Assessing the health of ageing blood vessels in the brain using fMRI: experimental design, modelling and analysis

在老龄化人口中，与控制脑血流有关的神经系统问题正在增加，并且是与老龄化有关的疾病（如阿尔茨海默病和其他形式的痴呆症）的一个促成因素。如果大脑中小动脉周围的平滑肌功能不佳，可能会供应过少的血液，导致神经功能出现问题。目前，我们正在开发实用的功能磁共振成像（fMRI）工具，以评估大脑血管的健康状况。这个博士项目的目标是开发新的功能磁共振成像技术和计算软件，以改善脑血管健康的措施。然后将在合适的患者人群中评估这些临床技术的效用。最初，学生将在二氧化碳挑战期间获取MR数据，这些挑战会对大脑血管造成压力。由于这种类型的挑战在软件中经常被混淆为头部运动，因此运动跟踪摄像机系统将被用作黄金标准。将开发运动混淆的量化和数据特征提取方法，以提高从该数据获得的血管健康测量的可靠性。第二种方法将利用现有的大规模成像数据库，通过开发新的信号处理技术来获得新的血管健康测量。当前的噪声校正方法丢弃了我们感兴趣的信息，因此这将需要对所采用的逻辑进行反转。在博士的这一部分，学生将开发算法来处理大数据。最后，将通过设计更舒适、患者友好的MR兼容设置并同时改进相关处理管道来寻求对生理挑战管理方式的实际改进。将开发一种最大限度地减少扫描仪运动的下体负压室。其目的是提高中等规模患者队列中相关血管健康指标的可重复性。

In an ageing population, neurological problems related to control of brain blood flow are increasing and are a contributing factor in conditions associated with ageing, such as Alzheimer's disease and other forms of dementia. If the smooth muscle around small arteries in the brain is not functioning well, too little blood may be supplied, causing problems for neurological function. Currently, we are developing pragmatic functional magnetic resonance imaging (fMRI) tools to assess the health of the brain's blood vessels. The objective of this PhD project is to develop novel fMRI imaging techniques and computational software to improve measures of brain vessel health. The utility of these clinical techniques will then be assessed in a suitable patient population. Initially, the student will acquire MR data during carbon dioxide challenges that stress the brain's blood vessels. Since this type of challenge can often be confused in software as head motion, a motion tracking camera system will be used in tandem as a gold standard. Quantification of motion confounds and data feature extraction methods will be developed to increase the reliability of vessel health measures obtained from this data. The second approach will take advantage of existing large scale imaging databases to derive new measure of vessel health by developing novel signal processing techniques. Current noise correction methods discard the information we are interested in and so this will require an inversion of the employed logic. In this section of the PhD, the student will develop algorithms to deal with large data. Finally, practical improvements to the way physiological challenges are administered will be sought by engineering more comfortable, patient- friendly MR compatible setups and by simultaneously improving related processing pipelines. A lower body negative pressure chamber that minimises motion in the scanner will be developed. The objective is to increase the repeatability of related vessel health measures in a medium sized patient cohort.