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Image-guided Computational and Experimental Analyses of Fractured Patient's Bone (GAP)

NCT04787679 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 52

Last updated 2026-01-29

No results posted yet for this study

Summary

Due to the increase in the average age of the population, the projections on the number of age-dependent bone fractures appear to be constantly increasing.

They are mainly due to bone pathologies, including osteoporosis. The latter leads to a reduction in bone mineral density and deterioration of the micro-architecture, with a consequent increase in bone fragility. However, the mechanisms of damage at the micro-scale have not yet been elucidated and there is no universally recognized damage criterion. Recent research has evaluated the importance of implementing computational models to study the influence of bone gaps, canaliculi and microporosities on the propagation of damage. These models need to be validated through experimental tests, still lacking, in particular on human bones, in the current scientific landscape. Once the experimental validation of computational models has been developed, it will be possible to introduce new fracture indices at the micro-scale, useful for a preventive diagnosis of osteoporosis.

Conditions

Interventions

PROCEDURE

Hip replacement surgery

After hip replacement surgery the sponsor obtains femoral head samples for the study

Sponsors & Collaborators

  • Ospedale San Donato

    collaborator OTHER

  • Laura Maria Vergani

    lead OTHER

Principal Investigators

  • Luigi Zagra · IRCCS Istituto Ortopedico Galeazzi

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-11-09
Primary Completion
2026-07-09
Completion
2028-08-09

Countries

  • Italy

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 NCT04787679 on ClinicalTrials.gov