Quantifying patient-specific changes in neuromuscular control in cerebral palsy

 描述（由申请人提供）：本研究的长期目标是量化神经肌肉控制的患者特异性变化，以优化治疗计划并改善脑瘫（CP）患者的活动能力。作为第一步，本提案的目的是评估CP患者最常见的治疗方法之一-矫形外科手术前后的神经肌肉控制。我们将评估基于肌肉协同作用框架的患者特异性神经肌肉控制措施是否可以预测手术后步行能力的改善。此外，我们将确定手术后神经肌肉控制是否发生变化，以及这些变化是否有助于改善运动。为了实现这些目标，我们将实施和测试新的工具，以量化神经肌肉控制，整合临床步态分析和两个计算技术：协同分析和动态肌肉骨骼模拟。我们之前的研究表明，CP患者在步态中使用的协同作用比未受损的个体少，并且协同作用与各种治疗后行走能力的变化相关。在目标1中，我们将前瞻性评估协同效应是否能预测骨科手术后的结局。在目标2中，我们将通过评价骨科手术后协同效应是否发生变化来评价协同效应的适应性。在目标3中，我们将使用肌肉骨骼模拟来评估改变的协同效应如何影响CP中三种最常见的病理步态模式的肌肉募集、运动受损和行走的能量消耗：蹲下步态、膝关节僵硬步态和马蹄步态。肌肉骨骼模拟提供了一个独特的工具，以探测患者特定的神经肌肉控制的变化，因为我们可以指定和评估不同的控制策略和计算机损伤。例如，我们可以使用来自临床步态分析的患者的实验测量的运动学和动力学来模拟他们的特定步态模式并检查不同控制策略的影响。我们将使用我们在OpenSim中开发的新算法，OpenSim是一个用于肌肉骨骼建模的开源平台，用于创建基于协同控制的模拟。本研究的结果将量化CP中神经肌肉控制的变化，并评估协同分析的临床效用。这项研究将为使用 改变神经肌肉控制的措施，为治疗计划提供信息，开发替代治疗方法，并改善CP和其他神经系统疾病的活动性。

 DESCRIPTION (provided by applicant): The long-term goals of this research are to quantify patient-specific changes in neuromuscular control in order to optimize treatment planning and improve mobility for individuals with cerebral palsy (CP). As a first step, the aims of this proposl are to evaluate neuromuscular control before and after one of the most common treatments for individuals with CP, orthopaedic surgery. We will evaluate if patient-specific measures of neuromuscular control, based upon the framework of muscle synergies, can predict improvements in walking ability after surgery. Further, we will determine whether neuromuscular control changes after surgery and if these changes contribute to improvements in movement. To achieve these goals we will implement and test new tools to quantify neuromuscular control which integrate clinical gait analysis and two computational techniques: synergy analysis and dynamic musculoskeletal simulation. Our prior research has demonstrated that individuals with CP use fewer synergies during gait than unimpaired individuals and that synergies are associated with changes in walking ability after a variety of treatments. In Aim 1, we will prospectively evaluate if synergies predict outcomes after orthopaedic surgery. In Aim 2, we will evaluate the adaptability of synergies by evaluating whether synergies change after orthopaedic surgery. In Aim 3 we will use musculoskeletal simulation to evaluate how altered synergies impact muscle recruitment, impaired movement, and energy costs of walking for three of the most common pathologic gait patterns in CP: crouch gait, stiff-knee gait, and equinus gait. Musculoskeletal simulation provides a unique tool to probe patient-specific changes in neuromuscular control because we can specify and evaluate different control strategies and impairments in silico. For example, we can use a patient's experimentally measured kinematics and kinetics from clinical gait analysis to simulate their specific gait pattern and examine the impact of different control strategies. We will use a new algorithm we developed in OpenSim, an open-source platform for musculoskeletal modeling, to create simulations with synergy-based control. The outcomes of this research will quantify changes in neuromuscular control in CP and evaluate the clinical utility of synergy analysis. This research will provide the foundation to use measures of altered neuromuscular control to inform treatment planning, develop alternative treatments, and improve mobility in CP and other neurologic disorders.