• Journal of the Korean Society of Radiology
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• v.15 no.6
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• pp.891-897
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• 2021

With the development of Amyloid PET Tracer, the accuracy of Alzheimer's diagnosis can be improved through the identification of beta-amyloid neurites. However, the long image acquisition time of 20 minutes can be difficult for the patient. PET/CT scans are sensitive to patient movement and may partially affect test results. In this study, we studied the proper image acquisition time without affecting the quantitative evaluation of the image through the list mode acquisition method according to the time of the distribution of radioactive drugs in the body. The list mode includes information about time compared to the existing frame mode, and it is easy to analyze data because it can reconstruct images about the time that researchers want. The research method obtained a reconstructed image by time using a list mode of 5min frame/bed, 10min frame/bed, 15min frame/bed, and 20min frame/bed to compare the difference between signal-to-pons take ratio (SNR) and lesion-to-pons uptake ratio (LPR) and the difference in reading time to obtain an appropriate image. As a result of quantitative analysis, when measuring in list mode, SUVmean values decreased in 6 regions of interest as the image acquisition time increased, but showed the largest difference in 5 min/bed images, followed by 10 min/bed and 15 min/bed. As a result, the difference in SUVmean values decreased. Therefore, it was found that SUVmean values at 15 min/bed did not differ enough to not affect image evaluation. There was no difference in LPR values. As a result of the qualitative analysis, there was no change in the reading findings according to the PET image acquisition time and there was no significant difference in the qualitative analysis score of the image reconstruction according to time. As a result of the study, there is no significant difference between 15 min/bed and 20 min/bed images during the ¹⁸F-flutemetamol PET/CT test, so it can be said that it is clinically useful to reduce the image acquisition time selectively using 15 min/bed via list mode depending on the patient's condition.

• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.1
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• pp.12-16
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• 2015

Purpose Principal component analysis (PCA) is a method often used in the neuroimagre analysis as a multivariate analysis technique for describing the structure of high dimensional correlation as the structure of lower dimensional space. PCA is a statistical procedure that uses an orthogonal transformation to convert a set of observations of correlated variables into a set of values of linearly independent variables called principal components. In this study, in order to investigate the usefulness of PCA in the brain PET image analysis, we tried to analyze C[11]-PIB PET image as a representative case. Materials and Methods Nineteen subjects were included in this study (normal = 9, AD/MCI = 10). For C[11]-PIB, PET scan were acquired for 20 min starting 40 min after intravenous injection of 9.6 MBq/kg C[11]-PIB. All emission recordings were acquired with the Biograph 6 Hi-Rez (Siemens-CTI, Knoxville, TN) in three-dimensional acquisition mode. Transmission map for attenuation-correction was acquired using the CT emission scans (130 kVp, 240 mA). Standardized uptake values (SUVs) of C[11]-PIB calculated from PET/CT. In normal subjects, 3T MRI T1-weighted images were obtained to create a C[11]-PIB template. Spatial normalization and smoothing were conducted as a pre-processing for PCA using SPM8 and PCA was conducted using Matlab2012b. Results Through the PCA, we obtained linearly uncorrelated independent principal component images. Principal component images obtained through the PCA can simplify the variation of whole C[11]-PIB images into several principal components including the variation of neocortex and white matter and the variation of deep brain structure such as pons. Conclusion PCA is useful to analyze and extract the main pattern of C[11]-PIB image. PCA, as a method of multivariate analysis, might be useful for pattern recognition of neuroimages such as FDG-PET or fMRI as well as C[11]-PIB image.

• Korean Journal of Food Science and Technology
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• v.51 no.2
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• pp.160-168
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• 2019

This study aimed to determine whether double-processed ginseng berry extract (PGBC) could improve learning and memory in an $A\hat{a}42$-induced Alzheimer's mouse model. Passive avoidance test (PAT) and Morris water-maze test (MWMT) were performed after mice were treated with PGBC, followed by acetylcholine (ACh) measurement and glial fibrillary acidic protein (GFAP) detection for brain damage. Furthermore, acetylcholinesterase (AChE) activity and choline acetyltransferase (ChAT) expression were analyzed using Ellman's and qPCR assays, respectively. Results demonstrated that PGBC contained a high amount of ginsenosides (Re, Rd, and Rg3), which are responsible for the clearance of $A{\hat{a}} 42$. They also helped to significantly improve PAT and MWMT performance in the $A{\hat{a}} 42-induced$ Alzheimer's mouse model when compared to the normal group. Interestingly, ACh and ChAT were remarkably upregulated and AChE activities were significantly inhibited, suggesting PGBC to be a palliative adjuvant for treating Alzheimer's disease. Altogether, PGBC was found to play a positive role in improving cognitive abilities. Thus, it could be a new alternative solution for alleviating Alzheimer's disease symptoms.