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NCT07739628

Validation of a Deep Learning Tool for Opportunistic Osteoporosis Screening Using Routine Non-Contrast CT Scans

Sponsor: Union Hospital, Tongji Medical College, Huazhong University of Science and Technology

View on ClinicalTrials.gov

Summary

The goal of this clinical trial is to test if an artificial intelligence (AI) tool called DeepBMD can accurately identify people at high risk for osteoporosis using routine chest or abdomen CT scans. The main questions it aims to answer are: 1. Can the DeepBMD tool correctly identify people who have osteoporosis compared to the standard bone density test, dual-energy X-ray absorptiometry (DXA)? 2. Is it practical to use this AI tool in real-world hospital settings to find and contact high-risk patients? Researchers will use the DeepBMD tool to analyze existing CT scans. If the tool flags a patient as high risk, researchers will call them to invite them for a standard bone density test (DXA). Participants will: 1. Have their existing chest or abdomen CT scan analyzed by the DeepBMD AI tool; 2. Receive a phone call from the research team if identified as high risk; 3. Visit the clinic for a free standard bone density test (DXA) if they agree to participate.

Official title: Prospective Clinical Validation Study of a Deep Learning Model for Opportunistic Osteoporosis Screening Based on Non-Contrast CT Scans

Key Details

Gender

All

Age Range

18 Years - Any

Study Type

OBSERVATIONAL

Enrollment

100

Start Date

2026-07

Completion Date

2026-09

Last Updated

2026-07-31

Healthy Volunteers

No

Conditions

Interventions

DIAGNOSTIC_TEST

DeepBMD model for osteoporosis risk screening

The DeepBMD model is applied to routine chest or abdominal CT scans to identify patients at high risk for osteoporosis. This is a non-invasive image analysis used solely for screening and recruitment purposes, not as a therapeutic intervention.

Locations (1)

Union Hospital, Tongji Medical College, Huazhong University of Science and Technology

Wuhan, Hubei, China