Title
Biomechanical analysis of proximal tibia bone grafting and the effect of the size of osteotomy using a validated finite element model.
Abstract
Harvesting bone graft from the proximal tibia is gaining popularity, with lower complication rates and adequate quantity of cancellous bone. The amount of harvested bone is dependent on the size of the cortical window introduced via osteotomy onto the proximal tibia, and its mechanical strength after surgery could be compromised. The aim of the study was to investigate the proximal tibia’s mechanical stability after bone harvesting and the effect of varying window sizes using a validated finite element model. Two cadaveric tibiae were tested with bone strains measured for different circular cortical window diameters (10–25 mm). Sixteen finite element models of the intact and harvested tibia were simulated and validated with experimental data. The experimental and predicted max/min principal bone strains were fitted into regression models and showed good correlations. It was predicted the maximum principal bone stresses were greatest and concentrated at postero-inferior and antero-superior regions of the cortical window. A stress line progressed from the edge of the window to the posterior side of the tibia, which became more prominent with the increase of size of the cortical window. It was found that large circular osteotomies for bone harvesting at the proximal tibia induced stress concentrations and stress lines which could lead to eventual failure.
Year
DOI
Venue
2019
10.1007/s11517-019-01988-x
Medical & Biological Engineering & Computing
Keywords
Field
DocType
Bone graft harvesting, Tibia bone harvesting, Finite element modelling, Stress concentration, Circular osteotomy
Biomedical engineering,Mechanical strength,Tibia bone,Computer vision,Cadaveric spasm,Osteotomy,Tibia,Finite element method,Artificial intelligence,Stress concentration,Cancellous bone,Mathematics
Journal
Volume
Issue
ISSN
57
8
0140-0118
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
David Q K Ng100.34
Chin Tat Lim200.34
Amit K Ramruttun300.34
Ken Jin Tan400.34
Wilson Wang500.34
Desmond Y.R. Chong6224.36