FDG-PET in der Differenzialdiagnostik neurodegenerativer Demenzerkrankungen

R. Buchert; S. Förster

doi:10.1055/s-0042-113848

Der Nuklearmediziner, Table of Contents

Der Nuklearmediziner 2016; 39(04): 287-298
DOI: 10.1055/s-0042-113848

Neurobildgebung

FDG-PET in der Differenzialdiagnostik neurodegenerativer Demenzerkrankungen

The Role of FDG PET in the Differential Diagnosis of Neurodegenerative Dementias

Authors

R. Buchert

¹Klinik für Nuklearmedizin, Charité-Universitätsmedizin Berlin, Berlin
S. Förster

²Klinik und Poliklinik für Nuklearmedizin, Klinikum rechts der Isar, Technische Universität München, München

³Klinik und Institut für Nuklearmedizin, Klinikum Bayreuth, Bayreuth

Abstract

Zusammenfassung

Die PET des Gehirns mit dem Glukoseanalogon [¹⁸F]FDG wird seit Jahrzehnten in der Diagnostik und Differenzialdiagnostik von Demenzerkrankungen eingesetzt, insbesondere bei klinisch unklarem Verdacht auf eine neurodegenerative Ätiologie. Während die FDG-PET in der Frühdiagnostik der Alzheimer-Krankheit künftig wahrscheinlich zunehmend durch spezifische Biomarker für Amyloid-Pathologie, z. B. die Amyloid-PET, ersetzt wird, ist davon auszugehen, dass sie in der Differenzialdiagnostik von Demenzerkrankungen weiterhin eine wichtige Rolle spielen wird.

Im vorliegenden Übersichtsartikel werden daher Grundlagen und aktueller Stellenwert der Hirn-[¹⁸F]FDG-PET in der Differenzialdiagnostik neurodegenerativer Demenzerkrankungen in der klinischen Patientenversorgung dargelegt. Darüber hinaus geht der Artikel auf methodische Aspekte von Patientenvorbereitung, Datenakquisition und (automatischer) Datenanalyse ein. Abschließend werden kurz mögliche Alternativverfahren wie die Hirnperfusions-SPECT und -MRT diskutiert.

Abstract

PET of the brain with the glucose analog [¹⁸F]FDG is successfully used since decades to support the diagnosis and differential diagnosis of dementia, particularly in patients with clinically uncertain suspicion of a neurodegenerative etiology. In the early diagnosis of Alzheimer’s disease, FDG-PET might be replaced by biomarkers of amyloid pathology in the future. However, we expect that FDG-PET will continue to play an important role in the differential diagnosis of dementias.

This review article elucidates the basic principles and the current value of brain-[¹⁸F]FDG-PET in the differential diagnosis of neurodegenerative diseases in everyday clinical patient care. Furthermore, the article discusses some important methodological aspects of patient preparation, data acquisition and (automatic) data analysis, as well as alternative imaging methods such as perfusion SPECT and perfusion MRI of the brain.

Schlüsselwörter

Alzheimer-Demenz - MCI - LKS - PET - [¹⁸F]FDG - Hirnmetabolismus

Key words

Alzheimer’s dementia - MCI - PET - [¹⁸F]FDG - brain metabolism

Full Text

References

Literatur
1 Albert MS, DeKosky ST, Dickson D 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
2 Alzheimer’s Association . 2014 Alzheimer’s disease facts and figures. Alzheimers Dement. 2014 10. e47-e92
3 Arlt S, Brassen S, Jahn H et al. Association between FDG uptake, CSF biomarkers and cognitive performance in patients with probable Alzheimer’s disease. Eur J Nucl Med Mol Imaging 2009; 36: 1090-1100
4 Barthel H, Schroeter ML, Hoffmann KT et al. PET/MR in dementia and other neurodegenerative diseases. Semin Nucl Med 2015; 45: 224-233
5 Baumgartner A, Rauer S, Mader I et al. Cerebral FDG-PET and MRI findings in autoimmune limbic encephalitis: correlation with autoantibody types. J Neurol 2013; 260: 2744-2753
6 Bermejo-Pareja F, Benito-Leon J, Vega S et al. Incidence and subtypes of dementia in three elderly populations of central Spain. J Neurol Sci 2008; 264: 63-72
7 Bhogal P, Mahoney C, Graeme-Baker S et al. The common dementias: a pictorial review. Eur Radiol 2013; 23: 3405-3417
8 Bickel H. Demenzsyndrom und Alzheimer Krankheit: Eine Schätzung des Krankenbestandes und der jährlichen Neuerkrankungen in Deutschland. Das Gesundheitswesen 2000; 62: 211-218
9 Biomarkers Definitions Working Group . Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther 2001; 69: 89-95
10 Bloudek LM, Spackman DE, Blankenburg M et al. Review and meta-analysis of biomarkers and diagnostic imaging in Alzheimer’s disease. J Alzheimers Dis 2011; 26: 627-645
11 Boelmans K, Buchert R. Zerebrale Bildgebung bei Demenzen: State-of-the-Art. Akt Neurol 2013; 40: 200-212
12 Burdette JH, Minoshima S, Vander Borght T et al. Alzheimer disease: improved visual interpretation of PET images by using three-dimensional stereotaxic surface projections. Radiology 1996; 198: 837-843
13 Bradley KM, O’Sullivan VT, Soper ND et al. Cerebral perfusion SPET correlated with Braak pathological stage in Alzheimer’s disease. Brain 2002; 125: 1772-1781
14 Brayne C, Richardson K, Matthews FE et al. Cambridge City Over-75s Cohort Cc75c Study Neuropathology C. Neuropathological correlates of dementia in over-80-year-old brain donors from the population-based Cambridge city over-75s cohort (CC75C) study. J Alzheimers Dis 2009; 18: 645-658
15 Buchert R, Santer R, Brenner W et al. Computer simulations suggest that acute correction of hyperglycaemia with an insulin bolus protocol might be useful in brain FDG PET. Nuklearmedizin 2009; 48: 44-54
16 Buchert R, Wilke F, Chakrabarti B et al. Adjusted scaling of FDG positron emission tomography images for statistical evaluation in patients with suspected Alzheimer’s disease. J Neuroimaging 2005; 15: 348-355
17 Das P, Murphy MP, Younkin LH et al. Reduced effectiveness of Abeta1-42 immunization in APP transgenic mice with significant amyloid deposition. Neurobiol Aging 2001; 22: 721-727
18 Davison CM, O’Brien JT. A comparison of FDG-PET and blood flow SPECT in the diagnosis of neurodegenerative dementias: a systematic review. Int J Geriatr Psychiatry 2014; 29: 551-561
19 Deutsche Gesellschaft für Neurologie und Deutsche Gesellschaft für Psychiatrie und Psychotherapie . 2016 S3-Leitlinie „Demenzen“
20 Doss S, Wandinger KP, Hyman BT et al. High prevalence of NMDA receptor IgA/IgM antibodies in different dementia types. Ann Clin Transl Neurol 2014; 1: 822-832
21 Drzezga A, Barthel H, Minoshima S et al. Potential Clinical Applications of PET/MR Imaging in Neurodegenerative Diseases. J Nucl Med 2014; 55: S47-S55
22 Dubois B, Feldman HH, Jacova C et al. Research criteria for the diagnosis of Alzheimer’s disease: revising the NINCDS-ADRDA criteria. Lancet Neurol 2007; 6: 734-746
23 Dubois B, Feldman HH, Jacova C et al. Advancing research diagnostic criteria for Alzheimer’s disease: the IWG-2 criteria. Lancet Neurol 2014; 13: 614-629
24 Dukart J, Mueller K, Horstmann A et al. Combined evaluation of FDG-PET and MRI improves detection and differentiation of dementia. PLoS One 2011; 6: e18111
25 Eckerstrom C, Olsson E, Borga M et al. Small baseline volume of left hippocampus is associated with subsequent conversion of MCI into dementia: The Goteborg MCI study. J Neurol Sci 2008
26 Farid K, Caillat-Vigneron N, Sibon I. Is brain SPECT useful in degenerative dementia diagnosis?. J Comput Assist Tomogr 2011; 35: 1-3
27 Finke C, Kopp UA, Pajkert A et al. Structural Hippocampal Damage Following Anti-N-Methyl-D-Aspartate Receptor Encephalitis. Biol Psychiatry 2016; 79: 727-734
28 Foster NL, Heidebrink JL, Clark CM et al. FDG-PET improves accuracy in distinguishing frontotemporal dementia and Alzheimer’s disease. Brain 2007; 130: 2616-2635
29 Friston KJ, Holmes AP, Worsley KJ et al. Statistical Parametric Maps in Functional Imaging: A General Linear Approach. Human Brain Mapping 1995; 2: 189-210
30 Förster S, Drzezga A. FDG-PET in der Demenzdiagnostik. Der Nuklearmediziner 2012; 35: 1-7
31 Garibotto V, Heinzer S, Vulliemoz S et al. Clinical Applications of Hybrid PET/MRI in Neuroimaging. Clin Nucl Med 2013; 38: e13-e18
32 Gascon-Bayarri J, Rene R, Del Barrio JL et al. Prevalence of dementia subtypes in El Prat de Llobregat, Catalonia, Spain: the PRATICON study. Neuroepidemiology 2007; 28: 224-234
33 Gorno-Tempini ML, Hillis AE, Weintraub S et al. Classification of primary progressive aphasia and its variants. Neurology 2011; 76: 1006-1014
34 Grant AM, Deller TW, Khalighi MM et al. 2-2012 performance studies for the SiPM-based ToF-PET component of the GE SIGNA PET/MR system. Med Phys 2016; 43: 2334
35 Grundman M, Jack Jr. CR, Petersen RC et al. Hippocampal volume is associated with memory but not monmemory cognitive performance in patients with mild cognitive impairment. J Mol Neurosci 2003; 20: 241-248
36 Habeck C, Foster NL, Perneczky R et al. Multivariate and univariate neuroimaging biomarkers of Alzheimer’s disease. Neuroimage 2008; 40: 1503-1515
37 Heine J, Pruss H, Bartsch T et al. Imaging of autoimmune encephalitis–Relevance for clinical practice and hippocampal function. Neuroscience 2015; 309: 68-83
38 Heiss WD, Habedank B, Klein JC et al. Metabolic rates in small brain nuclei determined by high-resolution PET. J Nucl Med 2004; 45: 1811-1815
39 Herholz K, Schopphoff H, Schmidt M et al. Direct comparison of spatially normalized PET and SPECT scans in Alzheimer’s disease. J Nucl Med 2002; 43: 21-26
40 Higdon R, Foster NL, Koeppe RA et al. A comparison of classification methods for differentiating fronto-temporal dementia from Alzheimer’s disease using FDG-PET imaging. Stat Med 2004; 23: 315-326
41 Hinrichs C, Singh V, Mukherjee L et al. Spatially augmented LPboosting for AD classification with evaluations on the ADNI dataset. Neuroimage 2009; 48: 138-149
42 Ibanez V, Pietrini P, Alexander GE et al. Regional glucose metabolic abnormalities are not the result of atrophy in Alzheimer’s disease. Neurology 1998; 50: 1585-1593
43 Ito K, Shimano Y, Imabayashi E et al. Concordance between (99m)Tc-ECD SPECT and 18F-FDG PET interpretations in patients with cognitive disorders diagnosed according to NIA-AA criteria. Int J Geriatr Psychiatry 2014; 29: 1079-1086
44 Jack Jr. CR, Bennett DA, Blennow K et al. A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers. Neurology 2016; 87: 539-547
45 Jack Jr. CR, Knopman DS, Jagust WJ et al. Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol 2013; 12: 207-216
46 Jellinger KA, Attems J. Neuropathological evaluation of mixed dementia. J Neurol Sci 2007; 257: 80-87
47 Johnson KA, Jones K, Holman BL et al. Preclinical prediction of Alzheimer’s disease using SPECT. Neurology 1998; 50: 1563-1571
48 Josephs KA, Duffy JR, Fossett TR et al. Fluorodeoxyglucose F18 positron emission tomography in progressive apraxia of speech and primary progressive aphasia variants. Arch Neurol 2010; 67: 596-605
49 Kadekaro M, Crane AM, Sokoloff L. Differential effects of electrical stimulation of sciatic nerve on metabolic activity in spinal cord and dorsal root ganglion in the rat. Proc Natl Acad Sci U S A 1985; 82: 6010-6013
50 Kalaria R. Similarities between Alzheimer’s disease and vascular dementia. J Neurol Sci 2002; 203-204: 29-34
51 Kessler RM, Ellis Jr. JR, Eden M. Analysis of emission tomographic scan data: limitations imposed by resolution and background. J Comput Assist Tomogr 1984; 8: 514-522
52 Koyama M, Kawashima R, Ito H et al. SPECT imaging of normal subjects with technetium-99m-HMPAO and technetium-99m-ECD. J Nucl Med 1997; 38: 587-592
53 Kuwabara Y, Ichiya Y, Otsuka M et al. Comparison of I-123 IMP and Tc-99m HMPAO SPECT studies with PET in dementia. Ann Nucl Med 1990; 4: 75-82
54 Lange C, Suppa P, Frings L et al. Optimization of Statistical Single Subject Analysis of Brain FDG PET for the Prognosis of Mild Cognitive Impairment-to-Alzheimer’s Disease Conversion. J Alzheimers Dis 2015; 49: 945-959
55 Lee S, Viqar F, Zimmerman ME et al. Dominantly Inherited Alzheimer N. White matter hyperintensities are a core feature of Alzheimer’s disease: Evidence from the dominantly inherited Alzheimer network. Ann Neurol 2016; 79: 929-939
56 Leypoldt F, Buchert R, Kleiter I et al. Fluorodeoxyglucose positron emission tomography in anti-N-methyl-D-aspartate receptor encephalitis: distinct pattern of disease. J Neurol Neurosurg Psychiatry 2012; 83: 681-686
57 Lim SM, Katsifis A, Villemagne VL et al. The 18F-FDG PET cingulate island sign and comparison to 123I-beta-CIT SPECT for diagnosis of dementia with Lewy bodies. J Nucl Med 2009; 50: 1638-1645
58 Markiewicz PJ, Matthews JC, Declerck J et al. Robustness of multivariate image analysis assessed by resampling techniques and applied to FDG-PET scans of patients with Alzheimer’s disease. Neuroimage 2009; 46: 472-485
59 Matsuda H. Cerebral blood flow and metabolic abnormalities in Alzheimer’s disease. Ann Nucl Med 2001; 15: 85-92
60 McKeith I, O’Brien J, Walker Z et al. Sensitivity and specificity of dopamine transporter imaging with 123I-FP-CIT SPECT in dementia with Lewy bodies: a phase III, multicentre study. Lancet Neurol 2007; 6: 305-313
61 McKhann GM, Knopman DS, Chertkow H et al. The diagnosis of dementia 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: 263-269
62 Meyer PT, Hellwig S, Amtage F et al. Dual-biomarker imaging of regional cerebral amyloid load and neuronal activity in dementia with PET and 11C-labeled Pittsburgh compound B. J Nucl Med 2011; 52: 393-400
63 Minoshima S, Foster NL, Sima AA et al. Alzheimer’s disease versus dementia with Lewy bodies: cerebral metabolic distinction with autopsy confirmation. Ann Neurol 2001; 50: 358-365
64 Minoshima S, Frey KA, Koeppe RA et al. A diagnostic approach in Alzheimer’s disease using three-dimensional stereotactic surface projections of fluorine-18-FDG PET. J Nucl Med 1995; 36: 1238-1248
65 Minoshima S, Giordani B, Berent S et al. Metabolic reduction in the posterior cingulate cortex in very early Alzheimer’s disease. Ann Neurol 1997; 42: 85-94
66 Mohr BC, Minoshima S. F-18 fluorodeoxyglucose PET/CT findings in a case of anti-NMDA receptor encephalitis. Clin Nucl Med 2010; 35: 461-463
67 Morbelli S, Garibotto V, Van De Giessen E et al., European Association of Nuclear M . A Cochrane review on brain [(1)(8)F]FDG PET in dementia: limitations and future perspectives. Eur J Nucl Med Mol Imaging 2015; 42: 1487-1491
68 Mosconi L, Perani D, Sorbi S et al. MCI conversion to dementia and the APOE genotype: a prediction study with FDG-PET. Neurology 2004; 63: 2332-2340
69 Mosconi L, Tsui WH, De Santi S et al. Reduced hippocampal metabolism in MCI and AD: automated FDG-PET image analysis. Neurology 2005; 64: 1860-1867
70 Mosconi L, Tsui WH, Herholz K et al. Multicenter standardized 18F-FDG PET diagnosis of mild cognitive impairment, Alzheimer’s disease, and other dementias. J Nucl Med 2008; 49: 390-398
71 Musiek ES, Chen Y, Korczykowski M et al. Direct comparison of fluorodeoxyglucose positron emission tomography and arterial spin labeling magnetic resonance imaging in Alzheimer’s disease. Alzheimers Dement 2012; 8: 51-59
72 Mutke MA, Madai VI, von Samson-Himmelstjerna FC et al. Clinical evaluation of an arterial-spin-labeling product sequence in steno-occlusive disease of the brain. PLoS One 2014; 9: e87143
73 National Institute for Health and Clinical Excellence: Guidance . Dementia: A NICE-SCIE Guideline on Supporting People With Dementia and Their Carers in Health and Social Care, Leicester (UK). 2007
74 Nicoll JA, Yamada M, Frackowiak J et al. Cerebral amyloid angiopathy plays a direct role in the pathogenesis of Alzheimer’s disease. Pro-CAA position statement. Neurobiol Aging 2004; 25: 589-597 discussion 603–584
75 O’Brien JT, Firbank MJ, Davison C et al. 18F-FDG PET and perfusion SPECT in the diagnosis of Alzheimer and Lewy body dementias. J Nucl Med 2014; 55: 1959-1965
76 Petersen RC. Mild cognitive impairment: current research and clinical implications. Semin Neurol 2007; 27: 22-31
77 Petersen RC, Smith GE, Waring SC et al. Mild cognitive impairment: clinical characterization and outcome. Arch Neurol 1999; 56: 303-308
78 Portnow LH, Vaillancourt DE, Okun MS. The history of cerebral PET scanning: from physiology to cutting-edge technology. Neurology 2013; 80: 952-956
79 Quarantelli M, Berkouk K, Prinster A et al. Integrated software for the analysis of brain PET/SPECT studies with partial-volume-effect correction. J Nucl Med 2004; 45: 192-201
80 Rabinovici GD, Jagust WJ, Furst AJ et al. Abeta amyloid and glucose metabolism in three variants of primary progressive aphasia. Ann Neurol 2008; 64: 388-401
81 Rascovsky K, Hodges JR, Knopman D et al. Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain 2011; 134: 2456-2477
82 Reivich M, Kuhl D, Wolf A et al. Measurement of local cerebral glucose metabolism in man with 18F-2-fluoro-2-deoxy-d-glucose. Acta Neurol Scand Suppl 1977; 64: 190-191
83 Ritter K, Lange C, Weygandt M et al. (akzeptiert) Combination of structural MRI and FDG PET of the brain improves diagnostic accuracy in newly manifested cognitive impairment in geriatric inpatients. Journal of Alzheimer’s Disease
84 Sadeghi N, Foster NL, Wang AY et al. In: Automatic classification of Alzheimer’s Disease vs. Frontotemporal dementia: A spatial decision tree approach with FDG-PET. Proceedings of the IEEE International Symposium on Biomedical Imaging – ISBI 2008; 408-411
85 Salmon E, Kerrouche N, Herholz K et al. Decomposition of metabolic brain clusters in the frontal variant of frontotemporal dementia. Neuroimage 2006; 30: 871-878
86 Saunders AM, Schmader K, Breitner JC et al. Apolipoprotein E epsilon 4 allele distributions in late-onset Alzheimer’s disease and in other amyloid-forming diseases. Lancet 1993; 342: 710-711
87 Schmidtke K, Hermeneit S. High rate of conversion to Alzheimer’s disease in a cohort of amnestic MCI patients. Int Psychogeriatr 2008; 20: 96-108
88 Silverman DH. Brain 18F-FDG PET in the diagnosis of neurodegenerative dementias: comparison with perfusion SPECT and with clinical evaluations lacking nuclear imaging. J Nucl Med 2004; 45: 594-607
89 Silverman DH, Small GW, Chang CY et al. Positron emission tomography in evaluation of dementia: Regional brain metabolism and long-term outcome. JAMA 2001; 286: 2120-2127
90 Smailagic N, Vacante M, Hyde C et al. (1)(8)F-FDG PET for the early diagnosis of Alzheimer’s disease dementia and other dementias in people with mild cognitive impairment (MCI). Cochrane Database Syst Rev 2015; 1: CD010632
91 Sokoloff L, Reivich M, Kennedy C et al. The [14C]deoxyglucose method for the measurement of local cerebral glucose utilization: theory, procedure, and normal values in the conscious and anesthetized albino rat. J Neurochem 1977; 28: 897-916
92 Strittmatter WJ, Saunders AM, Schmechel D et al. Apolipoprotein E: high-avidity binding to beta-amyloid and increased frequency of type 4 allele in late-onset familial Alzheimer disease. Proc Natl Acad Sci U S A 1993; 90: 1977-1981
93 Tahmasian M, Pasquini L, Scherr M et al. The lower hippocampus global connectivity, the higher its local metabolism in Alzheimer disease. Neurology 2015; 84: 1956-1963
94 Teipel SJ, Willoch F, Ishii K et al. Resting state glucose utilization and the CERAD cognitive battery in patients with Alzheimer’s disease. Neurobiol Aging 2006; 27: 681-690
95 Teune LK, Bartels AL, de Jong BM et al. Typical cerebral metabolic patterns in neurodegenerative brain diseases. Mov Disord 2010; 25: 2395-2404
96 Thomas BA, Erlandsson K, Modat M et al. The importance of appropriate partial volume correction for PET quantification in Alzheimer’s disease. Eur J Nucl Med Mol Imaging 2011; 38: 1104-1119
97 Trebeschi S, Riederer I, Preibisch C et al. Diagnostic Potential of Pulsed Arterial Spin Labeling in Alzheimer’s Disease. Front Neurosci 2016; 10: 154
98 United Nations . Department of Economic and Social Affairs, Population Division, 2015 Revision of World Population Prospects. https://esa.un.org/unpd/wpp/
99 Urbach H, Soeder BM, Jeub M et al. Serial MRI of limbic encephalitis. Neuroradiology 2006; 48: 380-386
100 Valentina G, Silvia M, Marco P. Dual-phase amyloid PET: hitting two birds with one stone. Eur J Nucl Med Mol Imaging 2016; 43: 1300-1303
101 Varma AR, Snowden JS, Lloyd JJ et al. Evaluation of the NINCDS-ADRDA criteria in the differentiation of Alzheimer’s disease and frontotemporal dementia. J Neurol Neurosurg Psychiatry 1999; 66: 184-188
102 Varrone A, Asenbaum S, Vander Borght T et al. EANM procedure guidelines for PET brain imaging using [18F]FDG, version 2. Eur J Nucl Med Mol Imaging 2009; 36: 2103-2110
103 Waxman AD, Herholz K, Lewis DH et al. Society of Nuclear Medicine Procedure Guideline for FDG PET Brain Imaging. Version 1.0, approved February 8, 2009
104 Wintermark M, Sesay M, Barbier E et al. Comparative overview of brain perfusion imaging techniques. Stroke 2005; 36: e83-e99
105 Ziegler U, Doblhammer G. Prevalence and incidence of dementia in Germany – a study based on data from the public sick funds in 2002. Gesundheitswesen 2009; 71: 281-290