Impairment of neocortical metabolism predicts progression in Alzheimer's disease

Measurement of neurodegeneration using a multivariate early frame amyloid PET classifier

Introduction

Amyloid measurement provides important confirmation of pathology for Alzheimer's disease (AD) clinical trials. However, many amyloid positive (Am+) early-stage subjects do not worsen clinically during a clinical trial, and a neurodegenerative measure predictive of decline could provide critical information. Studies have shown correspondence between perfusion measured by early amyloid frames post-tracer injection and fluorodeoxyglucose (FDG) positron emission tomography (PET), but with limitations in sensitivity. Multivariate machine learning approaches may offer a more sensitive means for detection of disease related changes as we have demonstrated with FDG.

Methods

Using summed dynamic florbetapir image frames acquired during the first 6 minutes post-injection for 107 Alzheimer's Disease Neuroimaging Initiative subjects, we applied optimized machine learning to develop and test image classifiers aimed at measuring AD progression. Early frame amyloid (EFA) classification was compared to that of an independently developed FDG PET AD progression classifier by scoring the FDG scans of the same subjects at the same time point. Score distributions and correlation with clinical endpoints were compared to those obtained from FDG. Region of interest measures were compared between EFA and FDG to further understand discrimination performance.

Results

The EFA classifier produced a primary pattern similar to that of the FDG classifier whose expression correlated highly with the FDG pattern (R-squared 0.71), discriminated cognitively normal (NL) amyloid negative (Am-) subjects from all Am+ groups, and that correlated in Am+ subjects with Mini-Mental State Examination, Clinical Dementia Rating Sum of Boxes, and Alzheimer's Disease Assessment Scale-13-item Cognitive subscale (R = 0.59, 0.63, 0.73) and with subsequent 24-month changes in these measures (R = 0.67, 0.73, 0.50).

Discussion

Our results support the ability to use EFA with a multivariate machine learning-derived classifier to obtain a sensitive measure of AD-related loss in neuronal function that correlates with FDG PET in preclinical and early prodromal stages as well as in late mild cognitive impairment and dementia.

Highlights

The summed initial post-injection minutes of florbetapir positron emission tomography  correlate with fluorodeoxyglucose.A machine learning classifier enabled sensitive detection of early prodromal Alzheimer's disease.Early frame amyloid (EFA) classifier scores correlate with subsequent change in Mini-Mental State Examination, Clinical Dementia Rating Sum of Boxes, and Alzheimer's Disease Assessment Scale-13-item Cognitive subscale.EFA classifier effect sizes and clinical prediction outperformed region of interest standardized uptake value ratio.EFA classification may aid in stratifying patients to assess treatment effect.

Primitive detection of Alzheimer’s disease using neuroimaging: A progression model for Alzheimer’s disease: Their applications, benefits, and drawbacks

Alzheimer’s disease (A.D.) is the most widespread type of Dementia, and it is not a curable neurodegenerative disease that affects millions of older people. Researchers were able to use their understanding of Alzheimer’s disease risk variables to develop enrichment processes for longitudinal imaging studies. Using this method, they reduced their sample size and study time. This paper describes the primitive detective of Alzheimer’s diseases using Neuroimaging techniques. Several preprocessing methods were used to ensure that the dataset was ready for subsequent feature extraction and categorization. The noise was reduced by converting and averaging many scan frames from real to DCT space. Both sides of the averaged image were filtered and combined into a single shot after being converted to real space. InceptionV3 and DenseNet201 are two pre-trained models used in the suggested model. The PCA approach was used to select the traits, and the resulting explained variance ratio was 0.99The Simons Foundation Autism Research Initiative (SFARI)—Simon’s Simplex Collection (SSC)—and UCI machine learning datasets showed that our method is faster and more successful at identifying complete long-risk patterns when compared to existing methods.

FDG PET Data is Associated with Cognitive Performance in Patients from a Memory Clinic

BACKGROUND

Various reasons may lead to cognitive symptoms in elderly, including the development of cognitive decline and dementia. Often, mixed pathologies such as neurodegeneration and cerebrovascular disease co-exist in these patients. Diagnostic work-up commonly includes imaging modalities such as FDG PET, MRI, and CT, each delivering specific information.

OBJECTIVE

To study the informative value of neuroimaging-based data supposed to reflect neurodegeneration (FDG PET), cerebral small vessel disease (MRI), and cerebral large vessel atherosclerosis (CT) with regard to cognitive performance in patients presenting to our memory clinic.

METHODS

Non-parametric partial correlations and an ordinal logistic regression model were run to determine relationships between scores for cortical hypometabolism, white matter hyperintensities, calcified plaque burden, and results from Mini-Mental State Examination (MMSE). The final study group consisted of 162 patients (female: 94; MMSE: 6-30).

RESULTS

Only FDG PET data was linked to and predicted cognitive performance (r(157) = -0.388, p < 0.001). Overall, parameters linked to cerebral small and large vessel disease showed no significant association with cognition. Further findings demonstrated a relationship between white matter hyperintensities and FDG PET data (r(157) = 0.230, p = 0.004).

CONCLUSION

Only FDG PET imaging mirrors cognitive performance, presumably due to the examination's ability to reflect neurodegeneration and vascular dysfunction, thus capturing a broader spectrum of pathologies. This makes the examination a useful imaging-based diagnostic tool in the work-up of patients presenting to a memory clinic. Parameters of vascular dysfunction alone as depicted by conventional MRI and CT are less adequate in such a situation, most likely because they reflect one pathology complex only.

Neuroimaging in aging and neurologic diseases

Neuroimaging biomarkers for neurologic diseases are important tools, both for understanding pathology associated with cognitive and clinical symptoms and for differential diagnosis. This chapter explores neuroimaging measures, including structural and functional measures from magnetic resonance imaging (MRI) and molecular measures primarily from positron emission tomography (PET), in healthy aging adults and in a number of neurologic diseases. The spectrum covers neuroimaging measures from normal aging to a variety of dementias: late-onset Alzheimer's disease [AD; including mild cognitive impairment (MCI)], familial and nonfamilial early-onset AD, atypical AD syndromes, posterior cortical atrophy (PCA), logopenic aphasia (lvPPA), cerebral amyloid angiopathy (CAA), vascular dementia (VaD), sporadic and familial behavioral-variant frontotemporal dementia (bvFTD), semantic dementia (SD), progressive nonfluent aphasia (PNFA), frontotemporal dementia with motor neuron disease (FTD-MND), frontotemporal dementia with amyotrophic lateral sclerosis (FTD-ALS), corticobasal degeneration (CBD), progressive supranuclear palsy (PSP), dementia with Lewy bodies (DLB), Parkinson's disease (PD) with and without dementia, and multiple systems atrophy (MSA). We also include a discussion of the appropriate use criteria (AUC) for amyloid imaging and conclude with a discussion of differential diagnosis of neurologic dementia disorders in the context of neuroimaging.

Alzheimer's disease: 3-Dimensional MRI texture for prediction of conversion from mild cognitive impairment

INTRODUCTION

Currently, there are no tools that can accurately predict which patients with mild cognitive impairment (MCI) will progress to Alzheimer's disease (AD). Texture analysis uses image processing and statistical methods to identify patterns in voxel intensities that cannot be appreciated by visual inspection. Our main objective was to determine whether MRI texture could be used to predict conversion of MCI to AD.

METHODS

A method of 3-dimensional, whole-brain texture analysis was used to compute texture features from T1-weighted MR images. To assess predictive value, texture changes were compared between MCI converters and nonconverters over a 3-year observation period. A predictive model using texture and clinical factors was used to predict conversion of patients with MCI to AD. This model was then tested on ten randomly selected test groups from the data set.

RESULTS

Texture features were found to be significantly different between normal controls (n = 225), patients with MCI (n = 382), and patients with AD (n = 183). A subset of the patients with MCI were used to compare between MCI converters (n = 98) and nonconverters (n = 106). A composite model including texture features, APOE-ε4 genotype, Mini-Mental Status Examination score, sex, and hippocampal occupancy resulted in an area under curve of 0.905. Application of the composite model to ten randomly selected test groups (nonconverters = 26, converters = 24) predicted MCI conversion with a mean accuracy of 76.2%.

DISCUSSION

Early texture changes are detected in patients with MCI who eventually progress to AD dementia. Therefore, whole-brain 3D texture analysis has the potential to predict progression of patients with MCI to AD.

The Role of Neuroimaging in the Assessment of the Cognitively Impaired Elderly

This article reviews the current diagnostic tools that are available for structural, functional, and molecular imaging of the brain, summarizing some of the key findings that have been reported in individuals diagnosed with Alzheimer disease, mild cognitive impairment, prodromal AD, or other prevalent dementias. Given recent advances in the development of amyloid PET tracers, current guidelines for the use of amyloid PET imaging in patients with cognitive complaints are reviewed. In addition, data addressing the potential value of amyloid PET imaging in the clinical setting are highlighted.

Imaging Alzheimer's disease pathophysiology with PET

Alzheimer's disease (AD) has been reconceptualised as a dynamic pathophysiological process characterized by preclinical, mild cognitive impairment (MCI), and dementia stages. Positron emission tomography (PET) associated with various molecular imaging agents reveals numerous aspects of dementia pathophysiology, such as brain amyloidosis, tau accumulation, neuroreceptor changes, metabolism abnormalities and neuroinflammation in dementia patients. In the context of a growing shift toward presymptomatic early diagnosis and disease-modifying interventions, PET molecular imaging agents provide an unprecedented means of quantifying the AD pathophysiological process, monitoring disease progression, ascertaining whether therapies engage their respective brain molecular targets, as well as quantifying pharmacological responses. In the present study, we highlight the most important contributions of PET in describing brain molecular abnormalities in AD.

Biochemical and Radiological Markers of Alzheimer's Disease Progression

Alzheimer's disease (AD) is a neurodegenerative, inevitably progressive disease with a rate of cognitive, functional, and behavioral decline that varies highly from patient to patient. Although several clinical predictors of AD progression have been identified, to our mind in clinical practice there is a lack of a reliable biomarker that enables one to stratify the risk of deterioration. Identification of biomarkers that allow the monitoring of AD progression could change the way physicians and caregivers make treatment decisions. This review summarizes the results of studies on potential biochemical and radiological markers related to AD progression.

¹⁸F-FDG PET for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI)

BACKGROUND

¹⁸F-FDFG uptake by brain tissue as measured by positron emission tomography (PET) is a well-established method for assessment of brain function in people with dementia. Certain findings on brain PET scans can potentially predict the decline of mild cognitive Impairment (MCI) to Alzheimer's disease dementia or other dementias.

OBJECTIVES

To determine the diagnostic accuracy of the ¹⁸F-FDG PET index test for detecting people with MCI at baseline who would clinically convert to Alzheimer's disease dementia or other forms of dementia at follow-up.

SEARCH METHODS

We searched the Cochrane Register of Diagnostic Test Accuracy Studies, MEDLINE, EMBASE, Science Citation Index, PsycINFO, BIOSIS previews, LILACS, MEDION, (Meta-analyses van Diagnostisch Onderzoek), DARE (Database of Abstracts of Reviews of Effects), HTA (Health Technology Assessment Database), ARIF (Aggressive Research Intelligence Facility) and C-EBLM (International Federation of Clinical Chemistry and Laboratory Medicine Committee for Evidence-based Laboratory Medicine) databases to January 2013. We checked the reference lists of any relevant studies and systematic reviews for additional studies.

SELECTION CRITERIA

We included studies that evaluated the diagnostic accuracy of ¹⁸F-FDG PET to determine the conversion from MCI to Alzheimer's disease dementia or to other forms of dementia, i.e. any or all of vascular dementia, dementia with Lewy bodies, and fronto-temporal dementia. These studies necessarily employ delayed verification of conversion to dementia and are sometimes labelled as 'delayed verification cross-sectional studies'.

DATA COLLECTION AND ANALYSIS

Two blinded review authors independently extracted data, resolving disagreement by discussion, with the option to involve a third review author as arbiter if necessary. We extracted and summarised graphically the data for two-by-two tables. We conducted exploratory analyses by plotting estimates of sensitivity and specificity from each study on forest plots and in receiver operating characteristic (ROC) space. When studies had mixed thresholds, we derived estimates of sensitivity and likelihood ratios at fixed values (lower quartile, median and upper quartile) of specificity from the hierarchical summary ROC (HSROC) models.

MAIN RESULTS

We included 14 studies (421 participants) in the analysis. The sensitivities for conversion from MCI to Alzheimer's disease dementia were between 25% and 100% while the specificities were between 15% and 100%. From the summary ROC curve we fitted we estimated that the sensitivity was 76% (95% confidence interval (CI): 53.8 to 89.7) at the included study median specificity of 82%. This equates to a positive likelihood ratio of 4.03 (95% CI: 2.97 to 5.47), and a negative likelihood ratio of 0.34 (95% CI: 0.15 to 0.75). Three studies recruited participants from the same Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort but only the largest ADNI study (Herholz 2011) is included in the meta-analysis. In order to demonstrate whether the choice of ADNI study or discriminating brain region (Chételat 2003) or reader assessment (Pardo 2010) make a difference to the pooled estimate, we performed five additional analyses. At the median specificity of 82%, the estimated sensitivity was between 74% and 76%. There was no impact on our findings. In addition to evaluating Alzheimer's disease dementia, five studies evaluated the accuracy of ¹⁸F-FDG PET for all types of dementia. The sensitivities were between 46% and 95% while the specificities were between 29% and 100%; however, we did not conduct a meta-analysis because of too few studies, and those studies which we had found recruited small numbers of participants. Our findings are based on studies with poor reporting, and the majority of included studies had an unclear risk of bias, mainly for the reference standard and participant selection domains. According to the assessment of Index test domain, more than 50% of studies were of poor methodological quality.

AUTHORS' CONCLUSIONS

It is difficult to determine to what extent the findings from the meta-analysis can be applied to clinical practice. Given the considerable variability of specificity values and lack of defined thresholds for determination of test positivity in the included studies, the current evidence does not support the routine use of ¹⁸F-FDG PET scans in clinical practice in people with MCI. The ¹⁸F-FDG PET scan is a high-cost investigation, and it is therefore important to clearly demonstrate its accuracy and to standardise the process of ¹⁸F-FDG PET diagnostic modality prior to its being widely used. Future studies with more uniform approaches to thresholds, analysis and study conduct may provide a more homogeneous estimate than the one available from the included studies we have identified.

Identification of diabetes-related dementia: Longitudinal perfusion SPECT and amyloid PET studies

AIMS

We attempted to identify a dementia subgroup with characteristics associated with diabetes mellitus (DM)-related metabolic abnormalities, referred to as diabetes-related dementia, using longitudinal single photon emission computed tomography (SPECT) and Pittsburgh compound-B (PiB) positron emission tomography (PET).

METHODS

We classified 175 patients with clinically diagnosed Alzheimer disease (AD) and DM into 4 subgroups based on brain imaging in a 2013 study. Among them, we investigated follow-up SPECT studies in 29 patients of an AD group showing decreased regional cerebral blood flow (rCBF) of the parietotemporal lobe on initial SPECT and 18 patients of a diabetes-related dementia group showing neither decreased rCBF of the parietotemporal lobe nor cerebrovascular disease, which is strongly associated with DM-related factors. Eleven of them underwent PiB PET.

RESULTS

Follow-up SPECT showed more profound rCBF reduction in the parietotemporal lobe and other areas of the AD group, whereas follow-up SPECT showed an rCBF reduction in small areas of the frontotemporal and limbic lobes of the diabetes-related dementia group. Six of 9 patients with diabetes-related dementia were negative or equivocal for PiB binding.

CONCLUSION

A subset of a dementia subgroup with characteristics predominantly associated with DM-related factors may underlie a pathophysiology different from AD, although these patients were clinically diagnosed as having AD. The identification of diabetes-related dementia may be necessary for considering an appropriate therapy and prevention in clinical practice.

Nonamyloid PET biomarkers and Alzheimer's disease: current and future perspectives

ABSTRACT 

Recent advances in neurobiology and PET have helped redefine Alzheimer's disease (AD) as a dynamic pathophysiological process, clinically characterized by preclinical, mild cognitive impairment due to AD and dementia stages. Though a majority of PET studies conducted within these populations have to date focused on β-amyloid, various ‘nonamyloid’ radiopharmaceuticals exist for evaluating neurodegeneration, neuroinflammation and perturbations in neurotransmission across the spectrum of AD. Importantly, findings using such tracers have been shown to correlate with various clinical, cognitive and behavioral measures. In the context of a growing shift toward early diagnosis and symptomatic and disease-modifying clinical trials, nonamyloid PET radiotracers will prove of use, and, potentially, contribute to improved therapeutic prospects for AD.

Brain imaging of mild cognitive impairment and Alzheimer's disease

The rapidly increasing prevalence of cognitive impairment and Alzheimer's disease has the potential to create a major worldwide healthcare crisis. Structural MRI studies in patients with Alzheimer's disease and mild cognitive impairment are currently attracting considerable interest. It is extremely important to study early structural and metabolic changes, such as those in the hippocampus, entorhinal cortex, and gray matter structures in the medial temporal lobe, to allow the early detection of mild cognitive impairment and Alzheimer's disease. The microstructural integrity of white matter can be studied with diffusion tensor imaging. Increased mean diffusivity and decreased fractional anisotropy are found in subjects with white matter damage. Functional imaging studies with positron emission tomography tracer compounds enable detection of amyloid plaques in the living brain in patients with Alzheimer's disease. In this review, we will focus on key findings from brain imaging studies in mild cognitive impairment and Alzheimer's disease, including structural brain changes studied with MRI and white matter changes seen with diffusion tensor imaging, and other specific imaging methodologies will also be discussed.

Neuroimaging in dementia

Over the last few years, advances in neuroimaging have generated biomarkers, which increase diagnostic certainty, provide valuable information about prognosis, and suggest a particular pathology underlying the clinical dementia syndrome. We aim to review the evidence for use of already established imaging modalities, along with selected techniques that have a great potential to guide clinical decisions in the future. We discuss structural, functional and molecular imaging, focusing on the most common dementias: Alzheimer's disease, fronto-temporal dementia, dementia with Lewy bodies and vascular dementia. Finally, we stress the importance of conducting research using representative cohorts and in a naturalistic set up, in order to build a strong evidence base for translating imaging methods for a National Health Service. If we assess a broad range of patients referred to memory clinic with a variety of imaging modalities, we will make a step towards accumulating robust evidence and ultimately closing the gap between the dramatic advances in neurosciences and meaningful clinical applications for the maximum benefit of our patients.

Neuroimaging biomarkers of neurodegenerative diseases and dementia

Neurodegenerative disorders leading to dementia are common diseases that affect many older and some young adults. Neuroimaging methods are important tools for assessing and monitoring pathological brain changes associated with progressive neurodegenerative conditions. In this review, the authors describe key findings from neuroimaging studies (magnetic resonance imaging and radionucleotide imaging) in neurodegenerative disorders, including Alzheimer's disease (AD) and prodromal stages, familial and atypical AD syndromes, frontotemporal dementia, amyotrophic lateral sclerosis with and without dementia, Parkinson's disease with and without dementia, dementia with Lewy bodies, Huntington's disease, multiple sclerosis, HIV-associated neurocognitive disorder, and prion protein associated diseases (i.e., Creutzfeldt-Jakob disease). The authors focus on neuroimaging findings of in vivo pathology in these disorders, as well as the potential for neuroimaging to provide useful information for differential diagnosis of neurodegenerative disorders.

Hypothesis on two different functionalities co-existing in frontal lobe of human brains

Human frontal lobe is a key area from where our cognition, memory and emotion display or function. In medical case study, there are patients with social dysfunctions, lack of passion or emotion as result of their frontal lobe damage caused by pathological changes, traumatic damage, and brain tumor remove operations. The syndrome of frontal lobe damage remains at large unanswered medically. From early stage of pregnancy, there exists lobe layers, nerve combine, and neurons synaptic, indicating a completion of growth of functionality inside frontal lobe. However, this completion of growth does not match the growth of human intelligence. Human infants only start and complete their cognition and memory functionality one full year after their birth which is marked by huge amount of neurons synaptic inside their frontal lobe, which is not part of a continual growth of originally developed functions. By reasoning on pathological changes of frontal lobe, a hypothesis was established that two individually functional mechanisms co-existed inside one frontal lobe. This neuron system is particularly for human beings.

Decoding Alzheimer's disease from perturbed cerebral glucose metabolism: implications for diagnostic and therapeutic strategies

Alzheimer's disease (AD) is an age-related devastating neurodegenerative disorder, which severely impacts on the global economic development and healthcare system. Though AD has been studied for more than 100 years since 1906, the exact cause(s) and pathogenic mechanism(s) remain to be clarified. Also, the efficient disease-modifying treatment and ideal diagnostic method for AD are unavailable. Perturbed cerebral glucose metabolism, an invariant pathophysiological feature of AD, may be a critical contributor to the pathogenesis of this disease. In this review, we firstly discussed the features of cerebral glucose metabolism in physiological and pathological conditions. Then, we further reviewed the contribution of glucose transportation abnormality and intracellular glucose catabolism dysfunction in AD pathophysiology, and proposed a hypothesis that multiple pathogenic cascades induced by impaired cerebral glucose metabolism could result in neuronal degeneration and consequently cognitive deficits in AD patients. Among these pathogenic processes, altered functional status of thiamine metabolism and brain insulin resistance are highly emphasized and characterized as major pathogenic mechanisms. Finally, considering the fact that AD patients exhibit cerebral glucose hypometabolism possibly due to impairments of insulin signaling and altered thiamine metabolism, we also discuss some potential possibilities to uncover diagnostic biomarkers for AD from abnormal glucose metabolism and to develop drugs targeting at repairing insulin signaling impairment and correcting thiamine metabolism abnormality. We conclude that glucose metabolism abnormality plays a critical role in AD pathophysiological alterations through the induction of multiple pathogenic factors such as oxidative stress, mitochondrial dysfunction, and so forth. To clarify the causes, pathogeneses and consequences of cerebral hypometabolism in AD will help break the bottleneck of current AD study in finding ideal diagnostic biomarker and disease-modifying therapy.

Clinical applications of neuroimaging in patients with Alzheimer's disease: a review from the Fourth Canadian Consensus Conference on the Diagnosis and Treatment of Dementia 2012

In May 2012, the Fourth Canadian Consensus Conference on the Diagnosis and Treatment of Dementia brought together in Montreal experts from around Canada to update Canadian recommendations for the diagnosis and management of patients with neurodegenerative conditions associated with deterioration of cognition. Multiple topics were discussed. The present paper is a highly condensed version of those recommendations that were produced to support discussions in the field of neuroimaging for clinical diagnosis of those conditions.

Neuroimaging and other biomarkers for Alzheimer's disease: the changing landscape of early detection

The goal of this review is to provide an overview of biomarkers for Alzheimer's disease (AD), with emphasis on neuroimaging and cerebrospinal fluid (CSF) biomarkers. We first review biomarker changes in patients with late-onset AD, including findings from studies using structural and functional magnetic resonance imaging (MRI), advanced MRI techniques (diffusion tensor imaging, magnetic resonance spectroscopy, perfusion), positron emission tomography with fluorodeoxyglucose, amyloid tracers, and other neurochemical tracers, and CSF protein levels. Next, we evaluate findings from these biomarkers in preclinical and prodromal stages of AD including mild cognitive impairment (MCI) and pre-MCI conditions conferring elevated risk. We then discuss related findings in patients with dominantly inherited AD. We conclude with a discussion of the current theoretical framework for the role of biomarkers in AD and emergent directions for AD biomarker research.

Effectiveness and safety of 18F-FDG PET in the evaluation of dementia: a review of the recent literature

Imaging that can detect pathophysiologic change in the brain holds great promise for diagnostic assessment of patients with Alzheimer disease (AD) and dementia. Although a previous metaanalysis centering on literature from 1990 to 2000 showed a summary accuracy of 86% for (18)F-FDG PET for AD diagnosis, the clinical value was considered uncertain because of methodologic shortcomings. Review of the recent literature since 2000 demonstrates that the evidence for (18)F-FDG PET in assessment of dementia has increased with new studies that include autopsy confirmation, wide-diagnostic-spectrum recruitment in primary care settings, historical and prospective cohort studies, and multicenter data analyses. These data support the role of (18)F-FDG PET as an effective and useful adjunct to other diagnostic information in the assessment of patients with symptoms of dementia. Findings are in line with recently revised diagnostic criteria of AD that for the first time recognize the unique role of biomarker evidence in disease definition.

Brain imaging in the study of Alzheimer's disease

Over the last 20 years, there has been extraordinary progress in brain imaging research and its application to the study of Alzheimer's disease (AD). Brain imaging researchers have contributed to the scientific understanding, early detection and tracking of AD. They have set the stage for imaging techniques to play growing roles in the clinical setting, the evaluation of disease-modifying treatments, and the identification of demonstrably effective prevention therapies. They have developed ground-breaking methods, including positron emission tomography (PET) ligands to measure fibrillar amyloid-β (Aβ) deposition, new magnetic resonance imaging (MRI) pulse sequences, and powerful image analysis techniques, to help in these endeavors. Additional work is needed to develop even more powerful imaging methods, to further clarify the relationship and time course of Aβ and other disease processes in the predisposition to AD, to establish the role of brain imaging methods in the clinical setting, and to provide the scientific means and regulatory approval pathway needed to evaluate the range of promising disease-modifying and prevention therapies as quickly as possible. Twenty years from now, AD may not yet be a distant memory, but the best is yet to come.

The influence of ApoE4 on clinical progression of dementia: a meta-analysis

OBJECTIVE

ApoE4 is a risk factor for the development of Alzheimer's disease, and has a functional role suggesting its importance in the neuropathology of dementia. We present a meta-analysis to investigate whether ApoE4 also affects the clinical progression of dementia in terms of cognitive decline or mortality.

METHODS

We searched Medline, Embase and PsychINFO from 1990 until April 2009, for case control or cohort studies which investigated the effect of ApoE4 on progression of dementia. We identified 427 studies; 17 were suitable for inclusion. In total, there were 1733 participants with dementia at baseline, of whom 975 were heterozygous or homozygous for ApoE4.

RESULTS

There was no significant difference in cognitive decline (random-model effect size = 0.02; 95% C.-I.: -0.09 to 0.14; p = 0.67) or mortality (random-model pooled odds ratio = 0.74; 95% C.-I.: 0.36 to 1.53; p = 0.41) based on the presence of ApoE4. There was no significant heterogeneity between studies using cognitive decline as an outcome. In meta-regressions of cognitive decline, duration of symptoms, age, gender and frequency of participants with ApoE4 in the samples did not contribute to outcome.

CONCLUSION

Different ApoE alleles do not modify the speed of clinical progression of dementia in a way that would be detectable in a sample of 1700 patients.

Pre-clinical detection of Alzheimer's disease using FDG-PET, with or without amyloid imaging

The development of prevention therapies for Alzheimer's disease (AD) would greatly benefit from biomarkers that are sensitive to subtle brain changes occurring in the preclinical stage of the disease. Early diagnostics is necessary to identify and treat at risk individuals before irreversible neuronal loss occurs. In vivo imaging has long been used to evaluate brain structural and functional abnormalities as predictors of future AD in non-demented persons. Prior to development of amyloid-beta (Abeta) tracers for positron emission tomography (PET), the most widely utilized PET tracer in AD was 2-[18F]fluoro-2-Deoxy-D-glucose (FDG) PET. For over 20 years, FDG-PET has been used to measure cerebral metabolic rates of glucose (CMRglc), a proxy for neuronal activity, in AD. Many studies have shown that CMRglc reductions occur early in AD, correlate with disease progression, and predict histopathological diagnosis. This paper reviews reports of clinical and preclinical CMRglc reductions observed in association with genetic and non-genetic risk factors for AD. We then briefly review brain Abeta PET imaging studies in AD and discuss the potential of combining symptoms-sensitive FDG-PET measures with pathology-specific Abeta-PET to improve the early detection of AD.

Comparing fludeoxyglucose F18-PET assessment of regional cerebral glucose metabolism and [11C]dihydrotetrabenazine-PET in evaluation of early dementia and mild cognitive impairment

OBJECTIVE

To compare assessment of regional cerebral metabolic changes with [(11)C]dihydrotetrabenazine (DTBZ)-positron emission tomography (PET) measurement of regional cerebral blood flow (K(1)) and fludeoxyglucose F18 (FDG)-PET measurement of regional cerebral glucose uptake (CMR(glc)) in a clinically representative sample of subjects with mild dementia and mild cognitive impairment (MCI).

DESIGN

[(11)C]Dihydrotetrabenazine-PET K(1) and FDG-PET CMR(glc) measurements were performed.

SETTING

University-based cognitive disorders clinic.

PARTICIPANTS

Fifty subjects with either mild dementia (Mini-Mental State Examination score > or = 18) or MCI. Their results were compared with those of 80 normal control subjects.

MAIN OUTCOME MEASURES

The DTBZ-PET regional K(1) and FDG-PET CMR(glc) measurements were compared with standard correlation analysis. The overall patterns of DTBZ-PET K(1) and FDG-PET CMR(glc) deficits were assessed with stereotaxic surface projections (SSPs) of parametric images.

RESULTS

The DTBZ-PET regional K(1) and FDG-PET CMR(glc) measurements were highly correlated, both within and between subjects. The SSP maps of deficits in DTBZ-PET regional K(1) and FDG-PET CMR(glc) measurements were markedly similar. The DTBZ-PET K(1) SSP maps exhibited a mild decrease in sensitivity relative to FDG-PET CMR(glc) maps.

CONCLUSIONS

Both DTBZ-PET K(1) and FDG-PET CMR(glc) measurements provide comparable information in assessment of regional cerebral metabolic deficits in mild dementia and MCI. Blood flow measures can assess regional cerebral metabolism deficits accurately in mild dementia and MCI. Blood flow assessments of regional cerebral metabolic deficits can be combined with tracer binding results to improve utility of PET imaging in mild dementia and MCI.

Imaging and biomarkers for Alzheimer's disease

The development of acetyl-cholinesterase inhibitors, and the prospect of future therapies to prevent, or modify, the course of Alzheimer's disease necessitates greater accuracy in diagnosis of this heterogeneous disease. Current diagnosis is based on clinical criteria and neuropathology. This is not always sufficient, and the development of sensitive and specific biomarkers would enable earlier and more accurate diagnosis. Genetic markers, such as Apolipoprotein E4, and cerebrospinal fluid markers such as beta-amyloid and tau, support a diagnosis of Alzheimer's disease. The latter can also predict conversion from mild cognitive impairment to dementia. Imaging markers improve diagnostic accuracy by reflecting brain function or aspects of in vivo pathological changes. In order for such biomarkers to become clinically useful, however, effective treatments need to become available, and long-term follow-up studies are necessary to evaluate the relevance of cross-sectional biomarker changes for the longitudinal natural history of the disease.

Evaluation of Early Dementia (Mild Cognitive Impairment)

Early diagnosis of Alzheimer disease (AD) is one of the major challenges for the prevention of this dementia. The pathologic lesions associated with AD develop many years before the clinical manifestations of the disease become evident, during a likely transitional period between normal aging and the appearance of first cognitive symptoms. AD biomarkers are needed not only to reveal these early pathologic changes but also to monitor progression in cognitive and behavioral decline and brain lesions. PET neuroimaging can reliably assess indirect and direct aspects of the molecular biology and neuropathology of AD. This article reviews the use of [18F] 2-fluoro-2-deoxy-D-glucose-PET and amyloid PET imaging in the early detection of AD.

Current Challenges for the Early Detection of Alzheimer's Disease: Brain Imaging and CSF Studies

The development of prevention therapies for Alzheimer's disease (AD) would greatly benefit from biomarkers that are sensitive to the subtle brain changes that occur in the preclinical stage of the disease. Reductions in the cerebral metabolic rate of glucose (CMRglc), a measure of neuronal function, have proven to be a promising tool in the early diagnosis of AD. In vivo brain 2-[¹⁸F]fluoro-2-Deoxy-D-glucose-positron emission tomography (FDG-PET) imaging demonstrates consistent and progressive CMRglc reductions in AD patients, the extent and topography of which correlate with symptom severity. There is increasing evidence that hypometabolism appears during the preclinical stages of AD and can predict decline years before the onset of symptoms. This review will give an overview of FDG-PET results in individuals at risk for developing dementia, including: presymptomatic individuals carrying mutations responsible for early-onset familial AD; patients with Mild Cognitive Impairment (MCI), often a prodrome to late-onset sporadic AD; non-demented carriers of the Apolipoprotein E (ApoE) ε4 allele, a strong genetic risk factor for late-onset AD; cognitively normal subjects with a family history of AD; subjects with subjective memory complaints; and normal elderly followed longitudinally until they expressed the clinical symptoms and received post-mortem confirmation of AD. Finally, we will discuss the potential to combine different PET tracers and CSF markers of pathology to improve the early detection of AD.

The progression of cognitive deterioration and regional cerebral blood flow patterns in Alzheimer's disease: a longitudinal SPECT study

BACKGROUND AND PURPOSE

The progression of cognitive deterioration in patients with Alzheimer's disease (AD) is considerably variable. The ability to predict the progression rate is important for clinicians to treat and manage patients with AD. We examined the possible relationship between the rate of cognitive deterioration and regional cerebral blood flow (rCBF) patterns in patients with AD.

METHODS

We followed 48 patients with AD for an average of 37 months. They were subsequently divided into the rapidly progressing group (n=24) and slowly progressing group (n=24) based on an annual Mini-Mental State Examination (MMSE) score change. Initial and follow-up rCBF were assessed using single photon emission CT (SPECT) and the SPECT data were analyzed by 3D-stereotactic surface projections.

RESULTS

At initial evaluation, the rapidly progressing group had greater rCBF deficits mainly in the parietotemporal and frontal regions, and left posterior cingulate than did the slowly progressing group. When compared with initial SPECT, follow-up SPECT showed a significant rCBF reduction in widespread regions, including parietotemporal and frontal lobes, of the rapidly progressing group, while showed in the scattered and small regions of hemispheres of the slowly progressing group.

CONCLUSION

Our longitudinal SPECT study suggests a significant association between rCBF deficits in the parietotemporal, posterior cingulate, and frontal regions and subsequent rapid cognitive and rCBF deterioration.

Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI

The Functional Activities Questionnaire (FAQ) and Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-cog) are frequently used indices of cognitive decline in Alzheimer's disease (AD). The goal of this study was to compare FDG-PET and clinical measurements in a large sample of elderly subjects with memory disturbance. We examined relationships between glucose metabolism in FDG-PET regions of interest (FDG-ROIs), and ADAS-cog and FAQ scores in AD and mild cognitive impairment (MCI) patients enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Low glucose metabolism at baseline predicted subsequent ADAS-cog and FAQ decline. In addition, longitudinal glucose metabolism decline was associated with concurrent ADAS-cog and FAQ decline. Finally, a power analysis revealed that FDG-ROI values have greater statistical power than ADAS-cog to detect attenuation of cognitive decline in AD and MCI patients. Glucose metabolism is a sensitive measure of change in cognition and functional ability in AD and MCI, and has value in predicting future cognitive decline.

Brain glucose hypometabolism and oxidative stress in preclinical Alzheimer's disease

One of the main features of Alzheimer's disease (AD) is the severe reduction of the cerebral metabolic rate for glucose (CMRglc). In vivo imaging using positron emission tomography with 2-[(18)F]fluoro-2-deoxy-D-glucose (FDG-PET) demonstrates consistent and progressive CMRglc reductions in AD patients, the extent and topography of which correlate with symptom severity. Increasing evidence suggests that CMRglc reductions occur at the preclinical stages of AD. CMRglc reductions were observed on FDG-PET before the onset of disease in several groups of at-risk individuals, including patients with mild cognitive impairment (MCI), often a prodrome to AD; presymptomatic individuals carrying mutations responsible for early-onset familial AD; cognitively normal elderly individuals followed for several years until they declined to MCI and eventually to AD; normal, middle-aged individuals who expressed subjective memory complaints and were carriers of the apolipoprotein E epsilon-4 allele, a strong genetic risk factor for late-onset AD. However, the causes of the early metabolic dysfunction forerunning the onset of AD are not known. An increasing body of evidence indicates a deficient or altered energy metabolism that could change the overall oxidative microenvironment for neurons during the pathogenesis and progression of AD, leading to alterations in mitochondrial enzymes and in glucose metabolism in AD brain tissue. The present paper reviews findings that implicate hypometabolism and oxidative stress as crucial players in the initiation and progression of synaptic pathology in AD.

Positron emission tomography in Alzheimer’s disease: early prediction and differentiation

The development of biomarkers for the preclinical detection of neurodegenerative diseases such as Alzheimer’s disease (AD) is a vital step in developing prevention therapies. One consistent feature of AD is a reduction in the cerebral metabolic rate of glucose (CMRglc), a measure of neuronal function. In vivo brain 2-[18F]fluoro-2-deoxy-D-glucose-PET imaging demonstrates consistent and progressive CMRglc reductions in AD patients, the extent and topography of which correlate with symptom severity. There is increasing evidence that CMRglc reductions occur at the preclinical stages of AD and predict decline years in advance of clinical symptoms. This review will give an overview of FDG-PET results in individuals at risk for developing dementia, including: presymptomatic individuals carrying mutations responsible for early-onset familial AD; patients with mild cognitive impairment, often a prodrome to late-onset sporadic AD; nondemented carriers of the ApoE ε4 allele, a strong genetic risk factor for late-onset AD; cognitively normal subjects with a family history of AD; subjects with subjective memory complaints; and normal elderly who were followed longitudinally until they expressed the clinical symptoms and later received postmortem confirmation of AD. We will then review the most recent studies using FDG-PET as an early differential diagnostic tool in AD.

Toward the validation of functional neuroimaging as a potential biomarker for Alzheimer's disease: implications for drug development

Despite investments carried out in the research since Alzheimer's disease (AD) was firstly defined as an isolated clinical entity, there is still a lack of appropriate cure and effective therapies to halt or slow the disease progression. While fundamental research has provided a better characterization of AD, much remains to be done for the development of new biological treatment strategies. It is now being debated whether functional neuroimaging (FNI) could help improve diagnostic accuracy and become a possible biomarker of AD. The primary purpose of this review was to determine whether data already published in the literature meet formal technology assessment standards for using regional cerebral blood flow (rCBF) or glucose metabolism (rCMRGlu) as a biomarker for AD. The secondary purpose was to identify any remaining gaps that might need to be systematically addressed before drug developers and regulators accept FNI as a biomarker for AD. The present paper reviews the literature regarding metabolic positron emission tomography (PET) and perfusion single photon emission computed tomography (SPECT) studies in AD. There is evidence that treatment with acetylcholinesterase inhibitors (AChEI) leads to changes in brain physiology within the brain regions critical to AD pathology, i.e. the temporal, parietal and frontal association cortex. However, a thorough analysis combining functional and neuropsychological data has not yet been attempted, and much research is needed to validate the role of FNI as a surrogate endpoint for AD clinical trials.

Positron emission tomography scans obtained for the evaluation of cognitive dysfunction

The degree of intactness of human cognitive functioning for a given individual spans a wide spectrum, ranging from normal to severely demented. The differential diagnosis for the causes of impairment along that spectrum is also wide, and often difficult to distinguish clinically, which has led to an increasing role for neuroimaging tools in that evaluation. The most frequent causes of dementia are neurodegenerative disorders, Alzheimer's disease being the most prevalent among them, and they produce significant alterations in brain metabolism, with devastating neuropathologic, clinical, social, and economic consequences. These alterations are detectable through positron emission tomography (PET), even in their earliest stages. The most commonly performed PET studies of the brain are performed with (18)F-fluorodeoxyglucose as the imaged radiopharmaceutical. Such scans have demonstrated diagnostic and prognostic utility for clinicians evaluating patients with cognitive impairment and in distinguishing among primary neurodegenerative disorders and other etiologies contributing to cognitive decline. In addition to focusing on the effects on cerebral metabolism examined with (18)F-fluorodeoxyglucose PET, some other changes occurring in the brains of cognitively impaired patients assessable with other radiotracers will be considered. As preventive and disease-modifying treatments are developed, early detection of accurately diagnosed disease processes facilitated by the use of PET has the potential to substantially impact on the enormous human toll exacted by these diseases.

Imaging of mild cognitive impairment and early dementia

The concept of mild cognitive impairment (MCI) has been introduced to describe older individuals who cognitively lie between normal ageing and dementia. Nowadays, there is a particular interest in MCI because this syndrome is thought to be a transitional stage to Alzheimer's disease (AD) that may define a window for effective therapeutic interventions. However, not all patients with MCI will go on to develop AD. Imaging offers an extraordinary opportunity to study MCI. We will review key findings of brain imaging studies in MCI, including structural brain changes studied with MRI, white matter changes with diffusion tensor imaging and altered brain activity and blood flow studied with various imaging modalities, such as positron emission tomography, single-photon emission computed tomography and arterial spin labelling MRI, a non-invasive approach to measure cerebral blood flow. The strength and limitations of each modality for diagnosis of MCI, prediction of MCI outcome and assessment of drug efficacy will be discussed.

Multicenter standardized 18F-FDG PET diagnosis of mild cognitive impairment, Alzheimer's disease, and other dementias

This multicenter study examined (18)F-FDG PET measures in the differential diagnosis of Alzheimer's disease (AD), frontotemporal dementia (FTD), and dementia with Lewy bodies (DLB) from normal aging and from each other and the relation of disease-specific patterns to mild cognitive impairment (MCI).

METHODS

We examined the (18)F-FDG PET scans of 548 subjects, including 110 healthy elderly individuals ("normals" or NLs), 114 MCI, 199 AD, 98 FTD, and 27 DLB patients, collected at 7 participating centers. Individual PET scans were Z scored using automated voxel-based comparison with generation of disease-specific patterns of cortical and hippocampal (18)F-FDG uptake that were then applied to characterize MCI.

RESULTS

Standardized disease-specific PET patterns were developed that correctly classified 95% AD, 92% DLB, 94% FTD, and 94% NL. MCI patients showed primarily posterior cingulate cortex and hippocampal hypometabolism (81%), whereas neocortical abnormalities varied according to neuropsychological profiles. An AD PET pattern was observed in 79% MCI with deficits in multiple cognitive domains and 31% amnesic MCI. (18)F-FDG PET heterogeneity in MCI with nonmemory deficits ranged from absent hypometabolism to FTD and DLB PET patterns.

CONCLUSION

Standardized automated analysis of (18)F-FDG PET scans may provide an objective and sensitive support to the clinical diagnosis in early dementia.

Functional imaging of cognition in Alzheimer's disease using positron emission tomography

Positron emission tomography in Alzheimer's disease (AD) demonstrates a metabolic decrease, predominantly in associative posterior cortices (comprising the posterior cingulate cortex), and also involving medial temporal structures and frontal regions at a lesser degree. The level of activity in this wide network is roughly correlated with dementia severity, but several confounds (such as age, education or subcortical ischemic lesions) may influence the brain-behaviour relationship. Univariate analyses allow one to segregate brain regions that are particularly closely related to specific neuropsychological performances. For example, a relationship was established between the activity in lateral associative cortices and semantic performance in AD. The role of semantic capacities (subserved by temporal or parietal regions) in episodic memory tasks was also emphasized. The residual activity in medial temporal structures was related to episodic memory abilities, as measured by free recall performance, cued recall ability and recognition accuracy. More generally, AD patients' performance on episodic memory tasks was correlated with the metabolism in several structures of Papez's circuit (including the medial temporal and posterior cingulate regions). Multivariate analyses should provide complementary information on impaired metabolic covariance in functional networks of brain regions and the consequences for AD patients' cognitive performance. More longitudinal studies are being conducted that should tell us more about the prognostic value of initial metabolic impairment and the neural correlates of progressive deterioration of cognitive performance in AD.

Bringing functional brain image analysis to the clinician: initial assessment of an online interactive diagnostic aide

Image database extensions for functional brain images were assessed by asking clinicians questions about (i) diagnosis confidence level before and after using the software; (ii) expected and unexpected differences between patient and control images; and (iii) an overall rating of the future usefulness of this application in an everyday clinical setting. Examining the difference image of a patient compared to a normative group affects the clinicians' initial diagnosis of the patient in two-thirds of the cases. All three clinicians stated that the interface would be a useful tool when added to the clinical workup of a patient.

Neuroimaging of individuals with Down's syndrome at-risk for dementia: evidence for possible compensatory events

BACKGROUND

We report functional and structural brain indicators that may precede the onset of dementia in individuals with Down's syndrome (DS).

METHODS

Middle-aged adults with DS (n=19), a group known to be at high risk for dementia, were studied with (1) positron emission tomography (PET) to determine cerebral glucose metabolic rate (GMR), (2) structural magnetic resonance imaging (MRI) to determine gray matter volume (GM), and (3) ratings of potential dementia indicators based on a structured interview of caregiver observations designed to evaluate individuals with low intelligence.

RESULTS

Although none of the participants showed clinical signs of dementia, ratings of dementia indicators were correlated to both functional and structural imaging. The strongest correlations (p<.05, corrected for multiple comparisons) included the combination of higher GMR and decreased GM volume in parts of the temporal cortex, including the parahippocampus/hippocampus, in the thalamus, caudate, and frontal lobe (BA 47).

INTERPRETATION

The combination of increased GMR overlapping with less gray matter in these areas may be consistent with a compensatory brain response to an early stage of the disease process.

Parietal cortex activation predicts memory decline in apolipoprotein E-epsilon4 carriers

Apolipoprotein E-epsilon4 is the main known genetic risk factor for Alzheimer's disease. Functional abnormalities in the parietal cortex have been reported for Alzheimer's disease patients and also for those at risk. Hence, a critical question is whether measurements of parietal cortex integrity may predict negative outcome among at-risk persons. We studied nondemented apolipoprotein E-epsilon4 carriers and found a significant relationship between parietal blood-oxygen-level-dependent functional magnetic resonance imaging response during a word categorization task and subsequent episodic memory performance. Thus, the results show that parietal cortex alterations predict memory decline in nondemented apolipoprotein E-epsilon4 carriers, and hence likely progression to Alzheimer's disease.

PET imaging of cortical 11C-nicotine binding correlates with the cognitive function of attention in Alzheimer's disease

RATIONALE

Patients suffering from Alzheimer's disease (AD) experience a marked reduction in cortical nicotinic acetylcholine receptors (nAChRs). In particular, selective loss of the alpha4beta2 nAChR subtype was observed in postmortem AD brain tissue. The alpha4 and alpha7 nAChR subunits were suggested to play an important role in cognitive function. Positron emission tomography (PET) has so far been used to visualize neuronal nAChRs in vivo by 11C-nicotine binding.

OBJECTIVES

To investigate the relationship between measures of cognitive function and in vivo 11C-nicotine binding in mild AD brain as assessed by PET.

MATERIALS AND METHODS

Twenty-seven patients with mild AD were recruited in this study. A dual tracer model with administration of 15O-water for regional cerebral blood flow and (S)(-)11C-nicotine was used to assess nicotine binding sites in the brain by PET. Cognitive function was assessed using neuropsychological tests of global cognition, episodic memory, attention, and visuospatial ability.

RESULTS

Mean cortical 11C-nicotine binding significantly correlated with the results of attention tests [Digit Symbol test (r = -0.44 and p = 0.02) and Trail Making Test A (TMT-A) (r = 0.42 and p = 0.03)]. No significant correlation was observed between 11C-nicotine binding and the results of tests of episodic memory or visuospatial ability. Regional analysis showed that 11C-nicotine binding in the frontal and parietal cortex, which are the main areas for attention, correlated significantly with the Digit Symbol test and TMT-A results.

CONCLUSION

Cortical nicotinic receptors in vivo in mild AD patients are robustly associated with the cognitive function of attention.

Early detection of Alzheimer's disease using neuroimaging

Neuroimaging is being increasingly used to complement clinical assessments in the early detection of Alzheimer's disease (AD). Structural magnetic resonance imaging (MRI) and metabolic positron emission tomography (FDG-PET) are the most clinically used and promising modalities to detect brain abnormalities in individuals who might be at risk for AD but who have not yet developed symptoms. The knowledge of established risk factors for AD enabled investigators to develop enrichment strategies for longitudinal imaging studies to reduce the sample sizes and study duration. The present review focuses on the results obtained by MRI and FDG-PET studies that examined the preclinical AD stages in several at risk populations: (1) individuals from families with autosomal dominant early-onset AD (FAD), (2) patients with mild cognitive impairment (MCI), particularly in memory, who are at very high risk for declining to AD with an estimated decline rate of 10-30% per year, (3) normal young and middle-age subjects carriers of known susceptibility genes for late-onset AD such as the Apolipoprotein E (ApoE) E4 allele, and (4) as age is the main risk factor for AD, normal elderly individuals followed to the onset of MCI and AD. Overall, these studies show that the use of imaging for the early detection of AD is successful even in the earlier stages of disease when clinical symptoms are not fully expressed and the regional brain damage may be limited.

PET network abnormalities and cognitive decline in patients with mild cognitive impairment

Temporoparietal and posterior cingulate metabolism deficits characterize patients with Alzheimer's disease (AD). A H(2)(15)O resting PET scan covariance pattern, derived by using multivariate techniques, was previously shown to discriminate 17 mild AD patients from 16 healthy controls. This AD covariance pattern revealed hypoperfusion in bilateral inferior parietal lobule and cingulate; and left middle frontal, inferior frontal, precentral, and supramarginal gyri. The AD pattern also revealed hyperperfusion in bilateral insula, lingual gyri, and cuneus; left fusiform and superior occipital gyri; and right parahippocampal gyrus and pulvinar. In an independent sample of 23 outpatients with mild cognitive impairment (MCI) followed at 6-month intervals, the AD pattern score was evaluated as a predictor of cognitive decline. In this MCI sample, an H2(15)O resting PET scan was carried out at baseline. Mean duration of follow-up was 48.8 (SD 15.5) months, during which time six of 23 MCI patients converted to AD. In generalized estimating equations (GEE) analyses, controlling for age, sex, education, and baseline neuropsychological scores, increased AD pattern score was associated with greater decline in each neuropsychological test score over time (Mini Mental State Exam, Selective Reminding Test delayed recall, Animal Naming, WAIS-R digit symbol; Ps<0.01-0.001). In summary, a resting PET covariance pattern previously reported to discriminate AD patients from control subjects was applied prospectively to an independent sample of MCI patients and found to predict cognitive decline. Independent replication in larger samples is needed before clinical application can be considered.

Magnetic resonance and PET studies in the early diagnosis of Alzheimer's disease

The demographics of aging identify an immediate need for the early diagnosis and development of dementia prevention strategies. Recent neuropathological studies have pointed to the early involvement of the hippocampus and entorhinal cortex in the progression of Alzheimer's disease in the brain. In particular, these studies have implicated tau-related pathology as an important cause of neuronal death. In addition, there is a large body of evidence showing that beta-amyloid, which has a predilection for the neocortex, is also involved early in the course of the disease and may also have toxic effects on cells. In vivo cerebrospinal fluid studies have shown that markers for these brain changes have a diagnostic value for Alzheimer's disease and that some measures also provide diagnostic specificity for Alzheimer's disease. Structural and metabolic imaging studies demonstrate brain changes in impaired and at-risk individuals. While currently available magnetic resonance and positron emission tomography techniques are not by themselves specific for the pathologic features of Alzheimer's disease, there are patterns of change that have been useful for the early diagnosis. As such, both prediction and longitudinal imaging studies demonstrate a capacity to recognize abnormalities that relate to future Alzheimer's disease and most recently to future mild cognitive impairment. This review highlights cross-sectional, prediction, and longitudinal magnetic resonance and positron emission tomography imaging studies and attempts to put into perspective their utility for the early diagnosis of Alzheimer's disease, and for their utility to provide diagnostic specificity. It is concluded that there is considerable promise for an early and specific diagnosis for Alzheimer's disease by combining information from imaging and biomarker modalities.