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Effects of dynamization timing and degree on bone healing of different fracture types.
Fu, Ruisen; Liu, Yang; Song, Fei; Fu, Jizhi; Du, Tianming; Liu, Youjun; Willie, Bettina M; Yang, Haisheng.
Afiliação
  • Fu R; Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China.
  • Liu Y; Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China.
  • Song F; Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China.
  • Fu J; Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China.
  • Du T; Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China.
  • Liu Y; Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China.
  • Willie BM; Department of Dentistry, McGill University, Montreal, Canada.
  • Yang H; Research Centre, Shriners Hospital for Children-Canada, Montreal, Canada.
J Orthop Res ; 41(11): 2394-2404, 2023 11.
Article em En | MEDLINE | ID: mdl-37138390
ABSTRACT
Dynamization, that is, increasing interfragmentary movement (IFM) by reducing fixation stiffness from a rigid to a more flexible state, has been successfully used in clinical practice to promote fracture healing. However, it remains unclear how dynamization timing and degree affect bone healing of different fracture types. Finite element models of tibial fractures based on the OTA/AO classification (Simple A1-Spiral, A2-Oblique, A3-Transverse; Wedge B2-Spiral, B3-Fragmented; Complex C2-Segment, C3-Irregular), in combination with fuzzy logic-based mechano-regulatory tissue differentiation algorithms, were used to simulate the healing process when dynamization of varied degrees (dynamization coefficient or DC = 0-0.9; 0.9 represents 90% reduction in the fixation stiffness relative to a rigid fixation) were applied at different time points after fracture. The fuzzy logic-based algorithms have been validated with a preclinical animal model. The results showed that the healing responses of type A fractures were more sensitive to the changes in dynamization degree and timing comparing with type B or C fractures. Additionally, the optimal dynamization regime for each fracture type was different. For type A fractures, a moderate dynamization degree (e.g., DC = 0.5) applied after Week 1 promoted the recovery of biomechanical integrity. For type B and C fractures, the effective dynamization included a greater dynamization degree (DC = 0.7) applied after Week 2. Our results further demonstrated that the fracture morphology affected interfragmentary strain environments within the callus, leading to varied healing results for different fracture types. These results suggest that the effects of dynamization are highly dependent of the fracture types. Therefore, specific dynamization strategies should be chosen for different fracture types to achieve optimal healing outcomes.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Fraturas da Tíbia / Fixação Interna de Fraturas Limite: Animals Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Fraturas da Tíbia / Fixação Interna de Fraturas Limite: Animals Idioma: En Ano de publicação: 2023 Tipo de documento: Article