Mapping the principal components of aphasic language recovery onto brain structure and function

将失语症语言恢复的主要组成部分映射到大脑结构和功能上

• 批准号: 1949289
• 金额: --
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-1949289
• 关键词: Mapping; principal; components; aphasic; language

Stroke is unfortunately a major global health problem, with a person somewhere in the world having their first stroke everytwo seconds. The greatest risk factor for stroke is age, hence it represents a significant healthcare challenge in countrieslike the UK with an aging population. Cognitive deficits (problems with memory, attention, and language) are very commonafter stroke. Problems with language, known as aphasia, are seen in one in every three stroke cases soon after the stroke,and persist for more than a year after stroke in one in five cases. At present, we do not understand why some people makea good recovery from aphasia after stroke while others are left with chronic language problems. Nor do we understand whysome people respond well to speech and language therapy while others fail to benefit. The goal of this project is tocombine advanced neuroimaging with sophisticated neuropsychology to answer these questions.Ideally, we would like to be able to determine from initial brain scans whether someone is likely to recover well from theircurrent stroke induced impairments. We need to determine prognosis for stroke aphasic patients accurately so we can thendirect therapeutic resources effectively to those who need them most. We also need to understand what aspects of brainstructure and function predict a person's response to standard interventions, as then we can focus on alternative strategieswhere needed. To achieve these goals, we need to develop neural biomarkers that can reliably be used to determineprognosis over recovery and rehabilitation. Previous attempts to achieve prognosis over the course of recovery have hadlimited success as they have not used the most advanced measures of neural integrity not have they focussed on the mostrelevant aspects of neural function.This project will exploit the Anatomical Connectivity Mapping (ACM) method developed and patented by Bioxydyn, aprovider of high value quantitative imaging services and diagnostic tools to the pharmaceutical industry, healthcare andacademia. ACM provides a unique measure of long range connectivity across the whole brain, and therefore allows us tosearch for changes in brain structure associated with improved performance over recovery and rehabilitation. Our currentwork on a cohort of over 65 chronic stroke aphasic patients has shown increases in right hemisphere connectivity that arenot apparent on any other structural measure of brain integrity. Moreover, our recently published work (Butler, Lambon Ralph, & Woollams, 2014, Brain) has adopted a novel approach to lesion symptom mapping by using PrincipleComponents Analysis (PCA) to identify key cognitive dimensions and their neural correlates. Current work has shown thattissue concentration in these areas significantly improves prediction of performance in our chronic stroke aphasic sample.This project will involve firstly using the ACM information from the neural regions associated with specific languagefunctions identified using PCA (phonology, semantics, fluency; Halai, Woollams, & Lambon Ralph, in press, Cortex) in ourchronic stroke cohort of more than 65 patients to demonstrate that consideration of long range connectivity improvesprediction of performance. We will also obtain functional imaging data from a subset of 20 of these patients to demonstratethat activation in the PCA defined regions offers additional predictive power. We will then test out the prognostic power ofthese predictive models directly by recruiting 20 participants for testing and scanning in the subacute stage after stroke. Wewill use their ACM and functional activation in the PCA derived regions to predict their recovery outcomes at retest afterone year. To the extent this approach proves effective, placement with Bioxydyn will facilitate its translation into clinicalpractice for prognosis and to provide baseline recovery trajectories for use in clinical trials.

不幸的是，中风是一个主要的全球性健康问题，每两秒钟就有一个人在世界上的某个地方首次中风。中风的最大风险因素是年龄，因此它在人口老龄化的国家（如英国）代表了重大的医疗保健挑战。认知缺陷（记忆、注意力和语言问题）在中风后很常见。被称为失语症的语言问题，在中风后不久的每三个中风病例中就有一个，并且在五个病例中有一个在中风后持续一年以上。目前，我们还不明白为什么有些人中风后失语症恢复得很好，而另一些人却留下了慢性语言问题。我们也不明白为什么有些人对言语和语言治疗反应良好，而另一些人却没有受益。这个项目的目标是结合先进的神经影像学和复杂的神经心理学来回答这些问题。理想情况下，我们希望能够通过最初的脑部扫描来确定一个人是否有可能从目前的中风引起的损伤中恢复得很好。我们需要准确地判断中风失语症患者的预后，这样我们才能有效地将治疗资源引导到最需要的人身上。我们还需要了解大脑结构和功能的哪些方面可以预测一个人对标准干预措施的反应，这样我们就可以在需要的地方专注于替代策略。为了实现这些目标，我们需要开发神经生物标志物，可以可靠地用于确定恢复和康复的预后。以前的尝试，以实现预后的恢复过程中取得了有限的成功，因为他们没有使用最先进的措施，神经完整性，他们没有集中在最相关的方面的神经functions.This项目将利用解剖连接映射（ACM）的方法开发和专利的Bioxydyn，高价值的定量成像服务和诊断工具的供应商，制药业，医疗保健和学术界. ACM提供了一个独特的测量整个大脑的长距离连接，因此允许我们搜索与恢复和康复性能改善相关的大脑结构变化。我们目前对超过65名慢性中风失语症患者的研究表明，右半球连接性的增加在任何其他大脑完整性的结构测量中都不明显。此外，我们最近发表的工作（Butler，Lambon Ralph，& Woollams，2014，Brain）采用了一种新的方法，通过使用主成分分析（PCA）来识别关键的认知维度及其神经相关性来绘制病变症状图。目前的工作表明，这些区域的组织集中显著提高了我们慢性中风失语症样本的预测能力。本项目将首先使用来自与使用PCA识别的特定语言功能相关的神经区域的ACM信息（语音，语义，流利性; Halai，Woollams，& Lambon Ralph，in press，Cortex）在我们的超过65名患者的慢性中风队列中证明考虑长距离连接改善了性能预测。我们还将从其中20名患者的子集中获得功能成像数据，以证明PCA定义区域的激活提供了额外的预测能力。然后，我们将招募20名参与者在中风后的亚急性期进行测试和扫描，直接测试这些预测模型的预后能力。我们将使用他们的ACM和PCA衍生区域的功能激活来预测他们在一年后重新测试时的恢复结果。在这种方法被证明有效的程度上，Bioxydyn的放置将促进其转化为临床实践，用于预后，并提供基线恢复轨迹用于临床试验。