Illuminating Brain Diseases Using Smart Multiread-out MRI

当涉及到理解疾病时，大脑是一个黑匣子。它充满了关键的细节，可以提供关于如何治疗和管理神经疾病和障碍的无数信息，但我们缺乏有效阅读这些细节的工具。虽然成像技术给了我们一个观察某些过程的窗口，但它们往往是极其有限的。磁共振成像(MRI)就是一个很好的例子，它在临床上取得了无数突破，每天都被用来诊断和管理患者。然而，它通常局限于一个单一的通道--本质上，我们观察的是黑白而不是彩色的大脑。当观察大脑的化学和生物特性时，这一限制尤其正确。有一些技术开始允许对多种信号(即颜色)进行成像，但它们仅限于大脑中存在的非常高丰度的物质。一个与此相关的经典例子是阿尔茨海默氏症。观察到的破坏性神经退行性变与大脑的自然防御系统之间存在着既定的关系。这种共同发生的疾病--神经炎症--与患者的长期恶化有关，但我们很难充分了解它们是如何联系在一起的，以及它们是如何相互作用的。就像经典的鸡和蛋的谜题一样，我们经常不确定哪个先出现，或者它是如何出现的。如果我们能够在活着的大脑中同时观察这些不同的过程是如何工作的，我们将显著提高我们的理解，并能够更密切地监测治疗和干预的效果。这种情况不仅限于阿尔茨海默氏症，而且几乎在我们能想到的所有神经疾病中都是如此。每一种神经退行性疾病、脑瘤、中风，甚至精神健康问题，都将受益于对各种生物系统协同工作--更重要的是，无法协同工作--的实时相互作用的更好理解。我开发了一种技术，通过在名为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。我们之前已经在体内展示了这种方法，现在我的目标是将这项技术应用于研究大脑疾病的标记物，比我们目前所能做的要详细得多。这项开创性的核磁共振技术将得到补充的尖端技术，如质谱仪成像，以进一步了解大脑在前所未有的深度。在我的研究员生涯的初始阶段，我将把重点放在中风和脑癌作为样本模型系统上，因为它们分别代表了急性和慢性炎症的临床重要例子。除此之外，我的工作发现将在神经退行性疾病和广泛的神经疾病中得到关键应用。通过结合这些全面检测、表征和监测大脑疾病标志物的新工具，我的方法将重新想象我们如何看待患病的大脑，并检索无数级别的信息，以帮助我们应对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.