• Eur Spine J · Dec 2013

    Parametric and cadaveric models of lumbar flexion instability and flexion restricting dynamic stabilization system.

    • Louis C Fielding, Todd F Alamin, Leonard I Voronov, Gerard Carandang, Robert M Havey, and Avinash G Patwardhan.
    • Simpirica Spine, Inc., San Carlos, CA, USA, lfielding@simpirica.com.
    • Eur Spine J. 2013 Dec 1; 22 (12): 271027182710-8.

    PurposeDevelopment of a dynamic stabilization system often involves costly and time-consuming design iterations, testing and computational modeling. The aims of this study were (1) develop a simple parametric model of lumbar flexion instability and use this model to identify the appropriate stiffness of a flexion restricting stabilization system (FRSS), and (2) in a cadaveric experiment, validate the predictive value of the parametric model.MethodsLiterature was surveyed for typical parameters of intact and destabilized spines: stiffness in the high flexibility zone (HFZ) and high stiffness zone, and size of the HFZ. These values were used to construct a bilinear parametric model of flexion kinematics of intact and destabilized lumbar spines. FRSS implantation was modeled by iteratively superimposing constant flexion stiffnesses onto the parametric model. Five cadaveric lumbar spines were tested intact; after L4-L5 destabilization (nucleotomy, midline decompression); and after FRSS implantation. Specimens were loaded in flexion/extension (8 Nm/6 Nm) with 400 N follower load to characterize kinematics for comparison with the parametric model.ResultsTo accomplish the goal of reducing ROM to intact levels and increasing stiffness to approximately 50 % greater than intact levels, flexion stiffness contributed by the FRSS was determined to be 0.5 Nm/deg using the parametric model. In biomechanical testing, the FRSS restored ROM of the destabilized segment from 146 ± 13 to 105 ± 21 % of intact, and stiffness in the HFZ from 41 ± 7 to 135 ± 38 % of intact.ConclusionsTesting demonstrated excellent predictive value of the parametric model, and that the FRSS attained the desired biomechanical performance developed with the model. A simple parametric model may allow efficient optimization of kinematic design parameters.

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