TY - JOUR ID - 11745 TI - Comparison of Count Normalization Methods for Statistical Parametric Mapping Analysis Using a Digital Brain Phantom Obtained from Fluorodeoxyglucose-positron Emission Tomography JO - Asia Oceania Journal of Nuclear Medicine and Biology JA - AOJNMB LA - en SN - 2322-5718 AU - Thet Pe, Win AU - Hosokai, Yoshiyuki AU - Minagawa, Takashi AU - Muroi, Kenzo AU - Miwa, Kenta AU - Maruyama, Ayaka AU - Yamaguchi, Toshiya AU - Okano, Kazuto AU - Khin Moh Moh, Htwe AU - Saito, Haruo AD - Department of Radiological Sciences, International University of Health and Welfare, School of Health Sciences AD - Department of Radiological Sciences, International Univercity of Health and Welfare AD - Department of Diagnostic Image Analysis, Course of Radiological Technology, Tohoku University Graduate School of Medicine AD - Department of Diagnostic Image Analysis, Tohoku University Graduate School of Medicine Y1 - 2019 PY - 2019 VL - 7 IS - 1 SP - 58 EP - 70 KW - Count normalization KW - FDG- PET KW - Neurodegenerative disease KW - SPM analysis KW - Yakushev method DO - 10.22038/aojnmb.2018.11745 N2 - Objective(s): Alternative normalization methods were proposed to solve the biased information of SPM in the study of neurodegenerative disease. The objective of this study was to determine the most suitable count normalization method for SPM analysis of a neurodegenerative disease based on the results of different count normalization methods applied on a prepared digital phantom similar to one obtained using fluorodeoxyglucose-positron emission tomography (FDG-PET) data of a brain with a known neurodegenerative condition.Methods: Digital brain phantoms, mimicking mild and intermediate neurodegenerative disease conditions, were prepared from the FDG-PET data of 11 healthy subjects. SPM analysis was performed on these simulations using different count normalization methods. Results: In the slight-decrease phantom simulation, the Yakushev method correctly visualized wider areas of slightly decreased metabolism with the smallest artifacts of increased metabolism. Other count normalization methods were unable to identify this slightly decreases and produced more artifacts. The intermediate-decreased areas were well visualized by all methods. The areas surrounding the grey matter with the slight decreases were not visualized withthe GM and VOI count normalization methods but with the Andersson. The Yakushev method well visualized these areas. Artifacts were present in all methods. When the number of reference area extraction was increased, the Andersson method better-captured the areas with decreased metabolism and reduced the artifacts of increased metabolism. In the Yakushev method, increasing the threshold for the reference area extraction reduced such artifacts.Conclusion: The Yakushev method is the most suitable count normalization method for the SPM analysis of neurodegenerative disease. UR - https://aojnmb.mums.ac.ir/article_11745.html L1 - https://aojnmb.mums.ac.ir/article_11745_67b54d265bd3ff26303ea8a7dd4759a6.pdf ER -