Strain and Bone Fracture Healing: Image-Based Mechanics Models to Redefine the Rules

项目摘要 本研究的长期目标是了解影响骨折愈合的力学因素 在大型动物和人类身上。在骨骼愈合的早期阶段，骨折的碎片可以移动 相对于彼此。这些微小的运动拉伸了参与早期骨折修复的软组织， 产生一种称为应变的机械效应。自20世纪70年代以来，应变与生物学密切相关 骨折修复，但在骨愈合的背景下解释应变的概念框架还没有 进化了四十年。今天，整形外科医生敏锐地意识到，应变调节骨折愈合， 但他们无法在病人身上测量。权威的临床教科书充斥着不具体的，令人担忧的， 和不切实际的建议，关于在恶劣的应变环境下固定骨折的风险。由于没有明确的 在指导下，外科医生学会依靠生物力学的经验法则来选择正确的植入物， 骨折的类型。几十年来，关于应变和骨愈合的混合信息和间接讨论， 在临床培训和植入物设计方面的创新造成了重大障碍。现在有一个主要的未满足的需求 开发创新的新研究工具，可以提供关于机械应变如何调节骨骼的见解 治愈为了满足这一需求，我们将汇集一套复杂的基于物理的模型和图像， 分析技术做什么一直是不可能的，直到现在：直接评估应变在组织水平，并显示 它与骨折愈合过程的关系。这项研究有两个技术目标。第一个目标，我们 将使用微型计算机断层扫描（µCT）扫描来创建绵羊胫骨的3D虚拟重建 骨折在手术后愈合我们将模拟骨骼上的步态诱导载荷，并使用模型来 测量骨折线内和周围的应变。从模型测量的应变将在空间上与 将确定新骨形成和容许应变的阈值。在第二个目标中，重点将 发生在愈合骨折附近的旧骨中的适应性变化。基于图像的模型将再次 用于测量应变，但现在将使用来自图像的高分辨率数据的空间互相关来测量应变。 评估旧骨外表面的应变是否与骨矿物质的内部损失有关 与受伤前相比。该项目的结果将为一个新的范例铺平道路， 思考应变和骨愈合。虽然我们将研究羊， 为该项目开发的药物在临床研究中具有很高的转化潜力。相同类型的 建模和图像数据挖掘技术可用于研究人类患者的骨折愈合。这将 最终有助于改善复杂骨折治疗的临床决策， 在外科医生中，对于骨折愈合的生物力学最佳应变是多少存在相当大的争论。

PROJECT SUMMARY The long-term goal of this research is to understand the mechanical factors that influence bone fracture healing in large animals and humans. In the early stages of bone healing, the fragments of a broken bone can move relative to one another. These small movements stretch the soft tissues that are involved in early fracture repair, producing a mechanical effect known as strain. Since the 1970s, strain has been strongly linked with the biology of fracture repair, but the conceptual framework for explaining strain in the context of bone healing has not evolved in four decades. Today, orthopaedic surgeons are keenly aware that strain regulates fracture healing, but they cannot measure it in their patients. Authoritative clinical textbooks are riddled with nonspecific, alarming, and impractical advice about the risks of fixing a fracture with a bad strain environment. In the absence of clear guidance, surgeons learn to rely on biomechanical rules of thumb for how to select the right implant for certain types of fractures. Decades of mixed messaging and indirect discussion about strain and bone healing have created significant barriers to innovation in clinical training and implant design. There is now a major unmet need to develop innovative new research tools that can provide insights on how mechanical strain regulates bone healing. To address this need, we will bring together a suite of sophisticated physics-based models and image analysis techniques to do what has been impossible until now: directly assess strain at the tissue level and show its association with the processes of fracture healing. This research has two technical aims. For the first aim, we will use micro-computed tomography (µCT) scans to create 3D virtual reconstructions of the shinbones of sheep with fractures that healed after surgery. We will simulate gait-induced loads on the bones and use the models to measure strain in and around the fracture line. Strain measured from the models will be spatially correlated with the new bone formation and a threshold for allowable strain will be determined. In the second aim, the focus will be on adaptive changes that occur in old bone near a healing fracture. The image-based models will again be used to measure strain, but now spatial cross-correlation of high-resolution data from the images will be used to assess whether strain on the outer surface of the old bone is associated with an internal loss of bone mineral density compared to before the injury. The results from this project will pave the way for a new paradigm of thinking about strain and bone healing. Although we will be studying sheep, the groundbreaking methodologies developed for this project have high translational potential for use in clinical research. The same types of modeling and image data-mining techniques could be used to study fracture healing in human patients. This will ultimately help improve clinical decision-making for treatment of complex fractures, where there is still considerable debate among surgeons about how much strain is biomechanically optimal for fracture healing.