Journal
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART H-JOURNAL OF ENGINEERING IN MEDICINE
Volume 232, Issue 12, Pages 1245-1254Publisher
SAGE PUBLICATIONS LTD
DOI: 10.1177/0954411918810707
Keywords
Scoliosis surgery; finite element analysis; intra-operative corrective forces; stress distribution; screw density
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Scoliosis is an abnormal sideways curvature of the spine and rib cage, which may need surgical treatments. Most of the corrective maneuvers in scoliosis surgeries are based on surgeon's experience; hence, there is great interest of understanding how the correction ratio can be influenced by the magnitude of forces and moments. Therefore, the objective of this study was to develop and validate a detailed finite element model of the thoracolumbar which can be used to simulate the scoliosis surgeries based on patient-specific clinical images. The validated models of five patients were carefully developed, and the surgery procedures were simulated and the corrective forces were estimated using inverse finite element analysis during the surgery. Furthermore, parametric studies including the influences of the corrective force magnitude and screw density were evaluated. The results showed that the maximum estimated correction force and moment were 173 (+/- 55.43) N and 10.67 (+/- 2.02) N m, respectively, which were aligned with measured clinical observations. The sensitivity analysis on the magnitude of applied force to the screws showed that correction ratio was slightly increased in level 1 (i.e. F-B = 1.3 x F) but decreased in level 2 (i.e. F-B = 1.6 x F). In addition, the parametric study on increasing the number of pedicle screws showed that there was no significant difference between lower and higher screw density. However, the stress distribution was significantly greater using higher screw density during correction maneuvers. In conclusion, this study shows a direct relationship between the applied force/moment and screw density and the correction ratio up to a border line which should be defined accurately. This detailed computational modeling can be used in clinic in hope of achieving the optimum outcome of scoliosis surgery using individual patient-specific characterization.
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