Clinical Diagnosis Of Alzheimer's Disease Research Articles

How to Assess Executive Functions in a Low-Educated and Multicultural Population Using a Switching Verbal Fluency Test (the TFA-93) in Neurodegenerative Diseases?

Few neuropsychological tests are available to assess executive dysfunction in low-educated and multicultural populations. To address this issue, the TFA-93, a switching verbal fluency test to assess cognitive flexibility, was administered to 70 healthy controls, 57 patients with a clinical diagnosis of Alzheimer's disease, and 21 with a clinical diagnosis of a neurodegenerative disease associated with frontal disorders. Most of the participants were low-educated and nonnative French speakers. The TFA-93 comprises 2 categorical fluency tasks (animals and fruits) and a fluency task in which participants have to switch between animals and fruits. Correct responses and errors were collected, and a flexibility index expressed the switching cost. Results showed that correct responses were lower, and the switching cost was greater in both patient groups. In low-educated and multicultural populations, the TFA-93 seems to be a good alternative to assess flexibility compared to the standard neuropsychological tools based on academic abilities.

BRIDGING THE GAP BETWEEN NEUROLOGY AND PSYCHIATRY-ATYPICAL PRESENTATION OF COMMON NEURODEGENERATIVE DISORDERS: Session 418

It is increasingly recognized that there is significant heterogeneity in phenotype and clinical trajectories both in Alzheimer's as well as in Parkinson's disease. Up to 25% of Alzheimer's disease (AD) cases do not show the typical neuropathology. Recently subtypes and atypical non-amnestic AD presentations have been formalized in the International Working Group (IWG) clinical diagnosis criteria. Clinical diagnosis of atypical AD has significantly been improved by the availability of biomarkers, including cerebrospinal fluid levels of Aβ42, total tau (t-tau) and phosphorylated tau181 (p-tau), MRI volumetric estimation of hippocampal and medial temporal atrophy, and amyloid brain PET imaging. We will review the typical and atypical forms of AD from these varied perspectives to help improve diagnostic confidence among clinicians. Special attention will be given to language variant of Alzheimer's disease. A predominant deficit in the language domain is a key feature of primary progressive aphasia but language impairment is commonly present in Alzheimer's disease. International diagnostic criteria for PPA and its three variants (agrammatic, logopenic, semantic) were published relatively recently in 2011. Since then, studies have investigated the validity of these criteria in classifying patients which includes clinical symptoms, neurocognitive presentations, distinct MRI signatures, and neuropathological differences. In this session, we will review the subtypes of PPA using the above parameters to assist clinicians in diagnosis of these conditions. Special attention will be given of logopenic PPA a syndrome frequently seen in atypical Alzheimer's disease. Another common neurodegenerative disorder, Parkinson's disease (PD) conceptualized as predominantly movement disorder presents with myriad of atypical features predominantly psychiatric in nature. Psychosis is one of the most debilitating symptoms of PD, as it is an independent risk factor for nursing home placements, increased caregiver distress and mortality. Visual hallucinations are the most common psychotic manifestation in PD. Auditory, olfactory, tactile and gustatory hallucinations are infrequently found and usually coexist with visual ones. Delusions occur in about 5% of Parkinson's disease patients. Cognitive correlates of hallucinations and delusions appear to be different in PD. They may have distinct pathogenic mechanisms and possibly anatomical substrates. Global cognitive deficits including attention, frontal executive dysfunction, visuospatial abnormalities, language and verbal memory were associated with the presence of hallucinations in Parkinson's disease, but did not correlate with the presence of delusions. APOE and glucocerebrosidase gene (GBA) mutations and polymorphisms found to be associated with a distinct cognitive profile of changes characterized by greater impairment in working memory/executive function and visuospatial abilities in PD patients. During this session new findings on pathognomonic, cognitive and genetic correlates of psychosis in PD will be presented.

Brain iron is associated with accelerated cognitive decline in people with Alzheimer pathology.

Cortical iron has been shown to be elevated in Alzheimer’s disease (AD), but the impact of directly measured iron on the clinical syndrome has not been assessed. We investigated the association between post-mortem iron levels with the clinical and pathological diagnosis of AD, its severity, and the rate of cognitive decline in the 12 years prior to death in subjects from the Memory and Aging project (n=209). Iron was elevated (β[S.E.]=9.7 [2.6]; P=3.0×10−4) in the inferior temporal cortex only in subjects who were diagnosed with clinical AD during life and had a diagnosis of AD confirmed post mortem by standardized criteria. Whereas iron was weakly associated with the extent of proteinopathy in tissue with AD neuropathology, it was strongly associated with the rate of cognitive decline (e.g. Global Cognition: β[S.E.]=−0.040 [0.005], P=1.6 ×10−14). Thus, cortical iron might act to propel cognitive deterioration upon the underlying proteinopathy of AD, possibly by inducing oxidative stress or ferroptotic cell death, or may be related to an inflammatory response.

Validation of a prototype tau Thr231 phosphorylation CSF ELISA as a potential biomarker for Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by the presence of extracellular amyloid plaques (senile plaques) and intracellular neurofibrillary tangles formed by hyperphosphorylated tau protein. This process leads to neuronal degradation and neuronal death. Phosphorylation of tau protein at threonine 231 (p-tau231) has been shown to be characteristic in post-mortem brain tissue of patients with AD and it can be sensitively detected in cerebrospinal fluid (CSF). Therefore, it may serve as a biomarker to support the diagnosis of AD. In this study, we analysed how well p-tau231 could differentiate between patients suffering from dementia either due or not due to AD by a sandwich enzyme immunoassay. CSF p-tau231 was significantly higher in patients with dementia due to AD than in those with dementia due to other causes. In addition, we studied different factors affecting p-tau231 levels in CSF. We found that apolipoprotein E genotype influences p-tau231 CSF levels. Gender and age did not affect p-tau231 levels in CSF. Our findings indicate that p-tau231 levels in CSF can be a valuable marker for the clinical diagnosis of AD.

Role of surfacelet transform in diagnosing Alzheimer’s disease

The clinical diagnosis of Alzheimer’s disease (AD) is based on the tedious questionnaire and prolonged tests, which require involvement of the patient, his/her family, and the clinician. Ultimately, the success of subjective evaluation depends on the expertise of the clinician. To eradicate this subjectivity, the present work proposes a method to automate the diagnosis of AD. The proposed method represents complex brain structure of the subject (captured by MRI, a safe and non-invasive medical imaging modality) in terms of quantifiable features and then performs classification of normal and AD subjects. It does so in three phases: (1) MRI volume is normalized and the gray matter, which is the most affected tissue in AD is extracted from the regions of interest. (2) Surfacelet transform, a 3D multi-resolution transform that captures intricate directional details, is applied on the volume to extract features. The features are then reduced by selecting relevant and non-redundant features using a combination of Fisher discriminant ratio, and minimum redundancy and maximum relevance feature selection methods. (3) Based on these features, AD patients and normal subjects are classified using support vector machine classifier with 10 runs of 10 fold cross-validation. The performance of the method was computed using three measures (sensitivity, specificity, classification accuracy) on three datasets, constructed from the publically available database. It achieved 78.04%, 98.00% and 84.37% classification accuracies on the three datasets respectively. The effectiveness of the proposed method is validated by comparing it with other existing methods under identical experimental settings using the above three performance measures as well as receiver operating characteristic curves, ranking and statistical tests. Overall, it significantly outperformed the existing methods. It indicates that the proposed method has the potential to assist clinicians in the decision making for the diagnosis of AD.

Investigation of frailty as a moderator of the relationship between neuropathology and dementia in Alzheimer's disease: a cross-sectional analysis of data from the Rush Memory and Aging Project

Some people with substantial Alzheimer's disease pathology at autopsy had shown few characteristic clinical symptoms or signs of the disease, whereas others with little Alzheimer's disease pathology have been diagnosed with Alzheimer's dementia. We aimed to examine whether frailty, which is associated with both age and dementia, moderates the relationship between Alzheimer's disease pathology and Alzheimer's dementia. We did a cross-sectional analysis of data from participants of the Rush Memory and Aging Project, a clinical-pathological cohort study of older adults (older than 59 years) without known dementia at baseline, living in Illinois, USA. Participants in the cohort study underwent annual neuropsychological and clinical evaluations. In the present cross-sectional analysis, we included those participants who did not have any form of dementia or who had Alzheimer's dementia at the time of their last clinical assessment and who had died and for whom complete autopsy data were available. Alzheimer's disease pathology was quantified by a summary measure of neurofibrillary tangles and neuritic and diffuse plaques. Clinical diagnosis of Alzheimer's dementia was based on clinician consensus. Frailty was operationalised retrospectively using health variable information obtained at each clincial evaluation using the deficit accumulation approach (41-item frailty index). Logistic regression and moderation modelling were used to assess relationships between Alzheimer's disease pathology, frailty, and Alzheimer's dementia. All analyses were adjusted for age, sex, and education. Up to data cutoff (Jan 20, 2017), we included 456 participants (mean age at death 89·7 years [SD 6·1]; 316 [69%] women). 242 (53%) had a diagnosis of possible or probable Alzheimer's dementia at their last clinical assessment. Frailty (odds ratio 1·76, 95% CI 1·54-2·02; p<0·0001) and Alzheimer's disease pathology (4·81, 3·31-7·01; p<0·0001) were independently associated with Alzheimer's dementia, after adjusting for age, sex, and education. When frailty was added to the model for the relationship between Alzheimer's disease pathology and Alzheimer's dementia, model fit improved (p<0·0001). There was a significant interaction between frailty and Alzheimer's disease pathology (odds ratio 0·73, 95% CI 0·57-0·94; pinteraction=0·015). People with an increased frailty score had a weakened direct link between Alzheimer's disease pathology and Alzheimer's dementia; that is, people with a low amount of frailty were better able to tolerate Alzheimer's disease pathology, whereas those with higher amounts of frailty were more likely both to have more Alzheimer's disease pathology and for it to be expressed as dementia. The degree of frailty among people of the same age modifies the association between Alzheimer's disease pathology and Alzheimer's dementia. That frailty is related to both odds of Alzheimer's dementia and disease expression has implications for clinical management, since individuals with even a low level of Alzheimer's disease pathology might be at risk for dementia if they have high amounts of frailty. Further research should assess how frailty and cognition change over time to better elucidate this complex relationship. None.

Training recurrent neural networks robust to incomplete data: Application to Alzheimer's disease progression modeling.

Disease progression modeling (DPM) using longitudinal data is a challenging machine learning task. Existing DPM algorithms neglect temporal dependencies among measurements, make parametric assumptions about biomarker trajectories, do not model multiple biomarkers jointly, and need an alignment of subjects' trajectories. In this paper, recurrent neural networks (RNNs) are utilized to address these issues. However, in many cases, longitudinal cohorts contain incomplete data, which hinders the application of standard RNNs and requires a pre-processing step such as imputation of the missing values. Instead, we propose a generalized training rule for the most widely used RNN architecture, long short-term memory (LSTM) networks, that can handle both missing predictor and target values. The proposed LSTM algorithm is applied to model the progression of Alzheimer's disease (AD) using six volumetric magnetic resonance imaging (MRI) biomarkers, i.e., volumes of ventricles, hippocampus, whole brain, fusiform, middle temporal gyrus, and entorhinal cortex, and it is compared to standard LSTM networks with data imputation and a parametric, regression-based DPM method. The results show that the proposed algorithm achieves a significantly lower mean absolute error (MAE) than the alternatives with p < 0.05 using Wilcoxon signed rank test in predicting values of almost all of the MRI biomarkers. Moreover, a linear discriminant analysis (LDA) classifier applied to the predicted biomarker values produces a significantly larger area under the receiver operating characteristic curve (AUC) of 0.90 vs. at most 0.84 with p < 0.001 using McNemar's test for clinical diagnosis of AD. Inspection of MAE curves as a function of the amount of missing data reveals that the proposed LSTM algorithm achieves the best performance up until more than 74% missing values. Finally, it is illustrated how the method can successfully be applied to data with varying time intervals. This paper shows that built-in handling of missing values in training an LSTM network benefits the application of RNNs in neurodegenerative disease progression modeling in longitudinal cohorts.

Metabolite Profile of Alzheimer's Disease in the Frontal Cortex as Analyzed by HRMAS 1H NMR.

Background: Investigation on neurochemical changes in the frontal cortex in individuals with Alzheimer’s disease (AD) and different Apolipoprotein E (APOE) genotypes, using ex vivo solid-state high-resolution NMR analysis, may lead to a better understanding of the neurochemistry associated with AD as well as new AD-specific metabolite biomarkers that might potentially improve the clinical diagnosis of AD.Methods: Intact tissue samples of the frontal cortex were obtained from 11 patients and 11 age-matched non-demented controls. Metabolite profiles in all samples were analyzed ex vivo, using solid-state high-resolution magic angle spinning (HRMAS) 600 MHz 1H nuclear magnetic resonance (NMR). A logistic regression analysis was used to rank metabolites based on their level of contribution in differentiating the AD patient tissues and the controls, and different AD-associated APOE genotypes (APOE ε4 vs. APOE ε3).Results: Tissue samples from the AD patients showed significantly lower NAA/Cr (p = 0.011), Ace/Cr (p = 0.027), GABA/Cr (p = 0.005), Asp/Cr (p < 0.0001), mI/Cr (p < 0.0001), and Tau/Cr (p = 0.021), and higher PCho/Cr (p < 0.0001), GPCho/Cr (p < 0.0001), and α&β-Glc/Cr (p < 0.0001) than the controls did. Specifically, a newly observed resonance at 3.71 ppm, referred to as α&β-Glc, was observed in 90.9% of the AD samples (10/11). Samples with APOE ε4 also exhibited higher PCho/Cr (p = 0.0002), GPCho/Cr (p = 0.0001), α&β-Glc/Cr (p < 0.0001), and lower Asp/Cr (p = 0.004) and GABA/Cr (p = 0.04) than the samples with APOE ε3 did. In the logistic regression analysis, PCho, GPCho, ASP, and α&β-Glc were found to be the most relevant metabolites for differentiating the AD patient tissues and the controls, and different APOE genotypes.Conclusion: HRMAS 1H NMR with high spectral resolution and sensitivity offers a powerful tool to gain quantitative information on AD associated neurochemical changes. There are important neurochemical differences in the frontal cortex between the AD patient tissues and the controls, and between those with different APOE genotypes. The resonance (α&β-Glc) found at 3.71 ppm in the AD patient tissues may be further investigated for its potential in the diagnosis and monitoring of AD.

Neuropathology-driven Whole-genome Sequencing Study Points to Novel Candidate Genes for Healthy Brain Aging.

Understanding the healthy brain aging process is key to uncover the mechanisms that lead to pathologic age-related neurodegeneration, including progression to Alzheimer disease (AD). We aimed to address the issue of pathologic heterogeneity that often underlies a clinical AD diagnosis. We performed a deep whole-genome sequencing study aiming to identify variants that are associated specifically with healthy brain aging. We examined samples from the community-based longitudinal Vienna Transdanubian Aging study comparing neuropathologically "healthy" aging in individuals above 80 years of age with pure AD patients of the same age. Focusing on potentially functional variants, we discovered a single variant (rs10149146) that lies on the autophagy-associated TECPR2 gene and was carried by 53.6% of the "healthy" brain elderly individuals (15/28). An additional nonsynonymous variant on the CINP gene (encoding a cell cycle checkpoint protein) was also found in 46% of healthy controls. Both variants are absent from all AD cases. TECPR2 and CINP appear to be "partner" genes in terms of regulation and their associated transcription factors have been previously implicated in AD and neurodegeneration. Our study underlines the strength of neuropathology-driven definitions in genetic association studies and points to a potentially neuroprotective effect of key molecules of autophagy and cell cycle control.

79. Amyloid-PET analysis based on tissue probability maps

Purpose The regional quantification of amyloid burden is crucial for the clinical diagnosis of Alzheimer’s disease [1]. The best method to evaluate regional amyloid deposition in PET is through the use MR imaging for brain space normalization. However, since MR imaging is not always available in the clinical practice, a MR-less methodology is needed in order to compute semi-quantitative and analyze regional amyloid burden. Methods Forty-four patients with clinical evidence of dementia, underwent 18F-Florbetaben PET (FBB-PET), FDG-PET, neuropsychological assessment and cerebrospinal fluid analysis. We implemented a methodology that uses SPM12 to import and normalize the FBB-PET images in Montreal Neurological Institute (MNI) space without MRI, and the Automated Anatomical Labeling (AAL) atlas [2] in order to extract regional uptake from normalized FBB-PET. SUVR has been computed by using cerebellum as control region (‘ Cerebelum _ 4 _ 5 ’ of AAL atlas). We then computed Receiver Operating Characteristic (ROC) curve in order to find best thresholds for identifying clinical subgroups in our patients. Results Semi-quantitative evaluation of FBB-PET images and ROC analysis stated that SUVR value of 1,006 in the bilateral inferior frontal cortex and a SUVR of 1.03 in the precuneus region were the best cutoff (AUC 0.883 and 0.826, respectively). Box-Plot analysis showed a trend distribution of elevated SUVR levels in bilateral frontal cortex, angular girus, occipital, parietal, precuneus and paracentral lobule, among AD patients. Conclusion MR-less methodology based on Tissue Probability Map and AAL atlas provide regional quantification of amyloid burden. The ROC analysis is able to retrieve useful thresholds for the classification of AD versus non-AD thus providing a tool in clinical practice. We will perform the study on a larger sample in order to confirm the results.

Clinical-Neuropathological Correlations of Alzheimer's Disease and Related Dementias in Latino Volunteers.

Clinical, neuropsychological, and neurological procedures used to diagnose Alzheimer's disease (AD) and related dementias were largely developed and validated in well-educated, non-Latino, English-speaking populations. Sociocultural and genetic differences in Latinos might influence the accuracy of clinical diagnosis of AD and other dementias. We aim to compare the accuracy of the clinical diagnosis of AD and related dementias in Latinos with the corresponding neuropathological diagnosis. From the UCSD Alzheimer's Disease Research Center longitudinal cohort, we selected all Latino participants who had autopsy neuropathological studies from 1991 to 2017. Participants underwent annual neurological clinical evaluations, standard neuropsychological tests, neuroimaging, and genotyping of Apolipoprotein E. We calculated the sensitivity and specificity of the clinical diagnosis of AD against the primary pathological diagnosis. Of the 34 participants with a primary neuropathological diagnosis of AD, 33 (97.1%) were correctly clinically diagnosed as having AD at the last clinical evaluation, and 1 was incorrectly diagnosed with dementia with Lewy bodies. Of the 19 participants without a primary neuropathological diagnosis of AD, 8 were incorrectly clinically diagnosed with probable AD at the last clinic evaluation. The clinical diagnosis of AD at the last clinical evaluation had 97.1% sensitivity and 57.9% specificity for autopsy-verified AD. In this Latino cohort, clinicians predicted AD pathological findings with high sensitivity but moderate specificity. Tangle-only dementia was the most common misdiagnosis. Our study suggests that current procedures and instruments to clinically determine AD in Latinos have high sensitivity compared with neuropathology, but specificity needs to be improved.

A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18F-FDG PET of the Brain.

Purpose To develop and validate a deep learning algorithm that predicts the final diagnosis of Alzheimer disease (AD), mild cognitive impairment, or neither at fluorine 18 (18F) fluorodeoxyglucose (FDG) PET of the brain and compare its performance to that of radiologic readers. Materials and Methods Prospective 18F-FDG PET brain images from the Alzheimer's Disease Neuroimaging Initiative (ADNI) (2109 imaging studies from 2005 to 2017, 1002 patients) and retrospective independent test set (40 imaging studies from 2006 to 2016, 40 patients) were collected. Final clinical diagnosis at follow-up was recorded. Convolutional neural network of InceptionV3 architecture was trained on 90% of ADNI data set and tested on the remaining 10%, as well as the independent test set, with performance compared to radiologic readers. Model was analyzed with sensitivity, specificity, receiver operating characteristic (ROC), saliency map, and t-distributed stochastic neighbor embedding. Results The algorithm achieved area under the ROC curve of 0.98 (95% confidence interval: 0.94, 1.00) when evaluated on predicting the final clinical diagnosis of AD in the independent test set (82% specificity at 100% sensitivity), an average of 75.8 months prior to the final diagnosis, which in ROC space outperformed reader performance (57% [four of seven] sensitivity, 91% [30 of 33] specificity; P < .05). Saliency map demonstrated attention to known areas of interest but with focus on the entire brain. Conclusion By using fluorine 18 fluorodeoxyglucose PET of the brain, a deep learning algorithm developed for early prediction of Alzheimer disease achieved 82% specificity at 100% sensitivity, an average of 75.8 months prior to the final diagnosis. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Larvie in this issue.

Cerebrospinal Fluid Biomarkers in Patients with Frontotemporal Dementia Spectrum: A Single-Center Study.

Cerebrospinal fluid (CSF) neurofilament light chain protein (NfL) and Alzheimer's disease (AD) core biomarker levels have been evaluated in cohorts of patients with frontotemporal dementia spectrum (FTD), but the distribution of values across the different clinical syndromes and underlying proteinopathies, and the relative diagnostic accuracy appear discordant among studies. We measured CSF NfL, total (t)-tau, phosphorylated (p)-tau, and amyloid-β (Aβ)42 in healthy controls (n = 38) and subjects with a clinical, genetic, CSF biomarker-based, and/or neuropathological diagnosis of FTD (n = 141) or AD (n = 60). Sub-analyses were conducted in a proportion of subjects with definite and/or probable frontotemporal lobar degeneration with tau (FTLD-TAU) (n = 42) or TDP43 pathology (FTLD-TDP) (n = 36). Both FTD and AD groups showed significantly increased CSF NfL levels in comparison to controls (p < 0.001). CSF NfL levels were significantly higher in FTD patients than in AD (p < 0.001), reaching the highest values in amyotrophic lateral sclerosis associated with FTD. Patients with probable and definite FTLD-TDP had significantly higher NfL levels (p < 0.001) and lower p-tau/t-tau values (p < 0.001) in comparison with probable and definite FTLD-TAU cases. NfL showed good diagnostic accuracy in the distinction between FTD and controls (AUC 0.862±0.027) and yielded an accuracy (AUC 0.861±0.045) comparable to that of the p-tau/t-tau ratio (AUC 0.814±0.050), with 80.0% sensitivity and 81.0% specificity, in the discrimination between probable/definite FTLD-TAU and FTLD-TDP. Our data further validate CSF NfL as a surrogate biomarker of neurodegeneration and disease severity in patients with FTD spectrum. Moreover, they demonstrate a good diagnostic value for NfL and p-tau/t-tau ratio in the discrimination between FTLD-TAU and FTLD-TDP.

Reappraisal of Aβ40 and Aβ42 Peptides Measurements in Cerebrospinal Fluid of Patients with Alzheimer's Disease.

Cerebrospinal fluid (CSF) biomarkers are currently included in the diagnostic criteria for Alzheimer's disease (AD), in particular, decreased concentrations of amyloid-β peptide 1-42 (Aβ42) in the CSF, coupled with increased levels of tau and phosphorylated tau proteins, are supportive of AD diagnosis. To date, the quantification of Aβ42 levels with antibody-dependent immunoassay shows a marked variability among different laboratories and is also affected by different pre-analytical factors, suggesting that part of Aβ42 peptides might be aggregated and thus undetected by antibodies. To bypass an antibody-dependent measurement, we determined the Aβ40 and Aβ42 levels by immunoblot. We analyzed CSF samples from 35 patients with clinical diagnosis of probable AD and from 15 age-matched normal controls; CSF Aβ levels were determined by two different ELISA kits and by immunoblot analysis. Aβ40 levels measured by ELISA were comparable to those obtained by immunoblot, whereas CSF concentrations of Aβ42 measured by ELISA were significantly lower compared to values obtained by immunoblot quantification. Biochemical analysis, following 1D- and 2D-PAGE analysis, showed that the qualitative composition of Aβ peptides in the CSF is similar in AD and controls but different from that of AD brain tissues. Moreover, sedimentation velocity in sucrose gradient of CSF and brain homogenate from AD demonstrated that Aβ42 in CSF is different from Aβ42 in brain in terms of solubility and aggregation state.

An MRI measure of degenerative and cerebrovascular pathology in Alzheimer disease.

To develop, replicate, and validate an MRI-based quantitative measure of both cerebrovascular and neurodegeneration in Alzheimer disease (AD) for clinical and potentially research purposes. We used data from a cross-sectional and longitudinal community-based study of Medicare-eligible residents in northern Manhattan followed every 18-24 months (n = 1,175, mean age 78 years). White matter hyperintensities, infarcts, hippocampal volumes, and cortical thicknesses were quantified from MRI and combined to generate an MRI measure associated with episodic memory. The combined MRI measure was replicated and validated using autopsy data, clinical diagnoses, and CSF biomarkers and amyloid PET from the Alzheimer's Disease Neuroimaging Initiative. The quantitative MRI measure was developed in a group of community participants (n = 690) and replicated in a similar second group (n = 485). Compared with healthy controls, the quantitative MRI measure was lower in patients with mild cognitive impairment and lower still in those with clinically diagnosed AD. The quantitative MRI measure correlated with neurofibrillary tangles, neuronal loss, atrophy, and infarcts at postmortem in an autopsy subset and was also associated with PET amyloid imaging and CSF levels of total tau, phosphorylated tau, and β-amyloid 42. The MRI measure predicted conversion to MCI and clinical AD among healthy controls. We developed, replicated, and validated an MRI measure of cerebrovascular and neurodegenerative pathologies that are associated with clinical and neuropathologic diagnosis of AD and related to established biomarkers.

Standardization of hippocampus volumetry using automated brain structure volumetry tool for an initial Alzheimer's disease imaging biomarker.

One significant barrier to incorporate Alzheimer's disease (AD) imaging biomarkers into diagnostic criteria is the lack of standardized methods for biomarker quantification. The European Alzheimer's Disease Consortium-Alzheimer's Disease Neuroimaging Initiative (EADC-ADNI) Harmonization Protocol project provides the most authoritative guideline for hippocampal definition and has produced a manually segmented reference dataset for validation of automated methods. To validate automated hippocampal volumetry using AccuBrain™, against the EADC-ADNI dataset, and assess its diagnostic performance for differentiating AD and normal aging in an independent cohort. The EADC-ADNI reference dataset comprise of manually segmented hippocampal labels from 135 volumetric T1-weighted scans from various scanners. Dice similarity coefficient (DSC), intraclass correlation coefficient (ICC), and Pearson's r were obtained for AccuBrain™ and FreeSurfer. The magnetic resonance imaging (MRI) of a separate cohort of 299 individuals (150 normal controls, 149 with AD) were obtained from the ADNI database and processed with AccuBrain™ to assess its diagnostic accuracy. Area under the curve (AUC) for total hippocampal volumes (HV) and hippocampal fraction (HF) were determined. Compared with EADC-ADNI dataset ground truths, AccuBrain™ had a mean DSC of 0.89/0.89/0.89, ICC of 0.94/0.96/0.95, and r of 0.95/0.96/0.95 for right/left/total HV. AccuBrain™ HV and HF had AUC of 0.76 and 0.80, respectively. Thresholds of ≤ 5.71 mL and ≤ 0.38% afforded 80% sensitivity for AD detection. AccuBrain™ provides accurate automated hippocampus segmentation in accordance with the EADC-ADNI standard, with great potential value in assisting clinical diagnosis of AD.

EVALUATION OF [F-18]-PI-2620, A SECOND-GENERATION SELECTIVE TAU TRACER, FOR THE ASSESSMENT OF ALZHEIMER’S AND NON-ALZHEIMER’S TAUOPATHIES

Most first-generation tau tracers bind to the typical 3R/4R tau deposits prevalent in Alzheimer's disease (AD). These first-generation tau tracers have varying degrees of “off-target” binding or lack of selectivity for tau. The new tau tracer, 18F-PI-2620 appears unique in that it binds to all types (3R, 4R and 3R/4R) of tau deposits in vitro. The purpose of the study was to assess the ability of 18F-PI-2620 to detect and measure global and regional tau burden in the brain in healthy older controls, AD and non-AD tauopathies such as Progressive Supranuclear Palsy (PSP) and Frontotemporal Lobar Degeneration (FTLD). Participants with clinical diagnosis of probable AD, PSP, FTLD as well as healthy age-matched controls (HC) and participants classified as suffering mild cognitive impairment (MCI), underwent a 50-70 min static scan with 18F-NAV4694 to establish Aβ-status (Aβ-/Aβ+), and 0-120 min dynamic tau imaging with 18F-PI-2620. Global and regional 18F-PI-2620 binding was assessed using Distribution Volume Ratios (DVR), and with standardized uptake value ratios (SUVR), calculated using the cerebellar cortex as reference region. No tracer retention was observed in Aβ-HC. No “off-target” binding in choroid plexus or basal ganglia was observed in any of the participants scanned. In Aβ+AD patients 18F-PI-2620 binding was significantly higher than in HC, with the highest tracer retention in temporoparietal and posterior cingulate areas (Figure 1A). Tracer presented reversible kinetics and apparent steady state was reached ∼80-90 min after 18F-PI-2620 injection (Figure 1B). There was high agreement between regional DVRCbCtx and SUVRCbCtx. Identical classification into tau-/tau+ resulted from semiquantitative measures and visual inspection of the images

Identifying Patterns in Signs and Symptoms Preceding the Clinical Diagnosis of Alzheimer's Disease: Retrospective Medical Record Review Study and a Nested Case-control Design.

Evidence suggests that individuals with Alzheimer's disease (AD) are often diagnosed in the later stages of their disease with a poor prognosis. This study is aimed to identify patterns in signs and symptoms preceding the clinical diagnosis of AD to suggest a predictive model for earlier diagnosis of the disease in the primary care. A retrospective medical record review; nested case control design. Participants included one hundred and nine patients from three general practice (GP) surgeries in Milton Keynes and Luton Clinical Commissioning Groups (CCG) (37 cases with AD and 72 controls without AD). A retrospective analysis using the logistic regression of the presence of signs and symptoms before the diagnosis of AD was attained. Identification of the timing and sequence of appearance of these presentations as first reported before the clinical diagnosis was measured. Episodic memory with an odds ratio of 1.85 was the most frequent presentation, documented in 1.38% of the controls and 75.6% in cases. Auditory disturbance with an odds ratio of 3.03, which has not previously been noted except in the form of auditory hallucination, could have a diagnostic value. Auditory disturbance, which occurred mostly in the Caucasian females, could discriminate individuals with AD from those without the disease. The symptom, which presented up to 14.5 (mean time) years prior to clinical diagnosis, was identified in Caucasians and mixed race individuals only. The study demonstrates that auditory disturbance could allow an earlier diagnosis of AD in Caucasian females. Episodic memory was confirmed as being frequently noted in AD patients prior to a clinical diagnosis as per previous publications. This study supports the development of a scoring system for the earlier diagnosis of AD. The data used was free from the confounding effects of misinformation, as this was written at the point of collection, thereby benefitting from the use of GP data that is diversified, reliable and valid. Limited sample size that will not allow for generalization of less frequent observations due to their low prevalence in case notes. Randomisation was not achieved; however, the best available nonrandomisation which is consecutive sampling was used. Patterns identified were in LOAD, the baseline could vary with other geographical areas.

Identifying signs and symptoms preceding the diagnosis of Alzheimer’s Disease: a retrospective medical record review

BackgroundEarly diagnosis of Alzheimer’s disease (AD) is beneficial as interventions work well at this stage.AimThe study sought to identify patterns in signs and symptoms as reported by patients, 10 years preceding the clinical diagnosis of AD and suggest a predictive model for the early detection of the disease.MethodA retrospective medical record review and nested case-control design were carried out on the charts of 109 individuals (37 cases and 72 in the control group) in three GP surgeries in Milton Keynes and Luton, diagnosed between the year 2006–2016. Data extracted included the demographic and clinical data (signs and symptoms preceding the diagnosis of the disease). Logistic regression and correlation coefficient was used for analysis of variables to identify patterns.ResultsAuditory disturbances (tinnitus), a symptom that has not been reported in AD, could have a diagnostic value with 3.03 increased odds for associating with AD and a P-value of ≤0.05; the symptom was presented with a mean age of 14.5 years before the clinical diagnosis of the disease. There was a positive correlation between auditory disturbance and AD; episodic memory and AD; the female gender and AD all at 1% level (2tailed).ConclusionAuditory disturbance in the form of tinnitus has not been fully investigated in AD apart from auditory hallucinations and, as this symptom has been associated with other conditions. While further research is advocated in a large scale due to the insufficiency of the sample to initiate subgroup analysis, the result suggests that auditory disturbance could be a confounding factor to support future plans to improve the early diagnosis of AD.

Antibody-Based In Vivo PET Imaging Detects Amyloid-β Reduction in Alzheimer Transgenic Mice After BACE-1 Inhibition.

Visualization of amyloid-β (Aβ) pathology with PET has become an important tool for making a specific clinical diagnosis of Alzheimer disease (AD). However, the available amyloid PET radioligands, such as 11C-Pittsburgh compound B, reflect levels of insoluble Aβ plaques but do not capture soluble and protofibrillar Aβ forms. Furthermore, the plaque load appears to be fairly static during clinical stages of AD and may not be affected by Aβ-reducing treatments. The aim of the present study was to investigate whether a novel PET radioligand based on an antibody directed toward soluble aggregates of Aβ can be used to detect changes in Aβ levels during disease progression and after treatment with a β-secretase (BACE-1) inhibitor. Methods: One set of transgenic mice (tg-ArcSwe, a model of Aβ pathology) aged between 7 and 16 mo underwent PET with the Aβ protofibril–selective radioligand 124I-RmAb158-scFv8D3 (where RmAb is recombinant mouse monoclonal antibody and scFv is single-chain variable fragment) to follow progression of Aβ pathology in the brain. A second set of tg-ArcSwe mice, aged 10 mo, were treated with the BACE-1 inhibitor NB-360 for 3 mo and compared with an untreated control group. A third set of tg-ArcSwe mice, also aged 10 mo, underwent PET as a baseline group. Brain tissue was isolated after PET to determine levels of Aβ by ELISA and immunohistochemistry. Results: The concentration of 124I-RmAb158-scFv8D3, as measured in vivo with PET, increased with age and corresponded well with the ex vivo autoradiography and Aβ immunohistochemistry results. Mice treated with NB-360 showed significantly lower in vivo PET signals than untreated animals and were similar to the baseline animals. The decreased 124I-RmAb158-scFv8D3 concentrations in NB-360–treated mice, as quantified with PET, corresponded well with the decreased Aβ levels measured in postmortem brain. Conclusion: Several treatments for AD are in phase 2 and 3 clinical trials, but the possibility of studying treatment effects in vivo on the important, nonfibrillar, forms of Aβ is limited. This study demonstrated the ability of the Aβ protofibril–selective radioligand 124I-RmAb158-scFv8D3 to follow disease progression and detect treatment effects with PET imaging in tg-ArcSwe mice.