• Progress in Medical Physics
• /
• v.15 no.1
• /
• pp.45-53
• /
• 2004

SPM has been widely applied for comparison studios of the functional image data among groups of patients or individuals under different conditions and these images are from people ranging from children to adults. However, the analysis of children's brain images by using SPM can make children's brain images normalized to an adult's template image and this can result in some errors. So this study created the children's mean MR images based on the Magnetic Resonance Images of 36 normal children (age: 2～6, average age: 4.36, SD age: 1.41, M/F: 17/19), and the children's mean SPECT images by using SPECT images of 13 normal children (age: 2～6, average age: 4.80, SD age: 1.17, M/F: 10/3). We created the Korean children's brain template image, based on those mean images, and then we compared between the positions of the clusters, based on the blood flow, by normalizing ADHD children's SPECT image to Korean children's template image and SPM adult's template image. As a result of the analysis, the variation of the cluster positions was found to be a maximum of 25 ㎜. Therefore, we should be aware that we need to consider the template image and the p-value when we analyze the chlidren's brain image by using SPM.

• The Korean Journal of Nuclear Medicine
• /
• v.32 no.3
• /
• pp.225-237
• /
• 1998

Purpose: We investigated the statistical methods to compose the functional brain map of human working memory and the principal factors that have an effect on the methods for localization. Materials and Methods: Repeated PET scans with successive four tasks, which consist of one control and three different activation tasks, were performed on six right-handed normal volunteers for 2 minutes after bolus injections of 925 MBq $H_2^{15}O$ at the intervals of 30 minutes. Image data were analyzed using SPM96 (Statistical Parametric Mapping) implemented with Matlab (Mathworks Inc., U.S.A.). Images from the same subject were spatially registered and were normalized using linear and nonlinear transformation methods. Significant difference between control and each activation state was estimated at every voxel based on the general linear model. Differences of global counts were removed using analysis of covariance (ANCOVA) with global activity as covariate. Using the mean and variance for each condition which was adjusted using ANCOVA, t-statistics was performed on every voxel To interpret the results more easily, t-values were transformed to the standard Gaussian distribution (Z-score). Results: All the subjects carried out the activation and control tests successfully. Average rate of correct answers was 95%. The numbers of activated blobs were 4 for verbal memory I, 9 for verbal memory II, 9 for visual memory, and 6 for conjunctive activation of these three tasks. The verbal working memory activates predominantly left-sided structures, and the visual memory activates the right hemisphere. Conclusion: We conclude that rCBF PET imaging and statistical parametric mapping method were useful in the localization of the brain regions for verbal and visual working memory.