scale screening programs to detect TB are not always feasible in low-income countries due to cost and availability of expert radiologists,” said study co-author, Rory Pilgrim.
CAD for TB can be a powerful tool for scaling up TB screening in remote regions. By improving access to timely and accurate diagnosis, it can ultimately reduce the burden of TB in these at-risk communities, promote health equity and strengthen the fight against TB globally.