Meta-analytic Comparison Between PIB-PET and FDG-PET Results in Alzheimer’s Disease and MCI

Cell Biochemistry and Biophysics

Volumn 71, Issue 1, 2015, Pages 17-26

  He, Wei ^a   Liu, Dinghua ^a   Radua, Joaquim ^b,c   Li, GuoQing ^a   Han, Bojun ^a   Sun, Zhigang ^a  

^a JIANGYIN PEOPLE S HOSPITAL   (China)

^b KING'S COLLEGE LONDON   (United Kingdom)

^c CENTRO DE INVESTIGACIÓN BIOMÉDICA EN RED DE SALUD MENTAL CIBERSAM   (Spain)

Author keywords

Meta analysis; Mild cognitive impairment; Voxel based morphometry

Indexed keywords

2-(4'-(METHYLAMINO)PHENYL)-6-HYDROXYBENZOTHIAZOLE; ANILINE DERIVATIVE; FLUORODEOXYGLUCOSE F 18; GLUCOSE; THIAZOLE DERIVATIVE;

ALZHEIMER DISEASE; COMPARATIVE STUDY; HUMAN; META ANALYSIS; METABOLISM; MILD COGNITIVE IMPAIRMENT; POSITRON EMISSION TOMOGRAPHY; PROCEDURES; SCINTISCANNING;

ALZHEIMER DISEASE; ANILINE COMPOUNDS; FLUORODEOXYGLUCOSE F18; GLUCOSE; HUMANS; MILD COGNITIVE IMPAIRMENT; POSITRON-EMISSION TOMOGRAPHY; THIAZOLES;

EID: 84922073672     PISSN: 10859195     EISSN: 15590283     Source Type: Journal    
DOI: 10.1007/s12013-014-0138-7     Document Type: Article

References (55)

1. Rinne, J. O., & Nagren, K. (2010). Positron emission tomography in at risk patients and in the progression of mild cognitive impairment to Alzheimer’s disease. Journal of Alzheimer’s Disease,19(1), 291–300.
2. Berti, V., Osorio, R. S., Mosconi, L., Li, Y., De Santi, S., & de Leon, M. J. (2010). Early detection of Alzheimer’s disease with PET imaging. Neurodegenerative Disease,7(1–3), 131–135.
3. Ashburner, J., & Friston, K. J. (2000). Voxel-based morphometry—The methods. Neuroimage,11(6 Pt 1), 805–821.
4. Ashburner, J., & Friston, K. J. (2001). Why voxel-based morphometry should be used. Neuroimage,14(6), 1238–1243.
5. Svarer, C., Madsen, K., Hasselbalch, S. G., Pinborg, L. H., Haugbol, S., Frokjaer, V. G., et al. (2005). MR-based automatic delineation of volumes of interest in human brain PET images using probability maps. Neuroimage,24(4), 969–979.
6. Radua, J., & Mataix-Cols, D. (2009). Voxel-wise meta-analysis of grey matter changes in obsessive-compulsive disorder. British Journal of Psychiatry,195(5), 393–402.
7. Radua, J., Mataix-Cols, D., Phillips, M. L., El-Hage, W., Kronhaus, D. M., Cardoner, N., et al. (2011). A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps. European Psychiatry,27(8), 605–611.
8. Turkeltaub, P. E., Eden, G. F., Jones, K. M., & Zeffiro, T. A. (2002). Meta-analysis of the functional neuroanatomy of single-word reading: Method and validation. Neuroimage,16(3 Pt 1), 765–780.
9. Wager, T. D., Lindquist, M., & Kaplan, L. (2007). Meta-analysis of functional neuroimaging data: Current and future directions. Social Cognitive and Affective Neuroscience,2(2), 150–158.
10. McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984). 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,34(7), 939–944.
11. Petersen, R. C., Doody, R., Kurz, A., Mohs, R. C., Morris, J. C., Rabins, P. V., et al. (2001). Current concepts in mild cognitive impairment. Archives of Neurology,58(12), 1985–1992.
12. Petersen, R. C., Parisi, J. E., Dickson, D. W., Johnson, K. A., Knopman, D. S., Boeve, B. F., et al. (2006). Neuropathologic features of amnestic mild cognitive impairment. Archives of Neurology,63(5), 665–672.
13. Lancaster, J. L., Tordesillas-Gutierrez, D., Martinez, M., Salinas, F., Evans, A., Zilles, K., et al. (2007). Bias between MNI and Talairach coordinates analyzed using the ICBM-152 brain template. Human Brain Mapping,28(11), 1194–1205.
14. Okello, A., Koivunen, J., Edison, P., Archer, H. A., Turkheimer, F. E., Nagren, K., et al. (2009). Conversion of amyloid positive and negative MCI to AD over 3 years: An 11C-PIB PET study. Neurology,73(10), 754–760.
15. Mikhno, A., Devanand, D., Pelton, G., Cuasay, K., Gunn, R., Upton, N., et al. (2008). Voxel-based analysis of 11C-PIB scans for diagnosing Alzheimer’s disease. Journal of Nuclear Medicine,49(8), 1262–1269.
16. Frisoni, G. B., Lorenzi, M., Caroli, A., Kemppainen, N., Nagren, K., & Rinne, J. O. (2009). In vivo mapping of amyloid toxicity in Alzheimer disease. Neurology,72(17), 1504–1511.
17. Ng, S. Y., Villemagne, V. L., Masters, C. L., & Rowe, C. C. (2007). Evaluating atypical dementia syndromes using positron emission tomography with carbon 11 labeled Pittsburgh Compound B. Archives of Neurology,64(8), 1140–1144.
18. Nelissen, N., Vandenbulcke, M., Fannes, K., Verbruggen, A., Peeters, R., Dupont, P., et al. (2007). Abeta amyloid deposition in the language system and how the brain responds. Brain,130(Pt 8), 2055–2069.
19. Drzezga, A., Grimmer, T., Henriksen, G., Muhlau, M., Perneczky, R., Miederer, I., et al. (2009). Effect of APOE genotype on amyloid plaque load and gray matter volume in Alzheimer disease. Neurology,72(17), 1487–1494.
20. Drzezga, A., Grimmer, T., Henriksen, G., Stangier, I., Perneczky, R., Diehl-Schmid, J., et al. (2008). Imaging of amyloid plaques and cerebral glucose metabolism in semantic dementia and Alzheimer’s disease. Neuroimage,39(2), 619–633.
21. Ziolko, S. K., Weissfeld, L. A., Klunk, W. E., Mathis, C. A., Hoge, J. A., Lopresti, B. J., et al. (2006). Evaluation of voxel-based methods for the statistical analysis of PIB PET amyloid imaging studies in Alzheimer’s disease. Neuroimage,33(1), 94–102.
22. Chetelat, G., Villemagne, V. L., Pike, K. E., Ellis, K. A., Bourgeat, P., Jones, G., et al. (2011). Independent contribution of temporal beta-amyloid deposition to memory decline in the pre-dementia phase of Alzheimer’s disease. Brain,134(Pt 3), 798–807.
23. Shin, J., Lee, S. Y., Kim, S. J., Kim, S. H., Cho, S. J., & Kim, Y. B. (2010). Voxel-based analysis of Alzheimer’s disease PET imaging using a triplet of radiotracers: PIB, FDDNP, and FDG. Neuroimage,52(2), 488–496.
24. Kemppainen, N. M., Aalto, S., Wilson, I. A., Nagren, K., Helin, S., Bruck, A., et al. (2007). PET amyloid ligand [11C]PIB uptake is increased in mild cognitive impairment. Neurology,68(19), 1603–1606.
25. Del Sole, A., Clerici, F., Chiti, A., Lecchi, M., Mariani, C., Maggiore, L., et al. (2008). Individual cerebral metabolic deficits in Alzheimer’s disease and amnestic mild cognitive impairment: An FDG PET study. European Journal of Nuclear Medicine and Molecular Imaging,35(7), 1357–1366.
26. Smith, G. S., Kramer, E., Ma, Y., Hermann, C. R., Dhawan, V., Chaly, T., et al. (2009). Cholinergic modulation of the cerebral metabolic response to citalopram in Alzheimer’s disease. Brain,132(Pt 2), 392–401.
27. Yakushev, I., Landvogt, C., Buchholz, H. G., Fellgiebel, A., Hammers, A., Scheurich, A., et al. (2008). Choice of reference area in studies of Alzheimer’s disease using positron emission tomography with fluorodeoxyglucose-F18. Psychiatry Research,164(2), 143–153.
28. Chetelat, G., Desgranges, B., Landeau, B., Mezenge, F., Poline, J. B., de la Sayette, V., et al. (2008). Direct voxel-based comparison between grey matter hypometabolism and atrophy in Alzheimer’s disease. Brain,131(Pt 1), 60–71.
29. Habeck, C., Foster, N. L., Perneczky, R., Kurz, A., Alexopoulos, P., Koeppe, R. A., et al. (2008). Multivariate and univariate neuroimaging biomarkers of Alzheimer’s disease. Neuroimage,40(4), 1503–1515.
30. Hunt, A., Schonknecht, P., Henze, M., Seidl, U., Haberkorn, U., & Schroder, J. (2007). Reduced cerebral glucose metabolism in patients at risk for Alzheimer’s disease. Psychiatry Research,155(2), 147–154.
31. Kim, S. H., Seo, S. W., Yoon, D. S., Chin, J., Lee, B. H., Cheong, H. K., et al. (2010). Comparison of neuropsychological and FDG-PET findings between early- versus late-onset mild cognitive impairment: A five-year longitudinal study. Dementia and Geriatric Cognitive Disorders,29(3), 213–223.
32. Lee, D. Y., Seo, E. H., Choo, I. H., Kim, S. G., Lee, J. S., Lee, D. S., et al. (2008). Neural correlates of the Clock Drawing Test performance in Alzheimer’s disease: A FDG-PET study. Dementia and Geriatric Cognitive Disorders,26(4), 306–313.
33. Matsunari, I., Samuraki, M., Chen, W. P., Yanase, D., Takeda, N., Ono, K., et al. (2007). Comparison of 18F-FDG PET and optimized voxel-based morphometry for detection of Alzheimer’s disease: Aging effect on diagnostic performance. Journal of Nuclear Medicine,48(12), 1961–1970.
34. Mosconi, L., Herholz, K., Prohovnik, I., Nacmias, B., De Cristofaro, M. T., Fayyaz, M., et al. (2005). Metabolic interaction between ApoE genotype and onset age in Alzheimer’s disease: Implications for brain reserve. Journal of Neurology, Neurosurgery and Psychiatry,76(1), 15–23.
35. Wu, X., Chen, K., Yao, L., Ayutyanont, N., Langbaum, J. B., Fleisher, A., et al. (2010). Assessing the reliability to detect cerebral hypometabolism in probable Alzheimer’s disease and amnestic mild cognitive impairment. Journal of Neuroscience Methods,192(2), 277–285.
36. Xu, C., Wang, Z., Fan, M., Liu, B., Song, M., Zhen, X., et al. (2010). Effects of BDNF Val66Met polymorphism on brain metabolism in Alzheimer’s disease. NeuroReport,21(12), 802–807.
37. Choo, I. H., Lee, D. Y., Youn, J. C., Jhoo, J. H., Kim, K. W., Lee, D. S., et al. (2007). Topographic patterns of brain functional impairment progression according to clinical severity staging in 116 Alzheimer disease patients: FDG-PET study. Alzheimer Disease and Associated Disorders,21(2), 77–84.
38. Ishii, K., Sasaki, H., Kono, A. K., Miyamoto, N., Fukuda, T., & Mori, E. (2005). Comparison of gray matter and metabolic reduction in mild Alzheimer’s disease using FDG-PET and voxel-based morphometric MR studies. European Journal of Nuclear Medicine and Molecular Imaging,32(8), 959–963.
39. Kanda, T., Ishii, K., Uemura, T., Miyamoto, N., Yoshikawa, T., Kono, A. K., et al. (2008). Comparison of grey matter and metabolic reductions in frontotemporal dementia using FDG-PET and voxel-based morphometric MR studies. European Journal of Nuclear Medicine and Molecular Imaging,35(12), 2227–2234.
40. Kawachi, T., Ishii, K., Sakamoto, S., Sasaki, M., Mori, T., Yamashita, F., et al. (2006). Comparison of the diagnostic performance of FDG-PET and VBM-MRI in very mild Alzheimer’s disease. European Journal of Nuclear Medicine and Molecular Imaging,33(7), 801–809.
41. Kim, E. J., Cho, S. S., Jeong, Y., Park, K. C., Kang, S. J., Kang, E., et al. (2005). Glucose metabolism in early onset versus late onset Alzheimer’s disease: An SPM analysis of 120 patients. Brain,128(Pt 8), 1790–1801.
42. Langbaum, J. B., Chen, K., Lee, W., Reschke, C., Bandy, D., Fleisher, A. S., et al. (2009). Categorical and correlational analyses of baseline fluorodeoxyglucose positron emission tomography images from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Neuroimage,45(4), 1107–1116.
43. Sakamoto, S., Ishii, K., Hosaka, K., Mori, T., Sasaki, M., & Mori, E. (2005). Detectability of hypometabolic regions in mild Alzheimer disease: Function of time after the injection of 2-[fluorine 18]-fluoro-2-deoxy-d-glucose. AJNR. American Journal of Neuroradiology,26(4), 843–847.
44. Samuraki, M., Matsunari, I., Chen, W. P., Yajima, K., Yanase, D., Fujikawa, A., et al. (2007). Partial volume effect-corrected FDG PET and grey matter volume loss in patients with mild Alzheimer’s disease. European Journal of Nuclear Medicine and Molecular Imaging,34(10), 1658–1669.
45. Yuan, X., Shan, B., Ma, Y., Tian, J., Jiang, K., Cao, Q., et al. (2010). Multi-center study on Alzheimer’s disease using FDG PET: Group and individual analyses. Journal of Alzheimer’s Disease,19(3), 927–935.
46. Ishii, H., Ishikawa, H., Meguro, K., Tashiro, M., & Yamaguchi, S. (2009). Decreased cortical glucose metabolism in converters from CDR 0.5 to Alzheimer’s disease in a community: The Osaki-Tajiri Project. International Psychogeriatrics,21(1), 148–156.
47. Morbelli, S., Piccardo, A., Villavecchia, G., Dessi, B., Brugnolo, A., Piccini, A., et al. (2010). Mapping brain morphological and functional conversion patterns in amnestic MCI: A voxel-based MRI and FDG-PET study. European Journal of Nuclear Medicine and Molecular Imaging,37(1), 36–45.
48. Schroeter, M. L., Stein, T., Maslowski, N., & Neumann, J. (2009). Neural correlates of Alzheimer’s disease and mild cognitive impairment: A systematic and quantitative meta-analysis involving 1351 patients. Neuroimage,47(4), 1196–1206.
49. Edison, P., Archer, H. A., Hinz, R., Hammers, A., Pavese, N., Tai, Y. F., et al. (2007). Amyloid, hypometabolism, and cognition in Alzheimer disease: An [11C]PIB and [18F]FDG PET study. Neurology,68(7), 501–508.
50. Herholz, K., Carter, S. F., & Jones, M. (2007). Positron emission tomography imaging in dementia. The British Journal of Radiology,80 Spec No. 2, S160–S167.
51. Wong, K. P., Wardak, M., Shao, W., Dahlbom, M., Kepe, V., Liu, J., et al. (2010). Quantitative analysis of [18F]FDDNP PET using subcortical white matter as reference region. European Journal of Nuclear Medicine and Molecular Imaging,37(3), 575–588.
52. Braak, H., & Braak, E. (1991). Neuropathological staging of Alzheimer-related changes. Acta Neuropathologica,82(4), 239–259.
53. Hoffman, E. J., Huang, S. C., & Phelps, M. E. (1979). Quantitation in positron emission computed tomography: 1. Effect of object size. Journal of Computer Assisted Tomography,3(3), 299–308.
54. Tohru, S., Isabelle, M., Ken, H., Gjermund, H., Christine, P., Markus, S., et al. (2009). The effect of partial volume effect correction on PIB and FDG PET data in MCI and AD patients. Journal of Nuclear Medicine,50(Supplement 2), 428.
55. Salimi-Khorshidi, G., Smith, S. M., Keltner, J. R., Wager, T. D., & Nichols, T. E. (2009). Meta-analysis of neuroimaging data: A comparison of image-based and coordinate-based pooling of studies. Neuroimage,45(3), 810–823.