Non-invasive assessment of ligament healing in vivo

描述(申请人提供)：该项目的总体目标是系统地改进和验证我们新的磁共振成像方案，用于非侵入性测量愈合软组织的生物力学特性。这一翻译工具将有利于临床前和临床试验，以评估未来的韧带和肌腱修复技术。在本研究中，我们将重点研究前交叉韧带(ACL)作为韧带损伤的模型。我们已经证明，韧带大小(即组织数量)和信号强度(即组织质量)的磁共振成像测量与前交叉韧带的生物力学特性相关，而韧带大小和信号强度的组合进一步改善了这些预测。不幸的是，信号强度取决于图像采集参数，因此取决于协议、磁铁，因此依赖于机构。然而，T2*弛豫时间是一种MR组织特性，它与组织中的胶原组织相关，而不是依赖于获取。我们现在有初步证据表明，愈合韧带内的T2*松弛时间提供了更可靠的结构属性估计。下一步是改进和验证这种基于T2*MR的预测方法，用于韧带愈合的纵向研究。在目标1中，我们将在两种修复策略下获得正在愈合的前交叉韧带的体积和T2*的MR测量。这些措施将收集在愈合的早期、中期和后期重塑阶段的横断面研究中，以检查该模型对这些愈合阶段的生物力学特性的预测能力，并在必要时将时间效应纳入模型中。在目标2中，我们将对我们基于MR的方法进行纵向研究，以验证其在区分两种已知在愈合方面产生差异的修复策略方面的有效性，并确定在愈合的早期阶段获得的扫描是否可以预测较长期的生物力学特性。这一发现将非常有价值，因为它将减少临床前和临床韧带愈合研究的周期时间。该项目将利用 我们完善的生物增强前交叉韧带修复的临床前模型。在这项研究中，我们的基于MR的多元回归预测模型将在目标1中得到改进，并在目标2中得到验证。主要的结果测量包括MR参数(T2*松弛时间、信号强度、体积)和愈合前交叉韧带的结构特性(失效负荷、线刚度)。次要结果包括前交叉韧带材料特性(破坏应力、切线弹性系数)和膝关节松弛。在研究完成后，我们将完善我们基于MR的预测模型，验证其在外科修复研究中的应用，并准备将MR技术用作前交叉韧带修复和重建临床试验的主要结果衡量标准。

DESCRIPTION (provided by applicant): The overall objective of this project is to systematically refine and validate our novel magnetic resonance imaging protocol for the non-invasive measurement of the biomechanical properties of healing soft tissues. This translational tool will be advantageous for pre-clinical and clinical trials to evaluate up-and-coming technologies for ligament and tendon repair. For this study we will focus on the anterior cruciate ligament (ACL) as a model of ligament injury. We have shown that magnetic resonance (MR) imaging measurements of ligament size (i.e., amount of tissue) and signal intensity (i.e., quality of tissue) correlate to the biomechanical properties of the ACL, and that the combination of ligament size and signal intensity further improved these predictions. Unfortunately, signal intensity is dependent on image acquisition parameters thus protocol, magnet, and hence institution dependent. However, T2* relaxation time is an MR tissue property that correlates to collagen organization in tissues that is not as acquisition dependent. We now have preliminary evidence to show that T2* relaxation times within a healing ligament provides a more reliable estimate of the structural properties. The next step is to refine and validate this T2* MR-based prediction method for use in longitudinal studies of ligament healing. In Aim 1, we will obtain MR-measures of volume and T2* of the healing ACL following two repair strategies. These measures will be collected in the early proliferative, middle and later remodeling stages of healing in a cross sectional study to examine how robustly the model predicts the biomechanical properties across these stages of healing, and to incorporate time effects into the model if necessary. In Aim 2, we will perform a longitudinal study of our MR-based approach to validate its utility for discriminating between two repair strategies known to produce differences in healing and to determine if scans obtained in the early stages of healing will predict the longer-term biomechanical properties. This finding would be very valuable as it would reduce the cycle time of both pre-clinical and clinical ligament healing studies. The project will take advantage of our well established pre-clinical model of bio-enhanced ACL repair. In this study, our MR based multi-regression prediction model will be refined in Aim 1 and validated in Aim 2. Primary outcome measures include the MR parameters (T2* relaxation time, signal intensity, volume) and the structural properties (failure load, linear stiffness) of the healing ACL. Secondary outcomes include the ACL material properties (failure stress, tangent modulus) and knee laxity. At study completion we will have refined our MR- based prediction models, validated its use for surgical repair studies, and be poised to use the MR technique as a primary outcome measure in clinical trials of ACL repair and reconstruction.