A new diagnostic tool that analyses a person’s breath for signs of silicosis has been developed by physicians and scientists from UNSW Sydney.
This new test offers the potential to detect the disease much earlier than traditional methods before irreversible lung damage occurs.
The research, published in the Journal of Breath Research, details a rapid, AI-powered breath test that could revolutionise silicosis diagnosis.
The test utilises mass spectrometry, a technique that analyses molecules, combined with artificial intelligence to quickly identify silicosis from breath samples.
This provides a fast and non-invasive diagnostic tool for workers at risk.
Silicosis, a debilitating lung disease caused by inhaling crystalline silica particles, is a significant occupational health concern in Australia.
Cases are increasing not only among engineered stone workers but also in the tunnelling and construction industries.
While the Australian government has banned engineered stone, the emergence of new cases from other high-risk sectors highlights the urgent need for improved diagnostic tools.
Traditional silicosis detection methods, such as X-rays and CT scans, often identify the disease in its later stages.
The new UNSW-developed test provides results in minutes, offering a significant advantage for early intervention.
The study involved analysing breath samples from 31 silicosis patients and 60 healthy individuals.
The test demonstrated a high level of accuracy in differentiating between those affected and unaffected by the disease.
Professor William Alexander Donald from UNSW’s School of Chemistry, the lead researcher, explained the process: “Our study shows that the AI-driven model accurately distinguished silicosis patients from healthy individuals based on their breath profiles, providing a reliable tool for early detection.
“This suggests that breath testing could be a practical tool for large-scale worker screening and early intervention.”
Participants simply breathe into a bag, and the breath content is then analysed by a mass spectrometer to detect the various molecules present.
“In human breath, there are thousands of organic molecules that you breathe out,” Prof. Donald said.
“Our instrument can make a profile of someone’s breath, and then we feed that into an artificial intelligence algorithm that’s really good at finding patterns.
“In this case, it’s looking for patterns in the organic compounds that are present in the breath of people in the early stages of silicosis.
“And we’re getting very high accuracies, like over 90 per cent accuracy, for just such a simple, non-invasive breath test.”
The entire process, from breath sampling to analysis, takes less than five minutes per patient, making it suitable for routine screening of at-risk workers.
Conjoint Professor Deborah Yates, a clinician who has seen numerous silicosis cases, emphasised the importance of early detection.
“It can be difficult to diagnose such patients, especially in the early stages of disease. Sometimes a biopsy is needed, which is invasive and expensive.
“So it is crucial to detect affected workers early and remove them from further silica exposure in order to stop the progression of their disease.”
Professor Yates added: “Breath testing is a new and simple technique for patients and doctors but has been valuable in other lung diseases such as asthma.
“It could provide the non-invasive method needed to monitor such workers for development of silicosis.
“Although this research is yet in its early stages and will need further development, it provides a ‘breath of hope’ for the future.”
While the breath test shows considerable promise, the researchers stress that further validation in larger groups is necessary before it can be implemented as a routine screening tool.
Currently, breath samples are collected in clinics and transported to the lab for analysis.
However, future implementation could allow for direct, on-site testing.
The research team has already installed the testing at a second site to assess its effectiveness with hundreds of at-risk workers, including coal miners.
Future studies will focus on refining the technique, incorporating it into screening programs for silica-exposed workers, and exploring its ability to differentiate silicosis from other lung diseases.
This research was supported by the iCare Dust Diseases Board through a Discovery and Innovation grant.
