Advanced MRI of Spinal Cord Injury

基本原理和初步数据：我们将进行一项人类脊髓损伤（SCI）的研究，以验证MRI 损伤严重程度的生物标志物和使用新的扩散MRI技术开发的结果的说明 专门用来检测脊髓的轴突损伤预测SCI的结果一直是一个长期的目标 用于更好的临床管理和帮助开发和测试治疗。传统神经病学 常规MRI，包括T2加权成像， 虽然可用于诊断，但不能准确预测恢复程度。扩散张量成像（DTI） 已显示出作为SCI预后影像学生物标志物的前景，但其临床应用受到以下因素的阻碍： 技术挑战和对潜在病理学的非特异性。我们在大鼠SCI模型中的临床前研究 已经证明双扩散编码（DDE）MRI对急性轴突损伤敏感，并预测 准确性优于DTI或传统功能评分。同样， 我们的合作小组已经证明了在金属外科手术附近使用扩散对比的能力， 硬件，容易产生伪影。虽然有希望，但这些技术的验证同时 提高对比度和质量对于推进该技术并确保其在人类受试者中的实用性至关重要， 临床环境。本项目将翻译这些技术，以促进对DTI变化的理解 作为受伤的标志我们的假设是：1）在急性情况下，DDE估计急性轴突损伤 损伤将预测长期功能结局，2）在慢性环境中，DDE估计永久性 轴突损失将与现有的功能结果相关。据预测，DDE将优于DTI， 常规MRI或SCI中的功能神经学检查。为了验证这一假设，我们将进行体内MRI 创伤性脊髓损伤后急性期的功能评估。在目标1中，我们将检查 通过随访功能评估，DDE预测后期神经功能恢复的预后能力。在Aim中 2，我们将详细说明DDE测量的轴突损失（保留）与永久神经功能之间的联系 SCI之后这些研究试图建立和验证DDE作为损伤严重程度和结果的替代指标 并与现有的SCI临床标准和MRI指标进行比较。我们假设 基于强有力的临床前结果，使用DDE检测微结构损伤将更准确地反映 神经功能损害的程度比MRI技术非特异性的基础病理学。的潜力 DDE突出了临床翻译，它是一种仅需几分钟的快速采集， 用于定量的后处理或事后分析。此外，DDE使可视化的程度 在个体受试者中的损伤，使其有望用于SCI患者的临床管理。总的来说，这些 研究将建立并验证DDE作为SCI的生物标志物，并有可能改善SCI的诊断。 人类脊髓损伤

Rationale and Preliminary Data: We will conduct a study of human spinal cord injury (SCI) to validate MRI biomarkers of injury severity and prognostication of outcome using a novel diffusion MRI technique developed specifically to detect axonal injury in the spinal cord. Predicting outcome from SCI has been a longstanding goal for better clinical management and aiding in the development and testing of therapies. Traditional neurological examination is not an accurate predictor of outcome, and conventional MRI, including T2-weighted imaging, while useful for diagnosis, does not accurately predict the degree of recovery. Diffusion tensor imaging (DTI) has shown promise as a prognostic imaging biomarker in SCI, but its clinical adoption has been hindered by technical challenges and non-specificity to the underlying pathology. Our preclinical studies in a rat SCI model have demonstrated that double diffusion encoding (DDE) MRI is sensitive to acute axonal injury and predicts outcome with accuracy better than either DTI or traditional functional scoring. Likewise, recent developments by our collaborative group have demonstrated the ability to employ diffusion contrast adjacent to metal surgical hardware, which is prone to artifacts. While promising, validation of these technologies to simultaneously improve contrast and quality is critical to advance the technology and ensure its utility in human subjects and clinical settings. This project will translate these techniques to advance the understanding of the DTI changes in the cord as markers of injury. Our hypotheses are 1) in the acute setting, DDE estimates of acute axonal injury will predict long-term functional outcomes, and 2) in the chronic setting, DDE estimates of permanent axonal loss will correlate with existing functional outcomes. It is predicted that DDE will outperform DTI, conventional MRI, or functional neurological exams in SCI. To test this hypothesis, we will perform in vivo MRI and functional assessments in the acute phase after traumatic spinal cord injury. In Aim 1, we will examine the prognostic ability of DDE to predict later neurological recovery using follow-up functional assessments. In Aim 2, we will detail the link between axonal loss (sparing) as measured by DDE and permanent neurological function after SCI. These studies seek to establish and validate DDE as a surrogate maker of injury severity and outcome and compare it with existing clinical standards and established MRI indicators of SCI. We hypothesize based on strong preclinical results that detection of microstructural injury using DDE will more accurately reflect the degree of neurological impairment than MRI techniques non-specific to underlying pathology. The potential for clinical translation is highlighted by DDE being a rapid acquisition of only a few minutes and requires minimal post-processing or post-hoc analysis for quantification. Moreover, DDE enables visualization of the degree of injury in individual subjects, making it promising for clinical management of SCI patients. Collectively, these studies will establish and validate DDE as a biomarker of SCI with the potential to improve prognostication in human SCI.