基于脊柱刚度对下肢动力学影响的参数预测分析,初步优化全髋关节置换术中杯状植入物的定位

IF 2.6 2区 工程技术 Q2 MECHANICS Multibody System Dynamics Pub Date : 2023-11-30 DOI:10.1007/s11044-023-09951-3
AliAsghar MohammadiNasrabadi, John McPhee
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引用次数: 0

摘要

传统的Lewinnek安全区域用于全髋关节置换术(THA)手术被发现是不够的,因为手术后不满意率上升。显然,为了获得最佳的手术结果,必须考虑到以前被忽视的脊柱参数和脊柱刚度因素。本文提出了一种新的预测动态建模方法来解决这一问题。该方法涉及到一个包含非线性脊柱元素的人体多体模型的开发,并通过将其与体外实验文献进行比较和进行动作捕捉实验来验证。为了模拟人体坐立运动,采用了基于轨迹优化的最优控制方法。人体关节角度从不同情景的模拟中提取:正常、融合和僵硬的脊柱。我们发现脊柱僵硬对下肢运动和植入物撞击的风险有显著影响。研究了不同的脊柱僵硬情况,如不同程度的脊柱融合或解剖上僵硬的脊柱。根据不同脊柱状况下的预测运动,根据植入物撞击标准计算最佳髋臼杯定位,并将结果与同类患者的临床推荐定位值进行比较。我们的初步优化建议,对于解剖性僵硬的脊柱,将前倾杯角从\(23 ^{\circ }\)(正常脊柱)增加到\(29 ^{\circ }\)。对于融合的脊椎,角度应在27-38°的范围内,视融合程度而定。这项研究是第一次在不同情况下检查脊柱灵活性及其对下肢运动的影响。本研究结果有助于改进THA手术计划,降低THA术后髋关节撞击或脱位的风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Preliminary optimization of cup-implant orientation in total-hip arthroplasty using a parametric predictive analysis of lower-limb dynamics influenced by spine stiffness

The traditional Lewinnek safe zone used for Total-Hip Arthroplasty (THA) surgery has been found to be inadequate, as dissatisfaction rates have risen after this surgery. It is evident that spinopelvic parameters and spine stiffness, factors that have been overlooked previously, must be taken into account for optimal surgical outcomes. In this paper, a novel predictive dynamic modeling approach was proposed to address this issue. This approach involved the development of a multibody model of a human that contained nonlinear spinal elements, which was validated by comparing it to literature in-vitro experiments and conducting a motion-capture experiment. To simulate human sit-to-stand motion, this model was employed with an optimal control approach based on trajectory optimization. Human joint angles were extracted from conducted simulations of different scenarios: normal, fused, and stiff spines. It was found that spine stiffness had a significant effect on lower-limb motion and the risk of implant impingement. Different scenarios of spine stiffness were examined, such as different levels of spinal fusion or an anatomically stiff spine. The optimal acetabular-cup orientation was calculated based on implant-impingement criteria using predicted motions for different spinal-condition scenarios, and the results compared to the clinically recommended orientation values for the same categories of patients. Our preliminary optimization suggests increasing the anteversion-cup angle from \(23 ^{\circ }\) (normal spine) to \(29 ^{\circ }\) for an anatomically stiff spine. For fused spines, the angle should fall within the range of 27–38, depending on the level of fusion. This research is the first of its kind to examine spine flexibility in different scenarios and its impact on lower-limb motion. The findings of this paper could help improve THA surgical planning and reduce the risk of hip impingement or dislocation after THA.

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来源期刊
CiteScore
6.00
自引率
17.60%
发文量
46
审稿时长
12 months
期刊介绍: The journal Multibody System Dynamics treats theoretical and computational methods in rigid and flexible multibody systems, their application, and the experimental procedures used to validate the theoretical foundations. The research reported addresses computational and experimental aspects and their application to classical and emerging fields in science and technology. Both development and application aspects of multibody dynamics are relevant, in particular in the fields of control, optimization, real-time simulation, parallel computation, workspace and path planning, reliability, and durability. The journal also publishes articles covering application fields such as vehicle dynamics, aerospace technology, robotics and mechatronics, machine dynamics, crashworthiness, biomechanics, artificial intelligence, and system identification if they involve or contribute to the field of Multibody System Dynamics.
期刊最新文献
Development of an identification method for the minimal set of inertial parameters of a multibody system Vibration transmission through the seated human body captured with a computationally efficient multibody model Data-driven inverse dynamics modeling using neural-networks and regression-based techniques Load torque estimation for cable failure detection in cable-driven parallel robots: a machine learning approach Mutual information-based feature selection for inverse mapping parameter updating of dynamical systems
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