AI-driven analysis of chest x-rays is shown to be a cost-effective method for osteoporosis screening in U.S. women over 50.
Key Details
- 1Researchers evaluated opportunistic osteoporosis screening by applying deep learning to chest x-rays in women 50+.
- 2A two-part economic model compared costs and health outcomes between AI-enabled screening and no screening scenarios.
- 3Five million individual simulations informed projections for costs, fractures, life years, and QALYs.
- 4AI-enabled screening had a cost per QALY gained of $72,085, below the U.S. $100,000 benchmark for cost-effectiveness.
- 5AI screening resulted in more QALYs and fewer fractures but increased treatment costs.
Why It Matters
Demonstrating cost-effectiveness is crucial for policy, reimbursement, and adoption of radiology AI tools. The study supports expanding opportunistic AI-based screening to close osteoporosis care gaps and improve public health outcomes.
Source
AuntMinnie
Related News
•AuntMinnie
AI Enables Safe 75% Gadolinium Reduction in Breast MRI Without Losing Sensitivity
AI-enhanced breast MRI with a 75% reduced gadolinium dose maintained diagnostic sensitivity comparable to full-dose protocols.
•Cardiovascular Business
Deep Learning AI Model Detects Coronary Microvascular Dysfunction Via ECG
A new AI algorithm rapidly detects coronary microvascular dysfunction using ECGs, with validation incorporating PET imaging.
•AuntMinnie
Debate at RSNA 2025 Examines If AI Is Ready for Autonomous Chest X-ray Reads
Experts at RSNA 2025 debated whether AI is ready for fully autonomous interpretation of chest x-rays, concluding that while technical progress is evident, significant challenges remain.