ENHANCEMENT OF FUNCTIONAL & NEUROCHEMICAL BRAIN PATTERNS

功能强化

• 批准号: 2123416
• 负责人: ALEJANDRO V LEVY
• 金额: $ 21.48万
• 依托单位: ASSOCIATED UNIV-BROOKHAVEN NATL LAB
• 依托单位国家: 美国
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-08-22 至 1998-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2123416
• 关键词: biomedical automation; brain mapping; brain metabolism; computational neuroscience; computer system design /evaluation; dopamine receptor; human data; image enhancement; magnetic resonance imaging; mathematical model; neurochemistry; positron emission tomography; statistics /biometry

The need to consolidate and integrate information on the functional, neurochemical and anatomical organization of the brain is widely recognized. The objective of this research is the development and validation of a fast and accurate computer-based method to detect and analyze faint whole brain 3-dimensional signals in PET and MRI images. Such methods will increase our capacity to detect functional and neurochemical patterns associated with activation studies, drug intervention or mental illness. They will also enable the generation of data bases for the study of variability in anatomical structure, metabolic and neurochemical patterns. Our working plan will achieve the following specific aims: a) improve the computing speed over existing methods, while minimizing the need of user supervision. b) improve the enhancement of the signal to noise ratio in group-specific brain patterns, over that of available existing methods. c) develop a strategy that avoids the need to select reference landmarks. d)develop a method that will have low sensitivity to camera resolution,(FWHM), image noise, camera slicing angle or missing brain slices. e) develop an automated method that will accurately project selected functional or neurochemical patterns into a brain anatomical atlas, (cadaver or MRI based). Our preliminary studies support the feasibility to achieve these aims. The basic strategy is to develop methods that reduce the intersubject variability due to patient positioning and the brain's functional, neurochemical and structural variability across the group. Taking advantage of the large variety of different radiotracers at Brookhaven National Laboratory, these methods will provide a unique perspective to individual data which has been collected over the past ten years. To begin we will examine group patterns for the following tracers: FDG, 18F-N-methylspiroperidol, 18F-NMS, 11C-cocaine, 11C- raclopride, 11C-L-deprenyl and 11C-benztropine. The feasibility of obtaining group, or disease specific, neurochemical and/or functional brain maps will represent a unique resource to the neuroscience and neuropsychiatric community.

需要合并和综合关于职能、 大脑的神经化学和解剖学组织被广泛地 认可. 本研究的目的是开发和 验证一种快速、准确的基于计算机的方法， 分析PET和MRI图像中微弱的全脑三维信号。 这些方法将提高我们检测功能性和 与激活研究相关的神经化学模式，药物 干预或精神疾病。 它们还将使 用于研究解剖结构变异性的数据库， 代谢和神经化学模式。 我们的工作计划将实现 具体目标如下：a）提高现有的计算速度 方法，同时最大限度地减少用户监督的需要。 B）改善 增强群体特异性脑中的信噪比 模式，超过现有的方法。 （三）发展A 避免需要选择参考标志的策略。 d）发展 一种对相机分辨率（FWHM）具有低灵敏度的方法， 图像噪声、摄像机切片角度或缺失的脑切片。 e）发展 一种自动化的方法，将准确地预测选定的功能或 神经化学模式到大脑解剖图谱（尸体或MRI 基于）。 我们的初步研究支持实现这些目标的可行性。 基本的策略是发展减少交互主体的方法 由于病人的位置和大脑的功能， 神经化学和结构变异性。 利用各种不同的放射性示踪剂， 布鲁克海文国家实验室，这些方法将提供一个独特的 过去十年收集的个人数据的观点 年 开始，我们将检查以下组模式 示踪剂：FDG、18F-N-甲基螺哌利多、18F-NMS、11 C-可卡因、11 C- 雷氯必利、11 C-L-丙炔苯丙胺和11 C-苯托品。 的可行性 获得组或疾病特异性的神经化学和/或功能 大脑地图将成为神经科学的独特资源， 神经精神病学社区