Microstructural Characterization of White Matter in Schizophrenia

描述（由申请人提供）：精神分裂症是一种慢性、严重和致残性疾病，其特征是幻觉、妄想和运动缺陷。此外，认知缺陷包括注意力、语言、记忆和执行功能的问题也与该障碍相关，并且极大地影响精神分裂症患者的日常正常功能。病理学、功能学和形态学研究表明，在精神分裂症中观察到的脑异常与连接不同脑区的白色物质通路的宏观和微观结构改变有关。额颞叶不连通模型已被提出来解释精神分裂症中观察到的一些缺陷。白色物质的微结构完整性已被广泛研究，使用扩散张量成像（DTI）技术和基于体素的形态测量技术或感兴趣区域的方法。然而，不同研究的结果并不一致。很少有研究探讨的行为相关性的白色物质异常所描绘的DTI。该项目的目标是使用微观结构完整性的典型DTI测量（平均扩散率和分数各向异性）和一个新指标（平均峰度）来研究精神分裂症患者白色物质的微观结构完整性，该指标已显示出更好的前景区分微观结构的变化白色物质。平均峰度将使用扩散峰度成像技术（DTI形式主义的推广）导出。我们还将探讨白色物质的微观结构和一套描述认知功能的措施之间的关系。将采用两种方法：1）基于体素的形态测量技术将用于探索精神分裂症患者组和健康受试者对照组之间白色微结构的差异。2)将使用白色物质纤维束成像技术分割出上级纵束的轨迹和范围，上纵束是连接前额叶、颞叶和顶叶的白色物质束。将在患者与对照组中研究全局和局部管道微结构扩散测量。本研究的结果可能揭示特定通路或脑区域的连接改变，从而有助于理解精神分裂症脑功能障碍的机制。对连接额叶和颞叶的白色物质通路的研究也将有助于理解在精神分裂症中通常观察到的异常额颞功能连接。公共卫生相关性：精神分裂症是一种严重的精神障碍，与严重的终身损害和高患病率有关，影响了美国超过200万人。这项研究将调查连接负责认知控制的功能性大脑区域的白色物质通路的完整性。大脑连接受损的知识将为精神分裂症大脑功能障碍的机制提供新的见解，并有可能提高我们更好地诊断和评估这种疾病治疗的能力。

DESCRIPTION (provided by applicant): Schizophrenia is a chronic, severe, and disabling disorder that is characterized by hallucinations, delusions, and motor deficits. In addition, cognitive deficits including problems with attention, language, memory, and the executive functions are also associated with the disorder and greatly affect normal day by day functioning of the schizophrenic patients. Pathological, functional, and morphometric studies have implied that the brain abnormalities that are observed in schizophrenia are associated with macro and microstructural alterations of the white matter pathways connecting different brain regions. Models of fronto-temporal disconnectivity have been proposed to explain some of the deficits observed in schizophrenia. Microstructural integrity of white matter has been extensively investigated using diffusion tensor imaging (DTI) techniques and either voxel based morphometry techniques or region of interest approaches. However, findings are rather inconsistent across different studies. Few studies have explored the behavioral correlations of the white matter abnormalities depicted by DTI. The goal of this project is to investigate the microstructure integrity of white matter mater in schizophrenia using both typical DTI measures of microstructural integrity - the mean diffusivity and fractional anisotropy and a new metric - the mean kurtosis, which has shown promise to better discriminate microstructural alterations of white matter. The mean kurtosis will be derived using the Diffusion Kurtosis Imaging technique, a generalization of the DTI formalism. We will also explore the relation between the white matter microstructure and a set of measures describing cognitive function. Two approaches will be undertaken: 1) Voxel based morphometry techniques will be used to explore differences in white microstructure between a group of patients with schizophrenia and a control group of healthy subjects. 2) White matter tractography techniques will be used to segment out the trajectory and extent of the superior longitudinal fasciculus, a white matter tract that connects the prefrontal, temporal, and parietal lobes. Both global and local tract microstructural diffusion measures will be investigated in patients versus the control group. The results of this study may reveal connectivity alterations in specific pathways or brain regions and thereby contribute to the understanding of the mechanisms underlying brain dysfunction in schizophrenia. The study of the white matter pathways connecting the frontal and temporal lobe will also contribute to the understanding of the abnormal fronto-temporal functional connectivity that is generally observed in schizophrenia. PUBLIC HEALTH RELEVANCE: Schizophrenia is a severe mental disorder associated with significant lifelong impairment and high prevalence, affecting more than two millions of people in the United States. This study will investigate the integrity of the white matter pathways that connect functional brain regions responsible for cognitive control. Knowledge of the impaired brain connectivity will provide new insights into the mechanisms that underlie brain dysfunction in schizophrenia and has the potential to improve our ability to better diagnose and assess treatment of this disorder.