Studies have shown that assessment of the spinal flexibility of AIS patients is of great significance in determining fusion segments, selecting surgical approaches, and predicting postoperative orthopedic effects. For AIS patients with relatively better flexibility, orthopedic surgery can be completed by reducing the screw density or shortening the fixed fusion segment. In comparison, patients with comparatively poorer flexibility need to increase the screw density or extend the fixed fusion segment to achieve the designated orthopedic purposes[24–26]. In addition, the role of spinal flexibility assessment in conservative treatment is also important. Scoliosis flexibility evaluation is the overall deformability of the spine under active or passive external force, and it is a quantification of the degree of spinal stiffness. At present, the commonly used methods for clinical evaluation of scoliosis flexibility include the supine bending method, fulcrum bending method, traction method, push prone method, and suspension-traction method[28, 29]. Berger et al. used flexibility index for systematic review of the predictive effect of the above five methods on the surgical orthopedic outcome, and concluded that the supine bending method was the most commonly used method, and the fulcrum bending method was the most accurate method. However, both assessment methods are conducted in a static and specific state, which hinders the overall assessment of spinal flexibility. In addition, the stiffness degree of AIS patients is often different under the same traction loads, which emphasizes the necessity of overall assessment of the patients' flexibility.
Although the finite element model has been widely used in the field of spinal surgery, especially in the spinal biomechanical analysis of AIS patients[32, 33], for the first time it was used to simulate scoliosis correction surgery by comparing the effect of lateral and longitudinal forces on the correction of scoliosis. Viviani et al. optimized the surgical strategy by comparing the simulated surgical effect with the actual surgical effect. Ghista et al. summarized the methods for biomechanical analysis of scoliosis orthopedic surgery. With the advancement in modeling technology, scholars have also performed finite element simulations of scoliosis orthopedic surgery from different perspectives[37, 38] and now the finite element model can also simulate internal fixation devices, surgical strategy, vertebral body growth rate and other elements[8–10, 39]. Further efforts have also been made to improve the simulation degree of the finite element model, including performance optimization and structure optimization, especially in terms of biomechanical characteristics. Lafage et al. established a simulated finite element model of scoliosis by referring to the supine bending method to optimize the mechanical parameters of soft tissues. Little et al. optimized the finite element model by using the fulcrum bending method, and after a detailed report of the specific simulation process and the adjustment of the relevant soft tissue stiffness index, they believed that the stiffness of the intervertebral disc fiber had a relatively strong impact on the flexibility of the spine. In a subsequent study, the authors also found that spinal flexibility in the fulcrum bending test was not governed by any single soft tissue structure acting in isolation. More detailed biomechanical characterisation of the fulcrum bending test is required to provide better data to determine the properties of patient-specific soft tissues. Kamal et al. achieved optimization by adding muscle simulation to the finite element model. In addition, other scholars were also committed to improving the simulation accuracy of the model. The individualized finite element model based on hexahedral meshing can simulate the structural characteristics of different scoliosis spines with more precision and make the stress distribution more uniform. However, the construction of a high-precision individualized model requires manual matching with the details of scoliosis features, which can be extremely time-consuming. As a result, Hadagali et al. proposed a block template method to construct a scoliosis thoracic spine model to improve the efficiency of modeling.
We believe that spinal flexibility in AIS patients is an important manifestation of biomechanical characteristics, and optimization of the finite element model needs to consider spinal flexibility. However, to the best of our knowledge, most models currently used to optimize the flexibility statically and in a specific state, and only the reduction degree in the range of flexion, extension, lateral flexion and rotation of the spine is consistent with AIS patients[18, 44]. In this study, we utilized the dynamic flexibility of AIS patients to optimize the finite element model. Although the dynamic flexibility in vivo is only under a longitudinal traction load, it can still be viewed as an exploration of a novel method of model optimization.
The present study has some limitations. Firstly, only a one-case model was optimized, the type (Lenke 1) of scoliosis was simple, and the representativeness of the main curve Cobb angle was questionable. Secondly, the flexibility of the spine in patients with scoliosis is affected by many factors, such as soft-tissue properties, but the model of the present study only optimized the elastic modulus of the intervertebral disc which was modelled as isotroptic with the same mechanical properties, while they may change depending on the spinal level. Meanwhile, the intervertebral disc was not distinguished between the nucleus pulposus and the annulus fibrosus. Instead, the annulus fibrosus was used as the main assignment subject. However, this does not affect the purpose that provide a new perspective and approach for model optimization of this study. Thirdly, the model was too simplified neglecting specific anatomical structure (i.e. nucleous pulposus, facet joints) and simplifying the boundary conditions. Although the purpose was to present a novel optimization method, more sophisticated model and realistic boundary conditions would undoubtedly increase the applicability. Finally, the dynamic flexibility was only under longitudinal traction load and may not represent the overall flexibility of one specific patient. And also, it is not clear to which degree the disc properties are related to the traction forces. More comprehensive dynamic flexibility evaluation methods would be worth studying in the future.