Illuminating Brain Diseases Using Smart Multiread-out MRI

在理解疾病时，大脑是一个黑盒子。它充满了至关重要的细节，可以提供关于如何治疗和管理神经疾病和紊乱的无数信息，但我们缺乏有效阅读这些细节的工具。虽然成像技术为我们提供了一个观察某些过程的窗口，但它们通常是非常有限的。磁共振成像（MRI）就是一个很好的例子，它在临床上带来了无数的突破，每天都被用于诊断和管理病人。然而，它通常局限于单一通道——从本质上讲，我们看到的大脑是黑白的，而不是彩色的。在观察大脑的化学和生物特性时，这种局限性尤其明显。有一些技术开始允许对多种信号（如颜色）进行成像，但它们仅限于大脑中丰度非常高的物质。一个与此相关的经典例子是阿尔茨海默病。在观察到的破坏性神经变性和大脑的自然防御系统之间有一个明确的关系。这种共同发生的情况，即神经炎症，与患者的长期恶化有关，但我们很难完全理解它们是如何联系在一起的，以及它们是如何相互作用的。就像经典的先有鸡还是先有蛋的难题一样，我们常常不确定哪个先出现，或者是如何出现的。如果我们能同时观察这些不同的过程是如何在一个活的大脑中同时工作的，我们将大大提高我们的理解，并能够更密切地监测治疗和干预的效果。这种情况不仅局限于阿尔茨海默病，而且几乎适用于我们能想到的所有神经系统疾病。每一种神经退行性疾病、脑肿瘤、中风，甚至精神健康问题，都将受益于对各种生物系统的实时相互作用的更好理解，这些生物系统都在一起工作——或者更重要的是，没有一起工作。我已经开发了一种技术，通过在称为PARASHIFT MRI的过程中使用精心设计的造影剂，极大地扩展了多信号MRI的范围和灵敏度。这种方法允许在活体大脑中检测到更低水平的化合物，并提供多个读数。我们之前已经在人体中展示了这种方法，我现在的目标是将这项技术应用于研究大脑疾病的标志物，比我们目前所能做到的更详细。这项开创性的MRI技术将辅以互补的尖端技术，如质谱成像，以前所未有的深度进一步了解大脑。在我的奖学金的初始阶段，我将重点关注中风和脑癌作为范例模型系统，因为它们分别代表了急性和慢性炎症的临床重要例子。此外，我的研究结果将在神经退行性疾病和广泛的神经系统疾病中得到关键应用。通过结合这些新工具来全面检测、表征和监测大脑疾病标志物，我的方法将重新想象我们如何看待患病的大脑，并检索无数的信息，以帮助我们解决这一紧迫的社会负担。

The brain is a black-box when it comes to understanding disease. It is full of crucial details that could give untold information on how to treat and manage neurological diseases and disorders, but we lack the tools to effectively read those details. While imaging technologies give us a window to observe certain processes, they are often extremely limited. A good example is magnetic resonance imaging (MRI), which has led to countless breakthroughs in the clinic and is used to diagnose and manage patients every day. It is, however, typically limited to a single channel - essentially, we are looking at the brain in black and white instead of colour. This limitation is particularly true when looking at chemical and biological properties of the brain. There are some techniques that begin to allow imaging of multiple signals (i.e. colours), but they are limited to substances present at very high abundances within the brain. A classic example where this would be relevant is in Alzheimer's disease. There is a well-established relationship between the devastating neurodegeneration observed and brain's natural defence system. This co-occurring condition, neuroinflammation, is linked to the long-term deterioration seen in patients, but we struggle to fully understand how they are connected and how they interplay. Much like the classic chicken and egg conundrum, we are often unsure on which comes first or how that comes to be. If we could simultaneously watch how these different processes work at the same time in a living brain, we would significantly improve our understanding and be able to monitor the effects of treatments and interventions more closely. This scenario is not just limited to Alzheimer's disease, but in almost every neurological disease we can think of. Every neurodegenerative disease, brain tumours, stroke, and even mental health issues would all benefit from an improved understanding of the real-time interplay of various biological systems all working - or, more importantly, failing to work - together. I have developed a technique that greatly expands the range and sensitivity of multi-signal MRI by using carefully designed contrast agents in a process called PARASHIFT MRI. This approach allows much lower levels of compounds to be detected in the living brain with multiple readouts available. We have previously demonstrated its approach in the body, and I now aim to focus on applying the technique to study markers of brain disease in much more detail than we are currently able. This pioneering MRI technique will be supplemented by complementary cutting-edge techniques, such as mass spectrometry imaging, to further understand the brain in unprecedented depth. I will focus on stroke and brain cancer as exemplar model systems in the initial stage of my fellowship as they represent clinically vital examples of both acute and chronic inflammation, respectively. Beyond, the findings from my work will have key applications in neurodegenerative disease and across a broad spectrum of neurological disorders. By combining these new tools for comprehensively detecting, characterising, and monitoring brain disease markers, my approach will reimagine how we look at the diseased brain and retrieve untold levels of information to help us tackle this pressing societal burden.