Development of advanced magnetic resonance spectroscopic imaging techniques for rapid high-resolution mapping of brain metabolite levels

这项拟议的研究计划专注于开发一种名为磁共振光谱成像(MRSI)的大脑成像技术。与磁共振成像(MRI)密切相关的是一种鲜为人知的技术，用于非侵入性地绘制组织内各种自然发生的化学物质(称为代谢物)的水平。核磁共振成像通常用于对大脑进行成像，目前是唯一可用于非侵入性绘制脑组织代谢物水平的工具。因此，核磁共振成像作为一种诊断工具提供了巨大的前景，可以检测导致癌症、阿尔茨海默病、抑郁症和精神分裂症等脑部疾病的化学失衡。尽管MRSI已经存在了30多年，但目前仍在使用的绝大多数MRSI采集方法都受到空间分辨率低、成像时间长和图像污染问题的限制，这些问题会降低所采集测量的准确性和精确度。因此，到目前为止，MRSI作为一种常规诊断工具还没有得到广泛的接受。然而，最近MRSI采集技术的重大进步已经显示出解决上述许多限制的潜力。具体地说，下一代MRSI图像采集技术将在采集速度和空间分辨率方面提供显著改进，并将能够产生更准确和精确的代谢物地图。随着这些重大进步，MRSI似乎更有可能被常规临床使用。然而，目前这种下一代快速核磁共振成像技术还处于初级阶段，仍然需要重大的发展。需要新的软件工具来帮助模拟和设计更好的采集方法，并处理和分析产生的大型高分辨率数据集。因此，这项拟议工作的总体目标是开发和分发用于快速高分辨率大脑磁共振成像的先进工具。具体地说，我建议：1)开发先进的开源模拟工具，以详细描述和优化新设计的MRSI快速采集方法；2)在3特斯拉和7特斯拉扫描仪上开发和分发用于脑MRSI的先进采集方法；以及3)开发先进的开源软件工具，用于处理、可视化和分析MRSI数据。这项工作的主要成果将是显著推进MRSI获取方法的最先进水平，并使MRSI更接近成为诊断疾病和改善加拿大人生活的常规临床工具。

This proposed research program is focused on the development of a brain imaging technique called magnetic resonance spectroscopic imaging (MRSI). Closely related to magnetic resonance imaging (MRI), MRSI is a lesser-known technique for non-invasively mapping the levels of various naturally occurring chemical substances, called metabolites, within tissue. MRSI is often used to image the brain, and currently stands as the only tool available for non-invasive mapping of brain tissue metabolite levels. As such, MRSI offers great promise as a diagnostic tool to detect chemical imbalances that underlie brain diseases such as cancer, Alzheimer's disease, depression, and schizophrenia, to name a few. Although MRSI has been in existence for more than three decades, the vast majority of the MRSI acquisition methods still used today are limited by poor spatial resolution, long imaging times, and image contamination issues which can reduce the accuracy and precision of the acquired measurements. As a result, MRSI has so far failed to gain widespread acceptance as a routine diagnostic tool. However, recent major advances in MRSI acquisition technology have shown the potential to address many of the above limitations. Specifically, the next generation of MRSI image acquisition techniques will offer dramatic improvements in acquisition speed and spatial resolution, and will be able to produce more accurate and precise metabolite maps. With these major advancements, MRSI appears more likely to be adopted for routine clinical use. Currently, however, this next generation of rapid MRSI techniques is in its infancy and major developments are still needed. New software tools are needed to help simulate and design better acquisition methods, and to process and analyse the large high-resolution datasets that are produced. Therefore, the overall aim of this proposed work is to develop and distribute advanced tools for rapid high-resolution MRSI of the brain. Specifically, I propose: 1) to develop advanced open-source simulation tools to allow detailed characterization and optimization of newly designed rapid MRSI acquisition methods; 2) to develop and distribute advanced acquisition methods for MRSI of the brain on 3 Tesla and 7 Tesla scanners; and 3) to develop advanced open-source software tools for processing, visualization and analysis of MRSI data. The primary outcomes of this work will be to significantly advance the state-of-the-art in MRSI acquisition methods, and to bring MRSI closer to becoming a routine clinical tool for diagnosing diseases and improving the lives of Canadians.