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

这项研究计划的重点是开发一种名为磁共振光谱成像（MRSI）的脑成像技术。与磁共振成像（MRI）密切相关，MRSI是一种鲜为人知的技术，用于非侵入性地绘制组织内各种天然存在的化学物质（称为代谢物）的水平。MRSI通常用于大脑成像，目前是唯一可用于脑组织代谢物水平非侵入性映射的工具。因此，MRSI作为一种诊断工具提供了很大的希望，以检测大脑疾病，如癌症，阿尔茨海默病，抑郁症和精神分裂症等的化学失衡。尽管MRSI已经存在了三十多年，但今天仍然使用的绝大多数MRSI采集方法受到空间分辨率差、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度和精度。因此，MRSI迄今未能作为常规诊断工具获得广泛接受。然而，最近在MRSI采集技术方面的重大进展已经显示出解决上述许多限制的潜力。具体而言，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着改进，并将能够产生更准确和精确的代谢物图谱。随着这些重大进展，MRSI似乎更有可能被用于常规临床使用。然而，目前，下一代快速MRSI技术仍处于起步阶段，仍需要重大发展。需要新的软件工具来帮助模拟和设计更好的采集方法，并处理和分析所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脑部MRSI的先进工具。具体而言，我建议：1）开发先进的开源模拟工具，以允许新设计的快速MRSI采集方法的详细表征和优化; 2）开发和分发3特斯拉和7特斯拉扫描仪上大脑MRSI的先进采集方法; 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着推进最先进的MRSI采集方法，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.