New methods to quantify axonal magnetic properties and myelin integrity using MRI

髓磷脂是大脑功能和结构的关键组成部分，特别是在白质（WM）中。它是一层由脂质和蛋白质组成的绝缘层，覆盖在大脑的许多轴突上，有助于动作电位的传递。如果受损，它会破坏轴突传递信息的能力，从而降低大脑的功能。髓磷脂在考虑多发性硬化症（MS）等疾病时尤其令人感兴趣，多发性硬化症涉及大脑和脊髓内神经的脱髓鞘。因此，开发准确量化髓磷脂状态的方法具有重要的临床意义。目前利用磁共振成像（MRI）对髓磷脂进行非侵入性定位的方法依赖于髓磷脂顺磁性引起的磁场不均匀性。敏感性张量成像（STI）是一种MRI技术，可以绘制髓磷脂诱导的磁场不均匀性，提供了一种非侵入性评估髓鞘形成的方法。然而，STI需要一个复杂的采集过程，为了获得髓鞘各向异性和方向的信息，患者需要在扫描仪内进行物理旋转。这意味着性传播感染并不总是适用于更广泛的临床环境。另一种方法是定量敏感性作图（QSM），它也可以绘制髓磷脂诱导的场不均匀性，但它不能表征髓磷脂的各向异性和取向。本项目将通过开发磁化率干扰MRI （MSI）建立一个新的范例：利用传统扩散加权MRI （dMRI）中通常用于使MRI信号对水扩散敏感的磁场梯度来探测由局部微观结构和髓磷脂敏感性分布引起的微观磁场梯度。我们的目标是：(a)发展MSI的核心；描述扩散敏化磁场梯度与髓鞘诱导的微观场不均匀性干扰对测量的dMRI信号的影响的生物物理模型(b)开发计算工具，通过(a)使用基于模拟/无似是而非的机器学习方法反演正演模型来估计髓鞘各向异性敏感性(c)使用在健康和脱髓鞘大鼠大脑中获得的STI/dMRI数据的独特数据集来演示MSI (d)通过优化采集和分析在卡迪夫大学脑研究成像中心（CUBRIC）的7T健康志愿者和多发性硬化症患者中收集的新数据，展示人类的MSI。拟议的研究将开发全新的成像技术，这将对理解脑功能的关键成分产生革命性的影响，并为旨在表征体内组织状态的研究项目提供全新的途径。一种非侵入性的方法来量化体内脑WM状态，正常和异常发育期间的髓磷脂形成以及疾病中的髓磷脂分解，将使人们对脑生理学的基本理解有新的认识。独特的dMRI/STI/MSI数据集将为从医学图像中理解和提取新的临床相关信息提供宝贵的资源，对医学成像研究领域具有重要价值。由于疾病或其他因素，大脑WM髓鞘形成如何以及在多大程度上随着时间的推移而变化，这一潜力对医学诊断、精准医学、改善疾病的药物发现、个性化治疗、监测或更深入地了解这些因素如何影响大脑具有重要意义。

Myelin is a key component of brain function and structure, specifically in white matter (WM). It is an insulating layer of lipids and proteins covering many of the brain's axons that aids in the transmission of action potentials. If compromised it disrupts the axons' ability to transmit information which reduces the brain's ability to function. Myelin is especially of interest when considering illnesses such as multiple sclerosis (MS), which involves the demyelination of nerves within the brain and spinal cord. Therefore developing methods to accurately quantify myelin status is of high clinical importance.Current methods of mapping myelin non-invasively using Magnetic Resonance Imaging (MRI) rely on the magnetic field inhomogeneities induced by myelin's paramagnetic properties. Susceptibility tensor imaging (STI) is a MRI technique that maps the magnetic field inhomogeneities induced by myelin, providing a non-invasive way of assessing myelination. However, STI requires a complex acquisition where a patient is physically rotated inside the scanner in order to obtain information about the myelin anisotropy and orientation. This means that STI is not always applicable to the wider clinical environment. An alternative approach is quantitative susceptibility mapping (QSM) which also maps the field inhomogeneities induced by myelin, but it cannot characterize the myelin anisotropy and orientation. This project will establish a novel paradigm by developing Magnetic Susceptibility Interference MRI (MSI): exploiting magnetic field gradients typically used to sensitize the MRI signal to water diffusion in conventional diffusion-weighted MRI (dMRI) to probe the microscopic magnetic field gradients induced by the local microstructure and distribution of myelin susceptibility. Our objectives are:(a) Developing MSI's core: a biophysical model describing the effects on measured dMRI signals of the interference of diffusion-sensitizing magnetic field gradients with the myelin-induced microscopic field inhomogeneities(b) Developing computational tools to estimate myelin anisotropic susceptibility by inverting the forward model in (a) using simulation-based/likelihood-free machine learning methods(c) Demonstrating MSI using a unique dataset of STI/dMRI data acquired in-vivo in healthy and demyelinating rat brains(d) Demonstrating MSI in humans by optimising the acquisition and analysing new data collected in healthy volunteers and MS patients at 7T in the Cardiff University Brain Research Imaging Centre (CUBRIC).The proposed research will develop brand new imaging techniques that will have a transformative impact on understanding key constituents of brain function and provide a whole new avenue of research programmes aimed at characterising tissue state in-vivo. A non-invasive methodology to quantify in-vivo the brain WM state, myelin formation during normal and abnormal development and myelin breakdown in disease will allow for new insights into the basic understanding of brain physiology. The unique dataset of dMRI/STI/MSI data will offer a precious resource for understanding and extracting new clinically relevant information from medical images, which is of great value to the Medical Imaging research area. Potential for accurate quantification of how and how much brain WM myelination changes over time due to disease or other factors has implications for medical diagnosis, precision medicine, disease-modifying drug discovery, personalized treatment, monitoring or a more in-depth understanding of how such factors affect the brain.