18F-THK 5351 and 11C-PiB PET of the Thai normal brain template | ||
| Asia Oceania Journal of Nuclear Medicine and Biology | ||
| مقاله 4، دوره 9، شماره 1، فروردین 2021، صفحه 21-30 اصل مقاله (1.18 M) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.22038/aojnmb.2020.49623.1338 | ||
| نویسندگان | ||
| Chanisa Chotipanich* ؛ Supaporn Kongthai؛ Anchisa Kunawudhi؛ Chetsadaporn Promteangtrong؛ Attapon Jantarato | ||
| National Cyclotron and PET Centre, Chulabhorn Hospital, Chulabhorn Royal Academy, Bangkok, Thailand | ||
| چکیده | ||
| Objective(s): The aim of the study was to create a local normal database brain template of Thai individuals for 11C-Pittsburgh compound B (11C-PiB) and 18F-THK 5351 depositions using statistical parametric mapping (SPM) software, and to validate and optimize the established specific brain template for use in clinical practice with a highly reliability and reproducibility. Methods: This prospective study was conducted in 24 healthy right-handed volunteers (13 men, 11 women; aged: 42–79 years) who underwent 18F-THK 5351 and 11C-PiB PET/CT scans. SPM was used for the 18F-THK 5351 and 11C-PiB PET/CT image analysis. All PET images were processed individually using Diffusion Tensor Image -Magnetic Resonance Imaging-weighted images (DTI-MRI images), which involved: (1) conversion of Digital Imaging and Communications in Medicine (DICOM) files into an analyzable file extension (.NIFTI) for statistical parametric mapping, (2) setting of the origin (the anterior commissure was used as the anatomical landmark), (3) re-alignment, (4) co-registration of PET with B0 (T1W) and DTI-MRI images, (5) normalization, and (6) normal verification using the Thai MRI standard. We then compared the normal PET template with the abnormal deposition area of different dementia syndromes, including Alzheimer’s disease and progressive supranuclear palsy. Results: This method was able to differentiate cognitively normal from Alzheimer’s disease and progressive supranuclear palsy subjects . Conclusions: This normal brain template was able to be integrated into clinical practice and research using PET analyses at our center. | ||
| کلیدواژهها | ||
| Brain template؛ Amyloid؛ Tau protein | ||
| مراجع | ||
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1. Gulisano W, Maugeri D, Baltrons MA, Fà M, Amato A, Palmeri A, et al. Role of Amyloid-β and Tau Proteins in Alzheimer’s disease: Confuting the Amyloid Cascade. J Alzheimers Dis. 2018; 64:S611–31.
2. GBD 2016 Dementia Collaborators. Global, regional, and national burden of Alzheimer’s disease and other dementias, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019; 18:88–106.
3. Zhang S, Smailagic N, Hyde C, Noel-Storr AH, Takwoingi Y, McShane R, et al. (11)C-PIB-PET for the early diagnosis of Alzheimer’s diseasedementia and other dementias in people with mild cognitive impairment (MCI). Cochrane Database Syst Rev. 2014; 23:CD010386. doi: 10.1002/14651858.CD010386.
4. Harada R, Okamura N, Furumoto S, Furukawa K, Ishiki A, Tomita N, et al. [18F]THK-5117 PET for assessing neurofibrillary pathology in Alzheimer’s disease. Eur J Nucl Med Mol Imaging. 2015; 20:42.
5. Okamura N, Harada R, Ishiki A, Kikuchi A, Nakamura T, Kudo Y. The development and validation of tau PET tracers: current status and future directions. Clin Transl Imaging. 2018; 6:305–16.
6. Quigley H, Colloby SJ, O’Brien JT. PET imaging of brain amyloid in dementia: a review. Int J Geriatr Psychiatry. 2011; 26:991–9.
7. Rao NP, Jeelani H, Achalia R, Achalia G, Jacob A, Bharath R dawn, et al. Population differences in brain morphology: Need for population specific brain template. Psychiatry Res. Neuroimaging. 2017; 265:1–8.
8. Duara R, Loewenstein DA, Lizarraga G, Adjouadi M, Barker WW, Greig-Custo MT, et al. Effect of age, ethnicity, sex, cognitive status and APOE genotype on amyloid load and the threshold for amyloid positivity. Neuroimage Clin. 2019; 22:101800. doi: 10.1016/j.nicl. 2019.101800.
9. Durbar U. Racial variations in different skulls. J Pharm Sci and Res. 2014; 6:370-2.
10. Wei L, Guo K, Li Y, Guo Z, Gao C, Yuan M, et al. Construction of a novel Chinese normal brain database using 18F-FDG PET images and MIMneuro software, the initial application in epilepsy. Int J Neurosci. 2018; 129:417-22.
11. Reiman EM, Chen K, Liu X, Bandy D, Yu M, Lee W, et al. Fibrillar amyloid- burden in cognitively normal people at 3 levels of genetic risk for Alzheimer's disease. Proc Natl Acad Sci USA. 2009; 106:6820-5.
12. Ward A, Crean S, Mercaldi CJ, Collins JM, Boyd D, Cook MN, et al. Prevalence of Apolipoprotein E4 Genotype and Homozygotes (APOE e4/4) among Patients Diagnosed with Alzheimer’s Disease: A Systematic Review and Meta-Analysis. Neuroepidemiology. 2012; 38:1-17.
13. Reitz C, Mayeux R. Alzheimer disease: Epidemiology, diagnostic criteria, risk factors and biomarkers. Biochem Pharmacol. 2014; 88:640-51.
14. Sun FT, Schriber RA, Greenia JM, He J, Gitcho A, Jagust WJ. Automated Template-based PET Region of Interest Analyses in the Aging Brain. Neuroimage. 2007; 34:608–17.
15. Mendez MF. Early-Onset Alzheimer’s Disease. Neurol Clin. 2017; 35:263–81.
16. Shinotoh H. IC-01-05: Mapping of amyloid deposition in early- and late-onset Alzheimer’s disease. Alzheimers Dement. 2008; 4:T3–4. doi: 10.1016/j.jalz.2008.05.1153.
17. Okamura N, Harada R, Furumoto S, Arai H, Yanai K, Kudo Y. Tau PET Imaging in Alzheimer’s Disease. Curr Neurol Neurosci Rep. 2014; 14:1–7.
18. Braak H, Braak E. Neuropathological staging of Alzheimer-related changes. Acta Neuropathol.1991; 82:239–59.
19. Schöll M, Maass A, Mattsson N, Ashton NJ, Blennow K, Zetterberg H, et al. Biomarkers for tau pathology. Mol Cell Neurosci. 2019; 97:18–33.
20. Alster P, Madetko NK, Koziorowski DM, Królicki L, Budrewicz S, Friedman A. Accumulation of Tau Protein, Metabolism and Perfusion-Application and Efficacy of Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT) Imaging in the Examination of Progressive Supranuclear Palsy (PSP) and Corticobasal Syndrome (CBS). Front Neurol. 2019; 10:101. doi: 10.3389/fneur.2019.00101.
21. Poussier S, Maskali F, Vexiau G, Verger A, Boutley H, Karcher G, et al. Quantitative SPM Analysis Involving an Adaptive Template May Be Easily Applied to [18F]FDG PET Images of the Rat Brain. Mol Imaging Biol. 2017; 19:731–5.
22. Nie B, Liu H, Chen K, Jiang X, Shan B. A Statistical Parametric Mapping Toolbox Used for Voxel-Wise Analysis of FDG-PET Images of Rat Brain. PLOS ONE. 2014; 9:e108295. doi: 10.1371/journal. pone.0108295.
23. Van Der Gucht A, Verger A, Guedj E, Malandain G, Hossu G, Yagdigul Y, et al. Age-related changes in FDG brain uptake are more accurately assessed when applying an adaptive template to the SPM method of voxel-based quantitative analysis. Ann Nucl Med. 2015; 29:921–8.
24. Della Rosa PA, Cerami C, Gallivanone F, Prestia A, Caroli A, Castiglioni I, et al. A standardized [ 18F]-FDG-PET template for spatial normalization in statistical parametric mapping of dementia. Neuroinformatics. 2014; 12:575–93.
25. Ng KP, Pascoal TA, Mathotaarachchi S, Therriault J, Kang MS, Shin M, et al. Monoamine oxidase B inhibitor, selegiline, reduces 18F-THK5351 uptake in the human brain. Alzheimers Res Ther. 2017; 9:25. doi: 10.1186/s13195-017-0253-y.
26. Harada R, Ishiki A, Kai H, Sato N, Furukawa K, Furumoto S, et al. Correlations of 18FTHK5351 PET with Postmortem Burden of Tau and Astrogliosis in Alzheimer Disease. J Nucl Med. 2018; 59:671-674. | ||
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