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Research Article

[18F]AV-45的简单合成及其在阿尔茨海默病诊断中的临床应用

卷 31, 期 10, 2024

发表于: 19 September, 2023

页: [1278 - 1288] 页: 11

弟呕挨: 10.2174/0929867331666230731123226

价格: $65

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摘要

目的：[18F]AV-45可以在Tracerlab FXF-N平台上使用自编辑合成程序和固相萃取纯化方法以简单、稳定和可重复的方式生产。将该技术应用于阿尔茨海默病（AD）的正电子发射断层扫描（PET）成像，以观察其在大脑各区域的分布和特征以及对该疾病的诊断效率。 方法：在120°C的无水二甲基亚砜中对前体进行亲核放射性氟化，然后对保护基进行酸水解。通过固相萃取纯化中和的反应混合物以获得具有高比活性的相对纯的[18F]AV-45产物。共有10名被诊断为阿尔茨海默病的参与者（AD组）和10名健康对照组（HC组）被纳入回顾性研究。所有患者均接受了[18F]AV-45脑PET/CT成像。视觉和半定量分析[18F]AV-45在AD组中的分布。 结果：本实验连续进行了6次放化合成。[18F]AV-45的平均生产时间为52分钟，放射化学产率为14.2%±2.7%（n=6），放射化学纯度大于95%。当与PET/CT成像一起使用时，视觉分析结果表明AD患者额叶、颞叶和顶叶[18F]AV-45放射性摄取增加。半定量分析显示，与其他大脑区域相比，后扣带回的诊断效率最高（P<0.001）。 结论：在Tracerlab FXF-N平台上，通过固相提取粗产物和自动化放射化学合成，成功制备了静脉[18F]AV-45。PET/CT成像可用于诊断和评估AD患者，并为临床医生诊断AD提供更有力的基础。

关键词: 自动化合成，[18F]AV-45，PET/CT，固相纯化，阿尔茨海默病，正电子发射断层扫描。

« 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]

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