AI algorithms can extract bone density data from routine CT scans to identify osteoporosis, enabling opportunistic screening.
Key Details
- 1NYU Langone Health and Visage developed an AI tool to analyze CT scans for bone loss indicators.
- 2Study used over 538,000 CT scans from 283,499 patients, covering multiple anatomical regions and CT machine models.
- 3Bone mineral density measurements accounted for age, gender, and race/ethnicity, revealing population trends.
- 4AI-based opportunistic screening could double osteoporosis testing rates and save over $2.5 billion annually in Medicare costs.
- 5Clinical trial is planned at NYU Langone Health for AI-based osteoporosis detection using existing CT images.
Why It Matters
This work demonstrates the practical value of applying AI to existing imaging data, potentially identifying millions of undiagnosed osteoporosis patients and reducing healthcare costs through earlier intervention. It exemplifies the expanding role of AI in repurposing radiology data for broader disease screening.
Source
EurekAlert
Related News
•EurekAlert
MD Anderson Unveils New AI Genomics Insights and Therapeutic Advances
MD Anderson reports breakthroughs in cancer therapeutics and provides critical insights into AI models for genomic analysis.
•EurekAlert
UCLA Researchers Present AI, Blood Biomarker Advances at SABCS 2025
UCLA Health researchers unveil major advances in breast cancer AI pathology, liquid biopsy, and biomarker strategies at the 2025 SABCS.
•EurekAlert
SH17 Dataset Boosts AI Detection of PPE for Worker Safety
University of Windsor researchers released SH17, a 8,099-image open dataset for AI-driven detection of personal protective equipment (PPE) in manufacturing settings.