Differential effects of global and cerebellar normalization on detection and differentiation of dementia in FDG-PET studies
Abstract
FDG-PET ([18F]fluorodeoxyglucose positron emission tomography) is frequently used to improve the differential diagnosis of dementia. However, a fundamental methodological issue of the reference area for the intensity normalization procedure is still unsolved. Here, we systematically compared the two most commonly used normalization methods to the cerebral and to the cerebellar metabolic rate for glucose with regard to detection and differentiation of dementia syndromes. FDG-PET imaging was performed on 19 subjects with early Alzheimer's disease, 13 subjects with early frontotemporal lobar degeneration and 10 subjects complaining of memory impairment, which had not been confirmed by comprehensive clinical testing. Images were normalized to either the cerebral or the cerebellar metabolic rate for glucose. Differences in relative regional glucose metabolism were assessed by voxelwise comparison. Analysis using the two normalization procedures revealed remarkable differential effects. Whereas cerebellar normalization was superior in identifying dementia patients in comparison to control subjects, cerebral normalization showed better results for differential diagnosis between types of dementia. These effects were shown for both, Alzheimer's disease and frontotemporal lobar degeneration. Relative hypermetabolism in comparison to the control group was only detected in both kinds of dementia using global normalization. The results indicate that normalization has a decisive impact on diagnostic accuracy in dementia. While cerebellar normalization seems to be more sensitive for early diagnosis, cerebral global normalization might be superior for differential diagnostic purposes in dementia syndromes.
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FDG-PET measurement can differentiate AD patients from other clinical diagnoses.
“this measurement can be used to differentiate AD patients from other clinical diagnoses [221]”
From Genetic architecture of Alzheimer's disease (2020) · cites this paper as [221]
Cites
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984) · Neurology · doi:10.1212/wnl.34.7.939 · Cited by 27,915 · see citing works
The Clinical Dementia Rating (CDR): Current version and scoring rules
Morris, J. C. (1993) · Neurology · doi:10.1212/wnl.43.11.2412-a · Cited by 9,882 · see citing works
Frontotemporal lobar degeneration: A consensus on clinical diagnostic criteria
Neary, D., Snowden, J. S., Gustafson, L., Passant, U., Stuss, D., Black, S., Freedman, M., Kertesz, A., Robert, P. H., Albert, M., et al. (1998) · Neurology · doi:10.1212/wnl.51.6.1546 · Cited by 5,047 · see citing works
Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS–ADRDA criteria
Dubois, B., Feldman, H. H., Jacova, C., DeKosky, S. T., Barberger-Gateau, P., Cummings, J., Delacourte, A., Galasko, D., Gauthier, S., Jicha, G., et al. (2007) · The Lancet Neurology · doi:10.1016/s1474-4422(07)70178-3 · Cited by 4,411 · see citing works
Correction for partial volume effects in PET: principle and validation.
ROUSSET, O. G., Ma, Y., & Evans, A. C. (1998) · PubMed · Cited by 919 · see citing works
Müller‐Gärtner, H. W., Links, J. M., Prince, J. L., Bryan, R. N., McVeigh, E. R., Leal, J. P., Davatzikos, C. A., & Frost, J. J. (1992) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.1992.81 · Cited by 756 · see citing works
Mosconi, L., Tsui, W. H., Herholz, K., Pupi, A., Drzezga, A., Lucignani, G., Reiman, E. M., Holthoff, V., Kalbe, E., Sorbi, S., et al. (2008) · Journal of Nuclear Medicine · doi:10.2967/jnumed.107.045385 · Cited by 726 · see citing works
Areas 3a, 3b, and 1 of Human Primary Somatosensory Cortex
Geyer, S., Schleicher, A., & Zilles, K. (1999) · NeuroImage · doi:10.1006/nimg.1999.0440 · Cited by 454 · see citing works
MCI conversion to dementia and the APOE genotype
Mosconi, L., Perani, D., Sorbi, S., Herholz, K., Nacmias, B., Holthoff‐Detto, V., Salmon, É., Baron, J., Cristofaro, M. T. D., Padovani, A., et al. (2004) · Neurology · doi:10.1212/01.wnl.0000147469.18313.3b · Cited by 344 · see citing works
Schroeter, M. L., Stein, T., Maslowski, N. I., & Neumann, J. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.05.037 · Cited by 334 · see citing works
Self-citationBrain activation in the processing of Chinese characters and words: A functional MRI study
Tan, L., Spinks, J. A., Gao, J., Liu, H., Perfetti, C. A., Xiong, J., Stofer, K. A., Pu, Y., Liu, Y., & Fox, P. T. (2000) · Human Brain Mapping · doi:10.1002/(sici)1097-0193(200005)10:1 · Cited by 304 · see citing works
What does fluorodeoxyglucose PET imaging add to a clinical diagnosis of dementia?
Jagust, W. J., Reed, B., Mungas, D., Ellis, W. G., & DeCarli, C. S. (2007) · Neurology · doi:10.1212/01.wnl.0000269790.05105.16 · Cited by 299 · see citing works
Minoshima, S., Frey, K. A., Foster, N. L., & Kuhl, D. E. (1995) · Journal of Computer Assisted Tomography · doi:10.1097/00004728-199507000-00006 · Cited by 252 · cited 10× · see citing works
“Second, normalization to the cerebellum provides an easily determined and reliable alternative to the sensorimotor cortex which is also frequently used (Minoshima et al., 1995; Santens et al., 2001; Sakamoto et al., 2002; Yakushev et al., 2008, 2009), but which has the disadvantage that the surface appearance and stru…”
BackgroundMethodInfluentialStructure of the human sensorimotor system. I: Morphology and cytoarchitecture of the central sulcus
WHITE, L. E. (1997) · Cerebral Cortex · doi:10.1093/cercor/7.1.18 · Cited by 234 · see citing works
Quarantelli, M., Berkouk, K., Prinster, A., Landeau, B., Svarer, C., Balkay, L., Alfano, B., Brunetti, A., Baron, J., & Salvatore, M. (2004) · PubMed · Cited by 224 · see citing works
Ishii, K., Willoch, F., Minoshima, S., Drzezga, A. E., Ficaro, E. P., Cross, D. J., Kuhl, D. E., & Schwaiger, M. (2001) · PubMed · Cited by 206 · see citing works
Cognitive profiles differ in autopsy-confirmed frontotemporal dementia and AD
Rascovsky, K., Salmon, D. P., Ho, G. J., Galasko, D. R., Peavy, G. M., Hansen, L. A., & Thal, L. J. (2002) · Neurology · doi:10.1212/wnl.58.12.1801 · Cited by 197 · see citing works
(2005) · PubMed · Cited by 191 · see citing works
Neural networks in frontotemporal dementia—A meta-analysis
Schroeter, M. L., Raczka, K. A., Neumann, J., & von Cramon, D. Y. (2006) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2006.10.023 · Cited by 164 · see citing works
Self-citationTowards a nosology for frontotemporal lobar degenerations—A meta-analysis involving 267 subjects
Schroeter, M. L., Raczka, K. A., Neumann, J., & von Cramon, D. Y. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.03.024 · Cited by 160 · see citing works
Self-citationDirect comparison of spatially normalized PET and SPECT scans in Alzheimer's disease.
Herholz, K., Schopphoff, H., Schmidt, M. V., Mielke, R., Eschner, W., Scheidhauer, K., Schicha, H., Heiss, W., & Ebmeier, K. P. (2002) · PubMed · Cited by 151 · see citing works
Mielke, R., Pietrzyk, U., Jacobs, A., Fink, G., Ichimiya, A., Kessler, J., Herholz, K., & Heiß, W.-D. (1994) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/bf00181059 · Cited by 140 · see citing works
Sakamoto, S., Ishii, K., Sasaki, M., Hosaka, K., Mori, T., Matsui, M., Hirono, N., & Mori, E. (2002) · Journal of the Neurological Sciences · doi:10.1016/s0022-510x(02)00114-4 · Cited by 139 · see citing works
Yakushev, I. Y., Hammers, A., Fellgiebel, A., Schmidtmann, I. M., Scheurich, A., Buchholz, H., Peters, J., Bartenstein, P., Lieb, K., & Schreckenberger, M. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.07.015 · Cited by 130 · see citing works
Yakushev, I. Y., Landvogt, C., Buchholz, H., Fellgiebel, A., Hammers, A., Scheurich, A., Schmidtmann, I. M., Gerhard, A., Schreckenberger, M., & Bartenstein, P. (2008) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2007.11.004 · Cited by 118 · see citing works
Sole, A. D., Clerici, F., Chiti, A., Lecchi, M., Mariani, C. B., Maggiore, L., Mosconi, L., & Lucignani, G. (2008) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-008-0773-6 · Cited by 110 · see citing works
Samuraki, M., Matsunari, I., Chen, W.-P., Yajima, K., Yanase, D., Fujikawa, A., Takeda, N., Nishimura, S., Matsuda, H., & Yamada, M. (2007) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-007-0454-x · Cited by 92 · see citing works
Ishii, K., Sasaki, H., Kono, A. K., Miyamoto, N., Fukuda, T., & Mori, E. (2005) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-004-1740-5 · Cited by 88 · see citing works
Borghammer, P., Cumming, P. D., Aanerud, J., & GJEDDE, A. H. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.07.042 · Cited by 82 · see citing works
Mosconi, L., Santi, S. D., Li, Y., Li, J., Zhan, J., Tsui, W. H., Boppana, M., Pupi, A., & de Leon, M. J. (2005) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-005-1956-z · Cited by 81 · see citing works
Cerebellar glucose consumption in normal and pathologic states using fluorine-FDG and PET.
Kushner, M., Tobin, M., Alavi, A., et al. (1987) · PubMed · Cited by 70 · see citing works
Walker, A., Meares, S., Sachdev, P. S., & Brodaty, H. (2005) · International Psychogeriatrics · doi:10.1017/s1041610204000778 · Cited by 62 · see citing works
Concurrent CBF and CMRGlc changes during human brain activation by combined fMRI–PET scanning
Newberg, A. B., Wang, J., Rao, H., Swanson, R. L., Wintering, N., Karp, J. S., Alavi, A. A., Greenberg, J. H., & Detre, J. A. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.06.040 · Cited by 60 · see citing works
Buchert, R., Wilke, F., Chakrabarti, B., Martin, B., Brenner, W., Mester, J., & Clausen, M. (2005) · Journal of Neuroimaging · doi:10.1111/j.1552-6569.2005.tb00335.x · Cited by 51 · see citing works
Buchert, R. (2005) · Journal of Neuroimaging · doi:10.1177/1051228405280169 · Cited by 40 · see citing works
Santens, P., Bleecker, J. D., Goethals, P., Strijckmans, K., Lemahieu, I. A., Slegers, G., Dierckx, R. A., & Reuck, J. D. (2001) · European Neurology · doi:10.1159/000052084 · Cited by 40 · see citing works
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Chouliaras, L., & O’Brien, J. T. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02215-8 · Cited by 186 · see citing works
“It is analysed either using expert visual rating or specialised quantitative analytical software [106 – 108].”
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Neuner, S. M., TCW, J., & Goate, A. M. (2020) · Neurobiology of Disease · doi:10.1016/j.nbd.2020.104976 · Cited by 126 · see citing works
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InfluentialMeyer, S., Mueller, K., Stuke, K., Bisenius, S., Diehl-Schmid, J., Jessen, F., Kassubek, J., Kornhuber, J., Ludolph, A. C., Prudlo, J., et al. (2017) · NeuroImage: Clinical · doi:10.1016/j.nicl.2017.02.001 · Cited by 83 · see citing works
Self-citationIaccarino, L., Sala, A., Caminiti, S. P., Presotto, L., Perani, D., & Initiative, F. T. A. D. N. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-190954 · Cited by 40 · see citing works
- Authors
- Dukart, J., Mueller, K., Horstmann, A., Vogt, B., Frisch, S., Barthel, H., Becker, G., Möller, H. E., Villringer, A., Sabri, O., & Schroeter, M. L.
- Affiliations
- Max Planck Institute for Human Cognitive and Brain Sciences (DE)
- Leipzig University (DE)
- Corresponding author
- Dukart, Juergen
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2010-01
- Volume
- 49
- Issue
- 2
- Pages
- 1490-1495
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2165206443
- Cited by
- 134
- References
- 36
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 6 · 2023: 5 · 2022: 3 · 2021: 7 · 2020: 7 · 2019: 13 · 2018: 10 · 2017: 11 · 2016: 11 · 2015: 13 · 2014: 10 · 2013: 8 · 2012: 7
- FWCI
- 4.32
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Max Planck Digital Library (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (submittedVersion)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- FDG-PET, global normalization, cerebral metabolic rate of glucose, Alzheimer's disease, frontotemporal lobar degeneration, differential diagnosis of dementia, early detection of dementia, regional glucose metabolism, memory impairment
- MeSH terms
- Age Factors, Alzheimer Disease, Analysis of Variance, Brain, Brain Mapping, Cerebellum, Dementia, Diagnosis, Differential, Female, Glucose, Humans, Male, Memory Disorders, Middle Aged, Severity of Illness Index, Signal Processing, Computer-Assisted, Radiopharmaceuticals, Fluorodeoxyglucose F18, Positron-Emission Tomography, Frontotemporal Lobar Degeneration
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