Infrequent false positive [18F]flutemetamol PET signal is resolved by combined histological assessment of neuritic and diffuse plaques

11C-PiB PET can underestimate brain amyloid-β burden when cotton wool plaques are numerous

Individuals with familial Alzheimer's disease due to PSEN1 mutations develop high cortical fibrillar amyloid-β load but often have lower cortical 11C-Pittsburgh compound B (PiB) retention than Individuals with sporadic Alzheimer's disease. We hypothesized this is influenced by limited interactions of Pittsburgh compound B with cotton wool plaques, an amyloid-β plaque type common in familial Alzheimer's disease but rare in sporadic Alzheimer's disease. Histological sections of frontal and temporal cortex, caudate nucleus and cerebellum were obtained from 14 cases with sporadic Alzheimer's disease, 12 cases with familial Alzheimer's disease due to PSEN1 mutations, two relatives of a PSEN1 mutation carrier but without genotype information and three non-Alzheimer's disease cases. Sections were processed immunohistochemically using amyloid-β-targeting antibodies and the fluorescent amyloid stains cyano-PiB and X-34. Plaque load was quantified by percentage area analysis. Frozen homogenates from the same brain regions from five sporadic Alzheimer's disease and three familial Alzheimer's disease cases were analysed for 3H-PiB in vitro binding and concentrations of amyloid-β1-40 and amyloid-β1-42. Nine sporadic Alzheimer's disease, three familial Alzheimer's disease and three non-Alzheimer's disease participants had 11C-PiB PET with standardized uptake value ratios calculated using the cerebellum as the reference region. Cotton wool plaques were present in the neocortex of all familial Alzheimer's disease cases and one sporadic Alzheimer's disease case, in the caudate nucleus from four familial Alzheimer's disease cases, but not in the cerebellum. Cotton wool plaques immunolabelled robustly with 4G8 and amyloid-β42 antibodies but weakly with amyloid-β40 and amyloid-βN3pE antibodies and had only background cyano-PiB fluorescence despite labelling with X-34. Relative to amyloid-β plaque load, cyano-Pittsburgh compound B plaque load was similar in sporadic Alzheimer's disease while in familial Alzheimer's disease it was lower in the neocortex and the caudate nucleus. In both regions, insoluble amyloid-β1-42 and amyloid-β1-40 concentrations were similar in familial Alzheimer's disease and sporadic Alzheimer's disease groups, while 3H-PiB binding was lower in the familial Alzheimer's disease than the sporadic Alzheimer's disease group. Higher amyloid-β1-42 concentration associated with higher 3H-PiB binding in sporadic Alzheimer's disease but not familial Alzheimer's disease. 11C-PiB retention correlated with region-matched post-mortem amyloid-β plaque load; however, familial Alzheimer's disease cases with abundant cotton wool plaques had lower 11C-PiB retention than sporadic Alzheimer's disease cases with similar amyloid-β plaque loads. PiB has limited ability to detect amyloid-β aggregates in cotton wool plaques and may underestimate total amyloid-β plaque burden in brain regions with abundant cotton wool plaques.

Classification of 18F-Flutemetamol scans in cognitively normal older adults using machine learning trained with neuropathology as ground truth

Purpose

End-of-life studies have validated the binary visual reads of ¹⁸F-labeled amyloid PET tracers as an accurate tool for the presence or absence of increased neuritic amyloid plaque density. In this study, the performance of a support vector machine (SVM)-based classifier will be tested against pathological ground truths and its performance determined in cognitively healthy older adults.

Methods

We applied SVM with a linear kernel to an ¹⁸F-Flutemetamol end-of-life dataset to determine the regions with the highest feature weights in a data-driven manner and to compare between two different pathological ground truths: based on neuritic amyloid plaque density or on amyloid phases, respectively. We also trained and tested classifiers based on the 10% voxels with the highest amplitudes of feature weights for each of the two neuropathological ground truths. Next, we tested the classifiers’ diagnostic performance in the asymptomatic Alzheimer’s disease (AD) phase, a phase of interest for future drug development, in an independent dataset of cognitively intact older adults, the Flemish Prevent AD Cohort-KU Leuven (F-PACK). A regression analysis was conducted between the Centiloid (CL) value in a composite volume of interest (VOI), as index for amyloid load, and the distance to the hyperplane for each of the two classifiers, based on the two pathological ground truths. A receiver operating characteristic analysis was also performed to determine the CL threshold that optimally discriminates between neuritic amyloid plaque positivity versus negativity, or amyloid phase positivity versus negativity, within F-PACK.

Results

The classifiers yielded adequate specificity and sensitivity within the end-of-life dataset (neuritic amyloid plaque density classifier: specificity of 90.2% and sensitivity of 83.7%; amyloid phase classifier: specificity of 98.4% and sensitivity of 84.0%). The regions with the highest feature weights corresponded to precuneus, caudate, anteromedial prefrontal, and also posterior inferior temporal and inferior parietal cortex. In the cognitively normal cohort, the correlation coefficient between CL and distance to the hyperplane was −0.66 for the classifier trained with neuritic amyloid plaque density, and −0.88 for the classifier trained with amyloid phases. This difference was significant. The optimal CL cut-off for discriminating positive versus negative scans was CL = 48–51 for the different classifiers (area under the curve (AUC) = 99.9%), except for the classifier trained with amyloid phases and based on the 10% voxels with highest feature weights. There the cut-off was CL = 26 (AUC = 99.5%), which closely matched the CL threshold for discriminating phases 0–2 from 3–5 based on the end-of-life dataset and the neuropathological ground truth.

Discussion

Among a set of neuropathologically validated classifiers trained with end-of-life cases, transfer to a cognitively normal population works best for a classifier trained with amyloid phases and using only voxels with the highest amplitudes of feature weights.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-022-05808-7.

Statistical Parametric Mapping in Amyloid Positron Emission Tomography

Alzheimer's disease (AD), the most common cause of dementia, has limited treatment options. Emerging disease modifying therapies are targeted at clearing amyloid-β (Aβ) aggregates and slowing the rate of amyloid deposition. However, amyloid burden is not routinely evaluated quantitatively for purposes of disease progression and treatment response assessment. Statistical Parametric Mapping (SPM) is a technique comparing single-subject Positron Emission Tomography (PET) to a healthy cohort that may improve quantification of amyloid burden and diagnostic performance. While primarily used in 2-[18F]-fluoro-2-deoxy-D-glucose (FDG)-PET, SPM's utility in amyloid PET for AD diagnosis is less established and uncertainty remains regarding optimal normal database construction. Using commercially available SPM software, we created a database of 34 non-APOE ε4 carriers with normal cognitive testing (MMSE > 25) and negative cerebrospinal fluid (CSF) AD biomarkers. We compared this database to 115 cognitively normal subjects with variable AD risk factors. We hypothesized that SPM based on our database would identify more positive scans in the test cohort than the qualitatively rated [11C]-PiB PET (QR-PiB), that SPM-based interpretation would correlate better with CSF Aβ42 levels than QR-PiB, and that regional z-scores of specific brain regions known to be involved early in AD would be predictive of CSF Aβ42 levels. Fisher's exact test and the kappa coefficient assessed the agreement between SPM, QR-PiB PET, and CSF biomarkers. Logistic regression determined if the regional z-scores predicted CSF Aβ42 levels. An optimal z-score cutoff was calculated using Youden's index. We found SPM identified more positive scans than QR-PiB PET (19.1 vs. 9.6%) and that SPM correlated more closely with CSF Aβ42 levels than QR-PiB PET (kappa 0.13 vs. 0.06) indicating that SPM may have higher sensitivity than standard QR-PiB PET images. Regional analysis demonstrated the z-scores of the precuneus, anterior cingulate and posterior cingulate were predictive of CSF Aβ42 levels [OR (95% CI) 2.4 (1.1, 5.1) p = 0.024; 1.8 (1.1, 2.8) p = 0.020; 1.6 (1.1, 2.5) p = 0.026]. This study demonstrates the utility of using SPM with a "true normal" database and suggests that SPM enhances diagnostic performance in AD in the clinical setting through its quantitative approach, which will be increasingly important with future disease-modifying therapies.

Chronic PPARγ Stimulation Shifts Amyloidosis to Higher Fibrillarity but Improves Cognition

We undertook longitudinal β-amyloid positron emission tomography (Aβ-PET) imaging as a translational tool for monitoring of chronic treatment with the peroxisome proliferator-activated receptor gamma (PPARγ) agonist pioglitazone in Aβ model mice. We thus tested the hypothesis this treatment would rescue from increases of the Aβ-PET signal while promoting spatial learning and preservation of synaptic density. Here, we investigated longitudinally for 5 months PS2APP mice (N = 23; baseline age: 8 months) and App^NL–G–F mice (N = 37; baseline age: 5 months) using Aβ-PET. Groups of mice were treated with pioglitazone or vehicle during the follow-up interval. We tested spatial memory performance and confirmed terminal PET findings by immunohistochemical and biochemistry analyses. Surprisingly, Aβ-PET and immunohistochemistry revealed a shift toward higher fibrillary composition of Aβ-plaques during upon chronic pioglitazone treatment. Nonetheless, synaptic density and spatial learning were improved in transgenic mice with pioglitazone treatment, in association with the increased plaque fibrillarity. These translational data suggest that a shift toward higher plaque fibrillarity protects cognitive function and brain integrity. Increases in the Aβ-PET signal upon immunomodulatory treatments targeting Aβ aggregation can thus be protective.

Glitter in the Darkness? Nonfibrillar β-Amyloid Plaque Components Significantly Impact the β-Amyloid PET Signal in Mouse Models of Alzheimer Disease

β-amyloid (Aβ) PET is an important tool for quantification of amyloidosis in the brain of suspected Alzheimer disease (AD) patients and transgenic AD mouse models. Despite the excellent correlation of Aβ PET with gold standard immunohistochemical assessments, the relative contributions of fibrillar and nonfibrillar Aβ components to the in vivo Aβ PET signal remain unclear. Thus, we obtained 2 murine cerebral amyloidosis models that present with distinct Aβ plaque compositions and performed regression analysis between immunohistochemistry and Aβ PET to determine the biochemical contributions to Aβ PET signal in vivo. Methods: We investigated groups of AppNL-G-F and APPPS1 mice at 3, 6, and 12 mo of age by longitudinal 18F-florbetaben Aβ PET and with immunohistochemical analysis of the fibrillar and total Aβ burdens. We then applied group-level intermodality regression models using age- and genotype-matched sets of fibrillar and nonfibrillar Aβ data (predictors) and Aβ PET results (outcome) for both Aβ mouse models. An independent group of double-hit APPPS1 mice with dysfunctional microglia due to knockout of triggering receptor expression on myeloid cells 2 (Trem2-/-) served for validation and evaluation of translational impact. Results: Neither fibrillar nor nonfibrillar Aβ content alone sufficed to explain the Aβ PET findings in either AD model. However, a regression model compiling fibrillar and nonfibrillar Aβ together with the estimate of individual heterogeneity and age at scanning could explain a 93% of variance of the Aβ PET signal (P < 0.001). Fibrillar Aβ burden had a 16-fold higher contribution to the Aβ PET signal than nonfibrillar Aβ. However, given the relatively greater abundance of nonfibrillar Aβ, we estimate that nonfibrillar Aβ produced 79% ± 25% of the net in vivo Aβ PET signal in AppNL-G-F mice and 25% ± 12% in APPPS1 mice. Corresponding results in separate groups of APPPS1/Trem2-/- and APPPS1/Trem2+/+ mice validated the calculated regression factors and revealed that the altered fibrillarity due to Trem2 knockout impacts the Aβ PET signal. Conclusion: Taken together, the in vivo Aβ PET signal derives from the composite of fibrillar and nonfibrillar Aβ plaque components. Although fibrillar Aβ has inherently higher PET tracer binding, the greater abundance of nonfibrillar Aβ plaque in AD-model mice contributes importantly to the PET signal.

Evaluation of semi-quantitative measures of 18F-flutemetamol PET for the clinical diagnosis of Alzheimer's disease

BACKGROUND

¹⁸F-flutemetamol positron emission tomography (PET) is used to assess cortical amyloid-β burden in patients with cognitive impairment to support a clinical diagnosis. Visual classification is the most widely used method in clinical practice although semi-quantification is beneficial to obtain an objective and continuous measure of the Aβ burden. The aims were: first to evaluate the correspondence between standardized uptake value ratios (SUVRs) from three different software, Centiloids and visual classification, second to estimate thresholds for supporting visual classification and last to assess differences in semi-quantitative measures between clinical diagnoses.

METHODS

This observational study included 195 patients with cognitive impairment who underwent ¹⁸F-flutemetamol PET. PET images were semi-quantified with SyngoVia, CortexID suite, and PMOD. Receiver operating characteristics curves were used to compare visual classification with composite SUVR normalized to pons (SUVRpons) and cerebellar cortex (SUVRcer), and Centiloids. We explored correlations and differences between semi-quantitative measures as well as differences in SUVR between two clinical diagnosis groups: Alzheimer's disease-group and non-Alzheimer's disease-group.

RESULTS

PET images from 191 patients were semi-quantified with SyngoVia and CortexID and 86 PET-magnetic resonance imaging pairs with PMOD. All receiver operating characteristics curves showed a high area under the curve (>0.98). Thresholds for a visually positive PET was for SUVRcer: 1.87 (SyngoVia) and 1.64 (CortexID) and for SUVRpons: 0.54 (SyngoVia) and 0.55 (CortexID). The threshold on the Centiloid scale was 39.6 Centiloids. All semi-quantitative measures showed a very high correlation between different software and normalization methods. Composite SUVRcer was significantly different between SyngoVia and PMOD, SyngoVia and CortexID but not between PMOD and CortexID. Composite SUVRpons were significantly different between all three software. There were significant differences in the mean rank of SUVRpons, SUVRcer, and Centiloid between Alzheimer's disease-group and non-Alzheimer's disease-group.

CONCLUSIONS

SUVR from different software performed equally well in discriminating visually positive and negative ¹⁸F-Flutemetamol PET images. Thresholds should be considered software-specific and cautiously be applied across software without preceding validation to categorize scans as positive or negative. SUVR and Centiloid may be used alongside a thorough clinical evaluation to support a clinical diagnosis.

Is Cerebral Amyloid-β Deposition Related to Post-stroke Cognitive Impairment?

Approximately two-thirds of ischemic stroke patients suffer from different levels of post-stroke cognitive impairment (PSCI), but the underlying mechanisms of PSCI remain unclear. Cerebral amyloid-β (Aβ) deposition, a pathological hallmark of Alzheimer's disease, has been discovered in the brains of stroke patients in some autopsy studies. However, less is known about the role of Aβ pathology in the development of PSCI. It is hypothesized that cerebral ischemic injury may lead to neurotoxic Aβ accumulation in the brain, which further induces secondary neurodegeneration and progressive cognitive decline after stroke onset. In this review, we summarized available evidence from pre-clinical and clinical studies relevant to the aforementioned hypothesis. We found inconsistency in the results obtained from studies in rodents, nonhuman primates, and stroke patients. Moreover, the causal relationship between post-stroke cerebral Aβ deposition and PSCI has been uncertain and controversial. Taken together, evidence supporting the hypothesis that brain ischemia induces cerebral Aβ deposition has been insufficient so far. And, there is still no consensus regarding the contribution of cerebral amyloid pathology to PSCI. Other non-amyloid neurodegenerative mechanisms might be involved and remain to be fully elucidated.

Advancement in Pharmacological Activities of Benzothiazole and its Derivatives: An Up to Date Review

Benzothiazole is a heterocyclic aromatic and bicyclic compound in which, benzene ring is attached with thiazole ring. This nucleus is established in marine as well as terrestrial natural compounds. The benzothiazole skeleton is established in a broad variety of bioactive heterocycles and natural products. The benzothiazole nucleus is considered as the principle moiety in several biologically active compounds. Over the decade, chemists are paying more attention towards the revision of the biological and therapeutic activities such as antimicrobial, analgesic, antiinflammatory, antitubercular, antiviral and antioxidant of benzothiazole containing compounds. The molecular structures of a number of potent drugs including Frentizole, Pramipexole, Thioflavin T and Riluzole etc., are based on benzothiazole skeleton. The present work is the compilation and presentation of all available information in a systematic manner with an aim to present the findings in a way, which may be beneficial for future research.

Head-to-Head Comparison of 18F-Florbetaben and 18F-Flutemetamol in the Cortical and Striatal Regions

BACKGROUND

18F-florbetaben (FBB) and 18F-flutemetamol (FMM) amyloid PET have been developed and approved for clinical use. It is important to understand the distinct features of these ligands to compare and correctly interpret the results of different amyloid PET studies.

OBJECTIVE

We performed a head-to-head comparison of FBB and FMM to compare with regard to imaging characteristics, including dynamic range of retention, and differences in quantitative measurements between the two ligands in cortical, striatal, and white matter (WM) regions.

METHODS

Paired FBB and FMM PET images were acquired in 107 participants. Correlations of FBB and FMM amyloid deposition in the cortex, striatum, and WM were investigated and compared in different reference regions (cerebellar gray matter (CG), whole cerebellum (WC), WC with brainstem (WC + B), and pons).

RESULTS

The cortical SUVR (R2 = 0.97) and striatal SUVR (R2 = 0.95) demonstrated an excellent linear correlation between FBB and FMM using a WC as reference region. There was no difference in the cortical SUVR ratio between the two ligands (p = 0.90), but the striatal SUVR ratio was higher in FMM than in FBB (p < 0.001). Also, the effect size of differences in striatal SUVR seemed to be higher with FMM (2.61) than with FBB (2.34). These trends were similarly observed according to four different reference regions (CG, WC, WC + B, and pons).

CONCLUSION

Our findings suggest that FMM might be better than FBB to detect amyloid burden in the striatum, although both ligands are comparable for imaging AD pathology in vivo.

Concordance in detecting amyloid positivity between 18F-florbetaben and 18F-flutemetamol amyloid PET using quantitative and qualitative assessments

We aimed to quantitatively and qualitatively assess whether there is a discrepancy in detecting amyloid beta (Aβ) positivity between 18F-florbetaben (FBB) and 18F-flutemetamol (FMM) positron emission tomography (PET). We obtained paired FBB and FMM PET images from 107 participants. Three experts visually quantified the Aβ deposition as positive or negative. Quantitative assessment was performed using global cortical standardized uptake value ratio (SUVR) with the whole cerebellum as the reference region. Inter-rater agreement was excellent for FBB and FMM. The concordance rates between FBB and FMM were 94.4% (101/107) for visual assessment and 98.1% (105/107) for SUVR cut-off categorization. Both FBB and FMM showed high agreement rates between visual assessment and SUVR positive or negative categorization (93.5% in FBB and 91.2% in FMM). When the two ligands were compared based on SUVR cut-off categorization as standard of truth, although not statistically significant, the false-positive rate was higher in FMM (9.1%) than in FBB (1.8%) (p = 0.13). Our findings suggested that both FBB and FMM had excellent agreement when used to quantitatively and qualitatively evaluate Aβ deposits, thus, combining amyloid PET data associated with the use of different ligands from multi-centers is feasible.

Post-mortem analyses of PiB and flutemetamol in diffuse and cored amyloid-β plaques in Alzheimer's disease

Specificity and sensitivity of positron emission tomography (PET) radiopharmaceuticals targeting fibrillar amyloid-β (Aβ) deposits is high for detection of neuritic Aβ plaques, a mature form of Aβ deposits which often have dense Aβ core (i.e., cored plaques). However, imaging-to-autopsy validation studies of amyloid PET radioligands have identified several false positive cases all of which had mainly diffuse Aβ plaques (i.e., plaques without neuritic pathology or dense amyloid core), and high amyloid PET signal was reported in the striatum where diffuse plaques predominate in Alzheimer's disease (AD). Relative contributions of different plaque types to amyloid PET signal is unclear, particularly in neocortical areas where they are intermixed in AD. In vitro binding assay and autoradiography were performed using [3H]flutemetamol and [3H]Pittsburgh Compound-B (PiB) in frozen brain homogenates from 30 autopsy cases including sporadic AD and non-AD controls with a range of brain Aβ burden and plaque density. Fixed tissue sections of frontal cortex and caudate from 10 of the AD cases were processed for microscopy using fluorescent derivatives of flutemetamol (cyano-flutemetamol) and PiB (cyano-PiB) and compared to Aβ immunohistochemistry and pan-amyloid (X-34) histology. Using epifluorescence microscopy, percent area coverage and fluorescence output values of cyano-PiB- and cyano-flutemetamol-labeled plaques in two-dimensional microscopic fields were then calculated and combined to obtain integrated density measurements. Using confocal microscopy, we analysed total fluorescence output of the entire three-dimensional volume of individual cored plaques and diffuse plaques labeled with cyano-flutemetamol or cyano-PiB. [3H]Flutemetamol and [3H]PiB binding values in tissue homogenates correlated strongly and their binding pattern in tissue sections, as seen on autoradiograms, overlapped the pattern of Aβ-immunoreactive plaques on directly adjacent sections. Cyano-flutemetamol and cyano-PiB fluorescence was prominent in cored plaques and less so in diffuse plaques. Across brain regions and cases, percent area coverage of cyano-flutemetamol-labeled plaques correlated strongly with cyano-PiB-labeled and Aβ-immunoreactive plaques. For both ligands, plaque burden, calculated as percent area coverage of all Aβ plaque types, was similar in frontal cortex and caudate regions, while integrated density values were significantly greater in frontal cortex, which contained both cored plaques and diffuse plaques, compared to the caudate, which contained only diffuse plaques. Three-dimensional analysis of individual plaques labeled with either ligand showed that total fluorescence output of a single cored plaque was equivalent to total fluorescence output of approximately three diffuse plaques of similar volume. Our results indicate that [18F]flutemetamol and [11C]PiB PET signal is influenced by both diffuse plaques and cored plaques, and therefore is likely a function of plaque size and density of Aβ fibrils in plaques. Brain areas with large volumes/frequencies of diffuse plaques could yield [18F]flutemetamol and [11C]PiB PET retention levels comparable to brain regions with a lower volume/frequency of cored plaques.

Appropriate reference region selection of 18F-florbetaben and 18F-flutemetamol beta-amyloid PET expressed in Centiloid

The Centiloid (CL) is a method for standardizing amyloid beta (Aβ) quantification through different ligands and methods. To find the most appropriate reference region to reduce the variance in the Aβ CL unit between ¹⁸F-florbetaben (FBB) and ¹⁸F-flutemetamol (FMM), we conducted head-to-head comparisons from 56 participants using the direct comparison of FBB-FMM CL (dcCL) method with four reference regions: cerebellar gray (CG), whole cerebellum (WC), WC with brainstem (WC + B), and pons. The FBB and FMM dcCL units were highly correlated in four reference regions: WC (R² = 0.97), WC + B (R² = 0.98), CG (R² = 0.92), and pons (R² = 0.98). WC showed the largest effect size in both FBB and FMM. Comparison of the variance of the dcCL values within the young control group showed that with FBB, WC + B had the smallest variance and with FMM, the WC had the smallest variance. Additionally, WC + B showed the smallest absolute difference between FBB and FMM, followed by the WC, pons, and CG. We found that it would be reasonable to use the WC or WC + B as the reference region when converting FBB and FMM SUVRs into dcCL, which can increase the accuracy of standardizing FBB and FMM PET results.

No evidence for amyloid pathology as a key mediator of neurodegeneration post-stroke - a seven-year follow-up study

Background

Cognitive impairment (CI) with mixed vascular and neurodegenerative pathologies after stroke is common. The role of amyloid pathology in post-stroke CI is unclear. We hypothesize that amyloid deposition, measured with Flutemetamol (¹⁸F-Flut) positron emission tomography (PET), is common in seven-year stroke survivors diagnosed with CI and, further, that quantitatively assessed ¹⁸F-Flut-PET uptake after 7 years correlates with amyloid-β peptide (Aβ₄₂) levels in cerebrospinal fluid (CSF) at 1 year, and with measures of neurodegeneration and cognition at 7 years post-stroke.

Methods

208 patients with first-ever stroke or transient Ischemic Attack (TIA) without pre-existing CI were included during 2007 and 2008. At one- and seven-years post-stroke, cognitive status was assessed, and categorized into dementia, mild cognitive impairment or normal. Etiologic sub-classification was based on magnetic resonance imaging (MRI) findings, CSF biomarkers and clinical cognitive profile. At 7 years, patients were offered ¹⁸F-Flut-PET, and amyloid-positivity was assessed visually and semi-quantitatively. The associations between ¹⁸F-Flut-PET standardized uptake value ratios (SUVr) and measures of neurodegeneration (medial temporal lobe atrophy (MTLA), global cortical atrophy (GCA)) and cognition (Mini-Mental State Exam (MMSE), Trail-making test A (TMT-A)) and CSF Aβ₄₂ levels were assessed using linear regression.

Results

In total, 111 patients completed 7-year follow-up, and 26 patients agreed to PET imaging, of whom 13 had CSF biomarkers from 1 year. Thirteen out of 26 patients were diagnosed with CI 7 years post-stroke, but only one had visually assessed amyloid positivity. CSF Aβ₄₂ levels at 1 year, MTA grade, GCA scale, MMSE score or TMT-A at 7 years did not correlate with ¹⁸F-Flut-PET SUVr in this cohort.

Conclusions

Amyloid binding was not common in 7-year stroke survivors diagnosed with CI. Quantitatively assessed, cortical amyloid deposition did not correlate with other measures related to neurodegeneration or cognition. Therefore, amyloid pathology may not be a key mediator of neurodegeneration 7 years post-stroke.

Trial registration

Clinicaltrials.gov (NCT00506818). July 23, 2007. Inclusion from February 2007, randomization and intervention from May 2007 and trial registration in July 2007.

The Spatial-Temporal Ordering of Amyloid Pathology and Opportunities for PET Imaging

Although clinical routine focuses on dichotomous and visual interpretation of amyloid PET, regional image assessment in research settings may yield additional opportunities. Understanding the regional-temporal evolution of amyloid pathology may enable earlier identification of subjects in the Alzheimer Disease pathologic continuum, as well as a finer-grained assessment of pathology beyond traditional dichotomous measures. This review summarizes current research in the detection of regional amyloid deposition patterns and its potential for staging amyloid pathology. Pathology studies, cross-sectional and longitudinal PET-only studies, and comparative PET and autopsy studies are included. Despite certain differences, cortical deposition generally precedes striatal pathology, and in PET-only studies, medial cortical regions are seen to accumulate amyloid earlier than lateral regions. Based on regional amyloid PET, multiple studies have developed and implemented models for staging amyloid pathology that could improve subject selection into secondary prevention trials and visual assessment in clinical routine.

Increased Inflammation and Unchanged Density of Synaptic Vesicle Glycoprotein 2A (SV2A) in the Postmortem Frontal Cortex of Alzheimer's Disease Patients

Sections from the middle frontal gyrus (Brodmann area 46) of autopsy-confirmed Alzheimer's disease (AD) patients and non-demented subjects were examined for the prevalence of hallmark AD pathology, including amyloid-β (Aβ) plaques, phosphorylated tau (pTau) tangles, neuroinflammation and synaptic loss (n = 7 subjects/group). Dense-core deposits of Aβ were present in all AD patients (7/7) and some non-demented subjects (3/7), as evidenced by 6E10 immunohistochemistry. Levels of Aβ immunoreactivity were higher in AD vs. non-AD cases. For pTau, AT8-positive neurofibrillary tangles and threads were exclusively observed in AD patient tissue. Levels of [³H]PK11195 binding to the translocator protein (TSPO), a marker of inflammatory processes, were elevated in the gray matter of AD patients compared to non-demented subjects. Levels of [³H]UCB-J binding to synaptic vesicle glycoprotein 2A (SV2A), a marker of synaptic density, were not different between groups. In AD patients, pTau immunoreactivity was positively correlated with [³H]PK11195, and negatively correlated with [³H]UCB-J binding levels. No correlation was observed between Aβ immunoreactivity and markers of neuroinflammation or synaptic density. These data demonstrate a close interplay between tau pathology, inflammation and SV2A density in AD, and provide useful information on the ability of neuroimaging biomarkers to diagnose AD dementia.

Amyloid-β PET-Correlation with cerebrospinal fluid biomarkers and prediction of Alzheimer´s disease diagnosis in a memory clinic

Background

Alzheimer’s disease (AD) remains a clinical diagnosis but biomarkers from cerebrospinal fluid (CSF) and more lately amyloid imaging with positron emission tomography (PET), are important to support a diagnosis of AD.

Objective

To compare amyloid-β (Aβ) PET imaging with biomarkers in CSF and evaluate the prediction of Aβ PET on diagnosis in a memory clinic setting.

Methods

We included 64 patients who had lumbar puncture and Aβ PET with ¹⁸F-Flutemetamol performed within 190 days. PET was binary classified (Flut+ or Flut-) and logistic regression analyses for correlation to each CSF biomarker; Aβ 42 (Aβ₄₂), total tau (T-tau) and phosphorylated tau (P-tau), were performed. Cut-off values were assessed by receiver operating characteristic (ROC) curves. Logistic regression was performed for prediction of clinical AD diagnosis. We assessed the interrater agreement of PET classification as well as for diagnoses, which were made both with and without knowledge of PET results.

Results

Thirty-two of the 34 patients (94%) in the Flut+ group and nine of the 30 patients (30%) in the Flut- group had a clinical AD diagnosis. There were significant differences in all CSF biomarkers in the Flut+ and Flut- groups. Aβ₄₂ showed the highest correlation with ¹⁸F-Flutemetamol PET with a cut-off value of 706.5 pg/mL, corresponding to sensitivity of 88% and specificity of 87%. ¹⁸F-Flutemetamol PET was the best predictor of a clinical AD diagnosis. We found a very high interrater agreement for both PET classification and diagnosis.

Conclusions

The present study showed an excellent correlation of Aβ₄₂ in CSF and ¹⁸F-Flutemetamol PET and the presented cut-off value for Aβ₄₂ yields high sensitivity and specificity for ¹⁸F-Flutemetamol PET. ¹⁸F-Flutemetamol PET was the best predictor of clinical AD diagnosis.

Neuropathological correlates of amyloid PET imaging in Down syndrome

Down syndrome (DS) results in an overproduction of amyloid-β (Aβ) peptide associated with early onset of Alzheimer's disease (AD). DS cases have Aβ deposits detectable histologically as young as 12-30 years of age, primarily in the form of diffuse plaques, the type of early amyloid pathology also seen at pre-clinical (i.e., pathological aging) and prodromal stages of sporadic late onset AD. In DS subjects aged >40 years, levels of cortical Aβ deposition are similar to those observed in late onset AD and in addition to diffuse plaques involve cored plaques associated with dystrophic neurites (neuritic plaques), which are of neuropathological diagnostic significance in AD. The purpose of this review is to summarize and discuss findings from amyloid PET imaging studies of DS in reference to postmortem amyloid-based neuropathology. PET neuroimaging applied to subjects with DS has the potential to (a) track the natural progression of brain pathology, including the earliest stages of amyloid accumulation, and (b) determine whether amyloid PET biomarkers predict the onset of dementia. In addition, the question that is still incompletely understood and relevant to both applications is the ability of amyloid PET to detect Aβ deposits in their earliest form.