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Intraoperative determination of the load–displacement behavior of scoliotic spinal motion segments: preliminary clinical results

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Hasler C, Scheffler,  K
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Reutlinger, C., Hasler C, Scheffler, K., & Büchler, P. (2012). Intraoperative determination of the load–displacement behavior of scoliotic spinal motion segments: preliminary clinical results. European Spine Journal, 21(6 Supplement), 860-867. doi:10.1007/s00586-012-2164-8.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0013-B67E-D
Zusammenfassung
Introduction Spinal fusion is a widely and successfully performed strategy for the treatment of spinal deformities and degenerative diseases. The general approach has been to stabilize the spine with implants so that a solid bony fusion between the vertebrae can develop. However, new implant designs have emerged that aim at preservation or restoration of the motion of the spinal segment. In addition to static, load sharing principles, these designs also require a profound knowledge of kinematic and dynamic properties to properly characterise the in vivo performance of the implants. Methods To address this, an apparatus was developed that enables the intraoperative determination of the load–displacement behavior of spinal motion segments. The apparatus consists of a sensor-equipped distractor to measure the applied force between the transverse processes, and an optoelectronic camera to track the motion of vertebrae and the distractor. In this intraoperative trial, measurements from two patients with adolescent idiopathic scoliosis with right thoracic curves were made at four motion segments each. Results At a lateral bending moment of 5 N m, the mean flexibility of all eight motion segments was 0.18 ± 0.08°/N m on the convex side and 0.24 ± 0.11°/N m on the concave side. Discussion The results agree with published data obtained from cadaver studies with and without axial preload. Intraoperatively acquired data with this method may serve as an input for mathematical models and contribute to the development of new implants and treatment strategies.