Analysis of improvements to post-stroke visual field mapping using prospective motion correction in fMRI

英国每年大约有11万例中风病例，中年男性患中风的终生风险为1/6，中年女性为1/5。据估计，60%的中风幸存者在中风后立即遭受某种形式的视力障碍。在这些人中，三分之一的人在中风发作三个月后仍然患有视力障碍。这种视觉损伤会对生活质量产生显著影响，因为它会导致缺乏灵活性，失去信心，碰撞和事故的发生率增加。在正在进行的工作中，我们一直在使用磁共振成像(MRI)来识别枕叶病变周围具有支持视力的备用皮质。通过功能磁共振成像，我们一直在估计备用视皮层内不同区域的视野覆盖范围，并使用这些信息来训练参与者完成一项困难的视觉任务。除了功能磁共振成像，还有一套强大的附加技术可以提供重要的附加信息。然而，尽管如此，这些额外的测量实际上从未在临床环境中结合使用。-扩散加权成像-血管成像/灌注测量-高分辨率解剖扫描这些技术经常不结合使用的主要原因之一是参与者必须在MR扫描仪上花费的时间以及与运动有关的问题和人工制品。例如，由于运动障碍的并存，如舞蹈病和中风后的震颤，许多中风幸存者可能无法从这种有针对性的干预中受益，因为这些疾病引起的非自愿运动可能会导致运动伪影(在MRI中)，因此也会导致所有成像数据。因此，详细研究改善fMRI数据质量的不同方法(预期运动校正、并行成像、多波段、压缩传感)的好处(和局限性)至关重要，并可能导致使用哪种成像协议来评估这些患者的切实改进。目的和目标调查和量化旨在加快和稳定磁共振成像(MRI)测量的新技术可实现的改进。特别是，我们将调查和量化目前使用的功能磁共振成像、扩散加权成像和血管成像/灌注测量的协议如何通过使用并行成像(例如SENSE)和多频段采集-基于导航回波对运动进行前瞻性校正-使用欠采样数据采集(压缩传感)-(时间允许)使用机器学习技术来改进血管造影成像衍生测量的量化等。学生将：-比较目前用于对中风幸存者和健康对照组进行成像的设置和成像方案(在3T)。-调查从目前使用的扫描仪(3T Achieva)转移到包括许多技术改进的更新硬件平台(3T雌驼龙)的质量改进(在健康参与者中)-使用2种互补的并行成像方法(SENSE和多波段)评估成像速度和数据质量之间的权衡-还通过使用计算密集型方法使用欠样本数据(压缩检测、稀疏信号重建)来研究进一步的加速，这将对血管造影术特别有益-评估通过加速和/或减少成像相关的声学噪声而实现的患者舒适度的改善。这对于我们发展患者和公众参与(PPI)尤其重要。与EPSRC的战略和研究领域保持一致，与脆弱对象的成像技术相关的特定主题呼吁。

There are approximately 110,000 stroke cases in England each year with the lifetime risk of a stroke for a middle-aged man being 1-in-6 and for a middle-aged woman being 1-in-5. It is estimated that 60% of stroke survivors suffer from some form of visual impairment immediately after a stroke. Of those, one in three still suffer from visual impairment three months post-stroke onset. This visual impairment can have a marked impact on quality of life, as it leads to a lack of mobility, loss of confidence and increased rates of collisions and accidents.In ongoing work we have been using magnetic resonance imaging (MRI) to identify spared cortex surrounding the lesions in the occipital lobe with capacity to support vision. With functional MRI, we have been estimating the visual field coverage of different areas within the spared visual cortex and using this information to train participants on a difficult visual task. In addition to functional MRI, there is a powerful set of additional techniques that can provide important additional information. Despite this however, these additional measurements are really never use in combination in the clinical setting.- diffusion weighted imaging - angiography/perfusion measurements - high resolution anatomical scansOne of the main reasons for these technologies are not often combined is the amount of time a participant has to spend in an MR scanner and problems and artefacts related to motion. For example, due to the co-occurrence of movement disorders such as chorea and tremors post-stroke, many stroke survivors may not be able to benefit from such a targeted intervention, since the involuntary movements caused by these disorders can cause motion artefacts in MRI) and therefore also all the imaging-dreived data. A detailed study of the benefits (and limits) of different approaches to improving data quality (prospective motion correction, parallel imaging, multiband, compressed sensing) for fMRI derived data is therefore crucially important and likely to lead to tangible improvements in what kind of imaging protocols are used to assess these patients.Aims and objectivesTo investigate and quantify the improvements attainable with new technologies aimed at speeding up and stabilising magnetic resonance imaging (MRI) measurements. In particular, we will investigate and quantify how currently used protocols for functional MRI, diffusion weighted imaging and angiography/perfusion measurements can be improved by- use of parallel imaging (e.g SENSE) and multiband acquisition- prospective correction for motion based on navigator echoes- using undersampled data acquisition (compressed sensing)- (time permitting) use of machine learning techniques to improve quantification of imaging-derived measures for angiography, etc.MethodologyThe plan for the start of the PhD program is as follows. The student will:- compare the currently used setup and imaging protocol (at 3T) for imaging a cohort of stroke survivors and healthy controls.- investigate the quality improvements (in healthy participants) of moving from currently used scanner (3T Achieva) to an updated hardware platform that includes many technical improvements (3T Ingenia)- assess the trade-off between imaging speed-up and data quality with 2 kinds of complementary parallel imaging approaches (SENSE and Multiband)- investigate further speed-ups by also using computationally intensive approaches to using undersample data (compressed sensing, reconstruction of sparse signals), which will be particularly beneficial for angiography- assess the improvements in patient comfort achieved by speeding up and/or reducing imaging related acoustic noise. This is particularly important for our development of Patient and Public Involvement (PPI).Alignment to EPSRC's strategies and research areas- specific thematic call, relating to Imaging technologies for vulnerable subjects.