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Automated Bone Age Estimation From Noncontrast Abdominal CT Using Deep Learning

NCT07162168 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 3000

Last updated 2025-12-03

No results posted yet for this study

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

Sponsors & Collaborators

  • Peking University People's Hospital

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2024-09-01
Primary Completion
2027-09-01
Completion
2027-12-01

Countries

  • China

Study Locations

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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 NCT07162168 on ClinicalTrials.gov