18F-flutemetamol Positron Emission Tomography Research Articles

Crossover evaluation of time-of-flight-based attenuation correction in brain 18F-FDG and 18F-flutemetamol PET.

Brain-dedicated positron emission tomography (PET) systems offer high spatial resolution and sensitivity for accurate clinical assessments. Attenuation correction (AC) is important in PET imaging, particularly in brain studies. This study assessed the reproducibility of attenuation maps (µ-maps) generated by a specialized time-of-flight (TOF) brain-dedicated PET system for imaging using different PET tracers. Twelve subjects underwent both 18F-fluorodeoxyglucose (FDG)-PET and 18F-flutemetamol (FMM) amyloid-PET scans. Images were reconstructed with µ-maps obtained by a maximum likelihood-based AC method. Voxel-based and region-based analyses were used to compare µ-maps obtained with FDG-PET versus FMM-PET; FDG-PET images reconstructed using an FDG-PET µ-map (FDG × FDG) versus those reconstructed with an FMM-PET µ-map (FDG × FMM); and FMM-PET images reconstructed using an FDG-PET µ-map (FMM × FDG) versus those reconstructed with an FMM-PET µ-map (FMM × FMM). Small but significant differences in µ-maps were observed between tracers, primarily in bone regions. In the comparison between the µ-maps obtained with FDG-PET and FMM-PET, the µ-maps obtained with FDG-PET had higher µ-values than those obtained with FMM-PET in the parietal regions of the head and skull, in a portion of the cerebellar dentate nucleus and on the surface of the frontal lobe. The comparison between FDG and FDG × FMM values in different regions yielded findings similar to those of the µ-maps comparison. FDG × FMM values were significantly higher than FDG values in the bilateral temporal bones and a small part of the temporal lobe. Similarly, FMM values were significantly higher than FMM × FDG values in the bilateral temporal bones. FMM × FDG values were significantly higher than FMM values in a small area of the right cerebellar hemisphere. However, the relative errors in these µ-maps were within ± 4%, suggesting that they are clinically insignificant. In PET images reconstructed with the original and swapped µ-maps, the relative errors were within ± 7% and the quality was nearly equivalent. These findings suggest the clinical reliability of the AC method without an external radiation source in TOF brain-dedicated PET systems.

Clinical effects of novel susceptibility genes for beta-amyloid: a gene-based association study in the Korean population.

Amyloid-beta (Aβ) is a pathological hallmark of Alzheimer's disease (AD). We aimed to identify genes related to Aβ uptake in the Korean population and investigate the effects of these novel genes on clinical outcomes, including neurodegeneration and cognitive impairments. We recruited a total of 759 Korean participants who underwent neuropsychological tests, brain magnetic resonance imaging, 18F-flutemetamol positron emission tomography, and microarray genotyping data. We performed gene-based association analysis, and also performed expression quantitative trait loci and network analysis. In genome-wide association studies, no single nucleotide polymorphism (SNP) passed the genome-wide significance threshold. In gene-based association analysis, six genes (LCMT1, SCRN2, LRRC46, MRPL10, SP6, and OSBPL7) were significantly associated with Aβ standardised uptake value ratio in the brain. The three most significant SNPs (rs4787307, rs9903904, and rs11079797) on these genes are associated with the regulation of the LCMT1, OSBPL7, and SCRN2 genes, respectively. These SNPs are involved in decreasing hippocampal volume and cognitive scores by mediating Aβ uptake. The 19 enriched gene sets identified by pathway analysis included axon and chemokine activity. Our findings suggest novel susceptibility genes associated with the uptake of Aβ, which in turn leads to worse clinical outcomes. Our findings might lead to the discovery of new AD treatment targets.

Comparison of automated quantification of amyloid deposition between PMOD and Heuron

Several programs are widely used for clinical and research purposes to automatically quantify the degree of amyloid deposition in the brain using positron emission tomography (PET) images. Given that very few studies have investigated the use of Heuron, a PET image quantification software approved for clinical use, this study aimed to compare amyloid deposition values quantified from 18F-flutemetamol PET images using PMOD and Heuron. Amyloid PET data obtained from 408 patients were analysed using each quantitative program; moreover, the standardized uptake value ratios (SUVRs) of target areas were obtained by dividing the standardized uptake value (SUV) of the target region by the SUV of cerebellar grey matter as a reference. Compared with PMOD, Heuron yielded significantly higher SUVRs for all target areas (paired sample t-test, p < 0.001), except for the PC/PCC (p = 0.986). However, the Bland–Altman plot analysis indicated that the two quantitative methods may be used interchangeably. Moreover, receiver operating characteristic curve analysis revealed no significant between-method difference in the performance of the SUVRs in evaluating the visual positivity of amyloid deposits (p = 0.948). In conclusion, Heuron and PMOD have comparable performance in quantifying the degree of amyloid deposits in PET images.

Automatic lesion detection and segmentation in 18F-flutemetamol positron emission tomography images using deep learning

BackgroundBeta amyloid in the brain, which was originally confirmed by post-mortem examinations, can now be confirmed in living patients using amyloid positron emission tomography (PET) tracers, and the accuracy of diagnosis can be improved by beta amyloid plaque confirmation in patients. Amyloid deposition in the brain is often associated with the expression of dementia. Hence, it is important to identify the anatomically and functionally meaningful areas of the human brain cortex surface using PET to diagnose the possibility of developing dementia. In this study, we demonstrated the validity of automated 18F-flutemetamol PET lesion detection and segmentation based on a complete 2D U-Net convolutional neural network via masking treatment strategies.MethodsPET data were first normalized by volume and divided into five amyloid accumulation zones through axial, coronary, and thalamic slices. A single U-Net was trained using a divided dataset for one of these zones. Ground truth segmentations were obtained by manual delineation and thresholding (1.5 × background).ResultsThe following intersection over union values were obtained for the various slices in the verification dataset: frontal lobe axial/sagittal: 0.733/0.804; posterior cingulate cortex and precuneus coronal/sagittal: 0.661/0.726; lateral temporal lobe axial/coronal: 0.864/0.892; parietal lobe axial/coronal: 0.542/0.759; and striatum axial/sagittal: 0.679/0.752. The U-Net convolutional neural network architecture allowed fully automated 2D division of the 18F-flutemetamol PET brain images of Alzheimer's patients.ConclusionsAs dementia should be tested and evaluated in various ways, there is a need for artificial intelligence programs. This study can serve as a reference for future studies using auxiliary roles and research in Alzheimer's diagnosis.

Automated semi-quantitative amyloid PET analysis technique without MR images for Alzheimer’s disease

ObjectiveAlthough beta-amyloid (Aβ) positron emission tomography (PET) images are interpreted visually as positive or negative, approximately 10% are judged as equivocal in Alzheimer’s disease. Therefore, we aimed to develop an automated semi-quantitative analysis technique using 18F-flutemetamol PET images without anatomical images.MethodsOverall, 136 cases of patients administered 18F-flutemetamol were enrolled. Of 136 cases, five PET images each with the highest and lowest values of standardized uptake value ratio (SUVr) of cerebral cortex-to-pons were used to create positive and negative templates. Using these templates, PET images of the remaining 126 cases were standardized, and SUVr images were produced with the pons as a reference region. The mean of SUVr values in the volume of interest delineated on the cerebral cortex was compared to those in the CortexID Suite (GE Healthcare). Furthermore, centiloid (CL) values were calculated for the 126 cases using data from the Centiloid Project (http://www.gaain.org/centiloid-project) and both templates. 18F-flutemetamol-PET was interpreted visually as positive/negative based on Aβ deposition in the cortex. However, the criterion "equivocal" was added for cases with focal or mild Aβ accumulation that were difficult to categorize. Optimal cutoff values of SUVr and CL maximizing sensitivity and specificity for Aβ detection were determined by receiver operating characteristic (ROC) analysis using the visual evaluation as a standard of truth.ResultsSUVr calculated by our method and CortexID were highly correlated (R2 = 0.9657). The 126 PET images comprised 84 negative and 42 positive cases of Aβ deposition by visual evaluation, of which 11 and 10 were classified as equivocal, respectively. ROC analyses determined the optimal cutoff values, sensitivity, and specificity for SUVr as 0.544, 89.3%, and 92.9%, respectively, and for CL as 12.400, 94.0%, and 92.9%, respectively. Both semi-quantitative analyses showed that 12 and 9 of the 21 equivocal cases were negative and positive, respectively, under the optimal cutoff values.ConclusionsThis semi-quantitative analysis technique using 18F-flutemetamol-PET calculated SUVr and CL automatically without anatomical images. Moreover, it objectively and homogeneously interpreted positive or negative Aβ burden in the brain as a supplemental tool for the visual reading of equivocal cases in routine clinical practice.

Evaluation of 18F-flutemetamol amyloid PET image analysis parameters on the effect of verubecestat on brain amlyoid load in Alzheimer's disease.

The BACE inhibitor verubecestat was previously found to reduce amyloid load as assessed by 18F-flutemetamol positron emission tomography (PET) composite cortical standard uptake value ratio (SUVr) in patients with mild-to-moderate Alzheimer's disease (AD) in a substudy of the EPOCH trial. Here, we report on additional analyses relevant to the EPOCH PET data, to help inform on the use of PET for assessing amlyloid load in AD clinical trials. The analyses addressed (1) identification of an optimal 18F-flutemetamol reference region, (2) determination of the threshold to characterize the magnitude of the longitudinal change, and (3) the impact of partial volume correction (PVC). Pons and subcortical white matter were evaluated as reference regions. The SUVr cutoffs and final reference region choice were determined using 162 18F-flutemetamol PET scans from the AIBL dataset. 18F-flutemetamol SUVrs were computed at baseline and at Week 78 in EPOCH participants who received verubecestat 12mg (n = 14), 40mg (n = 20), or placebo (n = 20). Drug effects on amyloid load were computed using either Meltzer (MZ), or symmetric geometric transfer matrix (SGTM) PVC and compared to uncorrected data. The optimal subcortical white matter and pons SUVr cutoffs were determined to be 0.69 and 0.62, respectively. The effect size to detect longitudinal change was higher for subcortical white matter (1.20) than pons (0.45). Hence, subcortical white matter was used as the reference region for the EPOCH PET substudy. In EPOCH, uncorrected baseline SUVr values correlated strongly with MZ PVC (r2 = 0.94) and SGTM PVC (r2 = 0.92) baseline SUVr values, and PVC did not provide improvement for evaluating treatment effects on amyloid load at Week 78. No change from baseline was observed in the placebo group at Week 78, whereas a 0.02 and a 0.04 decrease in SUVr were observed in the 12mg and 40mg arms, with the latter representing a 22% reduction in the amyloid load above the detection threshold. Treatment-related 18F-flutemetamol longitudinal changes in AD clinical trials can be quantified using a subcortical white matter reference region without PVC. clinicaltrials.gov NCT01739348.

Is Amyloid Burden Measured by 18F-Flutemetamol PET Associated with Progression in Clinical Alzheimer's Disease?

Background:Patients with Alzheimer’s disease (AD) show heterogeneity in clinical progression rate, and we have limited tools to predict prognosis. Amyloid burden from 18F-Flutemetamol positron emission tomography (PET), as measured by standardized uptake value ratios (SUVR), might provide prognostic information.Objective:We investigate whether 18F-Flutemetamol PET composite or regional SUVRs are associated with trajectories of clinical progression.Methods:This observational longitudinal study included 94 patients with clinical AD. PET images were semi-quantified with normalization to pons. Group-based trajectory modeling was applied to identify trajectory groups according to change in the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) over time. Multinomial logistic regression models assessed the association of SUVRs with trajectory group membership.Results:Three trajectory groups were identified. In the regression models, neither composite nor regional SUVRs were associated with trajectory group membership.Conclusion: There were no associations between CDR progression and 18F-Flutemetamol PET-derived composite SUVRs or regional SUVRs in clinical AD.

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

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. 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. 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. 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.

Cognitive decline according to amyloid uptake in patients with poststroke cognitive impairment.

Background and purpose:Poststroke cognitive impairment (PSCI) is common, but the impact of β-amyloid (Aβ) on PSCI is uncertain. The proposed study will investigate amyloid pathology in participants with PSCI and how differently their cognition progress according to the amyloid pathology.Methods:This multicenter study was designed to be prospective and observational based on a projected cohort size of 196 participants with either newly developed cognitive impairment, or rapidly aggravated CI, within 3 months after acute cerebral infarction. They will undergo 18F-flutemetamol positron emission tomography at baseline and will be categorized as either amyloid-positive (A+) or amyloid-negative (A−) by visual rating. The primary outcome measures will be based on Korean Mini-Mental State Examination changes (baseline to 12 months) between the A+ and A− groups. The secondary outcome measures will be the dementia-conversion rate and changes in the Korean version of the Montreal Cognitive Assessment (baseline to 12 months) between the A+ and A− groups.Conclusions:This study will provide a broadened perspective on the impact of Aβ on the cause and outcomes of PSCI in clinical practice. Identifying amyloid pathology in patients with PSCI will help select patients who need more focused treatments such as acetylcholinesterase inhibitorsTrial registration:Clinical Research Information Service identifier: KCT0005086

Novel Plasma miRNAs as Biomarkers and Therapeutic Targets of Alzheimer’s Disease at the Prodromal Stage

Background: Amnestic mild cognitive impairment (aMCI) is a prodromal stage of Alzheimer’s disease (AD) involving imbalanced beta-site amyloid precursor protein cleaving enzyme 1 (BACE1). MicroRNAs (miRNAs) are associated with AD. Objective: This study aimed to investigated whether plasma miRNAs can predict prodromal AD or are associated with AD pathology. Methods: Participants in the discovery set (n = 10), analysis set (n = 30), and validation set (n = 80) were screened from the China Longitudinal Aging Study. RNA was extracted from the participants’ plasma. Microarray sequencing provided miRNA profiles and differentially expressed miRNAs (DEmiRNAs) in the discovery set included patients with 18F-Flutemetamol positron emission tomography scan-confirmed aMCI. Potential biomarkers were screened in the analysis set. The predict capability of candidate miRNAs was assessed in the validation set. Candidate miRNAs modulation of BACE1 expression was explored in rat and human hippocampal neurons in vitro. Results: We verified 46 significant DEmiRNAs between the aMCI and NC groups (p &lt; 0.05), among which 33 were downregulated. In the analysis set, miR-1185-2-3p, miR-1909-3p, miR-22-5p, and miR-134-3p levels decreased significantly in the aMCI group. These miRNAs and previously identified miR-107 were selected as potential biomarkers. A prediction model comprising these five miRNAs showed outstanding accuracy (81.25%) to discriminate aMCI at cut-off value of 0.174. Except for miR-134-3p, the other four miRNAs significantly suppressed Bace1 expression in rat hippocampal neurons in vitro. BACE1 modulation of miR-1185-2-3p, miR-1909-3p, and miR-134-3p was confirmed in human hippocampal neurons in vitro. Conclusion: A predictive model consisting of five BACE1-related plasma miRNAs could be a novel biomarker for aMCI.

Longitudinal Observation of Early-Onset Alzheimer’s Disease Dementia with Positive CSF Biomarkers/Negative Amyloid-β Positron-Emission Tomography

We report a 61-year-old woman with clinical course for Alzheimer’s disease (AD) dementia and discordant amyloid-β positron-emission tomography (PET) and cerebrospinal fluid biomarkers. Brain magnetic resonance imaging revealed remarkable atrophy in the hippocampus. However, repeated delayed 18F-flutemetamol brain amyloid PET images with 1 year-interval revealed no amyloid deposition, whereas her CSF revealed low Aβ42, high total tau and p-tau181. This discordant amyloid-β PET and CSF biomarkers in this early-onset AD dementia might be associated with her low resilience or mixed pathology.

Harmonisation of PET imaging features with different amyloid ligands using machine learning-based classifier.

In this study, we used machine learning to develop a new method derived from a ligand-independent amyloid (Aβ) positron emission tomography (PET) classifier to harmonise different Aβ ligands. We obtained 107 paired 18F-florbetaben (FBB) and 18F-flutemetamol (FMM) PET images at the Samsung Medical Centre. To apply the method to FMM ligand, we transferred the previously developed FBB PET classifier to test similar features from the FMM PET images for application to FMM, which in turn developed a ligand-independent Aβ PET classifier. We explored the concordance rates of our classifier in detecting cortical and striatal Aβ positivity. We investigated the correlation of machine learning-based cortical tracer uptake (ML-CTU) values quantified by the classifier between FBB and FMM. This classifier achieved high classification accuracy (area under the curve = 0.958) even with different Aβ PET ligands. In addition, the concordance rate of FBB and FMM using the classifier (87.5%) was good to excellent, which seemed to be higher than that in visual assessment (82.7%) and lower than that in standardised uptake value ratio cut-off categorisation (93.3%). FBB and FMM ML-CTU values were highly correlated with each other (R = 0.903). Our findings suggested that our novel classifier may harmonise FBB and FMM ligands in the clinical setting which in turn facilitate the biomarker-guided diagnosis and trials of anti-Aβ treatment in the research field.

Default mode network dissociation linking cerebral beta amyloid retention and depression in cognitively normal older adults.

Cerebral beta amyloid (Aβ) deposition and late-life depression (LLD) are known to be associated with the trajectory of Alzheimer's disease (AD). However, their neurobiological link is not clear. Previous studies showed aberrant functional connectivity (FC) changes in the default mode network (DMN) in early Aβ deposition and LLD, but its mediating role has not been elucidated. This study was performed to investigate the distinctive association pattern of DMN FC linking LLD and Aβ retention in cognitively normal older adults. A total of 235 cognitively normal older adults with (n = 118) and without depression (n = 117) underwent resting-state functional magnetic resonance imaging and 18F-flutemetamol positron emission tomography to investigate the associations between Aβ burden, depression, and DMN FC. Independent component analysis showed increased anterior DMN FC and decreased posterior DMN FC in the depression group compared with the no depression group. Global cerebral Aβ retention was positively correlated with anterior and negatively correlated with posterior DMN FC. Anterior DMN FC was positively correlated with severity of depression, whereas posterior DMN FC was negatively correlated with cognitive function. In addition, the effects of global cerebral Aβ retention on severity of depression were mediated by subgenual anterior cingulate FC. Our results of anterior and posterior DMN FC dissociation pattern may be pivotal in linking cerebral Aβ pathology and LLD in the course of AD progression. Further longitudinal studies are needed to confirm the causal relationships between cerebral Aβ retention and LLD.

Quantitative Evaluation of 18F-Flutemetamol PET in Patients With Cognitive Impairment and Suspected Alzheimer's Disease: A Multicenter Study.

Background: In clinical practice, equivocal findings are inevitable in visual interpretation of whether amyloid positron emission tomography (PET) is positive or negative. It is therefore necessary to establish a more objective quantitative evaluation method for determining the indication for disease-modifying drugs currently under development.Aims: We aimed to determine cutoffs for positivity in quantitative analysis of 18F-flutemetamol PET in patients with cognitive impairment and suspected Alzheimer's disease (AD). We also evaluated the clinical efficacy of amyloid PET in the diagnosis of AD. This study was registered in the Japan Registry of Clinical Trials (jRCTs, 031180321).Methods: Ninety-three patients suspected of having AD underwent 18F-flutemetamol PET in seven institutions. A PET image for each patient was visually assessed and dichotomously rated as either amyloid-positive or amyloid-negative by two board-certified nuclear medicine physicians. If the two readers obtained different interpretations, the visual rating was rerun until they reached consensus. The PET images were quantitatively analyzed using the standardized uptake value ratio (SUVR) and standardized Centiloid (CL) scale with the whole cerebellum as a reference area.Results: Visual interpretation obtained 61 positive and 32 negative PET scans. Receiver operating characteristic analysis determined the best agreement of quantitative assessments and visual interpretation of PET scans to have an area under curve of 0.982 at an SUVR of 1.13 and a CL of 16. Using these cutoff values, there was high agreement between the two approaches (kappa = 0.88). Five discordant cases had SUVR and CL values ranging from 1.00 to 1.22 and from 1 to 26, respectively. In these discordant cases, either diffuse or mildly focal elevation of cortical activity confused visual interpretation. The amyloid PET outcome significantly altered the diagnosis of AD (χ2 = 51.3, p < 0.0001). PET imaging elevated the proportions of the very high likelihood category from 20.4 to 46.2% and the very low likelihood category from 0 to 22.6%.Conclusion: Quantitative analysis of amyloid PET using 18F-flutemetamol can objectively evaluate amyloid positivity using the determined cutoffs for SUVR and CL. Moreover, amyloid PET may have added value over the standard diagnostic workup in dementia patients with cognitive impairment and suspected AD.

Associations of rest-activity patterns with amyloid burden, medial temporal lobe atrophy, and cognitive impairment.

BackgroundWe sought to investigate the possible associations of rest-activity patterns with cortical amyloid burden, medial temporal lobe (MTL) neurodegeneration, and cognitive function in patients in the early stage of cognitive impairment.MethodsRest-activity patterns were assessed in 100 participants (70 with mild cognitive impairment and 30 with mild dementia) using wrist actigraphy. All participants underwent 18F-flutemetamol positron emission tomography (PET) imaging to quantify cortical amyloid burden, structural brain magnetic resonance imaging (MRI) to quantify MTL grey matter volume, neuropsychological testing, and clinical diagnosis. We used multiple linear regression models adjusted for covariates, including demographics, diabetes, hypertension, depressive symptom, psychotropic medication, sleep medication, weekend effect, and apolipoprotein-ε allele status.FindingsAfter adjusting for possible confounders, we found that the midline estimation of statistic of rhythm (MESOR) associated positively with frontal/executive function (estimate = 1.17, standard error [SE] = 0.37, p = 0.002). The least active 5-h (L5) onset time associated positively with MTL grey matter volume and memory function (estimate = 1.24, SE = 0.33, p = 0.001, and estimate = 3.77, SE = 1.22, p = 0.003, respectively), particularly in amyloid-negative participants. Additional path analysis revealed that MTL grey matter volume partially mediated the association between L5 onset time and memory function in amyloid-negative participants.InterpretationDecreased MESOR and advanced L5 onset time may be useful as early signs of cognitive decline or MTL neurodegeneration. Furthermore, amyloid pathology may act as a moderator of the relationships between rest-activity patterns, neurodegeneration, and cognitive function.FundingKorea Centres for Disease Control and Prevention (#4845–303); National Research Foundation of Korea (2019M3C7A1031905, 2019R1A5A2026045).

Functional Brain Network Connectivity Patterns Associated With Normal Cognition at Old-Age, Local β-amyloid, Tau, and APOE4

Background: Integrity of functional brain networks is closely associated with maintained cognitive performance at old age. Consistently, both carrier status of Apolipoprotein E ε4 allele (APOE4), and age-related aggregation of Alzheimer’s disease (AD) pathology result in altered brain network connectivity. The posterior cingulate and precuneus (PCP) is a node of particular interest due to its role in crucial memory processes. Moreover, the PCP is subject to the early aggregation of AD pathology. The current study aimed at characterizing brain network properties associated with unimpaired cognition in old aged adults. To determine the effects of age-related brain change and genetic risk for AD, pathological proteins β-amyloid and tau were measured by Positron-emission tomography (PET), PCP connectivity as a proxy of cognitive network integrity, and genetic risk by APOE4 carrier status.Methods: Fifty-seven cognitively unimpaired old-aged adults (MMSE = 29.20 ± 1.11; 73 ± 8.32 years) were administered 11C Pittsburgh Compound B and 18F Flutemetamol PET for assessing β-amyloid, and 18F AV-1451 PET for tau. Individual functional connectivity seed maps of the PCP were obtained by resting-state multiband BOLD functional MRI at 3-Tesla for increased temporal resolution. Voxelwise correlations between functional connectivity, β-amyloid- and tau-PET were explored by Biological Parametric Mapping (BPM).Results: Local β-amyloid was associated with increased connectivity in frontal and parietal regions of the brain. Tau was linked to increased connectivity in more spatially distributed clusters in frontal, parietal, occipital, temporal, and cerebellar regions. A positive interaction was observable for APOE4 carrier status and functional connectivity with brain regions characterized by increased local β-amyloid and tau tracer retention.Conclusions: Our data suggest an association between spatially differing connectivity systems and local β-amyloid, and tau aggregates in cognitively normal, old-aged adults, which is moderated by APOE4. Additional longitudinal studies may determine protective connectivity patterns associated with healthy aging trajectories of AD-pathology aggregation.

APOE4 moderates effects of cortical iron on synchronized default mode network activity in cognitively healthy old-aged adults.

IntroductionApolipoprotein E ε4 (APOE4)–related genetic risk for sporadic Alzheimer's disease is associated with an early impairment of cognitive brain networks. The current study determines relationships between APOE4 carrier status, cortical iron, and cortical network‐functionality.MethodsSixty‐nine cognitively healthy old‐aged individuals (mean age [SD] 66.1 [± 7.2] years; Mini‐Mental State Exam [MMSE] 29.3 ± 1.1) were genotyped for APOE4 carrier‐status and received 3 Tesla magnetic resonance imaging (MRI) for blood oxygen level–dependent functional magnetic resonance imaging (MRI) at rest, three‐dimensional (3D)–gradient echo (six echoes) for cortical gray‐matter, non‐heme iron by quantitative susceptibility mapping, and 18F‐flutemetamol positron emission tomography for amyloid‐βResultsA spatial pattern consistent with the default mode network (DMN) could be identified by independent component analysis. DMN activity was enhanced in APOE4 carriers and related to cortical iron burden. APOE4 and cortical iron synergistically interacted with DMN activity. Secondary analysis revealed a positive, APOE4 associated, relationship between cortical iron and DMN connectivity.DiscussionOur findings suggest that APOE4 moderates effects of iron on brain functionality prior to manifestation of cognitive impairment.

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

BackgroundAlzheimer’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.ObjectiveTo compare amyloid-β (Aβ) PET imaging with biomarkers in CSF and evaluate the prediction of Aβ PET on diagnosis in a memory clinic setting.MethodsWe 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.ResultsThirty-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.ConclusionsThe 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.

Topographical Heterogeneity of Alzheimer’s Disease Based on MR Imaging, Tau PET, and Amyloid PET

Alzheimer’s disease (AD) patients are known to have heterogeneous clinical presentation and pathologic patterns. We hypothesize that AD dementia can be categorized into subtypes based on multimodal imaging biomarkers such as magnetic resonance imaging (MRI), tau positron emission tomography (PET), and amyloid PET. We collected 3T MRI, 18F-THK5351 PET, and 18F-flutemetamol (FLUTE) PET data from 83 patients with AD dementia [Clinical Dementia Rating (CDR) ≤1] and 60 normal controls (NC), and applied surface-based analyses to measure cortical thickness, THK5351 standardized uptake value ratio (SUVR) and FLUTE SUVR for each participant. For the patient group, we performed an agglomerative hierarchical clustering analysis using the three multimodal imaging features on the vertices (n = 3 × 79,950). The identified AD subtypes were compared to NC using general linear models adjusting for age, sex, and years of education. We mapped the effect size within significant cortical regions reaching a corrected p-vertex <0.05 (random field theory). Our surface-based multimodal framework has revealed three distinct subtypes among AD patients: medial temporal-dominant subtype (MT, n = 44), parietal-dominant subtype (P, n = 19), and diffuse atrophy subtype (D, n = 20). The topography of cortical atrophy and THK5351 retention differentiates between the three subtypes. In the case of FLUTE, three subtypes did not show distinct topographical differences, although cortical composite retention was significantly higher in the P type than in the MT type. These three subtypes also differed in demographic and clinical features. In conclusion, AD patients may be clustered into three subtypes with distinct topographical features of cortical atrophy and tau deposition, although amyloid deposition may not differ across the subtypes in terms of topography.

DEVELOPMENT OF ALZHEIMER’S DISEASE BIOMARKER USING Aβ*56 SOLUBLE OLIGOMER IN HUMAN NASAL SECRETIONS

Although soluble Aβ oligomer (AβO) might play a pivotal role in pathogenesis of Alzheimer's disease (AD), development of biomarker using detection of AβO might be limited due to its structural heterogeneity. Recently, we found the 56kDa soluble Aβ*56(Aβ*56) which is known to be involved in a very early sate of AD in human nasal secretion. The aim of this study is to explore diagnostic validity of Aβ*56 in nasal secretions in discriminating AD pathology. A total of 60 patients (N=20 for normal control (NC), amnestic mild cognitive impairment (aMCI), and AD) were included in the study. They were dichotomized using 18F-Flutemetamol amyloid positron emission tomography (PET) into with and without detectable amyloid burden. Level of Aβ*56 in nasal secretions were measured using immune blotting. Group differences in nasal Aβ*56 level were analyzed and correlation between nasal Aβ*56 level and mean standardized uptake value ratio were also conducted. In addition, receiver operating characteristic (ROC) analysis was conducted to evaluate the sensitivity and specificity of the nasal Aβ*56 level to discriminate amyloid pathology. There were no group differences in age, gender, and education. The nasal Aβ*56 level were significantly higher in aMCI and AD than NC group, but no group differences were found between aMCI and dementia. The ROC analysis showed an AUC (area under curve) value of 0.92, sensitivity of 90% and specificity of 86% in discriminating Amyloid positivity. The nasal Aβ*56 level also had a positive correlation with cortical Aβ deposition on 18F-Flutemetamol PET.