By Eliza Chin, MD, MPH
May is Osteoporosis Awareness Month and the launch of AMWA’s campaign to promote bone health through the early detection and management of osteoporosis. This condition, marked by reduced bone density and an increased risk of fractures, often goes undiagnosed until significant damage has occurred—earning it the designation of a “silent” disease. While Dual-energy X-ray Absorptiometry (DXA) remains the gold standard for diagnosis, it may not be universally accessible or utilized, contributing to underdiagnosis and delayed treatment.
Recent advances in Artificial Intelligence (AI) are transforming this landscape by enabling the use of opportunistic imaging—repurposing scans taken for other clinical reasons—to assess bone health. Just last month, the FDA granted clearance for Bunkerhill BMD, an AI-powered algorithm that estimates bone density using existing non-contrast abdominal CT scans. Other studies are exploring the use of dental panoramic radiographs for similar purposes. Additionally, AI-assisted tools are being developed to enhance fracture detection through opportunistic imaging such as chest X-rays, offering a promising path to earlier diagnosis with reduced radiation exposure.
Beyond detection, AI is also being used to enhance osteoporosis management. Several AI algorithms are being studied to assess bone health and guide treatment. Notably, AI-powered fracture prediction models—functionally similar to the FRAX® tool—offer data-driven risk assessments that can inform preventive strategies and therapeutic decisions.
Implications for Clinical Practice
The integration of AI into osteoporosis detection and management holds significant promise for improving patient outcomes. By harnessing opportunistic imaging, enhancing fracture risk prediction, and streamlining clinical decision-making, AI offers a powerful tool to transform osteoporosis care—especially in settings where traditional diagnostic resources are limited.