May 2, 2020 /

New publication online: Loads distributed in vivo among vertebrae, muscles, spinal ligaments, and intervertebral discs in a passively flexed lumbar spine

A recently accepted manuscript to predict internal loads in passive spines is now online: Loads distributed in vivo among vertebrae, muscles, spinal ligaments, and intervertebral discs in a passively flexed lumbar spine (DOI: https://doi.org/10.1007/s10237-020-01322-7). This is a joint work of UStutt and APZ Erfurt.

The load distribution among lumbar spinal structures—still an unanswered question—has been in the focus of this hybrid
experimental and simulation study. First, the overall passive resistive torque-angle characteristics of healthy subjects’ lumbar spines during flexion–extension cycles in the sagittal plane were determined experimentally by use of a custom-made trunk-bending machine. Second, a forward dynamic computer model of the human body that incorporates a detailed lumbar spine was used to (1) simulate the human–machine interaction in accordance with the experiments and (2) validate the modeled properties of the load-bearing structures. Third, the computer model was used to predict the load distribution in the experimental situation among the implemented lumbar spine structures: muscle–tendon units, ligaments, intervertebral discs, and facet joints. Nine female and 10 male volunteers were investigated. Lumbar kinematics were measured with a marker-based infrared device. The lumbar flexion resistance was measured by the trunk-bending machine through strain gauges on the axes of the machine’s torque motors. Any lumbar muscle activity was excluded by simultaneous sEMG monitoring. A mathematical model was used to describe the nonlinear flexion characteristics. The subsequent extension branch of a flexion–extension torque–angle characteristic could be significantly distinguished from its flexion branch by the zero-torque lordosis angle shifted to lower values. A side finding was that the model values of ligament and passive muscle stiffnesses, extracted from well-established literature sources, had to be distinctly reduced in order to approach our measured overall lumbar stiffness values. Even after such parameter adjustment, the computer model still predicts too stiff lumbar spines in most cases in comparison with experimental data. A review of literature data reveals a deficient documentation of anatomical and mechanical parameters of spinal ligaments. For instance, rest lengths of ligaments—a very sensitive parameter for simulations—and cross-sectional areas turned out to be documented at best incompletely. Yet by now, our model well reproduces the literature data of measured pressure values within the lumbar disc at level L4/5. Stretch of the lumbar dorsal (passive) muscle and ligament structures as an inescapable response to flexion can fully explain the pressure values in the lumbar disc. Any further external forces like gravity, or any muscle activities, further increase the compressive load on a vertebral disc. The impact of daily or sportive movements on the loads of the spinal structures other than the disc cannot be predicted ad hoc, because, for example, the load distribution itself crucially determines the structures’ current lever arms. In summary, compressive loads on the vertebral discs are not the major determinants, and very likely also not the key indicators, of the load scenario in the lumbar spine. All other structures should be considered at least equally relevant in the future. Likewise, load indicators other than disc  compression are advisable to turn attention to. Further, lumbar flexion is a self-contained factor of lumbar load. It may be worthwhile, to take more consciously care of trunk flexion during daily activities, for instance, regarding long-term effects like lasting repetitive flexions or sedentary postures. doi: 10.1007/s10237-020-01322-7

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