Diffusion MRI at Ultra High Field

超高场扩散磁共振成像（MRI）测量描述组织中水扩散（即随机分子运动）的参数。扩散受到细胞膜的强烈影响，这使得扩散MRI能够非侵入性地探测微观组织特征。因此，弥散MRI提供了一种独特的能力，研究在发育和疾病过程中发生的大脑变化。 水在组织中的扩散对组织的细胞特性具有复杂的依赖性。然而，传统的扩散MRI使用不具有直接生理解释的简化信号模型。振荡梯度自旋回波（OGSE）扩散MRI扩展了实验，也可以测量扩散的频率依赖性。这可以允许估计特定的细胞特性，如大小或密度，但这种方法是耗时的，并且需要高信号强度。在超高场下的扩散MRI增加信号强度;然而，随着磁场强度的增加，扩散MRI遭受严重的失真。在解决这个失真问题方面已经取得了一些进展，但这些方法大大增加了扫描时间。因此，通常不执行超高场强下的扩散MRI。本提案的目的是开发超高场（7特斯拉）无畸变扩散MRI和时间高效OGSE扩散MRI的方法。这项工作将涉及新的数据采样方案的设计和数据冗余的利用，以减少失真和减少扫描时间（即，“压缩传感”），以及开发“基于模型的重建”，其对MRI采集的物理进行建模以去除任何剩余的失真。即使在这些较低的场强下，在大脑的某些区域，失真也是有问题的。因此，这项工作将打开大门，在这些地区的一套全新的神经学研究，无论是在超高场和典型的场强。此外，基本弥散MRI参数的变化（例如，“分数各向异性”）已经在老化、训练和许多神经病症中观察到。虽然这告诉我们大脑中的某些东西发生了变化，并且可能是在什么时候发生的，但对变化的答案通常并不清楚。通过OGSE实现的可量化的组织参数，如细胞大小或密度，可能会提高我们对这些变化的基本生理理解，这将有助于提高对健康大脑的理解，并有助于为神经系统疾病的可能干预提供信息。

Diffusion MRI at Ultra-High FieldDiffusion magnetic resonance imaging (MRI) measures parameters describing water diffusion (i.e. random molecular motion) in tissue. Diffusion is strongly affected by cell membranes, which allows diffusion MRI to non-invasively probe microscopic tissue characteristics. Accordingly, diffusion MRI has provided a unique ability to study changes in the brain that occur during development and in disease. The diffusion of water in tissue has a complex dependence on the cellular properties of the tissue. However, conventional diffusion MRI uses a simplified signal model that does not have a direct physiological interpretation. Oscillating gradient spin-echo (OGSE) diffusion MRI extends the experiment to also measure the frequency dependence of diffusion. This can allow the estimation of specific cell properties like size or density, but this method is time consuming and requires high signal strength. Diffusion MRI at ultra high fields increases the signal strength; however, diffusion MRI suffers from severe distortions as magnetic field strength is increased. Some progress towards solving this distortion issue has been made, but these methods drastically increase scan time. Accordingly, diffusion MRI at ultra high field strengths is not commonly performed. The objectives of this proposal are to develop methods for distortion-free diffusion MRI at ultra high field (7 Tesla) and time-efficient OGSE diffusion MRI. This work will involve the design of new data sampling schemes and exploitation of data redundancies to reduce distortions and decrease scan times (i.e., "compressed sensing"), and the development of “model-based reconstructions” that model the physics of the MRI acquisition to remove any remaining distortions.While these methods will be developed at ultra high field, they will be translatable to typical field strengths. Even at these lower field strengths, distortions are problematic in some regions of the brain. Accordingly, this work will open the door to a whole new set of neurological investigations in these regions, both at ultra high field and typical field strengths. In addition, changes in basic diffusion MRI parameters (e.g., “fractional anisotropy”) have been observed in aging, training, and many neurological conditions. While this tells us something has changed in the brain and potentially when it occurred, the answer to what has changed is usually not clear. Quantifiable tissue parameters, like cell size or density, enabled by OGSE can likely improve our basic physiological understanding of these changes, which would lead to improved understanding of the healthy brain and help to inform on possible interventions for neurological conditions.