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11C-Pittsburgh compound B and18F-THK 5351 positron emission tomography brain imaging in cognitively normal individuals


 National Cyclotron and PET Centre, Chulabhorn Hospital, Chulabhorn Royal Academy, Bangkok, Thailand

Correspondence Address:
Chanisa Chotipanich,
National Cyclotron and PET Centre, Chulabhorn Hospital, Chulabhorn Royal Academy, 906 Kamphaeng Phet 6 Road, Talat Bang Khen, Lak Si, Bangkok 10210
Thailand
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/wjnm.WJNM_57_20

Abnormal beta-amyloid plaques and tau protein accumulation are the core pathologic features of Alzheimer's disease. However, the accumulation of these proteins is also common in cognitively normal elderly people. Therefore, this study is aimed to evaluate the amyloid and tau accumulation in the cognitively normal population. A preliminary prospective study was conducted on 24 cognitively normal individuals who underwent Pittsburgh compound B (11C-PiB) and18F-THK 5351 positron emission tomography (PET)/computed tomography scans. The standardized uptake value ratio (SUVR) was used for quantitative analysis of the two tracers and comparisons between two age groups: ≤60 years and >60 years. Co-registration was applied between the dynamic acquisition PET and T1-weighted magnetic resonance imaging to delineate various cortical regions. P-mod software with the automated anatomical labeling-merged atlas was employed to generate automatic volumes of interest for different brain regions. The posterior cingulate versus precuneus SUVRs of PiB uptake was 1.40 ± 0.07 and 1.38 ± 0.22 versus 1.17 ± 0.07 and 1.14 ± 0.18 in those aged ≤≤60 years and >60 years, respectively, whereas the SUVRs of THK5351 retention at brain stem versus inferior temporal SUVRs were 1.84 ± 0.06 and 1.91 ± 0.18 versus 1.37 ± 0.04 and 1.48 ± 0.21 in the age groups of ≤ 60 years and >60 years, respectively (P = 0.20). Our findings allow the determination of the preliminary optimal cutoff points for SUVRs in amyloid and tau PET studies. Ultimately, these values can be applied to normal databases in clinical use to improve quantitative analysis.


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    -  Chotipanich C
    -  Jantarato A
    -  Kunawudhi A
    -  Kongthai S
    -  Promteangtrong C
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