Amyloid imaging represents a major advance in neuroscience, enabling the detection and quantification of pathologic protein aggregations in the brain. In this review we survey current amyloid imaging techniques, focusing on positron emission tomography (PET) with ^{11}carbon-labelled Pittsburgh Compound-B (11C-PIB), the most extensively studied and best validated tracer. PIB binds specifically to fibrillar beta-amyloid (A&#x3b2;) deposits, and is a sensitive marker for A&#x3b2; pathology in cognitively normal older individuals and patients with mild cognitive impairment (MCI) and Alzheimer&#x2019;s disease (AD). PIB-PET provides us with a powerful tool to examine in vivo the relationship between amyloid deposition, clinical symptoms, and structural and functional brain changes in the continuum between normal aging and AD. Amyloid imaging studies support a model in which amyloid deposition is an early event on the path to dementia, beginning insidiously in cognitively normal individuals, and accompanied by subtle cognitive decline and functional and structural brain changes suggestive of incipient AD. As patients progress to dementia, clinical decline and neurodegeneration accelerate and proceed independently of amyloid accumulation. In the future, amyloid imaging is likely to supplement clinical evaluation in selecting patients for anti-amyloid therapies, while MRI and FDG-PET may be more appropriate markers of clinical progression.

G. D. Rabinovici

W. J. Jagust

Amyloid Imaging in Aging and Dementia: Testing the Amyloid Hypothesis In Vivo

Neurodegenerative disorders, such as Alzheimer&#x2019;s disease (AD), are associated with characteristic patterns of neuropathological spread in the brain. Disease progression is usually accompanied by regional atrophy that can be detected noninvasively using structural magnetic resonance imaging (MRI). A wealth of data has demonstrated the value of quantitative measurements of regional atrophy in AD, suggesting that volumetric MRI (vMRI) may be a useful clinical tool. vMRI provides biological evidence of neurodegenerative disease in patients with cognitive impairment. However, several hurdles impede implementation of vMRI in clinical practice. These include a lack of standardized MRI acquisition protocols, spatial distortions in MRI data, labor-intensive vMRI methods susceptible to interoperator variability, a lack of normative ranges for volume measures, and difficulty integrating vMRI in clinical workflow. Advances in vMRI have resulted from multi-institutional studies of brain imaging, such as the Alzheimer&#x2019;s Disease Neuroimaging Initiative (ADNI), and help address these challenges. New, fully-automated measures of brain structure volumes coupled with large, multi-center studies using standardized MRI protocols now allow the development of age-adjusted normative ranges for vMRI. Such advances are critical for providing physicians a framework for assessing the pattern and degree of regional atrophy in a patient's brain and applying vMRI in clinical practice.

J. B. Brewer

Fully-Automated Volumetric MRI with Normative Ranges: Translation to Clinical Practice

During its earliest stage, before cell loss and independent of amyloid plaques and neurofibrillary tangles, Alzheimer's disease (AD) causes synaptic loss affecting the basal functional properties of neurons. In principle, synaptic loss can be detected by measuring AD-induced changes in basal function, or by measuring stimulus-evoked responses on top of basal changes. Functional magnetic resonance imaging (fMRI) is sensitive to both basal changes and evoked-responses, and there are therefore two experimental approaches in which fMRI can be used to pinpoint synaptic loss in AD. In this review, we will compare and contrast both approaches for pinpointing when and where synaptic loss in AD begins and for monitoring therapeutic efficacy.

Adam M. Brickman

Scott A. Small

Adam Fleisher

Pinpointing Synaptic Loss Caused by Alzheimer&#x2019;s Disease with fMRI

Critical to development of new therapies for Alzheimer&#x2019;s disease (AD) is the ability to detect clinical or pathological change over time. Clinical outcome measures typically used in therapeutic trials have unfortunately proven to be relatively variable and somewhat insensitive to change in this slowly progressive disease. For this reason, development of surrogate biomarkers that identify significant disease-associated brain changes are necessary to expedite treatment development in AD. Since AD pathology is present in the brain many years prior to clinical manifestation, ideally we want to develop biomarkers of disease that identify abnormal brain structure or function even prior to cognitive decline. Magnetic resonance imaging, fluorodeoxyglucose positron emission tomography, new amyloid imaging techniques, and spinal fluid markers of AD all have great potential to provide surrogate endpoint measures for AD pathology. The Alzheimer&#x2019;s disease neuroimaging initiative (ADNI) was developed for the distinct purpose of evaluating surrogate biomarkers for drug development in AD. Recent evidence from ADNI demonstrates that imaging may provide more sensitive, and earlier, measures of disease progression than traditional clinical measures for powering clinical drug trials in Alzheimer's disease. This review discusses recently presented data from the ADNI dataset, and the importance of imaging in the future of drug development in AD.

Adam S. Fleisher

Michael Donohue

Kewei Chen

James B. Brewer

Paul S. Aisen

the Alzheimer&#x2019;s Disease Neuroimaging Initiative

Applications of Neuroimaging to Disease-Modification Trials in Alzheimer&#x2019;s Disease

Alzheimer&#x2019;s disease (AD) is the most common form of dementia in old age, and is characterized by prominent impairment of episodic memory. Recent functional imaging studies in AD have demonstrated alterations in a distributed network of brain regions supporting memory function, including regions of the default mode network. Previous positron emission tomography studies of older individuals at risk for AD have revealed hypometabolism of association cortical regions similar to the metabolic abnormalities seen in AD patients. In recent functional magnetic resonance imaging (fMRI) studies of AD, corresponding brain default mode regions have also been found to demonstrate an abnormal fMRI task-induced deactivation response pattern. That is, the relative decreases in fMRI signal normally observed in the default mode regions in healthy subjects performing a cognitive task are not seen in AD patients, or may even be reversed to a paradoxical activation response. Our recent studies have revealed alterations in the pattern of deactivation also in elderly individuals at risk for AD by virtue of their APOE e4 genotype, or evidence of mild cognitive impairment (MCI). In agreement with recent reports from other groups, these studies demonstrate that the pattern of fMRI task-induced deactivation is progressively disrupted along the continuum from normal aging to MCI and to clinical AD and more impaired in e4 carriers compared to non-carriers. These findings will be discussed in the context of current literature regarding functional imaging of the default network in AD and at-risk populations.

Maija Pihlajam&#xe4;ki

Reisa A. Sperling

Functional MRI Assessment of Task-Induced Deactivation of the Default Mode Network in Alzheimer&#x2019;s Disease and At-Risk Older Individuals

Current research supports the strong potential of structural MRI profiles, even within cross-sectional designs, as a promising method for the discrimination of Alzheimer's Disease (AD) from normal controls and for the prediction of Mild Cognitive Impairment (MCI) progression and conversion to AD. Findings suggest that measures of structural change in mesial and lateral temporal, cingulate, parietal and midfrontal areas may facilitate the assessment of a treatment's ability to halt the progressive structural loss that accompanies clinical decline in MCI. The performance of prediction is likely to continue to improve with the incorporation of measures from other neuroimaging modalities, clinical assessments, and neuromedical biomarkers, as the regional profile of individuals at risk for progression is refined.

Christine Fennema-Notestine

Linda K. McEvoy

Donald J. Hagler

Mark W. Jacobson

Anders M. Dale

Structural Neuroimaging in the Detection and Prognosis of Pre-Clinical and Early AD

With longer life expectancy, dementia based on the age-related Alzheimers&#x2019; disease (AD) has turned into one of the most prevalent disorders of older age, representing a serious medical and socio-economic issue. There has been growing interest in early diagnosis of this disease, particularly regarding the initiation of new treatment strategies ahead of the onset of irreversible neuronal damage. It is accepted that the pathologic changes underlying AD appear in the brain years to decades before the symptomatic stages. Consequently, clinical measures of cognitive impairment, as used for definition of dementia, will not allow early diagnosis of AD-pathology in the mild or asymptomatic stages. Thus, a need for complementary sensitive biomarkers is apparent. Brain imaging markers are among the most promising candidates for this diagnostic challenge. Particularly, [18F]FDG PET as a marker of regional neuronal function has been demonstrated to represent a most sensitive and specific method for early identification of AD-pathology and thus for prediction of dementia of the Alzheimer type (DAT), even in the mild and asymptomatic stages. Currently, systematic data of comparable quality are hardly available for any other imaging procedure. The purpose of this article is to describe the typical findings of [18F]FDG PET in different stages of AD and to demonstrate its value for early and reliable diagnosis of Alzheimer's disease, particularly ahead of the stage of dementia of the Alzheimer&#x2019;s type.

Alexander Drzezga

Diagnosis of Alzheimer&#x2019;s Disease with [18F]PET in Mild and Asymptomatic Stages

Dementia is a debilitating and life-altering disease which leads to both memory impairment and decline of normal executive functioning. While causes of dementia are numerous and varied, the leading cause among patients 60 years and older is Alzheimer&#x2019;s disease. The gold standard for Alzheimer&#x2019;s diagnosis remains histological identification of amyloid plaques and neurofibrillary tangles within the medial temporal lobe, more specifically the entorhinal cortex and hippocampus. Although no definitive cure for Alzheimer's disease currently exists, there are treatments targeted at preserving cognition and memory while delaying continued loss of function. Alzheimer's disease exists along a spectrum of cognitive decline and is often preceded by Mild Cognitive Impairment (MCI). Patients with MCI demonstrate memory loss and cognitive impairment while still continuing normal activities of daily living, and are considered to be at increased risk for developing Alzheimer's Dementia. Identifying patients with prodromal states of Alzheimer's dementia such as MCI may allow initiation of appropriate treatment planning and delay of cognitive decline. Therefore, the need for a non-invasive early biomarker for the detection of Alzheimer's disease has never been greater. Multiple neuroimaging methods utilizing visual rating scales, volumetric measurements, and automated methods have been developed to identify, quantify, and track anatomic sequelae of Alzheimer&#x2019;s Disease.

Jason Appel

Elizabeth Potter

Qian Shen

Gustavo Pantol

Maria T. Greig

David Loewenstein

Ranjan Duara

A Comparative Analysis of Structural Brain MRI in the Diagnosis of Alzheimer&#x2019;s Disease

Identifying a preclinical phase of Alzheimer&#x2019;s Disease (PCAD) that is distinct from cognitive changes in healthy aging continues to be a major research focus. Combining neuropsychological and neuroimaging methodologies should improve our ability to differentiate healthy from pathological aging, although studies that utilize both methods often result in equivocal findings, possibly due to variability in cognitive test performance that may be capturing distinct phenotypes. One method of capturing this cognitive variability is to utilize contrasting neuropsychological tests to identify subgroups representative of distinct cognitive phenotypes, and determine whether differences in brain morphometry support these classifications. We review several approaches to defining cognitive subgroups, and we consider the possibility that cognitive asymmetry might provide one means of identifying both functional and structural changes associated with aging and dementia.

Anders Dale

Cognitive Phenotypes, Brain Morphometry and the Detection of Cognitive Decline in Preclinical AD

Structural magnetic resonance imaging (MRI) studies of Alzheimer&#x2019;s disease and mild cognitive impairment (MCI) have focused on the hippocampus and entorhinal cortex; gray matter structures in the medial temporal lobe. Few studies have investigated the integrity of white matter in patients with AD or MCI. Diffusion tensor imaging (DTI) is a MRI technique that allows for the interrogation of the microstructural integrity of white matter. Based on increases in translational diffusion (mean diffusivity: MD) and decreases directional diffusion (fractional anisotropy: FA) damage to white matter can be assessed. Studies have identified regions of increased MD and decreased FA in patients with AD and MCI in all lobes of the brain, as well as medial temporal lobe structures including the hippocampus, entorhinal cortex and parahippocampal white matter. The pattern of white matter integrity disruption tends to follow an anterior to posterior gradient with greater damage noted in posterior regions in AD and MCI. Recent studies have exploited inter-voxel directional similarities to develop models of white matter pathways, and have used these models to assess the integrity of inter-cerebral connections. Particular focus has been applied to the parahippocampal white matter (including the perforant path) and the posterior cingulum. Although many studies have found DTI indicators of impaired white matter in AD and MCI, other studies have failed to detect any differences in MD or FA between the groups, demonstrating the need for large replicative studies. DTI is an evolving technique and advances in its application ought to provide new insights into AD and MCI.

G. T. Stebbins

C. M. Murphy

Diffusion Tensor Imaging in Alzheimer&#x2019;s Disease and Mild Cognitive Impairment

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Papers are published upon acceptance, regardless of the Special Issue publication date.

Behavioural Neurology

Alzheimer’s Disease and Mild Cognitive Impairment: New Insights from Imaging

Alzheimer’s Disease and Mild Cognitive Impairment: New Insights from Imaging

Articles

Amyloid Imaging in Aging and Dementia: Testing the Amyloid Hypothesis In Vivo

Fully-Automated Volumetric MRI with Normative Ranges: Translation to Clinical Practice

Pinpointing Synaptic Loss Caused by Alzheimer’s Disease with fMRI

Applications of Neuroimaging to Disease-Modification Trials in Alzheimer’s Disease

Functional MRI Assessment of Task-Induced Deactivation of the Default Mode Network in Alzheimer’s Disease and At-Risk Older Individuals

Structural Neuroimaging in the Detection and Prognosis of Pre-Clinical and Early AD

Diagnosis of Alzheimer’s Disease with [18F]PET in Mild and Asymptomatic Stages

A Comparative Analysis of Structural Brain MRI in the Diagnosis of Alzheimer’s Disease

Cognitive Phenotypes, Brain Morphometry and the Detection of Cognitive Decline in Preclinical AD

Diffusion Tensor Imaging in Alzheimer’s Disease and Mild Cognitive Impairment