A patient-specific computational technique to predict spine injury risks associated with physical activities

项目摘要/摘要 椎体骨折是骨质疏松性骨折中最常见的一种。脊椎也是最常见的 骨转移，导致病理性脊椎骨折。而进行日常生活活动则是一种 在这些过程中，病理性和非病理性椎体骨折可能是健康衰老的重要组成部分 转移或骨质疏松脊椎的活动。这些骨折会引起疼痛和神经症状， 影响生活质量。目前，还没有客观的临床技术可以评估骨折的风险。 与身体活动相关的。为了填补这一空白，我们提出了一种针对患者的计算技术 定量评估与体力活动相关的脊柱损伤风险。这一新颖的方法将使 临床医生可靠地向老年人群推荐安全和个性化的活动。为了实现这一目标，我们 将使用视频运动分析从老年患者队列中获得运动和肌肉活动结果。 这些数据将被用作身体腰椎运动学运动分析和力学测试的输入 脊椎，来创建和验证我们的计算模型。这个项目的基本原理是QCT/FEA 可以模拟身体活动的过程将能够减少脊柱骨折并提高生活质量 老年患者群体。我们的长期目标是开发可靠的计算技术，以便更早地 老年肌肉骨骼疾病患者的损伤风险预测。我们的总体目标，在这方面 应用，是开发一种针对患者的基于计算机断层扫描的定量有限元分析 (QCT/FEA)方法，可以评估脊柱的运动学运动和骨折特征，以 评估体育活动的骨折风险。为实现总体目标，以下三个独立 具体目标将实现：1)获得腰椎活动范围和肌肉反应结果 老年患者在五次运动中的人群；2)对身体脊柱进行运动学测试 使用一种新的方法测量物理运动过程中的盘内压力；以及机械运动中的压力 对脊柱节段进行测试，以测量骨折时的椎间盘内压力；以及3)开发和验证 腰椎QCT/FEA模型以评估脊柱损伤风险。 这项研究将会引领这一领域的发展。 一种可以分配与体力活动相关的风险分数的计算工具。 此外，这项工作将 为未来的R01拨款提案提供初步数据，以预测与物理相关的骨折风险 患者群体中的运动和锻炼。

PROJECT SUMMARY/ABSTRACT Vertebral fracture is the most common type of osteoporotic fracture. Spine is also the most common site of bone metastasis, leading to pathologic vertebral fractures. While performing activities of daily living is an essential part of healthy aging, pathologic and non-pathologic vertebral fractures can occur during these activities in metastatic or osteoporotic spines. These fractures cause pain and neurologic manifestations, affecting quality of life. Currently, there is no objective clinical technique that can assess bone fracture risks associated with physical activities. To fill the gap, we propose a patient-specific computational technique to quantitatively evaluate spine injury risks associated with physical activities. This novel approach will enable clinicians to reliably recommend safe and individualized activities to elderly populations. To achieve this, we will obtain motions and muscle activity outcomes from an elderly patient cohort using video motion analysis. These data will be used as input for kinematic motion analyses and mechanical testing on cadaveric lumbar spines, to create and validate our computational models. The rationale for this project is that a QCT/FEA process that can mimic physical activities will be able to reduce vertebral fractures and improve quality of life in elderly patient populations. Our long-term goal is to develop reliable computational techniques to enable earlier injury risk predictions in elderly patients with musculoskeletal diseases. Our overall objective, in this application, is to develop a patient-specific quantitative computed tomography-based finite element analysis (QCT/FEA) method that can assess both kinematic motions and fracture characteristics of the spine, to estimate fracture risks of physical activities. To achieve the overall objective, the following three independent specific aims will be accomplished: 1) to obtain lumbar range of motion and muscle response outcomes in an elderly patient population during five physical movements; 2) to perform kinematic testing on cadaveric spines to measure intradiscal pressures –using a novel approach– during physical movements; and also mechanical testing on spine segments to measure intradiscal pressure at fracture; and 3) to develop and validate QCT/FEA models of the lumbar spine to estimate spine injury risks. This research will lead to the development of a computational tool that can assign a risk score associated with physical activities. Further, this work will provide preliminary data for future R01 grant proposals to predict fracture risks associated with physical movements and exercises in patient populations.