ENHANCEMENT OF FUNCTIONAL & NEUROCHEMICAL BRAIN PATTERNS

功能强化

• 批准号: 2443510
• 负责人: ALEJANDRO V LEVY
• 金额: $ 16.85万
• 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 1998-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2443510
• 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.

需要整合和整合有关职能部门、 大脑的神经化学和解剖学组织广泛存在 被认可了。这项研究的目的是为了更好地 验证一种快速而准确的基于计算机的方法来检测和 分析PET和MRI图像中微弱的全脑三维信号。 这样的方法将增加我们检测功能性和 与激活研究、药物相关的神经化学模式 干预或精神疾病。它们还将使 解剖结构可变性研究的数据库， 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)在现有基础上提高计算速度 方法，同时最大限度地减少对用户监督的需要。B)改善 组特异性脑内信噪比的提高 模式，而不是可用的现有方法。C)制定一项 避免选择参考地标的需要的策略。D)发展 一种对相机分辨率具有低灵敏度的方法(FWHM)， 图像噪声、摄像机切片角度或丢失的脑切片。E)发展 一种自动化方法，将准确地预测选定的功能或 脑部解剖图谱中的神经化学模式(身体或核磁共振 基于)。 我们的初步研究支持实现这些目标的可行性。 基本策略是开发减少交互主题的方法 由于病人的位置和大脑的功能而引起的变异， 整个群体的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的这些方法将提供一种独特的 透视过去十年收集的个人数据 好几年了。首先，我们将检查以下分组模式 示踪剂：FDG、18F-N-甲基螺哌啶、18F-NMS、11C-可卡因、11C- 拉氯普利、11C-L苯丙烯基和11C-苯并托品。的可行性。 获得组，或疾病特异性，神经化学和/或功能 脑图将代表神经科学和 神经精神病学社区。