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Visualization and Quantification of Brown and Beige Adipose Tissues in Mice using [18F]FDG Micro-PET/MR Imaging
Published on: July 1, 2021
Construction of a novel Chinese normal brain database using 18F-FDG PET images and MIMneuro software, the initial
Longxiao Wei1, Kun Guo2, Yunbo Li2
1a Department of Radiology , The First Affiliated Hospital of Xi'an Jiaotong University , Xi'an, Shanxi , China.
Purpose:
To create a standard Western Chinese normal functional brain database for quantitative analysis using 2-deoxy-2-[18F] fluoro-d-glucose (18F-FDG) positron emission tomography (PET) images and MIMneuro software.
Methods:
78 healthy right-handed Chinese volunteers from Tangdu Hospital were scanned using 18F-FDG PET to evaluate brain metabolism between March and October 2016. All PET images were processed using MIMneuro software to create a normal database platform. The platform included anatomical optimization to facilitate spatial localization of abnormalities and a statistical comparison with normal cases utilizing the Z-scores, which represent the number of standard deviations from the mean of the normal controls in the database.
Results:
The novel Chinese brain metabolism database platform including 78 healthy volunteers (male: female 40:38; age 3-78 years, mean age, 45 years) was constructed based on the MIMneuro software, which increased the diagnostic confidence in the test patient by quantifying and emphasizing the abnormality. The BrainAlignTM deformation algorithm of MIMneuro matched the size, shape, and orientation of the patient's brain scan to a template brain for comparison against a database of normal controls. The quantitative analysis performed on a voxel and regional level was useful in assessing the areas of abnormalities.
Conclusions:
A novel Chinese 18F-FDG PET-based normal brain function database was created to highlight the local regions of abnormal metabolic activity through quantitative comparisons against the normal database. The Z-scores obtained by MIMneuro potentially aid in visualizing and quantifying the subtle lesions on 18FDG-PET scan images as observed in a patient diagnosed with epilepsy.
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