BACKGROUND: The healing outcome of long bone fractures is strongly influenced by the interfragmentary movement of the bone fragments. This depends on the fixation stability, the optimum value of which is still not known. The aim of this study was to simulate a patient-specific human healing process using a numerical algorithm and to retrospectively analyse the influence of the fixation stability on the healing time. METHODS: The healing simulation was processed as an initial value problem. This was iteratively solved based on two mechanical (invariants of the strain tensor, calculated through a finite element analysis) and five biological state variables (local tissue composition and blood perfusion) using a previously published fuzzy logic algorithm. For validation purposes, the calculated interfragmentary movement was compared to in vivo measurements of this patient. By changing clinically adjustable parameters of the fixation device, the influence of the fixation stability on the healing time was analysed. FINDING: The time course showed good agreement of the interfragmentary movement compared with the in vivo measurements. The predicted healing time was strongly influenced by the fixation stability, i.e. by changing the parameters of the fixation device, it was possible to significantly reduce the healing time. INTERPRETATION: The time to heal could be greatly reduced by modification of the fixator design, i.e. increasing the fixation stiffness. When using external fixation devices, this could be achieved by decreasing the free bending length of the pins, using a stiff fixation body and a stiff connection between the pins and the body. Copyright (c) 2010 Elsevier Ltd. All rights reserved.
BACKGROUND: The healing outcome of long bone fractures is strongly influenced by the interfragmentary movement of the bone fragments. This depends on the fixation stability, the optimum value of which is still not known. The aim of this study was to simulate a patient-specific human healing process using a numerical algorithm and to retrospectively analyse the influence of the fixation stability on the healing time. METHODS: The healing simulation was processed as an initial value problem. This was iteratively solved based on two mechanical (invariants of the strain tensor, calculated through a finite element analysis) and five biological state variables (local tissue composition and blood perfusion) using a previously published fuzzy logic algorithm. For validation purposes, the calculated interfragmentary movement was compared to in vivo measurements of this patient. By changing clinically adjustable parameters of the fixation device, the influence of the fixation stability on the healing time was analysed. FINDING: The time course showed good agreement of the interfragmentary movement compared with the in vivo measurements. The predicted healing time was strongly influenced by the fixation stability, i.e. by changing the parameters of the fixation device, it was possible to significantly reduce the healing time. INTERPRETATION: The time to heal could be greatly reduced by modification of the fixator design, i.e. increasing the fixation stiffness. When using external fixation devices, this could be achieved by decreasing the free bending length of the pins, using a stiff fixation body and a stiff connection between the pins and the body. Copyright (c) 2010 Elsevier Ltd. All rights reserved.
Authors: Chao Liu; Robert Carrera; Vittoria Flamini; Lena Kenny; Pamela Cabahug-Zuckerman; Benson M George; Daniel Hunter; Bo Liu; Gurpreet Singh; Philipp Leucht; Kenneth A Mann; Jill A Helms; Alesha B Castillo Journal: Bone Date: 2018-01-04 Impact factor: 4.398
Authors: Brett S Klosterhoff; Jarred Kaiser; Bradley D Nelson; Salil S Karipott; Marissa A Ruehle; Scott J Hollister; Jeffrey A Weiss; Keat Ghee Ong; Nick J Willett; Robert E Guldberg Journal: Bone Date: 2020-03-07 Impact factor: 4.398