Neuromorphometry in Schizophrenia by Computer Algorithm

通过计算机算法进行精神分裂症的神经形态测量

• 批准号: 7051971
• 负责人: JOHN G CSERNANSKY
• 金额: $ 37.86万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-08-01 至 2007-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7051971
• 关键词: age difference; brain mapping; brain morphology; clinical research; computer assisted diagnosis; computer system design /evaluation; data collection methodology /evaluation; diagnosis design /evaluation; gender difference; human subject; longitudinal human study; magnetic resonance imaging; mathematical model; mental disorder diagnosis; neuropathology; racial /ethnic difference; schizophrenia

DESCRIPTION: (provided by applicant) Precisely defining the characteristics of neuroanatomical abnormalities in schizophrenia (i.e., volume losses, shape deformations and altered asymmetries) can provide critical evidence for determining the pathogenesis of schizophrenia. More recently, there has been substantial interest in determining whether such neuroanatomical abnormalities show progressive changes over time. However, improved methodologies for neuromorphometiy are needed for such experiments. During the first funding period of this project, we made further substantial progress in the development of high dimensional brain mapping (HDBM). In this renewal application, we show that HDBM can be used to measure brain structure volumes, shapes and asymmetries with excellent reliability, and that H1)BM can be used to detect abnormalities of the hippocampus and cingulate gyrus that discriminate matched groups of schizophrenia and control subjects. We now propose to collect and analyze high resolution magnetic resonance (MR) scans at three time points two years apart in matched schizophrenia and control subjects. Subjects recruited during the initial funding period will return for these additional assessments, and will be supplemented by new subjects as needed. Because other researchers have suggested that neurodegeneration may occur early in the course of schizophrenia, we propose to enrich our population of subjects by adding additional subjects who are in their first episode of schizophrenia. Clinical data in the subjects with schizophrenia will be collected quarterly throughout the study, and the impact of factors other than schizophrenia that might cause changes in brain structure (e.g., alcohol) will be carefully assessed and considered in the data analysis. Selected brain structure volumes, composite shapes derived from transformation vector fields, and hemispheric symmetries derived from symmetry group transformations will be compared across the selected time points. In addition, we propose to determine whether there are relationships between changes in clinical variables and changes in brain structure volume, shape and asymmetry.

描述：（由申请人提供）准确定义以下特征： 精神分裂症的神经解剖学异常（即体积损失、形状 变形和改变的不对称性）可以提供关键证据 确定精神分裂症的发病机制。最近，又出现了 对确定是否存在此类神经解剖异常有浓厚兴趣 显示随时间的渐进变化。然而，改进的方法 此类实验需要神经形态学。第一次融资期间 在此项目期间，我们在开发方面取得了进一步的实质性进展 高维脑图谱（HDBM）。在此续订申请中，我们展示了 HDBM 可用于测量大脑结构体积、形状和 具有出色可靠性的不对称性，并且 H1)BM 可用于检测 区分匹配的海马和扣带回异常 精神分裂症组和对照组。 我们现在建议收集和分析高分辨率磁共振 (MR) 在匹配的精神分裂症和对照中相隔两年的三个时间点进行扫描 科目。在初始资助期间招募的受试者将返回 这些额外的评估，并将由新科目作为补充 需要。因为其他研究人员认为神经退行性疾病可能 发生在精神分裂症的早期，我们建议丰富我们的人口 通过添加第一集中的其他受试者来增加受试者的数量 精神分裂症。精神分裂症受试者的临床数据将 在整个研究过程中每季度收集一次，以及除 可能导致大脑结构变化的精神分裂症（例如酒精）将 在数据分析中仔细评估和考虑。 选定的大脑结构体积，由变换衍生的复合形状 矢量场，以及从对称群导出的半球对称性 将在选定的时间点上比较转换。此外， 我们建议确定变化之间是否存在关系 临床变量以及大脑结构体积、形状和不对称性的变化。