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Study of the Influence of Age in (18)F-FDG PET Images Using a Data-Driven Approach and Its Evaluation in Alzheimer's Disease

OBJECTIVES: (18)F-FDG PET scan is one of the most frequently used neural imaging scans. However, the influence of age has proven to be the greatest interfering factor for many clinical dementia diagnoses when analyzing (18)F-FDG PET images, since radiologists encounter difficulties when deciding whe...

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Detalles Bibliográficos
Autores principales: Jiang, Jiehui, Sun, Yiwu, Zhou, Hucheng, Li, Shaoping, Huang, Zhemin, Wu, Ping, Shi, Kuangyu, Zuo, Chuantao, Neuroimaging Initiative, Alzheimer's Disease
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5822896/
https://www.ncbi.nlm.nih.gov/pubmed/29581708
http://dx.doi.org/10.1155/2018/3786083
Descripción
Sumario:OBJECTIVES: (18)F-FDG PET scan is one of the most frequently used neural imaging scans. However, the influence of age has proven to be the greatest interfering factor for many clinical dementia diagnoses when analyzing (18)F-FDG PET images, since radiologists encounter difficulties when deciding whether the abnormalities in specific regions correlate with normal aging, disease, or both. In the present paper, the authors aimed to define specific brain regions and determine an age-correction mathematical model. METHODS: A data-driven approach was used based on 255 healthy subjects. RESULTS: The inferior frontal gyrus, the left medial part and the left medial orbital part of superior frontal gyrus, the right insula, the left anterior cingulate, the left median cingulate, and paracingulate gyri, and bilateral superior temporal gyri were found to have a strong negative correlation with age. For evaluation, an age-correction model was applied to 262 healthy subjects and 50 AD subjects selected from the ADNI database, and partial correlations between SUVR mean and three clinical results were carried out before and after age correction. CONCLUSION: All correlation coefficients were significantly improved after the age correction. The proposed model was effective in the age correction of both healthy and AD subjects.