Using PET with 18F-AV-45 (florbetapir) to quantify brain amyloid load in a clinical environment

V Camus, P Payoux, L Barré, B Desgranges, T Voisin, C Tauber, R La Joie, M Tafani, C Hommet, G Chételat, K Mondon, V de La Sayette, J P Cottier, E Beaufils, M J Ribeiro, V Gissot, E Vierron, J Vercouillie, B Vellas, F Eustache, D Guilloteau, V Camus, P Payoux, L Barré, B Desgranges, T Voisin, C Tauber, R La Joie, M Tafani, C Hommet, G Chételat, K Mondon, V de La Sayette, J P Cottier, E Beaufils, M J Ribeiro, V Gissot, E Vierron, J Vercouillie, B Vellas, F Eustache, D Guilloteau

Abstract

Purpose: Positron emission tomography (PET) imaging of brain amyloid load has been suggested as a core biomarker for Alzheimer's disease (AD). The aim of this study was to test the feasibility of using PET imaging with (18)F-AV-45 (florbetapir) in a routine clinical environment to differentiate between patients with mild to moderate AD and mild cognitive impairment (MCI) from normal healthy controls (HC).

Methods: In this study, 46 subjects (20 men and 26 women, mean age of 69.0 ± 7.6 years), including 13 with AD, 12 with MCI and 21 HC subjects, were enrolled from three academic memory clinics. PET images were acquired over a 10-min period 50 min after injection of florbetapir (mean ± SD of radioactivity injected, 259 ± 57 MBq). PET images were assessed visually by two individuals blinded to any clinical information and quantitatively via the standard uptake value ratio (SUVr) in the specific regions of interest, which were defined in relation to the cerebellum as the reference region.

Results: The mean values of SUVr were higher in AD patients (median 1.20, Q1-Q3 1.16-1.30) than in HC subjects (median 1.05, Q1-Q3 1.04-1.08; p = 0.0001) in the overall cortex and all cortical regions (precuneus, anterior and posterior cingulate, and frontal median, temporal, parietal and occipital cortex). The MCI subjects also showed a higher uptake of florbetapir in the posterior cingulate cortex (median 1.06, Q1-Q3 0.97-1.28) compared with HC subjects (median 0.95, Q1-Q3 0.82-1.02; p = 0.03). Qualitative visual assessment of the PET scans showed a sensitivity of 84.6% (95% CI 0.55-0.98) and a specificity of 38.1% (95% CI 0.18-0.62) for discriminating AD patients from HC subjects; however, the quantitative assessment of the global cortex SUVr showed a sensitivity of 92.3% and specificity of 90.5% with a cut-off value of 1.122 (area under the curve 0.894).

Conclusion: These preliminary results suggest that PET with florbetapir is a safe and suitable biomarker for AD that can be used routinely in a clinical environment. However, the low specificity of the visual PET scan assessment could be improved by the use of specific training and automatic or semiautomatic quantification tools.

Figures

Fig. 1
Fig. 1
Representative axial, sagittal and coronal florbetapir-negative images of a HC subject (a) and a MCI patient (b), and florbetapir-positive images of a MCI patient (c) and an AD patient (d)
Fig. 2
Fig. 2
SUVr values for a set of volumes of interest in AD patients, MCI patients and HC subjects

References

    1. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 4th ed, text revision. Washington DC: American Psychiatric Association; 2000.
    1. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology. 1984;34:939–944.
    1. Braak H, Braak E. Frequency of stages of Alzheimer-related lesions in different age categories. Neurobiol Aging. 1997;18:351–357. doi: 10.1016/S0197-4580(97)00056-0.
    1. Delacourte A, David JP, Sergeant N, Buee L, Wattez A, Vermersch P, et al. The biochemical pathway of neurofibrillary degeneration in aging and Alzheimer’s disease. Neurology. 1999;52:1158–1165.
    1. Dubois B, Feldman HH, Jacova C, DeKosky ST, Barberger-Gateau P, Cummings J, et al. Research criteria for the diagnosis of Alzheimer’s disease: revising the NINCDS-ADRDA criteria. Lancet Neurol. 2007;6:734–746. doi: 10.1016/S1474-4422(07)70178-3.
    1. Albert MS, DeKosky ST, Dickson D, Dubois B, Feldman HH, Fox NC, et al. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 2011;7:270–279. doi: 10.1016/j.jalz.2011.03.008.
    1. Klunk WE, Engler H, Nordberg A, Wang Y, Blomqvist G, Holt DP, et al. Imaging brain amyloid in Alzheimer’s disease with Pittsburgh Compound-B. Ann Neurol. 2004;55:306–319. doi: 10.1002/ana.20009.
    1. Forsberg A, Engler H, Almkvist O, Blomquist G, Hagman G, Wall A, et al. PET imaging of amyloid deposition in patients with mild cognitive impairment. Neurobiol Aging. 2008;29:1456–1465. doi: 10.1016/j.neurobiolaging.2007.03.029.
    1. Rinne JO, Brooks DJ, Rossor MN, Fox NC, Bullock R, Klunk WE, et al. 11C-PiB PET assessment of change in fibrillar amyloid-beta load in patients with Alzheimer’s disease treated with bapineuzumab: a phase 2, double-blind, placebo-controlled, ascending-dose study. Lancet Neurol. 2010;9:363–372. doi: 10.1016/S1474-4422(10)70043-0.
    1. Mintun MA, Larossa GN, Sheline YI, Dence CS, Lee SY, Mach RH, et al. [11C]PIB in a nondemented population: potential antecedent marker of Alzheimer disease. Neurology. 2006;67:446–452. doi: 10.1212/01.wnl.0000228230.26044.a4.
    1. Jagust WJ, Landau SM, Shaw LM, Trojanowski JQ, Koeppe RA, Reiman EM, et al. Relationships between biomarkers in aging and dementia. Neurology. 2009;73:1193–1199. doi: 10.1212/WNL.0b013e3181bc010c.
    1. Kudo Y, Okamura N, Furumoto S, Tashiro M, Furukawa K, Maruyama M, et al. 2-(2-[2-Dimethylaminothiazol-5-yl]ethenyl)-6-(2-[fluoro]ethoxy)benzoxazole: a novel PET agent for in vivo detection of dense amyloid plaques in Alzheimer’s disease patients. J Nucl Med. 2007;48:553–561. doi: 10.2967/jnumed.106.037556.
    1. Waragai M, Okamura N, Furukawa K, Tashiro M, Furumoto S, Funaki Y, et al. Comparison study of amyloid PET and voxel-based morphometry analysis in mild cognitive impairment and Alzheimer’s disease. J Neurol Sci. 2009;285:100–108. doi: 10.1016/j.jns.2009.06.005.
    1. Shao H, Okamura N, Sugi K, Furumoto S, Furukawa K, Tashiro M, et al. Voxel-based analysis of amyloid positron emission tomography probe [C]BF-227 uptake in mild cognitive impairment and Alzheimer’s disease. Dement Geriatr Cogn Disord. 2010;30:101–111. doi: 10.1159/000318754.
    1. Small GW, Kepe V, Ercoli LM, Siddarth P, Bookheimer SY, Miller KJ, et al. PET of brain amyloid and tau in mild cognitive impairment. N Engl J Med. 2006;355:2652–2663. doi: 10.1056/NEJMoa054625.
    1. Thompson PW, Ye L, Morgenstern JL, Sue L, Beach TG, Judd DJ, et al. Interaction of the amyloid imaging tracer FDDNP with hallmark Alzheimer’s disease pathologies. J Neurochem. 2009;109:623–630. doi: 10.1111/j.1471-4159.2009.05996.x.
    1. Vandenberghe R, Van Laere K, Ivanoiu A, Salmon E, Bastin C, Triau E, et al. 18F-flutemetamol amyloid imaging in Alzheimer disease and mild cognitive impairment: a phase 2 trial. Ann Neurol. 2010;68:319–329. doi: 10.1002/ana.22068.
    1. Rowe CC, Ackerman U, Browne W, Mulligan R, Pike KL, O’Keefe G, et al. Imaging of amyloid beta in Alzheimer’s disease with (18)F-BAY94-9172, a novel PET tracer: proof of mechanism. Lancet Neurol. 2008;7:129–135. doi: 10.1016/S1474-4422(08)70001-2.
    1. Barthel H, Gertz HJ, Dresel S, Peters O, Bartenstein P, Buerger K, et al. Cerebral amyloid-β PET with florbetaben (18F) in patients with Alzheimer’s disease and healthy controls: a multicentre phase 2 diagnostic study. Lancet Neurol. 2011;10:424–435. doi: 10.1016/S1474-4422(11)70077-1.
    1. Carpenter AP, Jr, Pontecorvo MJ, Hefti FF, Skovronsky DM. The use of the exploratory IND in the evaluation and development of 18F-PET radiopharmaceuticals for amyloid imaging in the brain: a review of one company’s experience. Q J Nucl Med Mol Imaging. 2009;53:387–393.
    1. Choi SR, Golding G, Zhuang Z, Zhang W, Lim N, Hefti F, et al. Preclinical properties of 18F-AV-45: a PET agent for Abeta plaques in the brain. J Nucl Med. 2009;50:1887–1894. doi: 10.2967/jnumed.109.065284.
    1. Clark CM, Schneider JA, Bedell BJ, Beach TG, Bilker WB, Mintun MA, et al. Use of florbetapir-PET for imaging beta-amyloid pathology. JAMA. 2011;305:275–283. doi: 10.1001/jama.2010.2008.
    1. Lin KJ, Hsu WC, Hsiao IT, Wey SP, Jin LW, Skovronsky D, et al. Whole-body biodistribution and brain PET imaging with [18F]AV-45, a novel amyloid imaging agent – a pilot study. Nucl Med Biol. 2010;37:497–508. doi: 10.1016/j.nucmedbio.2010.02.003.
    1. Wong DF, Rosenberg PB, Zhou Y, Kumar A, Raymont V, Ravert HT, et al. In vivo imaging of amyloid deposition in Alzheimer disease using the radioligand 18F-AV-45 (flobetapir F 18) J Nucl Med. 2010;51:913–920. doi: 10.2967/jnumed.109.069088.
    1. Fleisher AS, Chen K, Liu X, Roontiva A, Thiyyagura P, Ayutyanont N, et al. Using positron emission tomography and florbetapir F18 to image cortical amyloid in patients with mild cognitive impairment or dementia due to Alzheimer disease. Arch Neurol. 2011;68:1404–1411. doi: 10.1001/archneurol.2011.150.
    1. Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E. Mild cognitive impairment: clinical characterization and outcome. Arch Neurol. 1999;56:303–308. doi: 10.1001/archneur.56.3.303.
    1. Sarazin M, Berr C, De Rotrou J, Fabrigoule C, Pasquier F, Legrain S, et al. Amnestic syndrome of the medial temporal type identifies prodromal AD: a longitudinal study. Neurology. 2007;69:1859–1867. doi: 10.1212/01.wnl.0000279336.36610.f7.
    1. Mattis S. Mental status examination for organic mental syndrome in the elderly patient. In: Bellak L, Karasu TB, editors. Geriatric psychiatry. New York: Grune & Stratton; 1976. pp. 77–121.
    1. Grober E, Buschke H, Crystal H, Bang S, Dresner R. Screening for dementia by memory testing. Neurology. 1988;38:900–903.
    1. Deloche G, Hannequin D, Dordain M, Perrier D, Pichard B, Quint S, et al. Picture confrontation oral naming: performance differences between aphasics and normals. Brain Lang. 1996;53:105–120. doi: 10.1006/brln.1996.0039.
    1. Golden CJ, Hammeke TA, Purisch AD. Diagnostic validity of a standardized neuropsychological battery derived from Luria’s neuropsychological tests. J Consult Clin Psychol. 1978;46:1258–1265. doi: 10.1037/0022-006X.46.6.1258.
    1. Mahieux-Laurent F, Fabre C, Galbrun E, Dubrulle A, Moroni C. Validation of a brief screening scale evaluating praxic abilities for use in memory clinics. Evaluation in 419 controls, 127 mild cognitive impairment and 320 demented patients. Rev Neurol (Paris) 2009;165:560–567. doi: 10.1016/j.neurol.2008.11.016.
    1. Rey A. Manuel: test de copie et de reproduction de mémoire de figures géométriques complexes. Paris: Centre de Psychologie Appliquée; 1959.
    1. Jensen AR. Scoring the Stroop Test. Acta Psychol. 1965;24:398–408. doi: 10.1016/0001-6918(65)90024-7.
    1. Wechsler D. Wechsler Memory Scale Revised manual. San Antonio: The Psychological Corporation; 1959.
    1. Reitan R. Validity of the Trail Making Test as an indicator of organic brain damage. Percept Mot Ski. 1958;8:271–276.
    1. Liu Y, Zhu L, Plössl K, Choi SR, Qiao H, Sun X, et al. Optimization of automated radiosynthesis of [18F]AV-45: a new PET imaging agent for Alzheimer’s disease. Nucl Med Biol. 2010;37:917–925. doi: 10.1016/j.nucmedbio.2010.05.001.
    1. R Development Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria; 2011. ISBN 3-900051-07-0. URL
    1. Ikonomovic MD, Klunk WE, Abrahamson EE, Mathis CA, Price JC, Tsopelas ND, et al. Post-mortem correlates of in vivo PiB-PET amyloid imaging in a typical case of Alzheimer’s disease. Brain. 2008;131:1630–1645. doi: 10.1093/brain/awn016.
    1. Raji CA, Becker JT, Tsopelas ND, Price JC, Mathis CA, Saxton JA, et al. Characterizing regional correlation, laterality and symmetry of amyloid deposition in mild cognitive impairment and Alzheimer’s disease with Pittsburgh Compound B. J Neurosci Methods. 2008;172:277–282. doi: 10.1016/j.jneumeth.2008.05.005.
    1. Rowe CC, Ng S, Ackermann U, Gong SJ, Pike K, Savage G, et al. Imaging beta-amyloid burden in aging and dementia. Neurology. 2007;68:1718–1725. doi: 10.1212/01.wnl.0000261919.22630.ea.
    1. Villemagne VL, Ong K, Mulligan RS, Holl G, Pejoska S, Jones G, et al. Amyloid imaging with (18)F-florbetaben in Alzheimer disease and other dementias. J Nucl Med. 2011;52:1210–1217. doi: 10.2967/jnumed.111.089730.
    1. Halliday G, Song Y, Harding A. Striatal β-amyloid in dementia with Lewy bodies but not Parkinson’s disease. J Neural Transm. 2011;118:713–719. doi: 10.1007/s00702-011-0641-6.
    1. Koivunen J, Verkkoniemi A, Aalto S, Paetau A, Ahonen JP, Viitanen M, et al. PET amyloid ligand [11C]PIB uptake shows predominantly striatal increase in variant Alzheimer’s disease. Brain. 2008;131:1845–1853. doi: 10.1093/brain/awn107.
    1. Furukawa K, Okamura N, Tashiro M, Waragai M, Furumoto S, Iwata R, et al. Amyloid PET in mild cognitive impairment and Alzheimer’s disease with BF-227: comparison to FDG-PET. J Neurol. 2010;257:721–727. doi: 10.1007/s00415-009-5396-8.
    1. Reiman EM, Chen K, Liu X, Bandy D, Yu M, Lee W, et al. Fibrillar amyloid-beta burden in cognitively normal people at 3 levels of genetic risk for Alzheimer’s disease. Proc Natl Acad Sci U S A. 2009;106:6820–6825. doi: 10.1073/pnas.0900345106.
    1. Grimmer T, Tholen S, Yousefi BH, Alexopoulos P, Forschler A, Forstl H, et al. Progression of cerebral amyloid load is associated with the apolipoprotein E epsilon4 genotype in Alzheimer’s disease. Biol Psychiatry. 2010;68:879–884. doi: 10.1016/j.biopsych.2010.05.013.

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