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Research paper
Clinical utility of amyloid PET imaging with (18)F-florbetapir: a retrospective study of 100 patients
  1. Christopher James Carswell1,
  2. Zarni Win2,
  3. Kirsty Muckle1,
  4. Angus Kennedy1,
  5. Adam Waldman3,
  6. Gemma Dawe2,
  7. Tara D Barwick4,5,
  8. Sameer Khan4,
  9. Paresh A Malhotra1,6,
  10. Richard J Perry1,6
  1. 1 Department of Neurology, Imperial College Healthcare NHS Trust, London, UK
  2. 2 Department of Neuroradiology, Imperial College Healthcare NHS Trust, London, UK
  3. 3 Centre for Clinical Brain Sciences, Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK
  4. 4 Department of Nuclear Medicine, Imperial College Healthcare NHS Trust, London, UK
  5. 5 Division of Cancer and Surgery, Imperial College, London, UK
  6. 6 Division of Brain Sciences, Faculty of Medicine, Imperial College, London, UK
  1. Correspondence to Dr Richard J Perry, Department of Neurology, Imperial NHS Trust, Charing Cross Hospital, London W6 8RF, UK; richard.perry{at}imperial.nhs.uk

Footnotes

  • PAM and RJP are joint senior authors.

  • Contributors The study was designed by RP, PAM and AW, the data were acquired and presented by CJC, KM, RK, TB, AK, AW, ZW, the data was interpreted by CJC, PM and RP, figures were created by CJC, the paper was written and revised by CJC, KM, RK, AK, PAM, GD, TB, ZW and RP.

  • Funding The 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 interests RP 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.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement We will consider sharing our data on request.

  • Correction notice This article has been corrected since it was published Online First. The joint senior author statement has been included.

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Introduction

Alzheimer’s disease (AD) is the most common form of dementia. Clinical diagnosis of AD 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 AD, and the ability to demonstrate their presence in vivo via amyloid positron emission tomography (PET) imaging (API) 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 with 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 API offers useful prognostic information on the progression of MCI subjects to convert to AD, 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 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 100 patients investigated with API at the IMC between December 2013 and January 2016.

Decision to investigate with API

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 multidisciplinary meetings where clinical details and structural brain imaging were discussed. Our imaging process was set up to follow the guidelines for appropriate use (online supplementary appendix S1).6

Supplementary file 2

Clinical details and diagnostic categorisation

The clinical details were retrospectively reviewed using the patient records, and demographic details, diagnosis, medical comorbidity, disease course, cognitive investigations and treatment were noted.

For the purposes of this study, patients were also categorised diagnostically both pre-API and post-API as subjective cognitive impairment (SCI), mild cognitive impairment (MCI), MCI-AD (for MCI which already had a positive cerebrospinal fluid (CSF) biomarker or hippocampal atrophy on MRI), AD dementia and non-AD dementia. Patients who were classified as MCI-AD due to positive CSF biomarkers 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 (eg, 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 and 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 1. 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 (eg, generalised atrophy, non-specific microangiopathic disease, prior stroke, prior traumatic brain injury, etc). All MRI scans had been reported by a specialist neuroradiologist.

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 min dynamic list mode PET acquisition of the brain was obtained beginning 40 min 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 min of PET data was selected visually for processing, prior to a diagnostic read. All 20 min of PET data was processed; if it was deemed that there was no significant movement. PET images were reconstructed using a 3D ordered subset expectation maximization algorithm (four 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 NMRs 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 Fisher’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 among the population (range 0.5–120) (table 1).

Table 1

Patient characteristics, source of referral and API indication

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 who were older than 65 years with cognitive impairment which was thought to be due to AD but with atypical clinical features making diagnosis uncertain (25 patients) (table 1). Two patients with 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, online 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).

Supplementary file 1

Figure 1

Atypical features present in those having amyloid imaging. Fifty-six patients had 64 atypical features. Two patients had mild cognitive impairment, 29 had young onset dementia and 25 had cognitive impairment over 65 years at onset. CAA, cerebral amyloid angiopathy.

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, online 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.

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 prior to API, 36 had non-specific abnormalities reported. A further group of 36 patients had imaging changes consistent with AD, 20 of whom had hippocampal volume loss and 16 of whom had additional non-medial temporal lobe changes suggestive of a diagnosis of AD (eg, biparietal atrophy or a posterior gradient of generalised volume loss). Twenty-three patients had normal initial MRI 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 frontotemporal lobar degeneration (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, figure 2). However, 12 patients with reported hippocampal atrophy (HA) or features of AD on MRI went on to have negative API. Conversely, six patients with normally reported MRI went on to have positive API (table 2, figures 2 and 3).

Figure 2

Comparison of MRI findings between those with positive and negative API. Patients with positive amyloid-PET imaging (API) were more likely to have MRI scans consistent with Alzheimer’s disease (AD) (p=0.012) and less likely to have normal MRI scans (p=0.017) than patients who had negative API.

Figure 3

API was sometimes negative when MRI was reported to show hippocampal atrophy. A 62-year-old lady with mild cognitive impairment was reported to have mild hippocampal atrophy (A). Corresponding API demonstrated good white/grey matter differentiation indicative of a negative scan (B). A 64-year-old lady presents with possible Alzheimer’s disease and is also reported to have mild hippocampalatrophy (C). Corresponding API in this case shows widespread loss of grey/white matter differentiation representing a positive amyloid scan (D). API, amyloid-PET imaging.

Table 2

Diagnosis after API and subsequent management

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 ventriculoperitoneal 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 postscan. In order to further examine the effect of API, we assessed the total number of investigations in individuals who first presented to the 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 was available (p<0.017) (figure 4).

Figure 4

The number of pre-API investigations per patient by API availability. Overall significantly fewer investigations were performed when API was initially available (p = 0.017). API, amyloid-PET imaging.

Discussion

Here we describe our experience, as a dementia multidisciplinary team, 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 years 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 psychosocial 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 API with patients seen at our clinic after the introduction of clinical API. 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 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 AD 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 with 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 7 out of 20 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 standardisation of assay protocols and the 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 Alzheimer’s disease Neuroimaging Initiative (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 6 had positive API whereas in the ADNI population, approximately half of the patients with MCI 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 patients with MCI 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, API reduces the number of further investigations and significantly affects clinical management, in addition to adding to improving diagnostic certainty.

Acknowledgments

The 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.

References

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Footnotes

  • PAM and RJP are joint senior authors.

  • Contributors The study was designed by RP, PAM and AW, the data were acquired and presented by CJC, KM, RK, TB, AK, AW, ZW, the data was interpreted by CJC, PM and RP, figures were created by CJC, the paper was written and revised by CJC, KM, RK, AK, PAM, GD, TB, ZW and RP.

  • Funding The 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 interests RP 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.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement We will consider sharing our data on request.

  • Correction notice This article has been corrected since it was published Online First. The joint senior author statement has been included.

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