Quantitative Sodium MR Imaging and Proton MR Spectroscopy in Traumatic Brain Injury

项目摘要 创伤性脑损伤（TBI）是世界上年轻人神经系统残疾的主要原因， 中年人口。计算机断层扫描（CT）和磁共振成像（MRI）在 由于临床相关但影像学上隐匿的损伤的广泛存在，患者管理受到限制。 我们提出了从钠（23 Na）MRI和质子MR获得的TBI损伤的新指标 波谱（1H MRS）。中心假设是联合23 Na MRI/1H MRS将提供 离子稳态丧失和神经退行性变的代谢成像标记物， 患者的长期临床结果。钠MRI是一种基于直接检测的非侵入性模式， 使用专用MRI软件和硬件测量Na+离子。它可以评估Na+稳态的丧失， 受到离子不平衡的过程的干扰，离子不平衡是细胞损伤级联背后的驱动力。的 Na+/K+交换泵可受到由于线粒体功能障碍引起的能量缺乏的影响，以及 弥漫性轴索损伤，TBI的组织病理学特征。这将导致细胞内 钠浓度（C1），而炎症，神经胶质增生和细胞损失将反映在变化的钠浓度（C1）， 细胞外容积分数（α 2）。我们建议将23 Na度量C1和α 2与1H结合联合收割机 MRS，其中定量N-乙酰天冬氨酸（NAA）、肌酸（Cr）、胆碱（Cho）和肌醇（mI） 可用于推断神经元健康/密度（NAA）、细胞能量/密度（Cr）、膜更新（Cho）和 星形胶质细胞活化（MI）。具体目标是：目标1：方法。(1.a)优化超短回波时间23 Na 在3 T下进行有和无液体抑制的MRI。为了优化图像重建， 压缩传感以提高信噪比、分辨率和采集速度。开发C1和 基于23 Na自旋动力学模拟和参考模型的α 2定量。(1.b)实施 全脑1H MRS采集，4阶匀场。目的2：临床应用。(2.a)比较C1 TBI患者和对照组在基线（TBI后≤10天）和α 2的变化率以及它们随时间的变化率（2- 10天）。 TBI随访1个月和1年，对照组随访1年），校正MRI（FLAIR、SWI、DTI）和1H 夫人(2.b)将MR指标的基线值及其随时间的变化率与临床 两次随访的结果。评估C1和α 2对MRI和1H MRS的附加价值。AIM 3： 机械模型。(3.a)考虑到ATP与NAA和C1之间的相互依赖性， TBI相关的C1改变是神经胶质的还是神经元的。(3.b)为了测试是否，基于一个机械模型 神经退行性变：（i）基线23 Na MRI和1H MRS结果将受到损伤严重程度的调节;（ii） 与神经退行性变一致的纵向23 Na MRI和1H MRS变化将与恶化相关。 两次随访的临床结果。(3.c)确定哪些MR测量（或其组合） 是长期TBI结果的最佳预测因子，基于机制模型和纵向数据。

Project Summary Traumatic brain injury (TBI) is the world's leading cause of neurological disability in the young adult and middle-aged population. The role of computed tomography (CT) and magnetic resonance imaging (MRI) in patient management is limited due to the widespread presence of clinically-relevant, but imaging-occult injury. We propose new metrics of TBI damage obtained from sodium (23Na) MRI and proton MR spectroscopy (1H MRS). The central hypothesis is that conjoint 23Na MRI/1H MRS will provide metabolic imaging markers for loss of ion homeostasis and neurodegeneration, which will predict patients’ long-term clinical outcome. Sodium MRI is a non-invasive modality based on the direct detection of Na+ ions using dedicated MRI software and hardware. It can assess loss of Na+ homeostasis, which can be disturbed by processes where ionic imbalance is the driving force behind the cascade of cell damage. The Na+/K+ exchange pump can be affected by energy deficits due to mitochondrial dysfunction, as well as by diffuse axonal injury, the histopathological signature of TBI. This would result in variations of the intracellular sodium concentration (C1), while inflammation, gliosis and cell loss would be reflected in variations of the extracellular volume fraction (alpha2). We propose to combine the 23Na metrics C1 and alpha2 with 1H MRS, from which quantification of N-acetylaspartate (NAA), creatine (Cr), choline (Cho) and myo-inositol (mI) can be used to infer neuronal health/density (NAA), cellular energy/density (Cr), membrane turnover (Cho) and astrocytic activation (mI). Specific aims are: AIM 1: Methodology. (1.a) To optimize ultrashort echo-time 23Na MRI with and without fluid suppression at 3 T. To optimize image reconstruction with denoising and compressed sensing to increase signal-to-noise ratio, resolution and speed of acquisition. To develop C1 and alpha2 quantification based on 23Na spin dynamics simulation and reference phantoms. (1.b) To implement whole-brain 1H MRS acquisition with 4th order shimming. AIM 2: Clinical application. (2.a) To compare C1 and alpha2 in TBI patients and controls at baseline (≤10 days after TBI) and their rates of change over time (2- month and 1-year follow-ups for TBI, 1-year follow-up for controls), adjusted for MRI (FLAIR, SWI, DTI) and 1H MRS. (2.b) To correlate the baseline values of the MR metrics, and their rates of change over time, with clinical outcome at the two follow-ups. To assess the added value of C1 and alpha2 to MRI and 1H MRS. AIM 3: Mechanistic model. (3.a) Given the interdependence between ATP and both NAA and C1, to determine whether TBI-related changes in C1 are glial or neuronal. (3.b) To test whether, based on a mechanistic model of neurodegeneration: (i) baseline 23Na MRI and 1H MRS findings will be moderated by injury severity; (ii) longitudinal 23Na MRI and 1H MRS changes consistent with neurodegeneration will correlate with worse clinical outcome at the two follow-ups. (3.c) To determine which MR measurements (or combinations thereof) are best predictors of long-term TBI outcome, based on the mechanistic model and the longitudinal data.