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Winnipeg, Apr 30:
In a significant leap for preventive healthcare, researchers from Edith Cowan University (ECU) in Australia and the University of Manitoba in Canada have unveiled a cutting-edge machine learning algorithm that can swiftly detect risks of heart disease and bone fractures using routine bone density scans.
The new technology, designed to analyze vertebral fracture assessment (VFA) images, identifies abdominal aortic calcification (AAC)-a silent but potent predictor of cardiovascular events like heart attacks and strokes, as well as falls and fractures. Traditionally, screening for AAC required five to six minutes per scan by trained experts. The AI-driven system now reduces this process to under a minute per image, enabling rapid, large-scale screening during standard osteoporosis checks.
“About 58 per cent of older women undergoing bone scans showed moderate to high levels of AAC, often without knowing they were at risk,” said ECU research fellow Cassandra Smith. She emphasized that cardiovascular disease in women remains under-screened and under-treated, and that this new tool could help flag high-risk individuals who would otherwise go unnoticed.
Further research by ECU’s Dr. Marc Sim highlighted that AAC is not just a marker for heart disease but also a powerful predictor of falls and fractures-outperforming traditional indicators such as bone density and previous fall history. “The higher the calcification in your arteries, the higher the risk of falls and fractures,” Sim explained, noting that vascular health is often overlooked in fall risk assessments.
The integration of this AI algorithm into routine bone scans could transform how clinicians assess overall fracture and cardiovascular risk, marking a major step forward in preventive medicine. The system leverages widely available, low-radiation bone density machines, making it accessible for large-scale use, particularly for older adults at higher risk.
Researchers are now focused on validating the algorithm’s performance in broader clinical settings and exploring commercial partnerships to make the technology widely available.
Disclaimer:
This article is based on recent research findings and statements from involved scientists. The AI algorithm is an emerging tool and, while promising, is not yet a substitute for professional medical advice or comprehensive diagnostic evaluation. Individuals should consult healthcare professionals for personalized assessment and treatment decisions.
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