Advanced MRI of Spinal Cord Injury

理论基础和初步数据：我们将对人类脊髓损伤(SCI)进行研究，以验证MRI的有效性 应用一种新的扩散磁共振成像技术检测损伤严重程度和预测预后的生物标志物 特别是为了检测脊髓中的轴突损伤。预测脊髓损伤的结果一直是一个长期的目标。 以便更好地进行临床管理并协助开发和测试治疗方法。传统神经病学 检查并不能准确预测结果，而常规MRI，包括T2加权成像， 虽然对诊断有用，但不能准确预测恢复的程度。扩散张量成像(DTI) 已经显示出作为脊髓损伤预后成像生物标记物的前景，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的非特异性。我们在大鼠脊髓损伤模型中的临床前研究 已证明双扩散编码(DDE)MRI对急性轴索损伤敏感并可预测 结果与DTI或传统功能评分相比，准确性更高。同样，最近的事态发展 由我们的协作小组展示了在金属手术附近使用弥散对比的能力 硬件，这很容易产生伪影。虽然前景看好，但这些技术的验证将同时 提高对比度和质量是推进这项技术并确保其在人类受试者和 临床环境。该项目将翻译这些技术，以促进对DTI更改的理解 在脐带上作为损伤的标志。我们的假设是：1)在急性背景下，急性轴索的DDE估计 损伤将预测长期的功能结果，以及2)在慢性环境中，DDE估计的永久性 轴突丢失将与现有的功能结果相关。据预测，DDE的表现将优于DTI， 常规核磁共振，或脊髓损伤的功能神经学检查。为了验证这一假设，我们将在体内进行核磁共振 以及创伤性脊髓损伤后急性期的功能评估。在目标1中，我们将研究 DDE通过后续功能评估预测神经功能恢复的能力。在AIM 2，我们将详细说明DDE测量的轴突丢失(Sparing)与永久性神经功能之间的联系 在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 并与现有的临床标准和已确立的脊髓损伤MRI指标进行比较。我们假设是基于 根据强大的临床前结果，使用DDE检测微结构损伤将更准确地反映 神经损害的程度比MRI技术对潜在病理的非特异性。潜在的 临床翻译的突出特点是DDE只需几分钟即可快速获得，并且所需时间最少 用于量化的后处理或后处理分析。此外，DDE使可视化程度成为可能 单个受试者的损伤，使其在脊髓损伤患者的临床治疗中具有良好的前景。总而言之，这些 研究将建立和验证DDE作为脊髓损伤的生物标志物，具有改善预后的潜力 人体SCI。

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.