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PET imaging of brain amyloid in dementia: a review

Harriet Quigley, Sean J. Colloby and John T. O’Brien

Institute for Ageing and Health, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK Correspondence to: S. J. Colloby, PhD, E-mail: [email protected]

Objective: To review the rapidly expanding literature of amyloid PET imaging with particular attention to Pittsburgh compound-B (PIB) in Alzheimer’s disease (AD), dementia with Lewy bodies (DLB), fronto-temporal dementia (FTD), mild cognitive impairment (MCI) and cognitively normal volunteers.

Design: Literature searches were performed using Medline up to February 2010. Individual articles were then examined for additional references not revealed by automated searches. This yielded 79 articles whose abstracts were read by the authors to select key papers.

Results: Amyloid deposition assessed using PIB-PET is significantly elevated in AD and DLB compared to controls and those with FTD. In MCI, uptake is often intermediate between AD and normal ageing, and excessive amyloid burden in non-demented individuals with MCI are likely to represent high-risk cases. Amyloid deposition appears to be an early event, and as dementia progresses clinical decline seems to be more associated with neurodegeneration than amyloid burden.

Conclusions: PIB-PET imaging is a sensitive and specific marker for underlying Ab amyloid deposition and represents an important investigative tool for examining the relationship between amyloid burden, clinical symptoms and structural and functional changes in dementia. Amyloid imaging may also be useful for selecting patients for anti-amyloid therapies. However, studies have identified PIB-positive cases in otherwise healthy older individuals (10–30%), limiting diagnostic specificity. Development of biomarkers for investigating other aspects of dementia pathology, i.e. soluble Ab, tau, synuclein and brain inflammation would further inform our understanding and assist in studying disease-modifying and preventive treatments in dementia. Copyright # 2010 John Wiley & Sons, Ltd.

Key words: amyloid; PET; dementia; MCI; ageing
History: Received 4 June 2010; Accepted 3 September 2010; Published online 28 December 2010 in Wiley Online Library
(wileyonlinelibrary.com).
DOI: 10.1002/gps.2640

Introduction

It is estimated that the number of people with dementia, 25 million worldwide in 2000, will increase to 63 million in 2030 and to 114 million in 2050 (Wimo et al., 2003), a result of changed demographics and increased longevity. This poses great challenges for both society and health-care systems. Therefore, considerable resources have been focused on devel-oping disease-modifying medications designed to directly delay the pathophysiological processes in conditions such as Alzheimer’s disease (AD). One research aim has been to search for biomarkers that allow both early detection of AD and to accurately chart its progression. Amyloid imaging, developed in an attempt to provide an in vivo measurement of one of

the key pathologic hallmarks of AD, fibrillar amyloid b (Ab) plaques, shows great potential to meet these aims.

The most prominent hypothesis for the aetiology of AD remains the amyloid cascade hypothesis (Hardy and Selkoe, 2002). Amyloid deposition is central to this hypothesis and considered an early event on the path to dementia (Hardy and Higgins, 1992). Briefly, it suggests that sufficient accumulation of an amyloid precursor protein derivative, beta amyloid (Ab), is the primary influence that drives significant biochemical, histological and clinical changes in the pathogenesis of AD (Hardy and Selkoe, 2002). However, note that amyloid deposition can also occur in normal aging as well (see below). Pathological studies, inevitably always cross-sectional, cannot provide information about events early in disease process, nor can they determine

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how key events (amyloid formation, tau formation, neuronal loss) are temporally related to each other. During the past five years amyloid imaging has established itself alongside magnetic resonance ima-ging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) as an important neuroima-ging tool for the investigation of brain ageing and dementia.

A number of compounds have been developed for the imaging of amyloid: radiolabelled amyloid-b peptide (Ab) antibodies and peptide fragments (Maggio et al., 1992; Friedland et al., 1994); small molecules (derivatives of Congo red, thioflavin, stilbene and acridine) for PET and single photon emission computed tomography (SPECT) imaging (Mathis et al., 2003; Zhuang et al., 2003); and putrescine–gadolinium–amyloid-b peptide (PUT– Gd–Ab) for MRI (Poduslo et al., 2002). However, due to the poor passage across the blood–brain barrier (Bornebroek et al., 1996), inadequate brain per-meability (Friedland et al., 1994) and/or low affinity to Ab aggregates, these compounds failed to provide a direct visualisation of amyloid and tau proteins in humans. More recently, several PET ligands have now been developed that demonstrate some affinity for amyloid plaques, i.e. [18F] 1,1-dicyano-2-[6-(dimethy-lamino)-2-naphthalenyl]propene (FDDNP) (Small
et al 11 N ´
., 2006), [ C] 4- -Methylamino-4-hydroxystil-bene (SB13) (Verhoeff et al., 2004) and N-methyl-[11C]2-(4-methylaminophenyl)-6-hydroxybenzothia-zole or simply ‘Pittsburgh Compound-B’ (PIB). The first PIB study in humans was performed in mild AD patients, where uptake patterns were consistent with amyloid plaque deposition described in post mortem studies of AD brains (Klunk et al., 2004), providing the first direct in vivo visualisation of brain amyloid.

This review will discuss the currently available amyloid imaging markers, focusing on the most extensively validated tracer, PIB. In addition, this review will concentrate on results from the rapidly expanding literature of PIB-PET in AD, dementia with Lewy bodies (DLB), fronto-temporal dementia (FTD), mild cognitive impairment (MCI) and cognitively normal volunteers, and summarise the contribution these studies have provided in understanding the association between amyloid, dementia and ageing.

Search strategy and selection criteria

All relevant original research papers were identified following MEDLINE searches using the key words: positron emission tomography or single photon

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emission computed tomography and amyloid, imaging and Alzheimer’s disease or dementia or mild cognitive impairment or MCI or Pick’s disease or vascular dementia or Lewy body disease or fronto-temporal dementia. Selection criteria: articles published between 2002 and February 2010, concerned with human studies, using the PET imaging modality, in English language. The selected articles were examined for additional references not revealed by automated searches. This yielded 85 articles whose abstracts were then read by all three authors. Based on subject matter and originality, a consensus was obtained in order to select the most relevant papers (n ¼ 48), which formed the basis of this review.

PET and amyloid imaging markers

PET utilises biologically active molecules in micro-molar or nanomolar concentrations that have been labelled with short-lived positron-emitting isotopes such as 15O (half-life 2 min), 11C (20 min) and 18F (110 min). The physical characteristics of isotopes and molecular specificity of labelled molecules, combined with high detection efficacy of modern PET scanners, provide a sensitivity for human in vivo measurement of indicator concentrations that are several orders of magnitude higher than with other imaging techniques (Santens and Petit, 1997). How-ever, the use of 15O and 11C limit their use to fully equipped PET centres with cyclotron and radio-pharmacy. Alternatively, 18F labelled tracers can be produced in a few specialised centres and then distributed regionally to a number of other sites within geographical reach that have solely PET scanning facilities.

FDDNP

Radiolabelled [18F]-FDDNP binds in vitro to Ab and tau proteins (Rabinovici and Jagust, 2009). The first human study with [18F]-FDDNP was undertaken in nine patients with early AD and seven similar age controls (Shoghi-Jadid et al., 2002). Compared to controls, tracer uptake ratios in AD were found to be 30% greater in medial temporal, hippocampus and amygdala, areas of dense neurofibrillary tangles (NFTs) and 10–15% greater in frontal, temporal and parietal cortices, regions of Ab plaques and less dense NFTs (Shoghi-Jadid et al., 2002). In terms of differentiating subject groups, FDDNP has been shown to distinguish AD from MCI (receiver operating characteristic (ROC)

PET imaging of brain amyloid

curve area ¼ 0.98) and MCI from those with no cognitive impairment (ROC curve area ¼ 0.95) (Small et al., 2006). However, FDDNP binding can be disrupted by commonly used non-steroidal anti-inflammatory drugs, which may prove one limitation on its wider utility (Agdeppa et al., 2003).

Pittsburgh compound-B (PIB)

Currently the most widely studied amyloid imaging agent and an analogue of the amyloid-binding dye Thioflavin-T. In vitro, PIB has been shown to bind specifically to extracellular and intravascular fibrillar Ab deposits in post mortem AD brains (Lockhart et al., 2007; Ikonomovic et al., 2008). At PET tracer concentrations, PIB does not significantly bind to other protein aggregates such as NFTs or Lewy bodies, hence a suitable tracer for diagnostically discriminating between AD and non-Ab dementias (Rabinovici et al., 2007; Rowe et al., 2008). PIB was originally labelled with 11C, limiting its use to PET centres with cyclotrons nearby.

Other imaging tracers

Current efforts are focused on developing a 18F equivalent to 11C-PIB, which may offer greater clinical utility. Three potential agents presently being investigated are 18F-AH110690 (a 30-fluoro analogue of PIB) (Vandenberghe et al., 2008), the stilbene derivative 18F-BAY94-9172 where results from a

preliminary study suggest similar characteristics to 11C-PIB (Rowe et al., 2008), and 18F-AV-45 (Klunk
and Mathis, 2008; Nordberg, 2008; Rowe et al., 2008). Further studies using these compounds are ongoing with results expected in the near future. Efforts are also underway to develop iodinated amyloid imaging agents for SPECT and magnetically labelled com-pounds that bind to amyloid for MRI (Nordberg, 2004).

Alzheimer’s disease

Using visual or semi-quantitative methods, investi-gations in AD have mainly revealed increased cortical PIB retention compared to controls (Klunk et al., 2004; Edison et al., 2007; Rabinovici et al., 2007; Rowe et al., 2007; Jack et al., 2008). In AD, the in vivo distribution of PIB has been shown to closely reflect the neuropathological distribution of Ab fibrillar plaques

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(Braak and Braak, 1991; Thal et al., 2002). More specifically, highest tracer binding has been consist-ently observed in AD subjects relative to controls in prefrontal cortex, precuneus and posterior cingulate, followed closely by lateral parietal, temporal cortex and striatum. Uptake in primary sensorimotor and visual cortices as well as medial temporal, hippocampus and amygdala were largely similar between groups. In addition, areas known to be relatively unaffected by amyloid deposition, such as subcortical white matter, pons and cerebellum, have shown low PIB binding in both AD and controls (Klunk et al., 2004; Klunk et al., 2007). Since the cerebellum shows little tracer uptake, also confirmed by post mortem results (Joachim et al., 1989), the cerebellum is frequently used as a reference region (Price et al., 2005).

Rowe et al. (2008) studied the effectiveness of 18F-BAY94-9172 in mild AD and older controls, where binding matched the reported post mortem distri-bution of Ab plaques (Rowe et al., 2008). In AD, widespread neocortical binding was significantly greater than in controls with an uptake pattern similar to PIB. Highest uptake occurred in the precuneus, posterior cingulate and frontal cortex followed by lateral temporal and parietal cortex. There was also relative sparing of the sensorimotor, occipital and medial temporal regions. The results suggest that 18F-BAY94-9172 detected Ab deposition analogous to PIB, and therefore may be a useful marker with the potential to aid: early diagnosis, differential diagnosis and therapeutic monitoring in AD. Further validation of 18F-BAY94-9172 is required, including characteris-ation of the metabolism and kinetics to determine the most precise and appropriate quantification methods (Rowe et al., 2008).

Using PIB, several longitudinal studies have been performed to assess disease progression. Engler et al. (2006) showed relatively stable PIB retention after 2 years of follow-up in patients with mild AD indicating that amyloid deposition reaches a plateau by the early clinical stages of the disease, consistent with the amyloid cascade hypothesis. Inter subject variability in PIB tracer uptake was high, and clinical and cognitive decline was shown to be more accurately monitored with FDG PET (Engler et al., 2006). Jack et al. (2009) found broadly similar results when examining global rates of change in PIB and brain atrophy over 1 year in a study comprising normal controls, MCI and AD (Jack et al., 2009). They found a small increase in global PIB over 1 year in AD, but this value was not significantly different from other diagnostic groups. Brain atrophy rates differed significantly by group and were highest in AD, intermediate in MCI and lowest in

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controls. Furthermore, clinical decline strongly corre-lated with brain atrophy rates but not changes in global PIB, and there was no association between brain atrophy and global PIB rates. In contrast, one study reported that rates of whole brain atrophy were significantly correlated to global and regional PIB binding, supporting the notion of amyloid deposition playing an early role in the pathogenesis of AD, triggering subsequent events such as neurodegenera-tion and brain atrophy which were more tightly coupled with clinical features such as cognitive decline (Archer et al., 2006). However, since only baseline PIB measures were used the relationship remains uncertain and longitudinal studies combining PIB, structural MR, other biomarkers and cognition are required.

In AD, studies have largely revealed a lack of association between PIB binding and measures of clinical and cognitive status. This may suggest that cognitive dysfunction is not directly related to amyloid plaque load in AD, and that clinical and cognitive progression proceed independently of amyloid depo-sition and are more closely coupled with neurodegen-eration (Engler et al., 2006; Jack et al., 2009; Rabinovici and Jagust, 2009). Such findings are consistent with the amyloid cascade hypothesis, and also the findings of raised amyloid burden both on CSF biomarkers and amyloid imaging in non-demented subjects with MCI (Forsberg et al., 2008; Koivunen et al., 2008).

Dementia with Lewy bodies and Parkinson’s disease dementia

Both DLB and Parkinson’s disease dementia (PDD) are characterised at autopsy by the presence of subcortical and/or cortical Lewy bodies. It has been well established that often there is also a substantial burden of amyloid pathology, though compared to AD plaques are more often diffuse than neuritic (Ballard et al., 2006). A limited number of PET studies have examined the amyloid burden in DLB and PDD in vivo (Edison et al., 2008; Gomperts et al., 2008). Edison et al. (2008) showed that in DLB mean brain PIB uptake was significantly higher than in controls, while uptake in PDD was comparable to controls and PD without dementia. In particular, 85% (11/13) of DLB patients had significantly increased amyloid load in one or more cortical regions, whereas 83% (10/12) of PDD patients had ‘normal’ PIB uptake. None of the PD patients showed any evidence of increased cortical amyloid deposition. A report by Gomperts et al. (2008) revealed that cortical amyloid burden as measured by PIB was higher in DLB than in PDD, but similar to AD.

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In agreement with Edison et al. (2008), cortical PIB binding in PDD was also found to be equivalent to PD and controls.

The findings suggest that global cortical amyloid burden is high in DLB but low and infrequent in PDD. An increased amyloid burden could contribute to the rapid progression of dementia in DLB (Edison et al., 2008), while it may also play a role in the timing of dementia relative to the motor symptoms of Parkin-sonism in DLB and PDD (Ballard et al., 2006; Gomperts et al., 2008).

Mild cognitive impairment

Assuming that people with MCI with underlying AD pathology are at higher risk of progressing to dementia, amyloid imaging may have potential in identifying MCI subjects who may be at high risk for progressing to AD, as well as separating such subjects from those with alternative causes for their cognitive impairment (Morris et al., 2001). However, this assumption requires careful testing as protective factors for AD also exist which may modify a relationship between Ab pathology and clinical expression of cognitive impair-ment (Stozicka et al., 2007).

Numerous studies in MCI have demonstrated that PIB uptake is intermediate between AD and controls (Lopresti et al., 2005; Kemppainen et al., 2007; Pike et al., 2007; Rowe et al., 2007; Forsberg et al., 2008; Jack et al., 2008; Mormino et al., 2009). However, in most studies, the distribution of PIB binding for the majority of cases with MCI show AD-like uptake levels, with a minority having low-control level binding and a small number falling in-between. Overall, 52-87% of MCI patients show elevated PIB binding, depending on the criteria used to diagnose MCI and the threshold used to define PIB-positivity (Lopresti et al., 2005; Kemppainen et al., 2007; Pike et al., 2007; Rowe et al., 2007; Forsberg et al., 2008; Jack et al., 2008; Mormino et al., 2009). Wolk et al. (2009) used PIB to determine the presence of AD pathology in different MCI subtypes, where 54% of their 26 subjects were PIB-positive (Wolk et al., 2009). Individuals meeting criteria for amnestic MCI were more likely to be PIB-positive than patients with non-amnestic MCI (Pike et al., 2007; Wolk et al., 2009). PIB-positivity is more common in Apo E4 carriers, compared to non-carriers (Pike et al., 2007). Cross-sectional comparisons of PIB-positive and PIB-negative MCI revealed lower episodic memory performance in PIB-positive patients in some studies (Pike et al., 2007), but not others (Rowe et al., 2007; Jack et al., 2008).

PET imaging of brain amyloid

Longitudinally, one report comprising 21 MCI, 21 AD and 6 healthy controls showed that 33% (7/21) of MCI subjects with elevated PIB binding later at clinical follow-up (mean SD; 8.1 6.0 months) converted to AD (Forsberg et al., 2008). While a study of 26 MCI subjects found 38% (5/13) of those defined as PIB-positive later converted to AD (21.2 16.0 months) (Wolk et al., 2009). Therefore, amyloid imaging may provide some prognostic information in MCI, and could select MCI subjects that are candidates for AD-specific therapies aimed at reducing amyloid, though further validation studies with longitudinal follow-up are required (Rabinovici and Jagust, 2009).

When PIB binding was examined as a continuous variable, significant negative correlations were found with episodic memory, implying that individuals with increased cortical PIB binding were already on the path to AD (Pike et al., 2007; Mormino et al., 2009). Of these studies, Mormino et al. (2009) also observed a negative association between PIB and hippocampal volume, suggesting that a decline in episodic memory in older subjects may be caused by amyloid induced hippocampal atrophy (Mormino et al., 2009).

Fronto-temporal dementia and other dementia subtypes

Fronto-temporal dementia (FTD) is a syndrome that can be difficult to distinguish clinically from AD. FTD also shares some of the characteristic structural deficits of AD, i.e. hippocampal atrophy (Galton et al., 2001). However, since amyloid deposition is not a neuro-pathological feature of FTD, PIB imaging may be of value in differentiating FTD from AD. Rowe et al. (2007) reported a cortical PIB pattern in FTD similar to that of healthy controls (Rowe et al., 2007), while more recently, Engler et al. (2008) showed that in 8 of their 10 patients with FTD little or no PIB retention was present, a pattern that was significantly different from AD (Engler et al., 2008).

Amyloid deposition is also a neuropathological marker of other dementias and movement disorders, including cerebral amyloid angiopathy (CAA) and posterior cortical atrophy (PCA) (Lucignani, 2009). Patients with CAA show relatively higher occipital PIB retention than AD patients, consistent with the distribution of this pathology at autopsy (Johnson et al., 2007). Other studies have suggested that PIB can also be used to exclude atypical presentations of AD in clinical syndromes usually associated with non-Ab pathology such as primary progressive aphasia (PPA) and prion disease (Rabinovici and Jagust, 2009). Single

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case studies have reported asymmetric left hemispheric PIB uptake in PPA and posterior-predominant PIB uptake in PCA. At a group level, PIB binding in PPA and PCA was found to be diffuse, symmetric and indistinguishable from the pattern observed in AD, and does not appear to correlate with clinical phenotype (Rabinovici and Jagust, 2009). Non-amnestic presen-tations of AD are relatively common at dementia referral centres, and PIB may have a future role in selecting patients with atypical clinical symptoms who may be candidates for anti-Ab therapies (Rabinovici and Jagust, 2009).

Cognitively normal controls

Several studies have consistently identified elevated PIB binding in a subset of otherwise apparently normal older volunteers. The proportion of PIB-positive cases has been shown to range from 10 to 30% depending on age of the cohort and threshold for defining PIB-positivity (Klunk et al., 2004; Mintun et al., 2006; Pike et al., 2007; Aizenstein et al., 2008; Jack et al., 2008; Mormino et al., 2009; Reiman et al., 2009). Amyloid pathology has been observed in autopsy brains of older persons without dementia in prefrontal cortex, lateral and medial parietal regions, lateral temporal cortex and striatum (Bennett et al., 2006). For ante mortem cases, binding patterns are more focal, with a number of studies demonstrating preferential PIB binding in prefrontal cortex and posterior cingulate/precuneus (Mintun et al., 2006; Rowe et al., 2008). A number of controls have shown focal binding in occipital cortex, a pattern which would be consistent of vascular amyloid deposition (Rowe et al., 2007). As yet, elevated levels of PIB have not been observed in normal younger individuals (Mintun et al., 2006).

Studies evaluating the relationship between PIB binding and cognition in apparently healthy subjects have yielded varying results. When subjects were dichotomised into PIB-positive and PIB-negative groups, a number of studies showed no significant differences in cognitive performance suggesting that even with a sizeable amyloid load individuals can remain cognitively normal (Mintun et al., 2006; Rowe et al., 2007; Aizenstein et al., 2008; Jack et al., 2008). However, others have reported significant negative correlations between PIB binding and episodic memory, implying a number of subjects with an appreciable amyloid burden present with some cognitive dysfunction (Pike et al., 2007; Villemagne et al., 2008; Mormino et al., 2009). Villemagne et al. (2008) retrospectively examined cognitive test scores over 6–10 years in 34 subjects

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enrolled in the Melbourne Healthy Aging Study who then had PIB-PET scans. They found that PIB-positivity was more common in subjects with declining cognitive test scores (70%) than in those with stable scores (17%) (Villemagne et al., 2008). Therefore, increased PIB uptake in normal older people may be associated with prior history of decreased episodic memory perform-ance and structural and functional brain changes suggestive of early AD. Several large longitudinal studies are currently underway to test this hypothesis.

PIB-PET, the amyloid hypothesis and anti-amyloid interventions

PIB-PET studies support a model in which amyloid aggregation is an early event on the path to dementia. By the time subjects reach a stage of MCI, amyloid accumulation already approximates that of AD, a process which may already have taken over two decades (Jack et al., 2009). As patients progress to mild dementia, clinical decline and neurodegeneration (as demonstrated by MRI or FDG-PET) accelerate and proceed together, but seemingly independent of amyloid accumulation, which has either reached a plateau or continues to progress very slowly (Rabino-vici and Jagust, 2009). This implies that the optimal time to initiate therapies targeting Ab may be in the pre-MCI stages when cognition is still intact, and neurodegeneration is mild. By the time patients are at MCI or mild AD, other pathologic processes that are independent of fibrillar Ab may already be established, and the therapeutic window for anti-amyloid inter-ventions may already be closed (Rabinovici and Jagust, 2009). Unfortunately, however, most current trials of anti-amyloid agents are in those with established AD, which may be a stage at which such intervention is too late. More work is needed to establish the quantitative relationship between PIB binding and Ab pathology at various disease stages. Most data are derived from cross-sectional studies, and need to be verified by increase in the number of follow-up investigations.

Conclusions and future directions

PET imaging with PIB appears to be a sensitive and specific marker for underlying Ab amyloidosis and an important investigative tool for examining the dynamic relationship between amyloid deposition, clinical symptoms and structural and functional changes in normal aging and dementia. Figure 1(a, b) summarises the standardised cortical PIB binding

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and pooled weighted estimates across the reviewed studies in controls, MCI and AD. It shows potential for distinguishing AD from FTD, and AD from healthy controls, though specificity for the latter requires further examination. It may help distinguish ADD from PDD, but not AD from DLB. Amyloid imaging in healthy controls may offer the possibility detecting those at high risk of future AD, as so candidates for early preventative measures if and when they become available. However, with approximately 30% of healthy older controls being PIB positive, specificity may be poor, though long term follow-up of such PIB-positive cases, ideally with autopsy correlation is needed to determine this. Amyloid imaging is also a potential tool for investigating AD pathology in other settings, for example in those after stroke or with high vascular risk, when it may help determine the relations between vascular factors and degenerative pathology. Previous reviews of amyloid imaging with PIB PET have recently been described in ageing and dementia (Brooks, 2009; Rabinovici and Jagust, 2009; Wolk and Klunk, 2009). However, the present review served as an update to the rapidly expanding literature.

To the best of our knowledge, only two studies have investigated the direct relationship between PIB binding and neuropathology in dementia. Both studies, one in AD the other in PDD demonstrated high selectivity of PIB for fibrillar Ab deposits (Ikonomovic et al., 2008; Burack et al., 2010). However, sample sizes were very small (AD: n ¼ 1; PDD: n ¼ 3) and therefore difficult to draw any accurate conclusions. The diagnostic utility of PET amyloid imaging in dementia is at present limited. This was largely due to small samples within these studies where it is often difficult to pursue a rigorous evaluation of diagnostic sensitivity and specificity. One study has described sensitivity and specificity of 90% in distinguishing AD from controls (Mormino et al., 2009), while another using CSF biomarkers to asses Ab1–42 and Tau concentrations yielded sensitivity 95% and specificity 83% for detection of AD from subjects with MCI (Hansson et al., 2006). However, the overall frequency of a disease will also affect predictive values such that specificity and sensitivity alone may be misleading. In addition, studies do not appear to calculate predictive probabilities. As in many initial studies investigating biomarkers, amyloid imaging studies to date have been undertaken on carefully selected samples who meet clear diagnostic criteria. Results may, therefore, not yet be generalisable to all dementia subjects and further studies in more clinically representative samples are required.

Amyloid deposition appears to be an early event on the path to dementia, and so at the time dementia

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Figure 1 (a) Cortical PIB binding profiles across studies in controls, MCI and AD. (b) Pooled weighted means of cortical PIB across studies in controls, MCI and AD. This figure is available in colour online at wileyonlinelibrary.com/journal/gps

becomes clinical progression may be better assessed using other imaging techniques such as MRI or FDG-PET. PIB binds only to fibrillar Ab, and apparent dissociations between PIB uptake and other disease measures may be accounted for by soluble forms of Ab which are not detected by PIB-PET. Thus, PIB only captures one aspect of amyloid pathology, and does not assess other potentially important changes in tau and other markers. Consistent with these observations, it has long been known that there is a closer relationship between synaptic loss and tau, rather than amyloid with cognitive impairment (Terry et al., 1991).

A number of promising 18F-labelled imaging markers are currently under development if successful will allow broader application of amyloid imaging to clinical practice and research. The development of in vivo biomarkers for other critical elements of AD pathogenesis such as soluble Ab, tau, acetylcholine and brain inflammation would further inform our under-standing of the disease and assist in developing and

testing disease-modifying therapies for AD and other dementia syndromes.

Conflict of interest

John O’Brien has acted as a consultant for Bayer Healthcare.

Disclosures

Authors have nothing to disclose.

Acknowledgements

This work was supported by the UK NIHR Biomedical Research Centre for Ageing and Age-related disease

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Key Points

PIB-PET imaging is a specific marker for underlying Aß amyloid deposition and represents an important investigative tool for examining the relationship between amyloid burden, clinical symptoms, and structural and functional changes in dementia. Amyloid deposition appears to be an early event, and as dementia progresses clinical decline seems to be more associated with neuro-degeneration than amyloid burden. Development of biomarkers for investigating other aspects of dementia pathology would increase our understanding in studying disease-modifying and preventive treatments in dementia.

awarded to the Newcastle upon Tyne Hospitals NHS Foundation Trust.

References

Agdeppa ED, Kepe V, Petri A, et al. 2003. 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-[(18)F]fluoroethyl)(methyl)a-mino]-2-naphthyl]ethylidene)malononitrile. Neuroscience 117: 723–730.

Aizenstein HJ, Nebes RD, Saxton JA, et al. 2008. Frequent amyloid deposition without significant cognitive impairment among the elderly. Arch Neurol 65: 1509–1517.

Archer HA, Edison P, Brooks DJ, et al. 2006. Amyloid load and cerebral atrophy in Alzheimer’s disease: an 11C-PIB positron emission tomography study. Ann Neurol 60: 145–147.

Ballard C, Ziabreva I, Perry R, et al. 2006. Differences in neuropathologic character-istics across the Lewy body dementia spectrum. Neurology 67: 1931–1934.

Bennett DA, Schneider JA, Arvanitakis Z, et al. 2006. Neuropathology of older persons without cognitive impairment from two community-based studies. Neurology 66: 1837–1844.

Bornebroek M, Verzijlbergen JF, Haan J, et al. 1996. Potential for imaging cerebral amyloid deposits using 123I-labelled serum amyloid P component and SPET. Nucl Med Commun 17: 929–933.
Braak H, Braak E. 1991. Neuropathological stageing of Alzheimer-related changes.
Acta Neuropathol 82: 239–259.

Brooks DJ. 2009. Imaging amyloid in Parkinson’s disease dementia and dementia with Lewy bodies with positron emission tomography. Mov Disord 24 (Suppl 2): S742– S747.

Burack MA, Hartlein J, Flores HP, et al. 2010. In vivo amyloid imaging in autopsy-confirmed Parkinson disease with dementia. Neurology 74: 77–84.

Edison P, Archer HA, Hinz R, et al. 2007. Amyloid, hypometabolism, and cognition in Alzheimer disease: an [11C]PIB and [18F]FDG PET study. Neurology 68: 501–508.

Edison P, Rowe CC, Rinne JO, et al. 2008. Amyloid load in Parkinson’s disease dementia and Lewy body dementia measured with [11C]PIB positron emission tomography. J Neurol Neurosurg Psychiatr 79: 1331–1338.

Engler H, Forsberg A, Almkvist O, et al. 2006. Two-year follow-up of amyloid deposition in patients with Alzheimer’s disease. Brain 129: 2856–2866.

Engler H, Santillo AF, Wang SX, et al. 2008. In vivo amyloid imaging with PET in frontotemporal dementia. Eur J Nucl Med Mol Imaging 35: 100–106.

Forsberg A, Engler H, Almkvist O, et al. 2008. PET imaging of amyloid deposition in patients with mild cognitive impairment. Neurobiol Aging 29: 1456–1465.

Friedland RP, Majocha RE, Reno JM, Lyle LR, Marotta CA. 1994. Development of an anti-A beta monoclonal antibody for in vivo imaging of amyloid angiopathy in Alzheimer’s disease. Mol Neurobiol 9: 107–113.

Galton CJ, Patterson K, Graham K, et al. 2001. Differing patterns of temporal atrophy in Alzheimer’s disease and semantic dementia. Neurology 57: 216–225.

Gomperts SN, Rentz DM, Moran E, et al. 2008. Imaging amyloid deposition in Lewy body diseases. Neurology 71: 903–910.

H. Quigley et al.

Hansson O, Zetterberg H, Buchhave P, et al. 2006. Association between CSF biomarkers and incipient Alzheimer’s disease in patients with mild cognitive impairment: a follow-up study. Lancet Neurol 5: 228–234.

Hardy J, Selkoe DJ. 2002. The amyloid hypothesis of Alzheimer’s disease: progress and
problems on the road to therapeutics. Science 297: 353–356.
Hardy JA, Higgins GA. 1992. Alzheimer’s disease: the amyloid cascade hypothesis.
Science 256: 184–185.

Ikonomovic MD, Klunk WE, Abrahamson EE, et al. 2008. Post-mortem correlates of in vivo PiB-PET amyloid imaging in a typical case of Alzheimer’s disease. Brain 131: 1630–1645.

Jack CR Jr, Lowe VJ, Senjem ML, et al. 2008. 11C PiB and structural MRI provide complementary information in imaging of Alzheimer’s disease and amnestic mild cognitive impairment. Brain 131: 665–680.

Jack CR Jr, Lowe VJ, Weigand SD, et al. 2009. Serial PIB and MRI in normal, mild cognitive impairment and Alzheimer’s disease: implications for sequence of pathological events in Alzheimer’s disease. Brain 132: 1355–1365.

Joachim CL, Morris JH, Selkoe DJ. 1989. Diffuse senile plaques occur commonly in the cerebellum in Alzheimer’s disease. Am J Pathol 135: 309–319.

Johnson KA, Gregas M, Becker JA, et al. 2007. Imaging of amyloid burden and distribution in cerebral amyloid angiopathy. Ann Neurol 62: 229–234.

Kemppainen NM, Aalto S, Wilson IA, et al. 2007. PET amyloid ligand [11C]PIB uptake is increased in mild cognitive impairment. Neurology 68: 1603–1606.

Klunk WE, Engler H, Nordberg A, et al. 2004. Imaging brain amyloid in Alzheimer’s disease with Pittsburgh Compound-B. Annal Neurol 55: 306–319.
Klunk WE, Mathis CA. 2008. The future of amyloid-beta imaging: a tale of radio-
nuclides and tracer proliferation. Curr Opin Neurol 21: 683–687.

Klunk WE, Price JC, Mathis CA, et al. 2007. Amyloid deposition begins in the striatum of presenilin-1 mutation carriers from two unrelated pedigrees. J Neurosci 27: 6174– 6184.

Koivunen J, Pirttila T, Kemppainen N, et al. 2008. PET amyloid ligand [11C]PIB uptake and cerebrospinal fluid beta-amyloid in mild cognitive impairment. Dementia Geriatr Cognit Disord 26: 378–383.

Lockhart A, Lamb JR, Osredkar T, et al. 2007. PIB is a non-specific imaging marker of amyloid-beta (Abeta) peptide-related cerebral amyloidosis. Brain 130: 2607– 2615.

Lopresti BJ, Klunk WE, Mathis CA, et al. 2005. Simplified quantification of Pittsburgh Compound B amyloid imaging PET studies: a comparative analysis. J Nucl Med 46: 1959–1972.
Lucignani G. 2009. Clinical applications of PET amyloid imaging: an update. Eur J
Nucl Med Mol Imaging 36: 1185–1190.

Maggio JE, Stimson ER, Ghilardi JR, et al. 1992. Reversible in vitro growth of Alzheimer disease beta-amyloid plaques by deposition of labeled amyloid peptide. Proc Natl Acad Sci USA 89: 5462–5466.

Mathis CA, Wang Y, Holt DP, et al. 2003. Synthesis and evaluation of 11C-labeled 6-substituted 2-arylbenzothiazoles as amyloid imaging agents. J Med Chem 46: 2740– 2754.

Mintun MA, Larossa GN, Sheline YI, et al. 2006. [11C]PIB in a nondemented population: potential antecedent marker of Alzheimer disease. Neurology 67: 446–452.

Mormino, EC, Kluth, JT, Madison, CM, et al. 2009. Episodic memory loss is related to hippocampal-mediated beta-amyloid deposition in elderly subjects. Brain 132: 1310–1323.

Morris JC, Storandt M, Miller JP, et al. 2001. Mild cognitive impairment represents early-stage Alzheimer disease. Arch Neurol 58: 397–405.

Nordberg A. 2004. PET imaging of amyloid in Alzheimer’s disease. Lancet Neurol 3:
519–527.

Nordberg A. 2008. Amyloid imaging in Alzheimer’s disease. Neuropsychologia 46:
1636–1641.

Pike KE, Savage G, Villemagne VL, et al. 2007. Beta-amyloid imaging and memory in non-demented individuals: evidence for preclinical Alzheimer’s disease. Brain 130: 2837–2844.

Poduslo JF, Wengenack TM, Curran GL, et al. 2002. Molecular targeting of Alzhei-mer’s amyloid plaques for contrast-enhanced magnetic resonance imaging. Neu-robiol Disease 11: 315–329.

Price JC, Klunk WE, Lopresti BJ, et al. 2005. Kinetic modeling of amyloid binding in humans using PET imaging and Pittsburgh Compound-B. J Cerebr Blood Flow Metabol 25: 1528–1547.

Rabinovici GD, Furst AJ, O’Neil JP, et al. 2007. 11C-PIB PET imaging in Alzheimer disease and frontotemporal lobar degeneration. Neurology 68: 1205–1212.

Rabinovici GD, Jagust WJ. 2009. Amyloid imaging in aging and dementia: testing the
amyloid hypothesis in vivo. Behav Neurol 21: 117–128.

Reiman EM, Chen K, Liu X, et al. 2009. Fibrillar amyloid-beta burden in cognitively normal people at 3 levels of genetic risk for Alzheimer’s disease. Proc Natl Acad Sci USA 106: 6820–6825.

Rowe CC, Ackerman U, Browne W, et al. 2008. Imaging of amyloid beta in Alzheimer’s disease with 18F-BAY94-9172, a novel PET tracer: proof of mechanism. Lancet Neurol 7: 129–135.

Rowe CC, Ng S, Ackermann U, et al. 2007. Imaging beta-amyloid burden in aging and dementia. Neurology 68: 1718–1725.

PET imaging of brain amyloid

Santens P, Petit H. 1997. Positron emission tomography in dementia. Acta Neurol Belg 97: 192–195.

Shoghi-Jadid K, Small GW, Agdeppa ED, et al. 2002. Localization of neurofibrillary tangles and beta-amyloid plaques in the brains of living patients with Alzheimer disease. Am J Geriatr Psychiatr 10: 24–35.

Small GW, Kepe V, Ercoli LM, et al. 2006. PET of brain amyloid and tau in mild cognitive impairment. New Engl J Med 355: 2652–2663.

Stozicka Z, Zilka N, Novak M. 2007. Risk and protective factors for sporadic Alzheimer’s disease. Acta Virologica 51: 205–222.

Terry RD, Masliah E, Salmon DP, et al. 1991. Physical basis of cognitive alterations in Alzheimer’s disease: synapse loss is the major correlate of cognitive impairment. Annal Neurol 30: 572–580.

Thal DR, Rub U, Orantes M, Braak H. 2002. Phases of A beta-deposition in the human brain and its relevance for the development of AD. Neurology 58: 1791–1800.

Vandenberghe R, Thurfjell L, Owenius R, et al. 2008. P1-303: Phase I study of the 18F-labelled benzothiazole derivative [18F]AH110690 as a biomarker of

999

Alzheimer’s disease-related brain amyloidosis. Alzheimer’s Dementia 4: T308– T308.

Verhoeff NPLG, Wilson AA, Takeshita S, et al. 2004. In-vivo imaging of Alzheimer disease beta-amyloid with [11C]SB-13 PET. Am J Geriatr Psychiatr 12: 584–595.

Villemagne VL, Pike KE, Darby D, et al. 2008. Abeta deposits in older non-demented individuals with cognitive decline are indicative of preclinical Alzheimer’s disease. Neuropsychologia 46: 1688–1697.

Wimo A, Winblad B, Aguero-Torres H, von Strauss E. 2003. The magnitude of dementia occurrence in the world. Alzheimer Disease Assoc Disord 17: 63–67.
Wolk DA, Klunk W. 2009. Update on amyloid imaging: from healthy aging to
Alzheimer’s disease. Curr Neurol Neurosci Rep 9: 345–352.

Wolk DA, Price JC, Saxton JA, et al. 2009. Amyloid imaging in mild cognitive impairment subtypes. Ann Neurol 65: 557–568.

Zhuang Z-P, Kung M-P, Wilson A, et al. 2003. Structure-activity relationship of imidazo[1,2-a]pyridines as ligands for detecting beta-amyloid plaques in the brain.compound 991

Abvos

The nucleus is made of one or more protons and a number of neutrons.

compound 991