Biomechanics of Spine Fracture

脊柱骨折的生物力学

• 批准号: 6954135
• 负责人: Tony M Keaveny
• 金额: $ 57.4万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-28 至 2008-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6954135
• 关键词: bioimaging /biomedical imaging; biomechanics; bone density; bone fracture; bone imaging /visualization /scanning; computed axial tomography; disease /disorder proneness /risk; human tissue; image processing; mechanical stress; osteoporosis; photon absorptiometry; physical model; postmortem; spine disorder; vertebrae

DESCRIPTION (provided by applicant): Vertebral osteoporosis is a major health concern both in the United States and worldwide, and is expected to affect substantially more people as the size of the aging population increases. Currently, the clinical gold standard for assessment of fracture risk for the spine is dual-energy x-ray absorptiometry (DXA). This two-dimensional scanning modality is limited in its ability to predict fracture risk, and improved methods of fracture risk prediction are therefore needed. Quantitative computed tomography (QCT), being a three-dimensional imaging modality, offers great promise at providing such improved measures, but the complexity of the underlying biomechanics of spine fractures undermines the ability of QCT alone to predict fracture risk. In particular, the vertebral body displays different strength properties for the different types of loads it encounters in vivo, such as compression vs. anterior bending. QCT scans, being descriptors of only the bone structure, cannot account for these different strengths. Recent advances in bone biomechanics and computational stress analysis techniques now enable us to produce patient-specific structural computer finite element models of an individual's vertebra directly from QCT scans in an almost entirely automated fashion. Ideally suited for clinical implementation, these "voxer' finite element models can provide a fracture risk prediction that overcomes the limitations associated with DXA and QCT. Through an unique multidisciplinary team of bioengineers, clinical QCT radiological experts, and epidemiologists, we plan to implement this computational modeling technique clinically and compare its performance against DXA and QCT. In particular, we will test its ability to predict fracture risk in an ongoing NIH-funded osteoporosis prospective fracture surveillance study of almost 6000 men aged over 65, for which both DXA and QCT scans are available at baseline. To ensure that our modeling technique is optimized for successful clinical usage, we will first perform a detailed biomechanical validation of the technique as applied to cadaver vertebrae for varied loading conditions, including compression and combined compression/forward bending. We will also address the role of the posterior elements, and treat the disc condition as an uncertainty variable. Our Hypothesis is that the QCT-based finite element modeling technique, being mechanistic, is better at clinical fracture risk prediction than purely densitometric techniques such as DXA and QCT. This research will provide insight into the biomechanical mechanisms of osteoporotic spine fractures by way of our cadaver studies. It will have profound clinical impact by improving substantially the ability to predict risk of vertebral fracture in the elderly. Finally, we hope this research will instigate a paradigm change in musculoskeletal imaging in which engineering mechanistic models are integrated into medical images to provide a true functional image, in this case the "biomechanical scan" of the vertebra.

描述（由申请人提供）： 椎体骨质疏松症是美国和世界范围内的一个主要健康问题，随着老龄化人口规模的增加，预计将影响更多的人。目前，评估脊柱骨折风险的临床金标准是双能X射线吸收测定法（DXA）。这种二维扫描方式预测骨折风险的能力有限，因此需要改进的骨折风险预测方法。定量计算机断层扫描 (QCT) 作为一种三维成像方式，在提供此类改进措施方面前景广阔，但脊柱骨折的基础生物力学的复杂性削弱了 QCT 单独预测骨折风险的能力。特别是，椎体对于其在体内遇到的不同类型的负载表现出不同的强度特性，例如压缩与前弯曲。 QCT 扫描仅描述骨骼结构，无法解释这些不同的强度。骨生物力学和计算应力分析技术的最新进展现在使我们能够以几乎完全自动化的方式直接根据 QCT 扫描生成患者特定的椎骨结构计算机有限元模型。这些“voxer”有限元模型非常适合临床实施，可以提供骨折风险预测，克服 DXA 和 QCT 相关的局限性。通过由生物工程师、临床 QCT 放射学专家和流行病学家组成的独特多学科团队，我们计划实施这一计划我们将在 NIH 资助的一项正在进行的近 6000 例骨质疏松症前瞻性骨折监测研究中测试其预测骨折风险的能力。 65 岁以上的男性，其基线可进行 DXA 和 QCT 扫描，为了确保我们的建模技术针对成功的临床使用进行优化，我们将首先对该技术在不同负载条件下应用于尸体椎骨进行详细的生物力学验证。 ，包括压缩和组合压缩/向前弯曲，我们还将讨论后部元件的作用，并将椎间盘状况视为不确定变量。我们的假设是，基于 QCT 的有限元建模技术是机械性的，比 DXA 和 QCT 等纯粹的密度测量技术更适合临床骨折风险预测。这项研究将通过我们的尸体研究来深入了解骨质疏松性脊柱骨折的生物力学机制。它将大幅提高预测老年人椎骨骨折风险的能力，从而产生深远的临床影响。最后，我们希望这项研究将引发肌肉骨骼成像的范式变革，将工程机械模型集成到医学图像中，以提供真实的功能图像，在本例中是椎骨的“生物力学扫描”。