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

NCT07739628 · Status: ENROLLING_BY_INVITATION · Type: OBSERVATIONAL · Enrollment: 100

Last updated 2026-07-31

No results posted yet for this study

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.

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.

Sponsors & Collaborators

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

    lead OTHER

Principal Investigators

  • Fan Yang, PhD, MD · Union Hospital, Tongji Medical College, Huazhong University of Science and Technology

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-07-31
Primary Completion
2026-08-31
Completion
2026-09-30

Countries

  • China

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07739628 on ClinicalTrials.gov