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Welcome to this issue of touchREVIEWS in Neurology, where we explore significant advances in neurology, cognitive health, and wearable technology in the management of various chronic conditions. This issue brings together a collection of expert perspectives and research that spans innovative therapies, preventive strategies, and case studies, each offering critical insights for clinicians and researchers. […]

Molecular Imaging in Alzheimer’s Disease

Karl Herholz
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Published Online: Jun 4th 2011 US Neurology, 2010;6(2):28-33 DOI: http://doi.org/10.17925/USN.2010.06.02.28
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1

Abstract

Overview

The most sensitive and accurate method for molecular imaging in human Alzheimer’s disease (AD) is positron emission tomography (PET). The most widely available PET tracer, which is also used in clinical oncology, is 18F-2-fluoro-2-deoxy-D-glucose (FDG). FDG is an imaging biomarker for early and differential diagnosis of AD. Even higher molecular specificity and sensitivity for detection of AD before dementia onset is provided by high-affinity ligands for fibrillary amyloid. 11C-Pittsburgh Compound B is widely being used in research laboratories, while new 18F-labeled ligands are currently undergoing formal clinical trials as amyloid imaging agents and are expected to become commercially available for clinical use in the near future. A large variety of tracers is being developed and used in dementia research for activated microglia and multiple neurotransmitter systems to study disease pathophysiology, biological correlates of clinical symptoms, and new possibilities for treatment. Current studies in humans are investigating cholinergic, serotonergic, and dopaminergic neurotransmission.

Keywords

Alzheimer’s disease (AD), dementia, positron emission tomography (PET), 18F-2-fluoro-2-deoxy-D-glucose (FDG), amyloid, microglia, acetylcholine, serotonin, dopamine

2

Article

Neurodegenerative dementia has become the most rapidly growing cause of severe disability in the world. The most important risk factor is old age, while genetics and lifestyle also contribute. Therefore, better treatment and effective intervention are urgently needed at an early stage before the onset of severe disability. This requires further research into the risk factors and pathophysiological determinants of disease manifestation in humans and better, specific diagnosis at an early stage before dementia develops. Molecular imaging can provide the tools to achieve these goals.

Positron Emission Tomography
The most sensitive and accurate method for molecular imaging in humans is positron emission tomography (PET) and therefore this article focuses on this technique. It employs minute amounts (in the micromolar range) of short-lived radioactive tracers. They are labeled with either:

  • carbon-11 (physical half-life 20 minuntes), which requires a cyclotron and associated radiopharmacy on site and therefore is not practical for widespread clinical use; or
  • fluorine-18 (half-life 90 minutes), which allows remote regional tracer production and delivery to clinical nuclear medicine departments.

Clinical PET scans typically involve intravenous tracer injection and subsequent brain scanning for 10–30 minutes at resting state. PET scans are associated with very low radiation exposure of approximately 5mSv.1 This article discusses imaging biomarkers that are provided by clinical PET for early diagnosis of disease and monitoring of disease progression.2,3 It describes the clinical utility of glucose and amyloid scanning. It also provides a brief overview of current research investigating possible determinants of disease progression, such as neuroinflammation, and changes in major neurotransmitter systems and their relation to clinical symptoms.

Amyloid Imaging
The deposition of amyloid-β (Aβ) is an early event in the pathogenesis of AD and is central in the amyloid cascade hypothesis. The first tracer to be used to label fibrillary Aβ selectively with high affinity in vivo was 11C-labelled Pittsburgh compound B (11C-PIB).4,5 Many research studies and recent multicenter studies have demonstrated that this tracer has a very high sensitivity of 90% for detecting fibrillary amyloid plaques in patients with Alzheimer’s disease (AD).6–9 The apolipoprotein E (APOE) e4 allele is a genetic risk factor for increased PIB uptake10–12 and cortical PIB binding is correlated negatively with abeta42 in cerebrospinal fluid.13–15 Similar results have been obtained with quantification of tracer binding by dynamic measurement and by simplified static imaging protocols recording cortical tracer uptake in a single scan lasting for 40 to 60 minutes following intravenous injection of 11C-PIB.16,17 These results demonstrate the robustness and clinical applicability of the method. The cerebellar cortex, which may exhibit diffuse but not fibrillary amyloid in AD, is generally used as a reference region without specific PIB binding.

Most normal control subjects exhibit very low cortical binding of PIB, with less than 1.5-fold PIB uptake relative to the cerebellar cortex. In addition, unspecific binding is observed mainly in white matter. A proportion of normal elderly controls show higher cortical PIB binding, typically resulting in a bimodal distribution of PIB uptake in samples of control subjects. Current studies indicate that the frequency of increased cortical PIB binding in controls increases rapidly from 10% or less below 70 years of age to 30–40% at 80 years of age, largely reflecting similar findings in previous autopsy studies.18 The clinical implications of Aβ deposition in elderly controls are not yet clear. Some elderly controls have indicators of the start of neurodegeneration19,20 or will develop cognitive deficits,21 but cerebral function in others may be resistant to Aβ deposition. Long-term follow-up studies are currently under way to clarify this issue.

Findings in patients with mild cognitive impairment (MCI) are heterogeneous. In most studies approximately two-thirds of patients showed increased binding, such as AD patients, while the rest were within normal limits. Published results from follow-up studies indicate that patients with increased binding are at high risk for progressing to AD with manifest dementia,22,23 while MCI patients with negative PIB scans very rarely develop dementia.24, Patients with amnestic MCI show more PIB binding than non-amnestic MCI.25 Aβ deposition is high in posterior association areas, where it correlates with a decline in glucose metabolism. However, it is also high in the frontal association cortex where that correlation is absent.26

The amount of Aβ deposition and PIB binding is highly variable in AD. Despite this, PIB imaging is very sensitive for detection of AD. It is likely that a significant proportion of the PIB-negative AD patients in clinical series (up to 10%) will be due to clinical misdiagnoses. Only under exceptional circumstances has PIB-negativity been confirmed in AD.27

Besides APOE e4, additional genetic factors that have not yet been identified appear to play a role.28 Initital follow-up studies with 11C-PIB in AD have indicated that there is little further increase in tracer uptake during progression of the disease.29 Howerver, recent preliminary results from large multicenter studies (ADNI and AIBL) do indicate further increase. A decrease in PIB binding has been observed in patients undergoing clinical trials of drugs that remove Aβ from the brain,30 but it has not yet been demonstrated that this would be associated with clinical benefit.

Differential Diagnosis using Amyloid Imaging
Amyloid imaging is expected to provide excellent differentiation of AD from frontotemporal dementia, which is not associated with Aβ deposition and increased 11C-PIB binding (see Figure 1).31 Dementia with Lewy bodies (DLB) often also shows fibrillary Aβ deposition in pathological studies and correspondingly positive PIB scans are reported in most patients.32,33 Moderately increased PIB binding, predominantly in occipital regions and on average less than in AD, has also been observed in non-demented patients with cerebral Aβ angiopathy.34

Tracers in Clinical Trials
There are currently three 18F-labeled tracers being studied in clinical trials that have been developed as proprietary tracers for commercial distribution. These are flutemetamol (GE-067, 3’-fluoro-PIB), florbetaben (BAY-94-9172, AV-1), and florbetapir (AV-45). They show high-affinity binding for fibrillary Aβ with Ki <10nM, similar to 11C-PIB, while non-specific binding in white matter is higher than with 11C-PIB. Ongoing research is aiming to develop tracers that show a lower level of non-specific binding.35,36Flutemetamol, florbetaben, and florbetapir appear to have largely similar imaging properties, although the optimum scanning time after intravenous injection varies. Results from clinical trials indicate that they will likely provide high diagnostic power for discrimination between AD patients and controls.37,38 They also demonstrate a close correlation between the cortical binding of 11C-PIB and 18F-fluoro-PIB in cortical regions.39 Preliminary results demonstrate a close correspondence of tracer binding with the amount of post-mortem Aβ deposition, as shown for florbetapir at the International Conference on Alzheimer’s Disease (ICAD) 10 conference.40

Another F-18-labeled amyloid tracer is 2-(1-(6-[(2-[F-18]fluoroethyl) (methyl)amino]-2-naphthyl)ethylidene)malononitrile, abbreviated to FDDNP, which binds to Aβ with less affinity than PIB and related compounds.41 It competes with non-steroidal antiphlogistics42 when binding and has significant affinity to pathological intracellular tau deposits (neurofibrillary tangles). These deposits are mainly located in the hippocampus in AD and also occur in other neurodegenerative diseases. Accordingly, a gradual increase in binding was observed in MCI and AD patients, mainly in the hippocampus but also in brain areas with predominant Aβ deposits.43 Direct comparison with C-11-PIB demonstrated the differences in spatial distribution, and greater overlap between controls and patients than with C-11-PIB.44,45

Microglial Activation
Microglia are the resident immune cells of the brain. In response to brain damage, microglia undergo changes in their morphology, migrate toward the lesion site, proliferate, and produce cytokines and reactive oxygen species. This is associated with expression of the peripheral benzodiazepine receptor, which is known to be located at the mitochondrial translocator protein.46 Activated microglia are present at sites of aggregated Aβ deposition in the brains of AD subjects47 and may contribute to Aβ removal. However, the secretion of cytokines associated with microglial activation may also contribute to tissue damage and apoptosis. Further research with longitudinal assessment of microglial activation in humans is therefore needed to understand its consequences and whether it is a major factor that influences the rate of disease progression.48

Tracers for Microglial Activation Imaging
The first tracer that became available for imaging of microglial activation in humans was 11C-PK11195. This has been shown to largely reflect the distribution of activated microglia in experimental and human brain disease,49,50 demonstrating microglial activation in multiple system atropy.51 The in vivo PET findings in AD are not particularly clear. An early study using racemic 11C-PK11195 was negative,52 probably due to the relatively high level of non-specific binding resulting in unfavorable signal strength. A recent study using the R-isomer according to current standards,53 on the other hand, found moderately increased binding. Thus, there is a need for the development of better tracers, ideally labeled with fluorine-18, for clinical use. A large number of new tracers have been tested in experimental animals.54 Initial clinical studies using various tracers have detected that there is an as yet unidentified genetic polymorphism that leads very low binding with some of the new tracers in about one-fourth of normal individuals tested so far.55,56 This complicates the clinical application of such tracers.

Glucose Metabolism
Cerebral glucose metabolism is measured by the most widely available PET tracer, 18F-2-fluoro-D-deoxyglucose (FDG). There is close coupling of glucose metabolism with neuronal function.57 Glucose is the main substrate for the energy production that is required to maintain neuronal ion gradients for neuronal activity. Coupling to synaptic activity is also mediated by the neuron-astrocyte glutamate shuttle.58,59 Over more than 20 years, multiple studies have demonstrated that glucose metabolism and blood flow are imparied in temporal-parietal association cortices, with the angular gyrus usually being located at the center of the metabolic impairment.60 The frontal association cortex may also be involved, but more variably so and usually to a lesser degree and only during progression of AD. There may be a distinct hemispheric asymmetry, which usually corresponds to the predominant cognitive deficits (language impairment in the dominant and visuospatial disorientation in the sub-dominant hemisphere). In contrast to other dementia types, glucose metabolism in basal ganglia, primary motor, visual cortex, and cerebellum is usually well preserved. This pattern generally reflects the clinical symptoms of AD, with impairment of memory and associative thinking, including higher-order sensory processing and planning of action, but with relative preservation of primary motor and sensory function. Glucose metabolism provides high diagnostic power, especially when used in combination with automated objective image evaluation software.61,62 As such, it has been recommended in current guidelines for dementia diagnosis.63

Longitudinal studies have demonstrated that the severity and extent of metabolic impairment in the temporal and parietal cortex increases with dementia progression and frontal reductions become more evident.64,65 The annual decrease of metabolism in association cortices is 5–6%.66,67 Asymmetrical metabolic impairment and associated predominance of language or visuospatial impairment tends to persist during progression.68,69 Based on these observations, FDG PET can serve as a surrogate marker in therapeutic trials.70–72 There are several indications that increased activation in some parts of the brain may provide compensation for the failure of function in other parts.73 During the pre-dementia stages of AD, frontal brain function may compensate for the failure of the Papez circuit—which includes the hippocampus and is essential for acquisition of long-term memory—as well as posterior association cortices. The prefrontal cortex was the region with the most pronounced decline in brain metabolism in a study of progression from MCI to dementia.74 Highly-educated patients beginning dementia appear able to partially compensate for impaired metabolism in the posterior cingulate cortex.75 The very high frontal Aβ load in most patients before the onset of dementia is not paralleled by a decrease in glucose metabolism,26 possibly indicating higher resistance of frontal neuronal function to pathological protein deposition.

Cholinergic Neurotransmission
It is known from pathological studies that there is a severe loss of cholinergic fibers and their characteristic enzymes and receptors in AD and DLB (see Figure 2).76

While there are no suitable tracers for acetylcholine transferase, tracers have been developed for other cholinergic markers. Labeled analogs of acetylcholine, which are also substrates for acetylcholine esterase (AChE), can be used to measure and image its activity in vivo. These acetylcholine analogs are 11C-N-methyl-4-piperidyl-acetate (MP4A, also known as AMP),77 which is 94% specific for AChE in human brain, and 11C-N-methyl-4-piperidyl-propionate (MP4P or PMP).78

A significant decrease in cortical AChE activity has been observed in MCI and AD,79 probably reflecting the loss of AChE that is associated with cholinergic axons.80 The loss is most severe in the temporal neocortex, where it is correlated with memory deficits, while in other brain areas it is mostly related to deficits in attention.81 The AChE imaging technique has also been used to measure drug-induced AChE inhibition in AD patients, which for all currently available cholinesterase inhibitors at standard clinical doses is in the range of 30–40%.82–84 Nicotinic receptors have attracted intense interest, but available tracers still suffer from methodological limitations. 11C-nicotine has a high level of unspecific binding, although reduced binding in AD can be detected.85,86 The a4b2 receptor subtype has been imaged using 18F-A8538087,88 and 131I-A85380.89 Reduction of binding has been observed using these agents in MCI and AD,90 as well as in Parkinson’s disease with cognitive impairment.91 Despite this, the binding kinetics are too slow for reliable quantitation and clinical use.92 The quest for faster kinetics is motivating ongoing research
or better ligands.Serotonin
Impairment of serotonergic innervation has mostly been studied in the context of depression. Depression is also a major clinical issue in dementia. A reduction of receptor binding potential in AD has been observed in AD, mainly for 5-HT(2A) receptors.93–95 In MCI, reduced 5-HT(2A) binding capacity in the striatum has been correlated with depression and anxiety scores.96 Reduced serotonin transporter binding potentials have also been observed using 11C-DASB and is most clear in AD patients with depression.97

Dopamine
The tracer most widely used to examine dopamine synthesis and vesicular storage is 18F-fluorodopa.98 A deficit of dopamine synthesis similar to Parkinson’s disease has been found in DLB, even at a stage when parkinsonism may not yet be prominent.99 As dopamine synthesis is normal in patients with AD, 18F-fluorodopa provides an important diagnostic marker. In contrast to the cholinergic impairment, which is severe in DLB but only mild in Parkinson’s disease without dementia, the dopaminergic deficit does not appear to be related to dementia.100 The dopaminergic degeneration in DLB is also evident in studies with ligands for dopamine transporters, such as 123I-FP-CIT.101

There is also interest in the imaging of vesicular monoamine transporters,102 which provide a very sensitive—albeit probably somewhat less specific—indication of dopaminergic neurodegeneration.103 Different transporter types have been compared in a multitracer study of the pathophysiology of dopamine turnover.104

Conclusion
Molecular imaging using PET in humans is providing powerful tools for specific and early diagnosis of AD even before the onset of dementia. There is a pressing need for the development of disease-modifying treatment that can prevent or delay dementia in patients who already carry the biological markers of AD but have little cognitive impairment. It is expected that molecular imaging will play an increasing role in reaching this goal by contributing to translational pathophysiological research, drug development and early clinical diagnosis.

2

References

  1. Hays MT, Watson EE, Thomas SR, et al., MIRD dose estimate report no. 19: radiation absorbed dose estimates from (18)F-FDG, J Nucl Med, 2002;43:210–4.
  2. Hampel H, Frank R, Broich K, et al., Biomarkers for Alzheimer’s disease: academic, industry and regulatory perspectives, Nat Rev Drug Discov, 2010;9:560–74.
  3. Nordberg A, Rinne JO, Kadir A, et al., The use of PET in Alzheimer disease, Nat Rev Neurol, 2010;6:78–87.
  4. Klunk WE, Engler H, Nordberg A, et al., Imaging brain amyloid in Alzheimer’s disease with Pittsburgh Compound-B, Ann Neurol, 2004;55:306–19.
  5. Klunk WE, Lopresti B, Nebes RD, et al., Development and application of beta-amyloid imaging agents in Alzheimer’s disease. In: Herholz K, Perani D, Morris CM (eds), The Dementias: Early Diagnosis and Evaluation, New York, Dekker, 2006.
  6. Edison P, Archer HA, Hinz R, et al., Amyloid, hypometabolism, and cognition in Alzheimer disease: an [11C]PIB and [18F]FDG PET study, Neurology, 2007;68:501–98.
  7. Kemppainen NM, Aalto S, Wilson IA, et al., Voxel-based analysis of PET amyloid ligand [11C]PIB uptake in Alzheimer disease, Neurology, 2006;67: 1575–80.
  8. Nordberg A, PET imaging of amyloid in Alzheimer’s disease, Lancet Neurol, 2004;3:519–27.
  9. Devanand DP, Mikhno A, Pelton GH, et al., Pittsburgh compound B (11C-PIB) and fluorodeoxyglucose (18 F-FDG) PET in patients with Alzheimer disease, mild cognitive impairment, and healthy controls, J Geriatr Psychiatry Neurol, 2010;23:185–98.
  10. Reiman EM, Chen K, Liu X, 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;106:6820–5.
  11. Rowe CC, Ng S, Ackermann U, et al., Imaging beta-amyloid burden in aging and dementia, Neurology, 2007;68:1718–25.
  12. Caselli RJ, Walker D, Sue L, et al., Amyloid load in nondemented brains correlates with APOE e4, Neurosci Lett, 2010;473:168–71.
  13. Koivunen J, Pirttila T, Kemppainen N, et al., PET amyloid ligand C-11-PIB uptake and cerebrospinal fluid beta-amyloid in mild cognitive impairment, Dement Geriatr Cogn Disord, 2008;26:378–83.
  14. Tolboom N, van der Flier WM, Yaqub M, et al., Relationship of cerebrospinal fluid markers to 11C-PiB and 18F-FDDNP binding, J Nucl Med, 2009;50:1464–70.
  15. Fagan AM, Mintun MA, Mach RH, et al., Inverse relation between in vivo amyloid imaging load and cerebrospinal fluid Abeta42 in humans, Ann Neurol, 2006;59:512–9.
  16. Edison P, Brooks DJ, Turkheimer FE, et al., Strategies for the generation of parametric images of [11C]PIB with plasma input functions considering discriminations and reproducibility, NeuroImage, 2009;48:329–38.
  17. Lopresti BJ, Klunk WE, Mathis CA, et al., Simplified quantification of Pittsburgh Compound B amyloid imaging PET studies: a comparative analysis, J Nucl Med, 2005;46:1959–72.
  18. Rowe CC, Ellis KA, Rimajova M, et al., Amyloid imaging results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging, Neurobiol Aging, 2010;31: 1275–83.
  19. Mormino EC, Kluth JT, Madison CM, et al., Episodic memory loss is related to hippocampal-mediated beta-amyloid deposition in elderly subjects, Brain, 2009;132:1310–23.
  20. Pike KE, Savage G, Villemagne VL, et al., Beta-amyloid imaging and memory in non-demented individuals: evidence for preclinical Alzheimer’s disease, Brain, 2007;130:2837–44.
  21. Morris JC, Roe CM, Grant EA, et al., Pittsburgh Compound B imaging and prediction of progression from cognitive normality to symptomatic Alzheimer disease, Arch Neurol, 2009;66:1469–75.
  22. Forsberg A, Engler H, Almkvist O, et al., PET imaging of amyloid deposition in patients with mild cognitive impairment, Neurobiol Aging, 2008;29:1456–65.
  23. Okello A, Koivunen J, Edison P, et al., Conversion of amyloid positive and negative MCI to AD over 3 years: an 11C-PIB PET study, Neurology, 2009;73:754–60.
  24. Jack CR Jr, Wiste HJ, Vemuri P, et al., Brain beta-amyloid measures and magnetic resonance imaging atrophy both predict time-to-progression from mild cognitive impairment to Alzheimer’s disease, Brain, 2010;133(11):3336–48.
  25. Lowe VJ, Kemp BJ, Jack CR, Jr, et al., Comparison of 18F-FDG and PiB PET in cognitive impairment, J Nucl Med, 2009;50:878–86.
  26. Cohen AD, Price JC, Weissfeld LA, et al., Basal cerebral metabolism may modulate the cognitive effects of A{beta} in mild cognitive impairment: An example of brain beserve, J Neurosci, 2009;29:14770–8.
  27. Cairns NJ, Ikonomovic MD, Benzinger T, et al., Absence of Pittsburgh Compound B detection of cerebral amyloid beta in a patient with clinical, cognitive, and cerebrospinal fluid markers of Alzheimer disease: a case report, Arch Neurol, 2009;66:1557–62.
  28. Hinrichs AL, Mintun MA, Head D, et al., Cortical binding of pittsburgh compound B, an endophenotype for genetic studies of Alzheimer’s disease, Biol Psychiatry, 2010;67:581–3.
  29. Engler H, Forsberg A, Almkvist O, et al., Two-year follow-up of amyloid deposition in patients with Alzheimer’s disease, Brain, 2006;129:2856–66.
  30. Rinne JO, Brooks DJ, Rossor MN, 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;9:363–72.
  31. Rabinovici GD, Furst AJ, O’Neil JP, et al., 11C-PIB PET imaging in Alzheimer disease and frontotemporal lobar degeneration, Neurology, 2007;68:1205–12.
  32. Gomperts SN, Rentz DM, Moran E, et al., Imaging amyloid deposition in Lewy body diseases, Neurology, 2008;71: 903–10.
  33. Edison P, Rowe CC, Rinne JO, et al., Amyloid load in Parkinson’s disease dementia and Lewy body dementia measured with [11C]PIB positron emission tomography, J Neurol Neurosurg Psychiatry, 2008;79:1331–8.
  34. Ly JV, Donnan GA, Villemagne VL, et al., 11C-PIB binding is increased in patients with cerebral amyloid angiopathy-related hemorrhage, Neurology, 2010;74:487–93.
  35. Nyberg S, Jonhagen ME, Cselenyi Z, et al., Detection of amyloid in Alzheimer’s disease with positron emission tomography using [(11)C]AZD2184, Eur J Nucl Med Mol Imaging, 2009;36:1859–63.
  36. Juréus A, Swahn BM, Sandell J, et al., Characterization of AZD4694, a novel fluorinated Abeta plaque neuroimaging PET radioligand, J Neurochem, 2010;114:784–94.
  37. Sabri O, Gertz H, Dresel S, et al, Multicentre phase 2 trial on florbetaben for {beta}-amyloid brain PET in Alzheimer disease, J Nucl Med, 2010;51(Suppl.):384.
  38. Wong DF, Rosenberg PB, Zhou Y, et al., In vivo imaging of amyloid deposition in Alzheimer disease using the radioligand 18F-AV-45 (flobetapir F 18), J Nucl Med, 2010;51:913–20.
  39. Vandenberghe R, Van Laere K, Ivanoiu A, et al., 18F-flutemetamol amyloid imaging in Alzheimer disease and mild cognitive impairment: a phase 2 trial, Ann Neurol, 2010;68:319–29.
  40. Opar A, Hope builds for earlier detection of Alzheimer’s disease, Nat Rev Drug Discov, 2010;9:579–81.
  41. Agdeppa ED, Kepe V, Liu J, et al., Binding characteristics of radiofluorinated 6-dialkylamino-2-naphthylethylidene derivatives as positron emission tomography imaging probes for beta-amyloid plaques in Alzheimer’s disease, J Neurosci, 2001;21:RC189.
  42. Agdeppa ED, Kepe V, Petri A, et al., In vitro detection of (S)-naproxen and ibuprofen binding to plaques in the Alzheimer’s brain using the positron emission tomography molecular imaging probe 2-(1-{6-[(2-[18F]fluoroethyl) (methyl)amino]-2-naphthyl}ethylidene)malononitrile, Neuroscience, 2003;117:723–30.
  43. Braskie MN, Klunder AD, Hayashi KM, et al., Plaque and tangle imaging and cognition in normal aging and Alzheimer’s disease, Neurobiol Aging, 2008;31(10):1669–78.
  44. Tolboom N, Yaqub M, van der Flier WM, et al., Detection of Alzheimer pathology in vivo using both 11C-PIB and 18F-FDDNP PET, J Nucl Med, 2009;50:191–97.
  45. Shin J, Lee SY, Kim SJ, et al., Voxel-based analysis of Alzheimer’s disease PET imaging using a triplet of radiotracers: PIB, FDDNP, and FDG, Neuroimage, 2010;52:488–96.
  46. Winkeler A, Boisgard R, Martin A, et al., Radioisotopic imaging of neuroinflammation, J Nucl Med, 2010;51:1–4.
  47. Mattiace LA, Davies P, Yen SH, et al., Microglia in cerebellar plaques in Alzheimer’s disease, Acta Neuropathol, 1990;80:493–8.
  48. Perry VH, Nicoll JA, Holmes C, Microglia in neurodegenerative disease, Nat Rev Neurol, 2010;6:193–201.
  49. Cagnin A, Brooks DJ, Kennedy AM, et al., In vivo measurement of activated microglia in dementia, Lancet, 2001;358:461–7.
  50. Banati RB, Newcombe J, Gunn RN, et al., The peripheral benzodiazepine binding site in the brain in multiple sclerosis: quantitative in vivo imaging of microglia as a measure of disease activity, Brain, 2000;123(Pt 11):2321–37.
  51. Gerhard A, Banati RB, Goerres GB, et al., [11C](R)-PK11195 PET imaging of microglial activation in multiple system atrophy, Neurology, 2003;61:686–9.
  52. Groom GN, Junck L, Foster NL, et al., PET of peripheral benzodiazepine binding sites in the microgliosis of Alzheimer’s disease, J Nucl Med, 1995;36:2207–10.
  53. Edison P, Archer HA, Gerhard A, et al., Microglia, amyloid, and cognition in Alzheimer’s disease: An [11C](R)PK11195-PET and [11C]PIB-PET study, Neurobiol Dis, 2008;32:412–9.
  54. Chauveau F, Boutin H, Van Camp N, et al., Nuclear imaging of neuroinflammation: a comprehensive review of [11C]PK11195 challengers, Eur J Nucl Med Mol Imaging, 2008;35:2304–19.
  55. Kreisl WC, Fujita M, Fujimura Y, et al., Comparison of [(11)C]-(R)-PK 11195 and [(11)C]PBR28, two radioligands for translocator protein (18 kDa) in human and monkey: Implications for positron emission tomographic imaging of this inflammation biomarker, Neuroimage, 2010;49:2924–32.
  56. Owen DR, Howell OW, Tang SP, et al., Two binding sites for [(3)H]PBR28 in human brain: implications for TSPO PET imaging of neuroinflammation, J Cereb Blood Flow Metab, 2010;30(9):1608–18.
  57. Sokoloff L, Relation between physiological function and energy metabolism in the central nervous system. [Review], J Neurochem, 1977;29:13–26.
  58. Kasischke KA, Vishwasrao HD, Fisher PJ, et al., Neural activity triggers neuronal oxidative metabolism followed by astrocytic glycolysis, Science, 2004;305:99–103.
  59. Pellerin L, Magistretti PJ, Glutamate uptake into astrocytes stimulates aerobic glycolysis: a mechanism coupling neuronal activity to glucose utilization, Proc Nat Acad Sci U S A, 1994;91:10625–9.
  60. Herholz K, PET studies in dementia, Ann Nucl Med, 2003;17:79–89.
  61. 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;36:1238–48.
  62. Haense C, Herholz K, Heiss WD, Validation of an automated FDG PET analysis to discriminate patients with Alzheimer’s disease from normal subjects, J Nucl Med, 2008;49(Suppl. 1):34P.
  63. Hort J, O’Brien JT, Gainotti G, et al., EFNS guidelines for the diagnosis and management of Alzheimer’s disease, Eur J Neurol, 2010;17:1236–48.
  64. Jagust WJ, Friedland RP, Budinger TF, et al., Longitudinal studies of regional cerebral metabolism in Alzheimer’s disease, Neurology, 1988;38:909–12.
  65. Mielke R, Herholz K, Grond M, et al., Clinical deterioration in probable Alzheimer’s disease correlates with progressive metabolic impairment of association areas, Dementia, 1994;5:36–41.
  66. Smith GS, de Leon MJ, George AE, et al., Topography of cross-sectional and longitudinal glucose metabolic deficits in Alzheimer’s disease. Pathophysiologic implications, Arch Neurol, 1992;49:1142–50.
  67. Landau SM, Harvey D, Madison CM, et al., Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI, Neurobiol Aging, 2009; [Epub ahead of print].
  68. Grady CL, Haxby JV, Schlageter NL, et al., Stability of metabolic and neuropsychological asymmetries in dementia of the Alzheimer type, Neurology, 1986;36:1390–2.
  69. Haxby JV, Grady CL, Koss E, et al., Longitudinal study of cerebral metabolic asymmetries and associated neuropsychological patterns in early dementia of the Alzheimer type, Arch Neurol, 1990;47:753–60.
  70. Heiss WD, Kessler J, Mielke R, et al., Long-term effects of phosphatidylserine, pyritinol, and cognitive training in Alzheimer’s disease. A neuropsychological, EEG, and PET investigation, Dementia, 1994;5:88–98.
  71. Alexander GE, Chen K, Pietrini P, et al., Longitudinal PET evaluation of cerebral metabolic decline in dementia: A potential outcome measure in Alzheimer’s disease treatment studies, Am J Psychiatry, 2002;159:738–45.
  72. Hirono N, Hashimoto M, Ishii K, et al., One-year change in cerebral glucose metabolism in patients with Alzheimer’s disease, J Neuropsychiatry Clin Neurosci, 2004;16:488–92.
  73. Park DC, Reuter-Lorenz P, The adaptive brain: aging and neurocognitive scaffolding, Annu Rev Psychol, 2009;60:173–96.
  74. Drzezga A, Lautenschlager N, Siebner H, et al., Cerebral metabolic changes accompanying conversion of mild cognitive impairment into Alzheimer’s disease: a PET follow-up study, Eur J Nucl Med Mol Imaging, 2003;30:1104–13.
  75. Garibotto V, Borroni B, Kalbe E, et al., Education and occupation as proxies for reserve in aMCI converters and AD: FDG-PET evidence, Neurology, 2008;71:1342–9.
  76. Perry EK, Haroutunian V, Davis KL, et al., Neocortical cholinergic activities differentiate Lewy body dementia from classical Alzheimer’s disease, Neuroreport, 1994;5:747–9.
  77. Namba H, Irie T, Fukushi K, et al., In vivo measurement of acetylcholinesterase activity in the brain with a radioactive acetylcholine analog, Brain Res, 1994;667:278–82.
  78. Kilbourn MR, Snyder SE, Sherman PS, et al., In vivo studies of acetylcholinesterase activity using a labeled substrate, n-[C-11]methylpiperdin-4-yl propionate ([C-11]PMP), Synapse, 1996;22:123–31.
  79. Herholz K, Acetylcholine esterase activity in mild cognitive impairment and Alzheimer’s disease, Eur J Nucl Med Mol Imaging, 2008;35(Suppl. 1):S25–9.
  80. Mesulam M, Neuroanatomy of cholinesterases in the normal human brain and in Alzheimer’s disease, In: Giacobini E (ed), Cholinesterases and Cholinesterase Inhibitors, London, UK, Martin Dunitz, 2000:121–37.
  81. Haense C, Kalbe E, Herholz K, et al., Cholinergic system function and cognition in mild cognitive impairment, Neurobiol Aging, Oct 18, 2010; [Epub ahead of print].
  82. Bohnen NI, Kaufer DI, Hendrickson R, et al., Degree of inhibition of cortical acetylcholinesterase activity and cognitive effects by donepezil treatment in Alzheimer’s disease, J Neurol, Neurosurg Psychiatry, 2005;76:315–9.
  83. Kaasinen V, Någren K, Jarvenpaa T, et al., Regional effects of donepezil and rivastigmine on cortical acetylcholinesterase activity in Alzheimer’s disease, J Clin Psychopharmacol, 2002;22:615–20.
  84. Kadir A, Darreh-Shori T, Almkvist O, et al., PET imaging of the in vivo brain acetylcholinesterase activity and nicotine binding in galantamine-treated patients with AD, Neurobiol Aging, 2007;29(8):1204–17.
  85. Nordberg A, Lundqvist H, Hartvig P, et al., Kinetic analysis of regional (S)(-)11C-nicotine binding in normal and Alzheimer brains—in vivo assessment using positron emission tomography, Alzheimer Dis Assoc Disord, 1995;9:21–7.
  86. Kadir A, Almkvist O, Wall A, et al., PET imaging of cortical 11C-nicotine binding correlates with the cognitive function of attention in Alzheimer’s disease, Psychopharmacology (Berl), 2006;188:509–20.
  87. Bottlaender M, Valette H, Roumenov D, et al., Biodistribution and radiation dosimetry of (18)f-fluoro-a-85380 in healthy volunteers, J Nucl Med, 2003;44:596–601.
  88. Mamede M, Ishizu K, Ueda M, et al., Quantification of human nicotinic acetylcholine receptors with 123I-5IA SPECT, J Nucl Med, 2004;45:1458–70.
  89. Pimlott SL, Piggott M, Owens J, et al., Nicotinic acetylcholine receptor distribution in Alzheimer’s disease, dementia with Lewy bodies, Parkinson’s disease, and vascular dementia: in vitro binding study using 5-[(125)i]-a-85380, Neuropsychopharmacology, 2004;29:108–16.
  90. Terrière E, Dempsey MF, Herrmann LL, et al., 5-(123)I-A-85380 binding to the alpha4beta2-nicotinic receptor in mild cognitive impairment, Neurobiol Aging, 2010;31:1885–93.
  91. Meyer PM, Strecker K, Kendziorra K, et al., Reduced alpha4beta2*-nicotinic acetylcholine receptor binding and its relationship to mild cognitive and depressive symptoms in Parkinson disease, Arch Gen Psychiatry, 2009;66:866–77.
  92. Horti AG, Gao Y, Kuwabara H, et al., Development of radioligands with optimized imaging properties for quantification of nicotinic acetylcholine receptors by positron emission tomography, Life Sci, 2010;86:575–84.
  93. Blin J, Crouzel C, Blood-cerebrospinal fluid and blood-brain barriers imaged by 18F-labeled metabolites of 18F-setoperone studied in humans using positron emission tomography, J Neurochem, 1992;58:2303–10.
  94. Meltzer CC, Price JC, Mathis CA, et al., PET imaging of serotonin type 2A receptors in late-life neuropsychiatric disorders, Am J Psychiatry, 1999;156:1871–8.
  95. Marner L, Frokjaer VG, Kalbitzer J, et al., Loss of serotonin 2A receptors exceeds loss of serotonergic projections in early Alzheimer’s disease: a combined [(11)C]DASB and [(18)F]altanserin-PET study, Neurobiol Aging, May 24, 2010; [Epub ahead of print].
  96. Hasselbalch SG, Madsen K, Svarer C, et al., Reduced 5-HT(2A) receptor binding in patients with mild cognitive impairment, Neurobiol Aging, 2008;29(12):1830–8
  97. Ouchi Y, Yoshikawa E, Futatsubashi M, et al., Altered brain serotonin transporter and associated glucose metabolism in Alzheimer disease, J Nucl Med, 2009;50:1260–6.
  98. Brooks DJ, Advances in imaging Parkinson’s disease, Curr Opin Neurol, 1997;10:327–31.
  99. Hu XS, Okamura N, Arai H, et al., 18F-fluorodopa PET study of striatal dopamine uptake in the diagnosis of dementia with lewy bodies, Neurology, 2000;55:1575–7.
  100. Hilker R, Thomas A, Klein JC, et al., Dementia in Parkinson’s disease: functional imaging of cholinergic and dopaminergic pathways, Neurology, 2005;65:1716–22.
  101. 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;6:305–13.
  102. Bohnen NI, Albin RL, Koeppe RA, et al., Positron emission tomography of monoaminergic vesicular binding in aging and Parkinson disease, J Cereb Blood Flow Metab, 2006;26: 1198–212.
  103. Okamura N, Villemagne VL, Drago J, et al., In vivo measurement of vesicular monoamine transporter type 2 density in Parkinson disease with (18)F-AV-133, J Nucl Med, 2010;51:223–8.
  104. Sossi V, de la Fuente-Fernandez R, Schulzer M, et al., Dopamine transporter relation to dopamine turnover in Parkinson’s disease: a positron emission tomography study, Ann Neurol, 2007;62:468–74.
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Disclosure

Karl Herholz, MD, FRCP, has received a research grant from AVID Radiopharmaceuticals.

Correspondence

Karl Herholz, MD, FRCP, Professor of Clinical Neuroscience, Wolfson Molecular Imaging Centre, University of Manchester, 27 Palatine Road, Manchester, M20 3LJ, UK. E: karl.herholz@manchester.ac.uk

Received

2010-10-19T00:00:00

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