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Journal article
Prediction of bone ingrowth into the porous swelling bone anchors using an osteoconnectivity-based adaptive finite element algorithm
Medical & biological engineering & computing, s11517-025-03370-6
07 May 2025
PMID: 40332631
Featured in Collection : Research Supported by Drexel Libraries' OA Programs
Abstract
In this study, a bone ingrowth framework was developed, which was integrated with a hygro-elastic swelling simulation, to evaluate the ingrowth of bone into porous co-polymeric swelling bone anchors. The aim was to investigate the impact of swelling-induced radial stress on bone ingrowth and the improvement in the mechanical properties and fixation strength of the anchors. Using the finite element method coupled with the osteoconnectivity matrix, the model successfully predicted the sequential bone formation within the porous bone anchor. The bone ingrowth framework was validated based on available experimental data, closely aligning with empirical observations. The results show that owing to radial stresses generated in the bone-anchor interface by swelling, considerable bone ingrowth could be stimulated. Moreover, among the three finite element models incorporating porosity within the recommended pore size range (300-600
), smaller pore sizes seem to promote faster and more extensive bone ingrowth, while larger pores exhibit slower ingrowth rates. Regardless of the pore sizes, the mechanical integrity and fixation strength of the anchors significantly improved. These findings strengthen the hypotheses that swelling of such anchors can stimulate bone ingrowth, and highlight the importance of pore geometry, size and interconnectivity in optimizing bone ingrowth and improving their performance.
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Details
- Title
- Prediction of bone ingrowth into the porous swelling bone anchors using an osteoconnectivity-based adaptive finite element algorithm
- Creators
- Amirreza Sadighi - Drexel UniversityNolan Black - Drexel UniversityMehrangiz Taheri - Drexel UniversityMoein Taghvaei - Drexel UniversitySorin Siegler - Drexel University, Mechanical Engineering and MechanicsThomas P Schaer - University of PennsylvaniaAhmad Raeisi Najafi (Corresponding Author) - Drexel University, Mechanical Engineering and Mechanics
- Publication Details
- Medical & biological engineering & computing, s11517-025-03370-6
- Publisher
- Springer Nature
- Number of pages
- 20
- Grant note
- Drexel Faculty Start-up Funding
The work was performed at Drexel University in the Multiscale Computational Mechanics and Biomechanics (MCMB) Lab. All simulations were conducted on Picotte, Drexel University's primary high-performance computing cluster, and on the clusters and PCs in the MCMB lab.
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Mechanical Engineering and Mechanics; College of Engineering
- Web of Science ID
- WOS:001483450700001
- Scopus ID
- 2-s2.0-105004438661
- Other Identifier
- 991022050050704721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Engineering, Biomedical
- Mathematical & Computational Biology
- Medical Informatics