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Systemic modulation of skeletal mineralization by magnesium implant promoting fracture healing: Radiological exploration enhanced with PCA-based machine learning in a rat femoral model.

Authors :
Sun, Yu
Helmholz, Heike
Willumeit-Römer, Regine
Source :
Journal of Magnesium & Alloys; Mar2024, Vol. 12 Issue 3, p1009-1020, 12p
Publication Year :
2024

Abstract

• Validation of promoted fracture healing via intramedullary Mg implantation. • Concurrent systemic and local bone modulation associated with retention of Mg implant. • Constructed radiological markers with improved differentiation of healing outcomes. • Preclinical evidence for comprehensive fracture research and developing Mg implants. The clinical application of magnesium (Mg) and its alloys for bone fractures has been well supported by in vitro and in vivo trials. However, there were studies indicating negative effects of high dose Mg intake and sustained local release of Mg ions on bone metabolism or repair, which should not be ignored when developing Mg-based implants. Thus, it remains necessary to assess the biological effects of Mg implants in animal models relevant to clinical treatment modalities. The primary purpose of this study was to validate the beneficial effects of intramedullary Mg implants on the healing outcome of femoral fractures in a modified rat model. In addition, the mineralization parameters at multiple anatomical sites were evaluated, to investigate their association with healing outcome and potential clinical applications. Compared to the control group without Mg implantation, postoperative imaging at week 12 demonstrated better healing outcomes in the Mg group, with more stable unions in 3D analysis and high-mineralized bridging in 2D evaluation. The bone tissue mineral density (TMD) was higher in the Mg group at the non-operated femur and lumbar vertebra, while no differences between groups were identified regarding the bone tissue volume (TV), TMD and bone mineral content (BMC) in humerus. In the surgical femur, the Mg group presented higher TMD, but lower TV and BMC in the distal metaphyseal region, as well as reduced BMC at the osteotomy site. Principal component analysis (PCA)-based machine learning revealed that by selecting clinically relevant parameters, radiological markers could be constructed for differentiation of healing outcomes, with better performance than 2D scoring. The study provides insights and preclinical evidence for the rational investigation of bioactive materials, the identification of potential adverse effects, and the promotion of diagnostic capabilities for fracture healing. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22139567
Volume :
12
Issue :
3
Database :
Supplemental Index
Journal :
Journal of Magnesium & Alloys
Publication Type :
Academic Journal
Accession number :
176539921
Full Text :
https://doi.org/10.1016/j.jma.2024.01.012