The effect of neighboring segments on the measurement of segmental stiffness in the intact lumbar spine

Background context Degeneration, injury, and surgical interventions may alter the mechanical properties of spinal motion segments, but the quantification of these alterations in vivo is problematic. Manual or instrumented loading of single segments in the intact spine as applied intraoperatively may overestimate the mechanical properties of this segment, because the applied load is partly sustained by the adjacent segments. Purpose The distribution of stiffness values of individual spinal segments within and across spines was determined so as to use these data as input to a model simulation of segment stiffness tests in intact spines, to assess measurement errors. Study design Biomechanical stiffness measurements on human cadaveric spines and model simulation to assess measurement errors. Methods Seventeen human cadaveric lumbar spines were loaded with pure moments in flexion/extension, lateral bending, and torsion. An optical system was used to measure the angular rotations of each motion segment and load-displacement curves were used to determine stiffness. With the distribution of measured stiffness data as input, a stochastic mechanical model was constructed to investigate how the stiffness of adjacent segments influences stiffness estimates obtained by loading a single segment in the intact spine. Results The variance in stiffness values was high for all directions, but covaried between segments within a spine. Model simulations indicated that stiffness estimates obtained by loading a single segment in an intact spine are highly correlated with actual stiffness, but overestimate stiffness by a median of 18% with peak errors of close to 400%. Conclusion Current measurement devices and manual assessment substantially overestimate segmental stiffness due to the effect of adjacent spinal levels. In addition, the variance in stiffness within spines can occasionally cause large errors, which might lead to erroneous surgical decisions.