Virtual mechanical tests out-perform morphometric measures for assessment of mechanical stability of fracture healing in vivo

Authors
Peter Schwarzenberg, Karina Klein, Stephen J Ferguson, Brigitte von Rechenberg, Salim Darwiche, Hannah L Dailey
Journal
J Orthop Res. 2020 Sep 24. doi: 10.1002/jor.24866.

Finite element analysis with models derived from computed tomography (CT) scans is potentially powerful as a translational research tool because it can achieve what animal studies and cadaver biomechanics cannot-low-risk, noninvasive, objective assessment of outcomes in living humans who have actually experienced the injury, or treatment being studied.

The purpose of this study was to assess the validity of CT-based virtual mechanical testing with respect to physical biomechanical tests in a large animal model. Three different tibial osteotomy models were performed on 44 sheep. Data from 33 operated limbs and 20 intact limbs was retrospectively analyzed. Radiographic union scoring was performed on the operated limbs and physical torsional tests were performed on all limbs. Morphometric measures and finite element models were developed from CT scans and virtual torsional tests were performed to assess healing with four material assignment techniques.

In correlation analysis, morphometric measures and radiographic scores were unreliable predictors of biomechanical rigidity, while the virtual torsion test results were strongly and significantly correlated with measured biomechanical test data, with high absolute agreement. Overall, the results validated the use of virtual mechanical testing as a reliable in vivo assessment of structural bone healing. This method is readily translatable to clinical evaluation for noninvasive assessment of the healing progress of fractures with minimal risk.

Clinical significance: virtual mechanical testing can be used to reliably and noninvasively assess the rigidity of a healing fracture using clinical-resolution CT scans and that this measure is superior to morphometric and radiographic measures.