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.
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