Clinical utility of amyloid PET imaging with (18)F-florbetapir: a

retrospective study of 100 patients

C Carswell, 1 Z Win, 3 K Muckle, 1 A Kennedy, 1 A Waldman, 2 G Dawe, 3

Tara Diane Barwick,4,5 Sameer Khan,4 Paresh Malhotra,1,6† Richard

Perry,1,6†

1 Department of Neurology, Imperial College Healthcare NHS Trust, London

2 Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh

3 Department of Neuroradiology, Imperial College Healthcare NHS Trust, London

4 Department of Nuclear Medicine, Imperial College Healthcare NHS Trust, London

5 Division of Cancer and Surgery, Imperial College London

6 Division of Brain Sciences, Faculty of Medicine, Imperial College London

Correspondence to:

Dr Richard Perry

1 Department of Neurology, Imperial NHS Trust, Charing Cross Hospital, Fulham Palace Road, London, W6 8RF

richard.perry@imperial.nhs.uk . Tel. 0203 311 1194

†joint senior authors

ABSTRACT

Background and 0bjective: Amyloid-PET Imaging (API) detects amyloid-beta pathology early

in the course of Alzheimer’s disease (AD) with high sensitivity and specificity. (18)F-

florbetapir (Amyvid) is an amyloid-binding PET ligand with a half-life suitable for clinical use

outside of the research setting. How API affects patient investigation and management in

the “real-world” arena is unknown. To address this we retrospectively documented the

effect of API in patients in the memory clinic.

Methods: We reviewed the presenting clinical features, the pre- and post-API investigations,

diagnosis and outcomes for the first 100 patients who had API as part of their routine work-

up at the Imperial Memory Centre, a tertiary referral clinic in the UK National Health

Service.

Results: API was primarily used to investigate patients with atypical clinical features (56

cases) or those that were young at onset (42 cases). MRI features of AD did not always

predict positive API (67%), and six of 23 patients with MRIs reported as normal were

amyloid-PET positive. There were significantly more cases categorised as non-AD dementia

post API (from 11 to 23). Patients investigated when API was initially available had fewer

overall investigations and all patients had significantly fewer investigations in total post API.

Conclusions: API has a clear impact upon the investigation of young onset or complex

dementia whilst reducing the overall burden of investigations. It was most useful in younger

patients, atypical presentations, or individuals with multiple possible causes of cognitive

impairment.

INTRODUCTION

Alzheimer’s disease (AD) is the most common form of dementia. Clinical diagnosis of

Alzheimer’s disease is usually based on clinical history, examination, and ancillary

investigations such as structural brain imaging with MRI and neuropsychological testing.

Even in the best centres, studies of diagnostic accuracy based on histopathological

confirmation can show sensitivity and specificity of about 80% and 55% respectively. 1–4

For patients presenting earlier, with atypical symptoms at onset, younger age at onset, or

with multiple pathologies that may cause cognitive impairment, the diagnostic accuracy is

even lower, often leading to delays in diagnosis. 5

Cerebral amyloid plaques are one of the pathological hallmarks of Alzheimer’s disease and

the ability to demonstrate their presence in vivo via amyloid PET imaging has led to a

considerable body of research over the last decade. However, early amyloid PET tracers had

short half-lives limiting their clinical application. Now three (18)F ligands, florbetapir

(Amyvid, Eli Lilly), florbetaben (NeuraCeq, Piramal), and flutemetamol (Vizamyl, GE

Healthcare), have been licensed for clinical use in specific populations and guidelines

regarding their use have been proposed. 6 The longer half-life of these fluorinated ligands

means that tracers can be readily distributed. 7–11 Importantly, (18)F-florbetapir has been

proven to be both highly sensitive and specific for AD when compared to autopsy findings. 12–15

The ability of these imaging techniques to contribute to clinical utility has not yet been

widely demonstrated. Evidence from research populations16–22 suggests that amyloid PET

imaging (API) offers useful prognostic information on the progression of MCI subjects to

convert to Alzheimer’s disease, can influence treatment decisions with acetyl cholinesterase

inhibitors, and provides clarity in those with atypical presentations.

Here, we present a retrospective review of 100 “real-world” patients investigated in a single

centre memory clinic who underwent amyloid PET imaging (API) as part of their diagnostic

work-up.

METHODS

Patient population

API became available at The Imperial Memory Centre (IMC) in December 2013. All funding

for API was via the UK National Health Service, through local arrangements within Imperial

College Healthcare NHS Trust. The patients are the first one hundred patients investigated

with API at the IMC between December 2013 and January 2016.

Decision to investigate with Amyloid-PET Imaging

Patients were seen at the IMC by one of four experienced cognitive neurologists; the

decision to perform API was made by consensus between neuroradiologists, nuclear

medicine specialists and cognitive neurologists at regular multi-disciplinary meetings where

clinical details and structural brain imaging were discussed. Our imaging process was set up

to follow the guidelines for appropriate use (supplementary appendix S1). 6

Clinical details and diagnostic categorisation

The clinical details were retrospectively reviewed using the patient records and

demographic details, diagnosis, medical co-morbidity, disease course, cognitive

investigations and treatment were noted.

For the purposes of this study patients were also categorised diagnostically both pre- and

post-API as Subjective Cognitive Impairment (SCI), Mild Cognitive Impairment (MCI), MCI-AD

(for MCI which already had a positive CSF biomarker or hippocampal atrophy on MRI), AD

dementia and non-AD dementia. Patients who were classified as MCI-AD due to positive CSF

biomarker with subsequent negative API were then re-classified as MCI.

For the purposes of this study cognitive investigations were classified as any imaging

modality to determine cause of cognitive impairment (e.g. MRI or CT head, DaT scan or FDG-

PET, CSF analysis, neuropsychological assessment and genetic blood tests). For counting the

number of investigations, the patient records (electronic and hard copy), electronic

radiology system, electronic pathology test records were reviewed individually for each

patient. Each “cognitive investigation” was noted to be before or after an index date (the

date of the Amyloid imaging at IMC) and given a value of one. The total number of

“cognitive investigations” before and after API was then summated.

MRI findings were documented using the formal MRI report (visual non-quantitative

readings) whether the imaging was performed at Imperial College Healthcare NHS Trust or

elsewhere. They were classified into one of four categories, those reported as normal, those

which were reported as being consistent with AD or with hippocampal atrophy, those being

consistent with another neurodegenerative disorder, and those with reported abnormalities

which were not pathognomonic of a specific dementia syndrome (e.g. generalised atrophy,

non-specific microangiopathic disease, prior stroke, prior traumatic brain injury etc). All MRI

scans had been reported by a specialist neuroradiologist.

Cerebrospinal fluid (CSF) biomarkers were classified as positive if abeta was reduced and

total tau was increased and negative when both abeta and tau were in the normal range.

Those with isolated low abeta or isolated raised tau were grouped separately. 2

(18)F-florbetapir Imaging

A 20-minute dynamic list mode PET acquisition of the brain was obtained beginning 40

minutes after injection of an intravenous bolus of 370 mBq (10 mCi) (18)F-florbetapir ,on a

Siemens Biograph 64 PET/CT scanner. The best motion-free 10 minutes of PET data was

selected visually for processing, prior to a diagnostic read. All 20 minutes of PET data was

processed if it was deemed there was no significant movement. PET images were

reconstructed using a 3D ordered subset expectation maximization (OSEM) algorithm (4

iterations, 14 subsets; Gaussian filter: 3 mm; zoom:2) with low dose CT based attenuation

correction. Images were analysed on a dedicated nuclear medicine workstation (Hermes,

Sweden). All images were qualitatively read as amyloid positive or amyloid negative by an

experienced nuclear medicine radiologist (NMR) using greyscale images. In equivocal cases

(20%) each scan was independently read by two NMR and a third in cases where there was

discordance to create a majority consensus opinion.

Statistical Analysis

Statistics were generated using Prism 6 (GraphPad Software). Datasets were not normally

distributed and non-parametric tests were applied. Comparison between groups of

qualitative data was performed using Fischer’s exact test. Paired data over time were

compared using two-tailed Wilcoxon matched-pairs signed rank test. Comparison of

quantitative data was performed using the two-tailed Mann Whitney U test.

RESULTS

Demographic and clinical profiles

One hundred patients seen at the IMC underwent API from December 2013 to January 2016

without complication. Forty four patients had been initially assessed before API was

available with the remainder presenting after. The duration of follow-up post-API (median

8.5 months) was not significantly different from pre-API (7.6 months) (Table 1). Patients who

were imaged tended to be young with a median age of 66.7 years (range 44.5-88) (Table 1).

The median duration of cognitive impairment at presentation was 24 months but this was

also highly variable amongst the population (range 0.5-120) (Table 1).

Patients undergoing API were formed of three main categories: undifferentiated MCI (33

patients with a median age of 69.5 years [range 44.5-80]), young onset dementia (YOD) (42

patients), and those with cognitive impairment who were older than 65 years which was

thought to be due to AD but with atypical clinical features making diagnosis uncertain (25

patients) (Table 1). Two patients with subjective cognitive impairment (SCI) had API, one

who had atrophy reported on MRI brain imaging and one about whom the family repeatedly

expressed concerns with regard to declining cognition.

Atypical clinical features were also sometimes present in those whose primary indication for

API was MCI (2 patients) or YOD (29 patients). There were distinct subpopulations within

those with atypical clinical features; those with multiple medical disorders which might

account for their cognitive impairment (15 patients), those in whom AD was thought most

likely but with non-corroborative investigations (14 patients), those with a progressive

aphasia (11 patients, supplementary appendix S2), those with prominent visual or frontal

symptoms (eight patients), those with parkinsonian features (six patients), those in whom

the clinical course was abnormally benign or aggressive (five patients), and those with

cognitive impairment thought to be secondary to cerebral amyloid angiopathy (CAA) (five

cases) (figure 1).

Of the patients with multiple medical disorders which potentially compromised

diagnostic clarity, 12 had disorders recognised to impair cognition (six with depression or

bipolar disorder, three with previous alcohol/substance abuse, two with previous traumatic

brain injury, and one with epilepsy); the remaining patients had either multiple vascular risk

factors and chronic kidney disease, or previous carcinoma treated with systemic

chemotherapy. Out of the 14 patients who were thought to have AD but had non-

supportive investigations, seven cases had normal or isolated raised tau on CSF, four had

consecutive CSF examinations which were conflicting, two had positive CSF biomarkers but

normal imaging and one had generalised atrophy on MRI with disproportionately enlarged

ventricles. Eleven patients presented with a progressive non-fluent aphasia (figure 1,

supplementary appendix S2). All had word-finding difficulty with variable grammar and

inability to repeat sentences. Eight of the 56 patients with atypical clinical features were

classified in more than one atypical subcategory.

Table 1 Patient characteristics, source of referral and API indication

General Characteristics ResultNo. female 41Median presenting age in years (range) [n100] 66.7 (44.5-88.0)Median years of education (range) [n49] 14 (10-21)Median duration of cognitive impairment in months (range) [n96]

24 (0.5-120)

Median duration pre-API at IMC (months) [n94] 7.1 (0-84)Median duration post-API at IMC (months) [n94] 8.5 (0.4-22.6)*

Source of Referred Patients [n100]Primary care physician 48Secondary care referral from neurologist / psychiatrist

52

API Indication [n100]SCI†/MCI 33YOD 42Atypical clinical features± 56* The difference between pre and post follow up duration is not significant.† Two patients had SCI.±25 patients were >65 years without MCI/YOD.

API, amyloid-PET imaging; IMC, Imperial Memory Centre; SCI, subjective cognitive impairment; MCI,

Mild Cognitive Impairment; YOD, Young Onset Dementia

API results could not reliably be predicted by pre-imaging investigations

All patients who underwent API were previously investigated with at least one MRI brain

scan (Table 1). While the majority of patients had pre-API neuropsychological assessments

(66 patients), only 37 patients had CSF biomarker studies; cerebral (18)F-FDG-PET imaging

was performed in 13 patients, with a minority having DaT scans (five patients) or genetic

testing (PRNP (x1), HD (x1), MAPT (x1), PRG (x1), PSEN1 (x1), PSEN2 (x1), APP (x1) all

negative. One patient had a negative API and subsequently had KRIT1 genotyping (familial

cerebral cavernous malformations) which was positive.

Out of the 100 patients who had MRI imaging prior to API, 36 had non-specific abnormalities

reported. A further group of 36 patients had imaging changes consistent with Alzheimer’s

disease, 20 of whom had hippocampal volume loss and 16 of whom had additional non-

medial temporal lobe changes suggestive of a diagnosis of Alzheimer’s disease (e.g.

bipariatal atrophy or a posterior gradient of generalised volume loss). Twenty three patients

had normal initial MRI imaging and five patients had scans reported as being diagnostic for a

non-AD cause of dementia or cognitive impairment (three had frontal operculum atrophy

suggestive of primary progressive aphasia, one with extensive small vessel disease and

peripheral microhaemorrhages suggestive of CAA, and one with frontal and bitemporal

atrophy suggesting FTLD). As expected, patients who eventually had positive API were

significantly more likely to have features of AD or hippocampal atrophy and less likely to

have a normal initial MRI scans than those with negative API (Table 2, Fig.2). However 12

patients with reported HA or features of AD on MRI went on to have negative API.

Conversely six patients with normally reported MRI imaging went on to have positive API

(Table 2, Figure 2, Figure 3).

CSF amyloid biomarkers were performed 42 times in 37 patients. Out of the 37

patients who had CSF analysis, 26 had positive API. Out of those 26 subjects, 11 had a low A-

beta (42%). Out of the 16 cases with negative API, 11 had normal CSF abeta (69%). (18)F-

FDG-PET was not commonly performed pre-API (13 cases) but was usually abnormal (12

cases); eight of the thirteen cases with FDG-PET imaging were also API positive (62%); three

had asymmetrical bitemporal hypometabolism, two had bihippocampal hypometabolism,

two had unilateral temporal hypometabolism (one which was suggested to be characteristic

of FTLD) and one had generalised hypometabolism. One patient had a normal FDG-PET and

also had negative API. Four of the thirteen patients with (18)F-FDG-PET scans clinically

presented with progressive aphasia (one with MRI findings suggestive of PNFA) and all four

had positive API. All patients who had positive API had abnormal (18)F-FDG-PET scans (eight

patients) but the findings varied.

Effect on outcomes

API was positive in approximately half of cases (49 patients) and yielded a change in

diagnosis in 30 cases. Numbers of cases with SCI, MCI and MCI-AD changed little post API

while there was a non-significant reduction in number of cases with AD (from 56 to 43) and

a statistically significant increase in numbers of those with non-AD dementia (from 11 to 22

p =0.02) suggesting that API usually confirmed diagnostic suspicion but identified some

patients without AD (Table 2).

API resulted in a change in management in 42 cases (Table 2). The most common

change in management was the addition of memantine or an acetyl cholinesterase inhibitor

(24 patients) but six were enrolled into clinical trials as a result of the new diagnosis, two

were started on depression treatment and seven patients had further diagnostic

investigations as a result of a negative scan. Indeed negative API sometimes also actively

changed treatment as one case with a negative scan was referred for consideration of a

ventriculo-peritoneal shunt for presumed normal pressure hydrocephalus and a further

patient underwent a trial of IV methyl prednisolone following a negative (18)F-florbetapir

scan as they had a high titre of thyroid peroxidase antibodies (Table 2).

API reduces the overall burden of cognitive investigations

When looking at the number of investigations performed we found that patients had

significantly fewer cognitive investigations after API than before (p<0.0001) even when a

similar period of time had elapsed post-scan. In order to further examine the effect of API,

we assessed the total number of investigations in individuals who first presented to memory

clinic when API was available, and compared this to those who presented before API was

available. We found that there was a statistically significant reduction in the total number of

investigations when API is available (p<0.017) (Figure 4).

Table 2 Diagnosis after API and subsequent management

Diagnosis Pre-API [n100] Post API [n96]*

SCI 2 1MCI 22 23MCI-AD 9 6AD 56 43Non-AD dementia 11 23†

Result NumberAPI positive 49Change in diagnosis[96] 30

Change in management [n90]± 42 ACE-I/Memantine Depression/behavioural treatment Clinical trial Other treatment¥

Further otherwise unplanned investigation

246237

* Four patients have had post the scan diagnosis documented yet.† Statistical difference between pre and post API p = 0.02.± Ten patients have not been seen following API imaging¥ Ventriculoperitoneal shunt insertion (1), course of methyl prednisolone (1), Donepezil stopped (1)

SCI, subjective cognitive impairment; MCI, Mild Cognitive Impairment; AD, Alzheimer’s disease; API, Amyloid PET Imaging; Acetyl cholinesterase – inhibitor, ACE-I.

DISCUSSION

Here we describe our experience, as a dementia multidisciplinary team (MDT), of a cohort of

100 patients who had clinical (18)F-florbetapir PET scans at our institution. The vast majority

of patients who were scanned (98 out of 100) clearly met appropriate use criteria as set out

by the Amyloid Imaging Taskforce (AIT), 6 and no complications were associated with

scanning. Apart from a lack of diagnostic clarity with standard dementia investigations, no

single indication for PET scanning was predominant; the patients scanned were relatively

young with a median age of 66.7 and over half the group presented with atypical features.

API was positive in 49 patients and led to a change in diagnosis in 30 individuals, suggesting

that it was being used in cases where there was genuine diagnostic uncertainty. Assessing

the impact of an imaging technique in changing clinical management is complex - our

criteria did not include the significant psycho-social and medical impacts of an exclusion of

AD pathology in younger patients and those with milder complaints. Nevertheless, by our

criteria, scanning resulted in an active change in clinical management in almost half of cases,

most commonly relating to medication commencement or enrolment into clinical trials.

One key finding from this study is that patients had significantly fewer cognitive

investigations following their (18)F-florbetapir scan than before. This finding of a reduction

in diagnostic uncertainty and therefore in ongoing investigation is strongly supported by our

comparison of the group of patients who were seen at a clinic without access to amyloid PET

imaging with patients seen at our clinic after the introduction of clinical amyloid PET

imaging. This showed that those individuals who presented at our clinic following the

introduction of API had fewer investigations in total, and suggests that use of Amyloid PET in

specific populations can reduce time to diagnosis. The data from our cohort of patients

suggest that API could follow structural MRI imaging in dementia investigation and may

reduce the number of patients who need formal neuropsychometric assessments, (18)F-

FDG PET scans, or CSF analysis. Although our clinical observational study was not designed

to assess the economic impact of API, further studies could explore the potential relative

cost savings of amyloid imaging in terms of reduction of other investigations, and reduction

in follow-up clinic visits prior to diagnosis.

The patients we describe had previously all had MRI scans, and these had been reported by

a neuroradiologist. Features consistent with AD were reported in 12 individuals who went

on to have negative Amyloid PET scans. In this small group of patients, the clinical

presentation was often atypical (seven cases) or another diagnostic test was often out of

keeping with the diagnosis of AD (five had normal CSF abeta). This does suggest that caution

should be employed when using isolated MRI features such as HA as a biomarker for

amyloid pathology. However, the majority of patients’ scans were reported as non-

diagnostic or normal. This is consistent with the characteristics of the patient group as a

whole, which fitted the suggested criteria for Amyloid PET use. That is, patients with MCI-

AD, patients with early onset AD, and AD patients with atypical presentations are less likely

to manifest clear-cut patterns of atrophy consistent with Alzheimer’s disease than elderly

patients with dementia that is more typical of AD. 23–26

Thirty-seven of the patients described here had undergone CSF examination prior to API,

and of these, five had more than one CSF examination. Although there is evidence to

suggest that CSF amyloid biomarkers are likely to become abnormal before API, 27 this is

primarily in the context of preclinical AD, and at present remains more pertinent to the

research setting. In our population, the concordance between CSF amyloid biomarkers and

API was unexpectedly low compared to research populations; a number of individuals (22)

who went on to have positive API had previously had isolated raised tau, low A-beta or

normal tau and abeta, such that there was still diagnostic uncertainty following CSF analysis.

In some centres and in the research setting, CSF analysis has been repeatedly shown to be

reliable and consistent even with different transfer methods, 28,29 but we note that this is not

always the case. 26,30 This is also supported by the results of another recent smaller study,

where API following CSF analysis was demonstrated to change diagnosis in seven out of

twenty individuals with cognitive impairment. 31 This tallies with our own experience where

CSF examination for amyloid status can be associated with sample handling and assay

problems, although these have improved considerably over the last year, and are likely to

improve further with the advent of new CSF biomarkers, improving standardization of assay

protocols and he implementation of newer assay platforms. 32 In addition, as a non-invasive

investigation, API was very acceptable to patients with a rapid turnaround time for results.

One difference that we note between our clinical population and major research cohorts,

including the ADNI dataset, is the difference in the proportion of patients with MCI who

were amyloid PET positive. Of the 31 patients in our group with MCI before florbetapir

imaging only six had positive API whereas in the Alzheimer’s disease Neuroimaging Initiative

(ADNI) population, approximately half of the MCI patients were amyloid PET positive. 16,17,19,21,22,28,33 Although this may be an aberration related to our much smaller sample size,

we would suggest that this difference genuinely reflects the population differences between

the two cohorts. Our patients were younger than those in the ADNI cohort, and were often

individuals who had been referred by other clinicians because of diagnostic uncertainty.

Therefore, they are likely to represent a more atypical group of MCI patients than might be

recruited to research cohorts. API also changed diagnosis in 30 of 100 cases which is more

than has been described in research populations. 16,17

Overall, our experience suggests that there is a clear role for Amyloid PET scanning in the in

the work-up of patients with cognitive impairment in the memory clinic independent of

research studies. The patients included here were a purely clinical group rather than a

research cohort, but we acknowledge that they would not be entirely representative all

clinical populations attending for memory assessment in the UK healthcare system. The cost

and availability of Amyloid PET, preclude its use for the majority of patients with AD for

now. However, if used in individuals who meet AIT criteria, amyloid PET imaging reduces the

number of further investigations and significantly affects clinical management, in addition to

adding to improving diagnostic certainty.

AcknowledgementsThe authors would like to thank the medical, nursing and administrative staff at the IMC. RP had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

ContributorsThe study was designed by RP, PM and AW, the data were acquired and presented by CC, KM, RK, TDB, AK, AW, ZW, the data was interpreted by CC, PM and RP, figures were created by CC, the paper was written and revised by CC, KM, RK, AK, PM, GD, TDB, ZW and RP.

FundingThe patients were investigated within their treatment in the NHS. No specific external funding was acquired. This work was supported by the NIHR Biomedical Research Centre at Imperial College London.

Competing interestsRP has worked in an advisory role for Roche, Eli Lilly, Merck, and GE. PM has a ‘drugs-only’ grant from Shire Pharmaceuticals and research funding from the UK National Institute of Health Research and Medical Research Council. Patient consent and ethics approvalThe study was retrospective and observational. The data were anonymised and there were no experimental conditions outside of routine patient care. No individual patient consent or ethics approval was required.

Provenance and peer reviewNot commissioned; externally peer reviewed.

Data sharing statementWe will consider sharing our data on request.

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