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

项目概要/摘要 脊椎骨折是脊椎骨骨折最常见的类型。脊柱也是最常见的部位， 骨转移导致病理性脊椎骨折虽然进行日常生活活动是一种 健康老龄化的重要组成部分，病理性和非病理性椎骨骨折可能发生在这些 转移性或骨质疏松性脊柱中的活动。这些骨折会引起疼痛和神经症状， 影响生活质量。目前，没有客观的临床技术可以评估骨折风险 与身体活动有关。为了填补差距，我们提出了一种患者特异性计算技术， 定量评估与体力活动相关的脊柱损伤风险。这种新方法将使 临床医生向老年人推荐安全和个性化的活动。因此我们 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。 这些数据将用作尸体腰椎的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。本项目的基本原理是， 一个可以模拟身体活动的过程将能够减少脊椎骨折，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，以便更早地实现 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 应用，是开发一种基于有限元分析的患者特异性定量计算机断层扫描 (QCT/FEA）方法，该方法可以评估脊柱的运动学运动和骨折特征， 估计身体活动的骨折风险。为了实现总体目标，以下三个独立的 具体目标是：1）获得腰椎活动范围和肌肉反应结果， 老年患者人群在五种身体运动期间; 2）对尸体脊柱进行运动学测试 测量椎间盘内压力-使用一种新的方法-在身体运动期间;以及机械 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 腰椎的QCT/FEA模型，以估计脊柱损伤风险。 这项研究将导致发展 一种计算工具，可以分配与身体活动相关的风险评分。 此外，这项工作将 为未来的R 01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.