NCT07162168

Automated Bone Age Estimation From Noncontrast Abdominal CT Using Deep Learning

Development and Evaluation of a Deep Learning-Based Model for Automated Osteoporosis Assessment Using CT Images

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 3,000 (estimated)
• Sponsor: Peking University People's Hospital · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Accepted

Summary

This study is a retrospective analysis that uses abdominal CT scans, which were originally taken for other medical reasons, to estimate bone age. By applying advanced deep learning methods, the investigators aim to develop a tool that can evaluate bone health and detect early signs of osteoporosis without requiring additional scans or radiation. This approach may help doctors better understand bone aging, improve screening for bone weakness, and provide patients with more personalized information about their bone health.

Conditions

• Bone Aging
• Osteoporosis Diagnosis

Timeline

• Start date: 2024-09-01
• Primary completion: 2027-09-01
• Completion: 2027-12-01
• First posted: 2025-09-09
• Last updated: 2025-12-03

Locations

1 site across 1 country: China