Identification of increased fracture risk through non-invasive determination of cortical micro- and macro-structural properties using quantitative bone ultrasound imaging

• Conditions: M80; M85; Osteoporosis with pathological fracture; Other disorders of bone density and structure

• Registration Number: DRKS00025849
• Lead Sponsor: Charite - Universitätsmedizin Berlin; Berlin-Brandenburg Center for Regenerative Therapies (BCRT)

Brief Summary

Not available

Detailed Description

Not available

Study Timeline

• Study Start: 2021-07-14
• Study Completion: 2022-12-31
• Results First Posted: 2024-03-13
• Last Update Posted: 19 August 2024

Recruitment & Eligibility

• Status: Complete
• Sex: All
• Target Recruitment: 129

Inclusion Criteria

For all study participants:
- written informed consent to participate in the study.

For patients:
- Age:> 55 years
- Guideline-compliant bone mineral density measurement

For healthy subjects:
- Age: 18 - 50 years

Exclusion Criteria

- BMI> 30
- Edema on the lower extremity to be measured
- Metal implants on the lower extremity to be measured
- Paralysis of the lower extremity to be measured
- Participants who are unable to undergo the examinations prescribed in the protocol or who have cognitive impairments that preclude understanding of the study protocol.

Study & Design

• Study Type: observational
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
The discrimination performance for fragility fractures is better for QUSIB biomarkers than for DXA-based T-scores.<br><br>Using Partial Least Squares (PLS) regression and discrimination analyzes, associations between the multivariate biomarkers (ultrasound and clinically indicated DXA bone mineral density measurement) are examined and the parameters that make the greatest contribution to fracture discrimination are determined. Age, BMI, gender and drugs that affect bone metabolism are taken into account as covariates. In particular, the discrimination performance of X-ray and US-based parameters and their combination in terms of correctness, sensitivity and specificity are compared with each other with the help of an ROC analysis and determination of the area-under-the-curve (AUC) (Arm 1 and 2)

Secondary Outcome Measures

Name	Time	Method
The QUSIB biomarkers and the discrimination thresholds derived from them are age and gender dependent.