Cardiff University-Equipment Account

核磁共振扫描仪被广泛用于诊断疾病和了解健康身体的运作。然而，尽管对某些诊断有用，但它们不能在微观长度尺度（千分之一毫米）上捕获重要过程发生的组织特性，例如在连接不同大脑区域的“轴突”中，或在重要器官的细胞中，例如肝脏。这种详细的检查通常需要在显微镜下进行侵入性“活组织检查”。然而，活组织检查只能提供有关器官小区域的信息，具有破坏性，因此不能重复进行监测，并且可能存在风险，例如在大脑中进行活检。这个项目集合了工程师、物理学家、数学家和计算机科学家来开发新的MRI方法，用于在微观尺度上量化组织结构。主要的方法是观察精细的组织结构如何阻碍水的运动。目前的MRI硬件限制了测量相对较大的分子位移和具有相对强和长寿命信号的组织成分。这模糊了我们的图像，并阻止我们量化重要的特征，如单个细胞的尺寸，或神经纤维的包装。MRI对较小分子运动和较弱信号的敏感性主要受可用磁场梯度（扫描仪内磁场强度的受控变化）的限制。我们已经说服MRI制造商建立一个定制的MRI系统，具有超强的梯度（比标准MRI扫描仪强7倍），位于新的卡迪夫大学大脑研究成像中心。目前存在一个类似的系统（在美国波士顿），但主要用于制作大脑线路模式的定性图像。我们的团队拥有独特的专业知识组合，可以在全新的方向上开发和利用这种硬件。通过设计新的物理方法将扫描仪“调谐”到重要的（否则不可见的）信号，开发新的生物物理模型来解释这些信号，并抑制不需要的信号，我们将能够首次量化重要的组织特性。使这样的系统可用带来了几个关键的工程挑战，例如电磁场建模，以处理随着梯度变强而变得显著的混淆，以及对神经/心脏组织的影响建模，以施加安全约束。然而，申请人联盟目前的工作为克服这些挑战提供了强有力的起点。加速MR数据采集的既定方法将受到更强梯度的影响，需要开发新的物理方法来快速收集数据。一旦实现，更快的采集和获取新的可见信号成分将使我们能够开发新的微观结构数学模型，包括更细的长度尺度，以增加对健康和疾病组织结构的理解，并对重要的生物物理参数（如大脑中的神经传导速度）做出可测试的预测。这将导致更早和更准确的诊断，更具体和更有针对性的治疗，改善治疗监测，并改善患者的整体预后。最终目标是开发成像软件，使这种硬件大规模可用，从而使新一代主流微观结构成像和宏观结构连接映射技术转化为一线实践。

MRI scanners are used widely to diagnose disease and to understand the workings of the healthy body. However, while useful for some diagnoses, they do not capture tissue properties at microscopic length scales (thousandths of a millimetre) where important processes occur, e.g. in the 'axons' connecting different brain areas, or in cells in vital organs, e.g. liver. Such detailed examination usually requires an invasive 'biopsy' which is studied under a microscope. However, biopsies only provide information about small regions of an organ, are destructive and so cannot be performed repeatedly for monitoring, and can be risky to collect, e.g. in the brain.This project assembles engineers, physicists, mathematicians and computer scientists to develop new MRI methods for quantifying tissue structure at the microscopic scale. The principal approach looks at how fine tissue structure impedes the movement of water. Current MRI hardware restricts measurement to relatively large molecular displacements and from tissue components with a relatively strong and long-lived signal. This blurs our picture and prohibits us from quantifying important characteristics, such as individual cell dimensions, or packing of nerve fibres.The sensitivity of MRI to smaller molecular movements and weaker signals is mainly limited by the available magnetic field gradients (controlled alterations in the field strength within the scanner). We have persuaded MRI manufacturers to build a bespoke MRI system with ultra-strong gradients (7 times stronger than available on standard MRI scanners) to be situated in the new Cardiff University Brain Research Imaging Centre. One similar system currently exists (in Boston, USA) but is used predominantly to make qualitative pictures of the brain's wiring pattern. Our team has the unique combination of expertise to develop and exploit this hardware in completely new directions. By designing new physics methods to 'tune' the scanner to important (otherwise invisible) signals, developing new biophysical models to explain these signals, and suppressing unwanted signals, we will be able to quantify important tissue properties for the first time. Making such a system usable poses several key engineering challenges, such as modelling of electromagnetic fields, to deal with confounds that become significant with stronger gradients, and modelling of the effects on nerves/cardiac tissue, to impose safety constraints. However, the current work of the consortium of applicants provides strong starting points for overcoming these challenges. Established methods for accelerating MR data acquisition will be compromised with stronger gradients, requiring development of new physics methods for fast data collection. Once achieved, faster acquisition and access to newly-visible signal components will enable us to develop new mathematical models of microstructure incorporating finer length-scales to increase understanding of tissue structure in health and disease, and to make testable predictions on important biophysical parameters such as nerve conduction velocities in the brain. This will result in earlier and more accurate diagnoses, more specific and better-targeted therapy, improved treatment monitoring, and overall improved patient outcome. The ultimate goal is to develop the imaging software that brings this hardware to mass availability, in turn enabling a new generation of mainstream microstructure imaging and macrostructural connectivity mapping techniques to translate to frontline practice.