3-D Visualization and Prediction of Spine Fractures

椎体骨折是骨质疏松性骨折中最常见的一种，大约三分之一的患者会受到影响。 女性和六分之一的男性年龄在50岁以上。尽管其流行率很高，但敏感和具体的估计 脊椎骨折风险的预测仍然难以捉摸。这在很大程度上是由于精确度和精密度有限。 目前估计脊椎强度的方法。骨密度(BMD)的平均测量解释 只有50%-70%的脊椎强度差异，考虑到异质性，这个结果并不令人惊讶 骨组织在整个椎骨中的分布。越来越多令人信服的证据表明 这种异质性在控制椎骨的力学行为方面的重要性。的最新进展 定量计算机断层扫描(QCT)允许非侵入性测量骨密度分布 甚至整个骨骼的骨小梁各向异性。我们建议可以使用这些额外的测量方法 目的：建立脊柱骨折危险性的临床评估新标准。我们的总体假设是CT- 基于密度和骨小梁各向异性非均匀分布的方法 与单纯基于平均值的方法相比，椎骨提供了更准确的椎体强度预测 骨密度。提出了四个具体目标。目标1将测试基于CT的椎体内测量 密度的异质性是椎体强度的独立预测因子。目标#2-#4紧密相连 实验和计算研究将测试结合特定样本的重要性， 基于QCT的椎骨有限元(FE)模型中的各向异性材料特性。这些研究将 研究这种材料特性分配对椎体有限元预测准确性的影响 强度和破坏行为。目标2将使用微观有限元分析来量化各向异性弹性 整个椎体的财产。目标3将使用材料进行基于QCT的有限元分析 在目标#2中获得的属性以及也使用纯粹基于BMD或基于 骨密度和骨小梁各向异性。椎体力学行为的有限元预测的准确性将是 通过在目标4中执行的实验进行评估。这些实验将使用3-D故障可视化 我们在过去几年里开发的技术。这些技术为我们提供了独特的能力 为了评估有限元模型预测骨强度和真实变形的保真度，以及 椎骨的破坏行为。这样的评估对于衡量这些模型的性能至关重要，例如 确定改进其预测的方法，并使其能够在 临床领域。综上所述，拟议的研究构成了一套具体和相应的步骤 我们的长期目标是开发高度准确的、针对患者的预测技术 来自临床可行测量的脊椎强度。因此，这项工作具有很强的潜力，可以引领 如何更好地诊断、治疗和预防脊柱骨折。1/3的女性和1/6的男性在50岁以上会遭受脊柱骨折。 余生。这个项目的重点是开发方法，以获得更准确的 对脊椎骨骼强度的预测。

Vertebral fractures are the most common type of osteoporotic fracture, afflicting approximately one in three women and one in six men over the age of 50. Despite their high prevalence, sensitive and specific estimates of vertebral fracture risk have remained elusive. This is due in large part to the limited accuracy and precision of current methods of estimating vertebral strength. Average measures of bone mineral density (BMD) explain only 50-70% of the variance in vertebral strength, a result that is not surprising given the heterogeneous distribution of bone tissue throughout the vertebra. A growing and compelling amount of evidence points to importance of this heterogeneity in governing the mechanical behavior of the vertebra. Recent advances in quantitative computed tomography (QCT) allow non-invasive measurement of the distribution of bone density and even trabecular anisotropy in whole bones. We propose that these additional measurements can be used to establish a new standard for clinical evaluation of vertebral fracture risk. Our overall hypothesis is that CT- based methods that account for the heterogeneous distribution of density and trabecular anisotropy throughout the vertebra provide more accurate predictions of vertebral strength than do methods based solely on average BMD. Four specific aims are proposed. Aim #1 will test whether CT-based measures of the intra-vertebral heterogeneity in density are independent predictors of vertebral strength. Aims #2-#4 are closely coupled experimental and computational studies that will test the importance of incorporating specimen-specific, anisotropic material properties in QCT-based finite element (FE) models of the vertebra. These studies will investigate the effect of this material property assignment on the accuracy of the FE predictions of vertebral strength and failure behavior. Aim #2 will use micro-finite element analysis to quantify the anisotropic elastic properties throughout the centrum. Aim #3 will carry out the QCT-based FE analyses using the material properties obtained in Aim #2 and also using properties determined purely from estimates based on BMD or on BMD and trabecular anisotropy. The accuracy of the FE predictions of vertebral mechanical behavior will be evaluated through experiments performed in Aim #4. These experiments will use 3-D failure visualization techniques that we have developed over the past several years. These techniques afford us the unique ability to assess the fidelity with which the FE models predict bone strength as well as the true deformation and failure behavior of the vertebra. Such assessment is critical for gauging the performance of these models, for identifying means of improving their predictions, and for enabling their widespread implementation in the clinical arena. Taken together, the proposed studies constitute a set of concrete and consequential steps towards our long-term goal of developing techniques for highly accurate, patient-specific predictions of vertebral strength from clinically feasible measurements. As such, this work has strong potential for leading the way to better diagnosis, treatment, and prevention of spine fractures. One in three women and one in six men over age 50 will suffer a spine fracture in their remaining lifetime. This project focuses on developing methods for obtaining more accurate predictions of bone strength in the spine.