Non-invasive assessment of ligament healing in vivo

体内韧带愈合的无创评估

• 批准号: 8928046
• 负责人: Braden C Fleming
• 金额: $ 56.98万
• 依托单位: RHODE ISLAND HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-16 至 2017-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8928046
• 关键词: Animal Model; Animals; Anterior Cruciate Ligament; Biomechanics; Biopsy; Blood; Clinical; Clinical Trials; Collagen; Cross-Sectional Studies; Data; Failure; Future; Goals; Healed; Health; Image; Imaging Techniques; Individual; Injury; Institution; Knee; Ligaments; Longitudinal Studies; Magnetic Resonance; Magnetic Resonance Imaging; Maps; Measurement; Measures; Mechanics; Methods; Miniature Swine; Modeling; Operative Surgical Procedures; Outcome; Outcome Measure; Patients; Performance; Phase; Physicians; Plague; Pre-Clinical Model; Process; Property; Protocols documentation; Rehabilitation therapy; Relaxation; Research Personnel; Scanning; Signal Transduction; Site; Staging; Stress; Structural Models; Structure; Surgical sutures; Techniques; Technology; Tendon structure; Testing; Time; Tissue Sample; Tissues; anterior cruciate ligament healing; anterior cruciate ligament reconstruction; base; design; healing; improved; in vivo; injury and repair; interest; ligament injury; new technology; novel; pre-clinical; primary outcome; reconstruction; repaired; research study; scaffold; secondary outcome; soft tissue; tissue repair; tool; treatment strategy

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.

描述（由申请人提供）：该项目的总体目的是系统地完善和验证我们的新型磁共振成像方案，以对愈合软组织的生物力学特性进行非侵入性测量。该翻译工具对于临床前和临床试验将是有利的，以评估韧带和肌腱修复的新兴技术。在这项研究中，我们将重点介绍前交叉韧带（ACL）作为韧带损伤的模型。我们已经表明，磁共振（MR）成像测量的韧带大小（即组织量）和信号强度（即组织质量）与ACL的生物力学特性以及韧带大小和信号强度的组合相关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，因此协议，磁铁及其依赖机构。然而，T2*松弛时间是MR组织特性，它与组织中胶原蛋白组织相关的，而不是依赖于获取。现在，我们有初步证据表明，愈合韧带内的T2*放松时间提供了对结构特性的更可靠的估计。下一步是完善和验证这种基于T2*的基于T2*的预测方法，用于用于韧带愈合的纵向研究。在AIM 1中，我们将在两种维修策略之后获得ACL的体积和T2*的MR测量。这些措施将在横截面研究中的早期增殖，中间和后来的愈合阶段收集，以检查模型如何预测这些疗法这些阶段的生物力学特性，并在必要时将时间效应纳入模型。在AIM 2中，我们将对基于MR的方法进行纵向研究，以验证其效用以区分已知的两种修复策略，这些修复策略已知会产生愈合差异，并确定在愈合的早期阶段获得的扫描是否会预测长期生物力学特性。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 我们建立的生物增强ACL修复的临床前模型。在这项研究中，我们的基于MR的多回归预测模型将在AIM 1中进行完善，并在AIM 2中进行验证。主要结果度量包括MR参数（T2*放松时间，信号强度，体积）和结构性特性（故障负载，失败负载，愈合ACL的线性刚度）。次要结果包括ACL材料特性（故障应力，切线模量）和膝盖松弛。在研究完成时，我们将完善基于MR的预测模型，验证了其在手术修复研究中的用途，并准备将MR技术用作ACL修复和重建的临床试验中的主要结果度量。