Keywords β-amyloid -
18 F-florbetaben - PET/CT - brain PET - Alzheimer's disease
Introduction
The most common cause of neurodegenerative dementia is Alzheimer's disease (AD), accounting
for 60–80% of all dementias and affecting over 6 million people in the USA and 50
million people worldwide. AD is a leading cause of mortality in the elderly (sixth-leading
cause of death in the United States and the fifth-leading cause of death among Americans
aged 65 years and older) and, with increasing longevity, is projected to impact up
to 13.8 million people in the USA by 2060 with an associated significant rise in healthcare
cost, which is projected to exceed $1 trillion by 2050.[1 ]
[2 ]
[3 ] Histopathologically, the AD cascade, originally described by Alois Alzheimer in
1907, is characterized by brain infiltration of two amyloid-β (Aβ) isoforms (Aβ1-42
and Aβ1-40
), leading to Aβ deposition and the formation of diffuse and dense-core Aβ plaques
with concomitant phosphorylation of tau protein and accumulation of neurofibrillary
tangles and neurodegeneration.[4 ]
[5 ]
[6 ] Amyloid-β in the human brain follows a distinct sequence in which the regions are
hierarchically involved, beginning in the neocortex and spreading anterogradely into
regions that receive neuronal projections from regions already exhibiting cortical
Aβ burden, as described by Thal et al in 2002.[7 ] Of note, amyloid deposition precedes cognitive changes and tau deposition although
the relationship between amyloid, tau, and clinical progression is complex and still
needs to be fully elucidated.[8 ]
[9 ]
There is intense interest in minimally invasive neuroimaging biomarkers in neurodegenerative
disease definitions and for use in clinical trials, particularly in the setting of
novel disease-modifying therapies, where accurate confirmation of AD pathology is
paramount.[10 ] In 2016, Jack et al outlined a novel system as an unbiased descriptive classification
scheme for research purposes when characterizing patients presenting with cognitive
impairment,[11 ]
[12 ] classifying key biomarkers into three binary categories: “A” refers to the value
of total β-amyloid biomarker (amyloid positron emission tomography [PET], or cerebrospinal
fluid [CSF] Aβ42 can be used); “T,” to the value of a tau biomarker (tau PET, CSF
p-tau, or recently plasma p-tau); and “N,” to a biomarker of neurodegeneration or
neuronal injury (18 F-fluorodeoxyglucose–PET, structural magnetic resonance imaging [MRI], CSF total tau,
or plasma neurofilament light chain). Each biomarker category is rated as positive
or negative and staging can be accomplished for research purposes by the presence/absence
of these biomarkers. Given its independent approach to categorizing multidomain biomarker
findings at the individual level, without specifying disease labels per se, it is
ideally suited as a research framework given the lack of consensus on terminology
across the spectrum of cognitive aging and impairment. In fact, the A/T/N classification
has been endorsed by the National Institute on Aging and the Alzheimer's Association
(NIA-AA) for implementation in the research and clinical trial setting.[12 ]
[13 ]
In the characterization of AD for research, amyloid PET plays a vital role in in vivo
detection of β-amyloid (Aβ) accumulation in patients presenting with cognitive impairment,
and this is taking on a new dimension with the recent Federal Drug Administration's
(FDA) approval of the first potentially disease-modifying therapy in the treatment
of AD,[14 ] the amyloid-targeting monoclonal antibody aducanumab (trade name: Aduhelm) in June
2021. Given the first-of-its-kind treatment for AD, trainees and infrequent neuroradiological
readers will be required to interpret these studies in a clinical setting, and their
interpretations will have a direct impact on patient management. Therefore, semiquantitative
tools available in routine clinical practice are becoming increasingly important to
support diagnostic efforts. However, there are limited data assessing the correspondence
between visual assessment and semiquantitative analysis in the evaluation of cortical
amyloid burden.[15 ]
[16 ]
[17 ] In this study, we retrospectively reviewed 18 F-florbetaben PET/CT studies acquired at our institution as part of the Imaging Dementia-Evidence
for Amyloid Scanning (IDEAS) study[18 ] to determine if the qualitative assessment of amyloid PET scans may be facilitated
by relying on results from the semiquantitative analysis.
Methods
Ethics: This study received local institutional review board (IRB) approval. The IRB waived
the need for written informed consent, given the retrospective nature of the study.
Patient Selection
Subjects were referred from memory clinics for 18 F-florbetaben PET/CT as part of the IDEAS study from June 2016 to May 2018. Eligible
patients were Medicare beneficiaries age 65 years or older, English or Spanish speaking,
with a diagnosis of mild cognitive impairment (MCI) or dementia established by a dementia
specialist within the past 24 months. All subjects were required to have completed
a comprehensive diagnostic assessment, including global cognition assessed via the
Mini-Mental State Examination (range, 0 [worst] to 30 [best]) or Montreal Cognitive
Assessment (range, 0 [worst] to 30 [best]) at the time of enrollment, laboratory testing
within the past 12 months, and head CT or MRI within the past 24 months. Patients
were further required to meet appropriate use criteria for amyloid PET[19 ]: (1) the etiologic cause of cognitive impairment remained uncertain after a comprehensive
evaluation by a dementia specialist, (2) Alzheimer's disease was a diagnostic consideration,
and (3) knowledge of amyloid PET status was expected to alter diagnosis and management.
Patients were excluded if amyloid status was already known based on prior PET or CSF
analysis or if learning amyloid status could, in the opinion of the specialist, cause
significant psychological harm.
Image Acquisition
Amyloid PET was completed within 30 days of the pre-PET assessment following published
practice guidelines.[20 ] Subjects received 300 MBq (8.1 mCi) of 18 F-florbetabem intravenously and were placed in a quiet room during the tracer uptake
period. Approximately 90 to 120 min after radiopharmaceutical injection, patients
were scanned on a GE Discovery 710 PET/CT scanner. Transmission data (head CT) was
acquired for approximately 2 min and parameters were as follows: kVp 120; mA 95; helical
scanning; rotation = 0.8 mm/rot; and pitch = 1.375:1. Emission data (brain PET) was
acquired for approximately 20 min (static acquisition with dynamic replay in 10 frames
at 2 min/frame). Images were reconstructed using the VUE Point FX reconstruction with
32 subsets and two iterations; z-axis filter = “heavy” and 4.0 mm FWHM Gaussian post-filtering.
Quantitative corrections included attenuation, scatter, random, detector efficiency,
decay, and deadtime. Acquired PET data were scaled to injected dose and body weight
to produce standardized uptake value (SUV) images.
Image Analysis
Visual interpretation to determine Aβ+ status was conducted by two independent readers
blinded to each other's interpretation. One of the readers (DP) was a trainee with
1 year of experience, the other (AMF) was a board-certified neuroradiologist with
dedicated PET/MRI training and 5 years of clinical and research expertise in brain
PET. Studies were classified as either positive (1) or negative (0) for increased
cortical Aβ burden. After qualitative reads were completed, scans were post-processed
utilizing MIM-Neuro version 7.1.6 (MIM Software, Inc., Cleveland, Ohio, United States).
MIMNeuro is a commercially available program that aids in the analysis and post-processing
of PET and single-photon emission computed tomography (SPECT) studies. It performs
voxel- and region-based comparison of radiotracer uptake between its database of normal
studies and a given study with the aid of built-in anatomic atlases. The differences
in radiotracer uptake are represented with a Z-score of standard deviation from normal,
or the SUV ratio. For our study, MIMNeuro generated regional-based semiquantitative
Z-scores, indicating cortical amyloid burden following industry standards including
using the whole cerebellum as the reference region. Z-score values were reported for
12 brain regions total: right and left posterior cingulate gyrus, right and left precuneus,
right and left inferior medial frontal gyrus, right and left anterior cingulate gyrus,
right and left lateral temporal lobe, and right and left superior parietal lobule.
Statistical Analysis
Descriptive characteristics are provided using averages, standard deviations, and
percentiles. Examples of positive and negative scans are provided. Reader agreement
was reported using the Kappa statistic (κ), and overall levels of agreement were also
reported. Unilateral regional Z-scores and differences between amyloid-positive and
amyloid-negative scans were reported. The area under the receiver-operating curve
(AUC) was reported as a measure of overall predictive power for semi-quantitative
Z-scores to identify amyloid-positive individuals. Regional spread of amyloid was
reported using a number of regions exceeding 2.575 and 3.3 standard deviations above
normal (p = 0.01 and p = 0.001, respectively). Patients were presented in rank order from the highest to
the lowest mean amyloid positivity scores across unilateral regions (organized sequentially
with left on top and right below). A two-tailed α = 0.05 was used to determine statistical
significance.
Results
A total of 167 subjects (83 females, 84 males; mean age 76.1 ± 6.8 years) underwent
18 F-florbetaben PET/CT. Of these cases, 92/167 (reader 1) and 101/167 scans (reader
2) scans were considered positive for amyloid deposition (agreement = 92.2%, κ = 0.84).
[Figs. 1 ] and [2 ] demonstrate an example of a positive and negative amyloid brain PET, respectively,
upon visual analysis. Notably, 12 of the 13 cases with visually discordant results
were deemed positive in some or all regions by semiquantitative analysis. Upon repeat
(unblinded) visual assessment, the readers sided with semiquantitative results in
all but one case (92%). Furthermore, 4 of these 13 cases (31%) demonstrated advanced
atrophy on structural imaging, which oftentimes poses a diagnostic challenge, especially
for qualitative analysis.
Fig. 1 (A ) Positive 18 F-florbetaben PET/CT with diffuse tracer uptake in the cerebral cortex. (B ) Semiquantitative analysis using the z-scores calculated in comparison to age-matched
normal controls reveals significantly increased z-score values in analyzed brain regions
including in the posterior cingulate gyrus, precuneus, inferior medial frontal gyrus,
anterior cingulate gyrus, lateral temporal lobe, and superior parietal lobule (reference
region: cerebellum).
Fig. 2 (A ) Negative 18 F-florbetaben PET/CT with tracer uptake only in the cerebral white matter, and no
evidence of amyloid burden in the cerebral cortex. (B ) Semiquantitative analysis using the z-scores calculated in comparison to age-matched
normal controls reveals no significantly increased z-score values in analyzed brain
regions including in the posterior cingulate gyrus, precuneus, inferior medial frontal
gyrus, anterior cingulate gyrus, lateral temporal lobe, and superior parietal lobule
(reference region: cerebellum).
An additional nine scans were subsequently identified as possible amyloid-positive
based solely on semiquantitative analyses. The largest semiquantitative differences
were identified in the left frontal lobe (Z = 7.74 in Aβ+ vs. 0.50 in Aβ− subjects),
as depicted in [Table 1 ]. All unilateral regions showed statistically significant differences in Aβ burden
(p ≤ 2.08E-28 in all cases). Semiquantitative scores were highly sensitive to Aβ+ status
and highly accurate in their ability to identify amyloid-positive patients ([Table 2 ]), defined as a positive scan by both readers (AUC ≥ 0.90 [0.79–1.00]). Of the nine
cases in which both reviewers evaluated the case to be negative and semiquantitative
analysis deemed the case positive, advanced atrophy was present in three cases (33%).
In addition, limited regional-only amyloid deposition was present in five of the nine
cases (55%), which were positive solely by semiquantitative analysis.
Table 1
Regional Z-score differences between individuals determined to be visually positive
versus negative on qualitative analysis
Region
Mean Z-score negative
SD negative
Mean Z-score positive
SD positive
Diff.
Area under the receiver-operating curve (95% C.I.)
p -Value
Left PCG
1.81
2.53
8.17
2.29
6.36
0.96 (0.93–1.00)
2.42E-35
Right PCG
1.99
2.51
8.09
2.31
6.11
0.96 (0.93–0.99)
7.16E-34
Left precuneus
1.07
2.07
8.22
2.43
7.15
0.98 (0.95–1.00)
1.10E-46
Right precuneus
1.09
1.93
7.18
2.17
6.09
0.97 (0.95–1.00)
3.73E-43
Left frontal
0.50
2.29
7.74
2.68
7.25
0.98 (0.95–1.00)
1.54E-42
Right frontal
0.36
2.36
7.03
2.48
6.67
0.97 (0.94–1.00)
5.34E-39
Left parietal
0.86
1.52
5.36
1.96
4.50
0.96 (0.94–0.99)
3.17E-37
Right parietal
0.79
1.35
4.33
1.62
3.54
0.94 (0.91–0.98)
2.17E-33
Left temporal
0.25
1.54
5.52
2.20
5.27
0.98 (0.96–1.00)
2.14E-41
Right temporal
0.37
1.41
4.86
2.10
4.50
0.96 (0.93–0.99)
1.01E-36
Left ACG
−0.08
2.00
4.34
2.05
4.42
0.94 (0.91–0.98)
4.38E-29
Right ACG
–0.13
2.09
4.40
2.13
4.53
0.90 (0.79–1.00)
2.08E-28
Abbreviations: ACG: anterior cingulate gyrus; AUC: area under the receiver-operating
curve; Diff.: difference between amyloid+ and amyloid- participants; PCG: posterior
cingulate gyrus; 95% CI: 95% confidence interval.
Table 2
Cut points derived for each cortical region along with sensitivity and specificity
at the optimal cut point
Regional Z-scores
Suggested cutoffs
Sensitivity at cutoff
Specificity at cutoff
Left PCG
4.63
0.94
0.93
Right PCG
5.38
0.90
0.94
Left precuneus
3.87
0.97
0.96
Right precuneus
4.58
0.90
0.96
Left frontal
3.82
0.96
0.96
Right frontal
3.24
0.96
0.94
Left parietal
3.20
0.85
0.96
Right parietal
1.69
0.94
0.82
Left temporal
2.21
0.95
0.93
Right temporal
2.09
0.95
0.90
Left ACG
1.65
0.90
0.87
Right ACG
1.44
0.94
0.83
Abbreviations: ACG: anterior cingulate gyrus; PCG: posterior cingulate gyrus.
Spread analyses suggested that amyloid deposition was most severe in the left posterior
cingulate gyrus, where amyloid-positive individuals were most likely to cross standard
cutoffs ([Fig. 3 ]). Using a single Z-score cutoff as shown in [Fig. 3A ], the largest differences between negative and positive individuals were in the left
frontal lobe, and analyses using region-specific cutoffs indicated that the presence
of amyloid in the temporal and anterior cingulate cortex, while exhibiting relatively
low Z-scores, was the most common. Of note, among individuals whose qualitative and
quantitative results were non-concordant, quantitative measures of amyloid positivity
were the lowest in the temporal and parietal lobes potentially suggesting that qualitative
examinations are more difficult in these regions. By examining spread using the region-specific
cutoffs determined in this study as shown in [Fig. 3B ], we found that though having relatively low Z-scores, amyloid was more often elevated
in the temporal lobe and anterior cingulate gyri. Of note, when the temporal lobe
and anterior cingulate gyrus were elevated, but other regions including the frontal
and posterior cingulate gyrus were not sufficient to cross relatively higher Z-score
cutoffs in those regions, qualitative results were often discordant from the quantitative
results.
Discussion
Amyloid PET provides a critical clinical neuroimaging tool in patients with possible
AD. The purpose of this study was to evaluate whether qualitative adjudication of
Aβ positivity in the clinical setting may be facilitated by relying on results from
semi-quantitative Z-score analysis.
Amyloid PET allows for in vivo visualization of β-amyloid deposition, a hallmark pathologic
change in AD that has been described to be the earliest neuroimaging predictor of
future cognitive impairment in healthy elderly.[21 ] Available amyloid-targeting PET radiotracers include the research radiotracer [11 C]-Pittsburgh compound (PiB), as well as three FDA-approved [18 F]-labeled radiopharmaceuticals (florbetaben, florbetapir, and flutemetamol), all
of which demonstrate high-affinity binding to cortical β-amyloid plaques.[22 ]
[23 ] While most of the early studies used [11 C]-PiB, the short half-life of 11 C limits its pragmatic clinical use. All three FDA-approved amyloid radiotracers have
been shown to be acceptable clinical surrogates for PiB in the detection of Aβ and
are widely used, with reported sensitivity and specificity of 90% or higher for the
detection of increased cortical amyloid burden. In one study, cortical retention for
each pair of tracers was strongly correlated, regardless of reference region (PiB-flutemetamol,
ρ = 0.84–0.99; PiB-florbetapir, ρ = 0.83–0.97) and analysis method (ρ = 0.90–0.99).[24 ]
[25 ] Similarly, there was a strong association between PiB and florbetapir cortical retention
ratios (Spearman ρ = 0.86–0.95). In another study, there was an excellent linear correlation
between PiB and florbetaben global SUVR values (r = 0.97, p < 0.0001) with similar effect sizes for distinguishing AD from control subjects for
both radiotracers (Cohen's d = 3.3 for PiB and 3.0 for florbetaben).[26 ]
Clinical interpretation is typically binary: “amyloid-positive” when there is evidence
of cortical uptake and loss of gray–white matter differentiation versus “amyloid-negative”
when there is non-specific white matter uptake and lack of cortical uptake resulting
in preserved gray–white matter differentiation ([Figs. 1 ] and [2 ]).[27 ] While amyloid PET can reliably detect β-amyloid deposition in vivo, the amyloid
burden does not correlate with the degree of cognitive impairment,[21 ] and β-amyloid deposition can be seen in healthy older adults, adding an additional
dimension to image interpretation in the clinical setting.[28 ]
[29 ] Therefore, a positive amyloid PET scan is necessary but insufficient to provide
a positive diagnosis of AD, though a negative amyloid uptake has a good negative predictive
value for AD. Among Medicare beneficiaries with MCI or dementia of uncertain etiology
evaluated by specialists as part of the ACR-sponsored IDEAS study, amyloid PET was
associated with changes in clinical management in over 60% of cases, while the etiologic
diagnosis changed from AD to non-AD and vice versa in 35% of patients.[30 ] Furthermore, Aβ-amyloid PET imaging is widely used in patient selection and evaluation
of treatment response and target engagement in disease-modifying clinical trials,
and is expected to become a staple in the clinical management of AD patients, given
recent regulatory approval of aducanumab, a high-affinity, fully human IgG1 monoclonal
antibody against a conformational epitope found on Aβ in the brain.[14 ]
Quantitative PET measurements have been reported to have a good correlation with visual
interpretations, and standardized uptake value ratio (SUVR) and regional counts per
reference count have been commonly used in quantitative analysis of amyloid PET.[31 ] Prior studies in the literature have assessed kinetic model-based approaches to
quantify β-amyloid binding in the brain from dynamic PET data. For example, Becker
et al[15 ] performed 18 F-florbetaben PET with concurrent multiple arterial sampling after tracer injection
in AD subjects and controls. Regional brain-tissue time-activity curves for 90 min
were analyzed by a one-tissue-compartment model and a two-tissue-compartment model
(2TCM) with metabolite-corrected plasma data estimating the specific distribution
volume (VS) and distribution volume ratio (DVR [2TCM]) and a multilinear reference
tissue model estimating DVR (DVR [MRTM]) using the cerebellar cortex as the reference
tissue. In their study, all β-amyloid-binding parameters (VS, DVR [2TCM], DVR [MRTM],
and SUVR) were significantly increased in AD patients and excellent in discriminating
between β-amyloid-positive and -negative scans. Furthermore, most amyloid PET cases
can be easily classified as positive or negative on the bases of visual assessment;
however, the findings are equivocal in approximately 10% of cases.[32 ] Because conventional mean cortical SUVR measures accumulation in both gray matter
(GM) and white matter, it may misestimate amyloid deposits. Therefore, Ishii et al[16 ] developed a regional gray matter-dedicated SUVR (GMSUVR) system for amyloid PET
images with three-dimensional (3D-MRI) and demonstrated its utility for discriminating
between amyloid-positive and -negative subjects, even in cases where qualitatively,
amyloid deposition was equivocal. In addition, neocortical atrophy typically present
in elderly patients also reduces PET signal intensity, potentially affecting the diagnostic
efficacy of β-amyloid PET data. Rullman et al[33 ] used partial-volume effect correction (PVEC), to adjust for atrophy bias, and demonstrated
that PVEC improves quantitative analysis of 18 F-florbetaben PET scans. In clinical practice, careful attention should be paid to
the selection of regions of interest (ROIs) by post-processing software as it may
be suboptimal, particularly in small and adjacent regions such as the cingulate cortices,
and in cases of advanced atrophy on structural imaging.[34 ]
[35 ] More recently, the Centiloid Project working group standardized quantitative amyloid
imaging measures by scaling the outcome of each particular analysis method or tracer
to a 0 to 100 scale, anchored by young controls (≤ 45 years) and typical AD patients,
with units of this scale referred to as “Centiloids” for PiB PET and all three 18 F-labelled FDA-approved amyloid PET tracers.[36 ]
[37 ]
Heavily quantitative approaches are cumbersome, require a trained quantitative analyst,
and may not be feasible in a busy clinical practice. Additionally, not all clinical
centers have access to the high-resolution 3D MRI sequences needed to help with this
process. In a clinical setting, qualitative adjudication of Aβ positivity in clinical
amyloid PET studies may be facilitated by relying on results from semi-quantitative
Z-score analysis, which is of practical benefit, especially to trainees and inexperienced
or infrequent readers. Therefore, we evaluated the correspondence between visual assessment
and semiquantitative analysis in evaluating the cortical amyloid burden on clinical
amyloid PET scans. Limitations of this study include its retrospective nature and
lack of longitudinal follow-up. Additionally, only a single vendor post-processing
algorithm was validated. Replication of these findings on other clinical PET software
tools is needed prior to widespread implementation in routine clinical practice.
In conclusion, visual assessment and semiquantitative z-score analysis provide highly
congruent results, thereby enhancing reader confidence and improving scan interpretation.
This is particularly relevant given the recent emphasis on amyloid-targeting disease-modifying
therapeutics, as they emerge from the research setting and enter clinical practice.
Fig. 3 Regional amyloid positivity analysis across patients. Patients are presented in rank
order from the highest to the lowest mean amyloid positivity scores across unilateral
regions (organized sequentially with left on top and right below). Regions are ordered
from most affected (top ) to least affected. Qualitative analysis status is shown using orange bars along
the top, with two positive reads indicated by the presence of a dark orange bar and
a single positive read indicated by a lighter orange bar. Panel A: Person-region observations
are colored based on deviation from expectations (2.58 SDs are light gray, 3.3 SDs
are dark gray, 5 SDs are charcoal). Panel B: Person-region observations are colored
based on whether that observation cleared the estimated region-specific cutoffs noted
in [Table 2 ]. ACG: anterior cingulate gyrus; PCG: posterior cingulate gyrus. Amyloid positivity
status was determined qualitatively and shown using dark orange if both visual readers
identified the person as positive, and light orange if only one reader identified
the visual positive.
