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

髓鞘是大脑功能和结构的关键组成部分，特别是在白质(WM)中。它是一层绝缘层，由脂质和蛋白质组成，覆盖着许多大脑的轴突，帮助传递动作电位。如果受到损害，它会扰乱轴突传递信息的能力，从而降低大脑的功能。当考虑到多发性硬化症(MS)等疾病时，髓鞘尤其令人感兴趣，多发性硬化症涉及大脑和脊髓内神经的脱髓鞘。因此，发展准确定量髓鞘状态的方法具有重要的临床意义。目前利用核磁共振成像(MRI)对髓鞘进行无创性定位的方法依赖于髓鞘顺磁性引起的磁场不均匀。磁化率张量成像(STI)是一种磁共振成像技术，它映射髓鞘诱导的磁场不均匀，提供了一种非侵入性的评估髓鞘形成的方法。然而，STI需要复杂的采集，即患者在扫描仪内进行物理旋转，以获得有关髓鞘各向异性和方向的信息。这意味着STI并不总是适用于更广泛的临床环境。另一种方法是定量磁化率映射(QSM)，它也映射髓鞘引起的场不均匀，但它不能表征髓鞘的各向异性和取向。该项目将通过开发磁化率干扰磁共振成像(MSI)建立一种新的范式：利用常规弥散加权磁共振成像(DMRI)中通常用于敏感MRI信号到水扩散的磁场梯度来探测由髓鞘局部微结构和分布所引起的微观磁场梯度。我们的目标是：(A)开发MSI的核心：描述扩散敏感型磁场梯度与髓磷脂诱导的微观场不均匀的干扰对测量的dMRI信号的影响的生物物理模型(B)开发计算工具，通过(A)使用基于模拟的/无似然机器学习方法中的正向模型来估计髓鞘各向异性易感性(C)使用在健康和脱髓鞘的大鼠脑内获得的独特的STI/dMRI数据集来演示MSI(D)通过优化采集和分析在7T的健康志愿者和MS患者中收集的新数据来在人类中演示MSI在加的夫大学脑研究成像中心(Cubric)，这项拟议的研究将开发全新的成像技术，将对了解大脑功能的关键组成部分产生革命性影响，并提供一种全新的研究方案，旨在表征体内组织状态。一种非侵入性的方法来量化体内脑白质状态、正常和异常发育过程中的髓鞘形成以及疾病中的髓鞘分解，将使我们能够对大脑生理学的基本理解有新的见解。独特的dMRI/STI/MSI数据集将为理解和提取医学图像中新的临床相关信息提供宝贵的资源，这对医学影像研究领域具有重要价值。准确量化由于疾病或其他因素导致的脑白质髓鞘形成随时间变化的方式和程度的可能性，对于医学诊断、精确医学、疾病修饰药物的发现、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.