Login Register Cart 0
Generic placeholder image

Current Medicinal Chemistry

Editor-in-Chief

ISSN (Print): 0929-8673
ISSN (Online): 1875-533X

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe Translate in Chinese
Research Article

Simple Synthesis of [18F] AV-45 and its Clinical Application in the Diagnosis of Alzheimer's Disease

Author(s): Qi-Zhou Zhang, Nazi Yilihamu, Yu-Bin Li, Xiao-Hong Li and Yong-De Qin*

Volume 31, Issue 10, 2024

Published on: 19 September, 2023

Page: [1278 - 1288] Pages: 11

DOI: 10.2174/0929867331666230731123226

Price: $65

conference banner
Abstract

Objective: [18F] AV-45 can be produced in a simple, stable, and repeatable manner on the Tracerlab FXF-N platform using a self-editing synthetic procedure and solid-phase extraction purification method. This technique is applied to positron emission tomography (PET) imaging of Alzheimer's disease (AD) to observe its distribution and characteristics in various brain regions and its diagnostic efficiency for the disease.

Methods: The precursor was subjected to nucleophilic radiofluorination at 120°C in anhydrous dimethyl sulfoxide, followed by acid hydrolysis of the protecting groups. The neutralized reaction mixture was purified by solid phase extraction to obtain a relatively pure [18F] AV-45 product with a high specific activity. A total of 10 participants who were diagnosed with Alzheimer's disease (AD group) and 10 healthy controls (HC group) were included retrospectively. All of them underwent [18F] AV-45 brain PET/CT imaging. The distribution of [18F] AV-45 in the AD group was analyzed visually and semi-quantitatively.

Results: Six consecutive radiochemical syntheses were performed in this experiment. The average production time of [18F] AV-45 was 52 minutes, the radiochemical yield was 14.2 % ± 2.7% (n = 6), and the radiochemical purity was greater than 95%. When used with PET/CT imaging, the results of the visual analysis indicated increased [18F] AV-45 radioactivity uptake in the frontal, temporal, and parietal lobes in AD patients. Semiquantitative analysis showed the highest diagnostic efficacy in the posterior cingulate gyrus compared with other brain regions (P < 0.001).

Conclusion: Intravenous [18F] AV-45 was successfully prepared on the Tracerlab FXF-N platform by solid-phase extraction of crude product and automated radiochemical synthesis. PET/CT imaging can be used to diagnose and evaluate AD patients and provide a more robust basis for clinicians to diagnose AD.

Keywords: Automated synthesis, [18F] AV-45, PET/CT, solid phase purification, Alzheimer's disease, positron emission tomography.

« Previous Next »
[1]
Weidner, W.S.; Barbarino, P. Thestate of the art of dementia research: New frontiers. Alzheimers Dement., 2019, 15(7), P1473.
[http://dx.doi.org/10.1016/j.jalz.2019.06.4115]
[2]
Zhang, Y.L.; Hu, X.L.; Li, Y.H.; Zhao, C.X. International clinical practice guideline of Chinese medicine Alzheimer. World J. Tradit. Chin. Med., 2021, 7, 265-275.
[3]
Levin, O.S.; Vasenina, E.E. 25 Years of the amyloid hypothesis of the origin of Alzheimer’s disease: Advances, failures, and new perspectives. Neurosci. Behav. Physiol., 2017, 47(9), 1065-1070.
[http://dx.doi.org/10.1007/s11055-017-0513-0]
[4]
Litvinenko, I.V.; Emelin, A.Y.; Lobzin, V.Y. he amyloid hypothesis of Alzheimer’s disease: Past and present, hopes and disappointments. Neurology neuropsychiatry. Psychosomatics, 2019, 11(3), 4-10.
[5]
Rinne, J.O.; Brooks, D.J.; Rossor, M.N.; Fox, N.C.; Bullock, R.; Klunk, W.E.; Mathis, C.A.; Blennow, K.; Barakos, J.; Okello, A.A.; de LIano, S.R.M.; Liu, E.; Koller, M.; Gregg, K.M.; Schenk, D.; Black, R.; Grundman, M. 11C-PiB PET assessment of change in fibrillar amyloid-β load in patients with Alzheimer’s disease treated with bapineuzumab: A phase 2, double-blind, placebo- controlled, ascending-dose study. Lancet Neurol., 2010, 9(4), 363-372.
[http://dx.doi.org/10.1016/S1474-4422(10)70043-0] [PMID: 20189881]
[6]
Liu, E.; Schmidt, M.E.; Margolin, R.; Sperling, R.; Koeppe, R.; Mason, N.S.; Klunk, W.E.; Mathis, C.A.; Salloway, S.; Fox, N.C.; Hill, D.L.; Les, A.S.; Collins, P.; Gregg, K.M.; Di, J.; Lu, Y.; Tudor, I.C.; Wyman, B.T.; Booth, K.; Broome, S.; Yuen, E.; Grundman, M.; Brashear, H.R. Amyloid-β11 C-PiB-PET imaging results from 2 randomized bapineuzumab phase 3 AD trials. Neurology, 2015, 85(8), 692-700.
[http://dx.doi.org/10.1212/WNL.0000000000001877] [PMID: 26208959]
[7]
Koole, M.; Lewis, D.M.; Buckley, C.; Nelissen, N.; Vandenbulcke, M.; Brooks, D.J.; Vandenberghe, R.; Van Laere, K. Whole-body biodistribution and radiation dosimetry of 18F-GE067: A radioligand for in vivo brain amyloid imaging. J. Nucl. Med., 2009, 50(5), 818-822.
[http://dx.doi.org/10.2967/jnumed.108.060756] [PMID: 19372469]
[8]
Snellman, A.; Rokka, J.; López-Picón, F.R.; Eskola, O.; Salmona, M.; Forloni, G.; Scheinin, M.; Solin, O.; Rinne, J.O.; Haaparanta-Solin, M. In vivo PET imaging of beta-amyloid deposition in mouse models of Alzheimer’s disease with a high specific activity PET imaging agent [18F]flutemetamol. EJNMMI Res., 2014, 4(1), 37.
[http://dx.doi.org/10.1186/s13550-014-0037-3] [PMID: 25977876]
[9]
Sabri, O.; Sabbagh, M.N.; Seibyl, J.; Barthel, H.; Akatsu, H.; Ouchi, Y.; Senda, K.; Murayama, S.; Ishii, K.; Takao, M.; Beach, T.G.; Rowe, C.C.; Leverenz, J.B.; Ghetti, B.; Ironside, J.W.; Catafau, A.M.; Stephens, A.W.; Mueller, A.; Koglin, N.; Hoffmann, A.; Roth, K.; Reininger, C.; Schulz-Schaeffer, W.J. Florbetaben PET imaging to detect amyloid beta plaques in Alzheimer’s disease: Phase 3 study. Alzheimers Dement., 2015, 11(8), 964-974.
[http://dx.doi.org/10.1016/j.jalz.2015.02.004] [PMID: 25824567]
[10]
Devous, M.D., Sr; Fleisher, A.S.; Pontecorvo, M.J.; Lu, M.; Siderowf, A.; Navitsky, M.; Kennedy, I.; Southekal, S.; Harris, T.S.; Mintun, M.A. Relationships between cognition and neuropathological tau in Alzheimer’s disease assessed by 18F flortaucipir PET. J. Alzheimers Dis., 2021, 80(3), 1091-1104.
[http://dx.doi.org/10.3233/JAD-200808] [PMID: 33682705]
[11]
Chandra, A.; Valkimadi, P.E.; Pagano, G.; Cousins, O.; Dervenoulas, G.; Politis, M. Applications of amyloid, tau, and neuroinflammation PET imaging to Alzheimer’s disease and mild cognitive impairment. Hum. Brain Mapp., 2019, 40(18), 5424-5442.
[http://dx.doi.org/10.1002/hbm.24782] [PMID: 31520513]
[12]
Nakamura, T.; Iwata, A.; Ueda, K.; Namiki, C. Clinical implications and appropriate use of amyloid imaging with florbetapir (18F) in diagnosis of patients with Alzheimer disease. Brain Nerve, 2016, 68(10), 1215-1222.
[PMID: 27703109]
[13]
Asghar, M.; Hinz, R.; Herholz, K.; Carter, S.F. Dual-phase [18F]florbetapir in frontotemporal dementia. Eur. J. Nucl. Med. Mol. Imaging, 2019, 46(2), 304-311.
[http://dx.doi.org/10.1007/s00259-018-4238-2] [PMID: 30569187]
[14]
Soffers, F.; Ceyssens, S.; Buffet, W.; de Surgeloose, D.; Crols, R. 18F-florbetapir PET in primary cerebral amyloidoma. Clin. Nucl. Med., 2020, 45(10), 838-839.
[http://dx.doi.org/10.1097/RLU.0000000000003214] [PMID: 32796236]
[15]
Bateman, R.J.; Xiong, C.; Benzinger, T.L.S.; Fagan, A.M.; Goate, A.; Fox, N.C.; Marcus, D.S.; Cairns, N.J.; Xie, X.; Blazey, T.M.; Holtzman, D.M.; Santacruz, A.; Buckles, V.; Oliver, A.; Moulder, K.; Aisen, P.S.; Ghetti, B.; Klunk, W.E.; McDade, E.; Martins, R.N.; Masters, C.L.; Mayeux, R.; Ringman, J.M.; Rossor, M.N.; Schofield, P.R.; Sperling, R.A.; Salloway, S.; Morris, J.C. Clinical and biomarker changes in dominantly inherited Alzheimer’s disease. N. Engl. J. Med., 2012, 367(9), 795-804.
[http://dx.doi.org/10.1056/NEJMoa1202753] [PMID: 22784036]
[16]
Fleisher, A.S.; Chen, K.; Quiroz, Y.T.; Jakimovich, L.J.; Gutierrez Gomez, M.; Langois, C.M.; Langbaum, J.B.S.; Roontiva, A.; Thiyyagura, P.; Lee, W.; Ayutyanont, N.; Lopez, L.; Moreno, S.; Muñoz, C.; Tirado, V.; Acosta-Baena, N.; Fagan, A.M.; Giraldo, M.; Garcia, G.; Huentelman, M.J.; Tariot, P.N.; Lopera, F.; Reiman, E.M. Associations between biomarkers and age in the presenilin 1 E280A autosomal dominant Alzheimer disease kindred: A cross-sectional study. JAMA Neurol., 2015, 72(3), 316-324.
[http://dx.doi.org/10.1001/jamaneurol.2014.3314] [PMID: 25580592]
[17]
Donohue, M.C.; Jacqmin-Gadda, H.; Le Goff, M.; Thomas, R.G.; Raman, R.; Gamst, A.C.; Beckett, L.A.; Jack, C.R., Jr; Weiner, M.W.; Dartigues, J.F.; Aisen, P.S. Estimating long-term multivariate progression from short-term data. Alzheimers Dement., 2014, 10(5S)(Suppl.), S400-S410.
[http://dx.doi.org/10.1016/j.jalz.2013.10.003] [PMID: 24656849]
[18]
Young, A.L.; Oxtoby, N.P.; Daga, P.; Cash, D.M.; Fox, N.C.; Ourselin, S.; Schott, J.M.; Alexander, D.C. A data- driven model of biomarker changes in sporadic Alzheimer’s disease. Brain, 2014, 137(9), 2564-2577.
[http://dx.doi.org/10.1093/brain/awu176] [PMID: 25012224]
[19]
Xiong, C.; Jasielec, M.S.; Weng, H.; Fagan, A.M.; Benzinger, T.L.S.; Head, D.; Hassenstab, J.; Grant, E.; Sutphen, C.L.; Buckles, V.; Moulder, K.L.; Morris, J.C. Longitudinal relationships among biomarkers for Alzheimer disease in the adult children study. Neurology, 2016, 86(16), 1499-1506.
[http://dx.doi.org/10.1212/WNL.0000000000002593] [PMID: 27009258]
[20]
Jack, C.R., Jr; Bennett, D.A.; Blennow, K.; Carrillo, M.C.; Dunn, B.; Haeberlein, S.B.; Holtzman, D.M.; Jagust, W.; Jessen, F.; Karlawish, J.; Liu, E.; Molinuevo, J.L.; Montine, T.; Phelps, C.; Rankin, K.P.; Rowe, C.C.; Scheltens, P.; Siemers, E.; Snyder, H.M.; Sperling, R.; Elliott, C.; Masliah, E.; Ryan, L.; Silverberg, N. NIA-AA research framework: Toward a biological definition of Alzheimer’s disease. Alzheimers Dement., 2018, 14(4), 535-562.
[http://dx.doi.org/10.1016/j.jalz.2018.02.018] [PMID: 29653606]
[21]
Ismail, Z.; Black, S.E.; Camicioli, R.; Chertkow, H.; Herrmann, N.; Laforce, R., Jr; Montero-Odasso, M.; Rockwood, K.; Rosa-Neto, P.; Seitz, D.; Sivananthan, S.; Smith, E.E.; Soucy, J.P.; Vedel, I.; Gauthier, S. Recommendations of the 5th Canadian Consensus Conference on the diagnosis and treatment of dementia. Alzheimers Dement., 2020, 16(8), 1182-1195.
[http://dx.doi.org/10.1002/alz.12105] [PMID: 32725777]
[22]
Lee, J.S.; Kim, G.H.; Kim, H.J.; Kim, H.J.; Na, S.; Park, K.H.; Park, Y.H.; Suh, J. Shin, J.H.; Oh, S.I.; Yoon, B. Clinical practice guideline for dementia (diagnosis and evaluation): 2021 revised edition. Dement Neurocogn. Disord., 2022, 21(1), 42-44.
[23]
Shiino, A.; Shirakashi, Y.; Ishida, M.; Tanigaki, K. Machine learning of brain structural biomarkers for Alzheimer’s disease (AD) diagnosis, prediction of disease progression, and amyloid beta deposition in the Japanese population. Alzheimers Dement. (Amst.), 2021, 13(1), e12246.
[http://dx.doi.org/10.1002/dad2.12246] [PMID: 34692983]
[24]
Spencer, B.E.; Jennings, R.G.; Brewer, J.B. Combined biomarker prognosis of mild cognitive impairment: An 11-year follow-up study in the Alzheimer’s disease neuroimaging initiative. J. Alzheimers Dis., 2019, 68(4), 1549-1559.
[http://dx.doi.org/10.3233/JAD-181243] [PMID: 30958366]
[25]
Writing Goup of the Dementia and Cognitive Society of Neurology Committee of Chinese Medical Association. [Guidelines for dementia and cognitive impairment in China: The diagnosis and treatment of mild cognitive impairment] Zhonghua Yi Xue Za Zhi, 2018, 98(13), 7.
[26]
Morris, E.; Chalkidou, A.; Hammers, A.; Peacock, J.; Summers, J.; Keevil, S. Diagnostic accuracy of 18F amyloid PET tracers for the diagnosis of Alzheimer’s disease: A systematic review and meta-analysis. Eur. J. Nucl. Med. Mol. Imaging, 2016, 43(2), 374-385.
[http://dx.doi.org/10.1007/s00259-015-3228-x] [PMID: 26613792]
[27]
Zhang, C.; Wang, C.; Xin, M. Value of visual analysis and SUVR during ^18F-AV45 PET/CT imaging in the diagnosis of mild cognitive impairment and Alzheimer′s disease. Chin. J. Nucl. Med. Mol. Imaging, 2020, 40(4), 201-206.
[28]
Zhang, L.; Zhang, A.; Yao, X.; Zhang, Y.; Liu, F.; Hong, H.; Zha, Z.; Liu, Y.; Wu, Z.; Qiao, J.; Zhu, L.; Kung, H.F. An improved preparation of [18F]AV-45 by simplified solid-phase extraction purification. J. Labelled Comp. Radiopharm., 2020, 63(3), 108-118.
[http://dx.doi.org/10.1002/jlcr.3813] [PMID: 31697847]
[29]
Zhang, Q.Z.; Li, Y.B.; Yilihamu, N.; Li, X.H.; Ba, Y.; Qin, Y.D. Optimization of automatic synthesis and separation of [18F] AV-45 and quality control. Front Chem., 2022, 10, 826678.
[http://dx.doi.org/10.3389/fchem.2022.826678] [PMID: 35494660]
[30]
Han, P.; Shi, J. A theoretical analysis of the synergy of amyloid and tau in Alzheimer’s disease. J. Alzheimers Dis., 2016, 52(4), 1461-1470.
[http://dx.doi.org/10.3233/JAD-151206] [PMID: 27104897]
[31]
Zhu, Z.; Zhu, H. Research progress in imaging agents targeting Aβ and Tau protein in Alzheimer’s disease Z. Chin J Nucl Med Mol Imaging, 2018, 38(4), 291-294.
[32]
Trembath, L.; Newell, M.; Devous, M.D., Sr Technical considerations in brain amyloid PET imaging with 18 F-florbetapir. J. Nucl. Med. Technol., 2015, 43(3), 175-184.
[http://dx.doi.org/10.2967/jnmt.115.156679] [PMID: 26271806]
[33]
Veitch, D.P.; Weiner, M.W.; Aisen, P.S.; Beckett, L.A.; DeCarli, C.; Green, R.C.; Harvey, D.; Jack, C.R., Jr; Jagust, W.; Landau, S.M.; Morris, J.C.; Okonkwo, O.; Perrin, R.J.; Petersen, R.C.; Rivera-Mindt, M.; Saykin, A.J.; Shaw, L.M.; Toga, A.W.; Tosun, D.; Trojanowski, J.Q. Using the Alzheimer’s disease neuroimaging initiative to improve early detection, diagnosis, and treatment of Alzheimer’s disease. Alzheimers Dement., 2022, 18(4), 824-857.
[http://dx.doi.org/10.1002/alz.12422] [PMID: 34581485]
[34]
Mukherjee, S.; Mez, J.; Trittschuh, E.H.; Saykin, A.J.; Gibbons, L.E.; Fardo, D.W.; Wessels, M.; Bauman, J.; Moore, M.; Choi, S.E.; Gross, A.L.; Rich, J.; Louden, D.K.N.; Sanders, R.E.; Grabowski, T.J.; Bird, T.D.; McCurry, S.M.; Snitz, B.E.; Kamboh, M.I.; Lopez, O.L.; De Jager, P.L.; Bennett, D.A.; Keene, C.D.; Larson, E.B.; Crane, P.K. Genetic data and cognitively defined late-onset Alzheimer’s disease subgroups. Mol. Psychiatry, 2020, 25(11), 2942-2951.
[http://dx.doi.org/10.1038/s41380-018-0298-8] [PMID: 30514930]

Rights & Permissions Print Cite
Article Metrics
38
2
Wayfinder Image
© 2024 Bentham Science Publishers | Privacy Policy