Data-driven identification of intensity normalization region based on longitudinal coherency of18F-FDG metabolism in the healthy brain.
In brain18F-FDG PET data intensity normalization is usually applied to control for unwanted factors confounding brain metabolism. However, it can be difficult to determine a proper intensity normalization region as a reference for the identification of abnormal metabolism in diseased brains. In neurodegenerative disorders, differentiating disease-related changes in brain metabolism from age-associated natural changes remains challenging. This study proposes a new data-driven method to identify proper intensity normalization regions in order to improve separation of age-associated natural changes from disease related changes in brain metabolism.



127 female and 128 male healthy subjects (age: 20 to 79) with brain18F-FDG PET/CT in the course of a whole body cancer screening were included. Brain PET images were processed using SPM8 and were parcellated into 116 anatomical regions according to the AAL template. It is assumed that normal brain18F-FDG metabolism has longitudinal coherency and this coherency leads to better model fitting. The coefficient of determination R2was proposed as the coherence coefficient, and the total coherence coefficient (overall fitting quality) was employed as an index to assess proper intensity normalization strategies on single subjects and age-cohort averaged data. Age-associated longitudinal changes of normal subjects were derived using the identified intensity normalization method correspondingly. In addition, 15 subjects with clinically diagnosed Parkinson's disease were assessed to evaluate the clinical potential of the proposed new method.



Intensity normalizations by paracentral lobule and cerebellar tonsil, both regions derived from the new data-driven coherency method, showed significantly better coherence coefficients than other intensity normalization regions, and especially better than the most widely used global mean normalization. Intensity normalization by paracentral lobule was the most consistent method within both analysis strategies (subject-based and age-cohort averaging). In addition, the proposed new intensity normalization method using the paracentral lobule generates significantly higher differentiation from the age-associated changes than other intensity normalization methods.



Proper intensity normalization can enhance the longitudinal coherency of normal brain glucose metabolism. The paracentral lobule followed by the cerebellar tonsil are shown to be the two most stable intensity normalization regions concerning age-dependent brain metabolism. This may provide the potential to better differentiate disease-related changes from age-related changes in brain metabolism, which is of relevance in the diagnosis of neurodegenerative disorders.
PET Center, Huashan Hospital, Fudan University, Shanghai, China.
Huiwei
H
Zhang
PET Center, Huashan Hospital, Fudan University, Shanghai, China.
Ping
P
Wu
Dept. Nuclear Medicine, Technische Universität München, Munich, Germany.
Sibylle I
SI
Ziegler
PET Center, Huashan Hospital, Fudan University, Shanghai, China.
Yihui
Y
Guan
Department Nuclear Medicine, The Third Affiliated Hospital of Soochow University, Soochow, China.
Yuetao
Y
Wang
PET Center, Huashan Hospital, Fudan University, Shanghai, China.
Jingjie
J
Ge
Dept. Nuclear Medicine, Technische Universität München, Munich, Germany.
Markus
M
Schwaiger
Department Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, USA.
Sung-Cheng
SC
Huang
PET Center, Huashan Hospital, Fudan University, Shanghai, China. Electronic address: zuoct_cn2000@126.com.
Chuantao
C
Zuo
Dept. Nuclear Medicine, Technische Universität München, Munich, Germany; TUM Neuroimaging Center (TUM-NIC), Technische Universität München, Munich, Germany.
Stefan
S
Förster
Dept. Nuclear Medicine, Technische Universität München, Munich, Germany.
Kuangyu
K
Shi
D000328:Adult; D000368:Aged; D001921:Brain / Q000000981:diagnostic imaging / Q000378:metabolism*; D001931:Brain Mapping / Q000379:methods*; D005260:Female; D019788:Fluorodeoxyglucose F18 / Q000378:metabolism / Q000493:pharmacokinetics*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D008875:Middle Aged; D010300:Parkinson Disease / Q000000981:diagnostic imaging / Q000378:metabolism; D049268:Positron-Emission Tomography; D012815:Signal Processing, Computer-Assisted; D055815:Young Adult
D019788:Fluorodeoxyglucose F18
(18)F-fluorodeoxyglucose; Positron emission tomography; intensity normalization