Neuroimaging in Alzheimer disease: an evidence-based review

Exploring easily accessible neurophysiological biomarkers for predicting Alzheimer's disease progression: a systematic review

Alzheimer disease (AD) remains a significant global health concern. The progression from preclinical stages to overt dementia has become a crucial point of interest for researchers. This paper reviews the potential of neurophysiological biomarkers in predicting AD progression, based on a systematic literature search following PRISMA guidelines, including 55 studies. EEG-based techniques have been predominantly employed, whereas TMS studies are less common. Among the investigated neurophysiological measures, spectral power measurements and event-related potentials-based measures, including P300 and N200 latencies, have emerged as the most consistent and reliable biomarkers for predicting the likelihood of conversion to AD. In addition, TMS-based indices of cortical excitability and synaptic plasticity have also shown potential in assessing the risk of conversion to AD. However, concerns persist regarding the methodological discrepancies among studies, the accuracy of these neurophysiological measures in comparison to established AD biomarkers, and their immediate clinical applicability. Further research is needed to validate the predictive capabilities of EEG and TMS measures. Advancements in this area could lead to cost-effective, reliable biomarkers, enhancing diagnostic processes and deepening our understanding of AD pathophysiology.

A longitudinal MRI analysis reveals altered brain connectivity and microstructural changes in a transgenic mouse model of Alzheimer's disease

Alzheimer's disease (AD) is characterized by progressive cognitive decline and neuropathological changes, yet the underlying neurobiological mechanisms remain elusive. Here, we employed a multimodal longitudinal neuroimaging approach, using anatomical and functional sequences on a high field magnetic resonance imaging (MRI) preclinical scanner, to investigate alterations in brain connectivity and white matter microstructure in a transgenic mouse model of AD (J20) when compared to wild-type (WT) littermates. Functional connectivity analysis revealed distinct network disruptions in J20 mice, primarily involving connections between posterior and anterior brain regions; importantly, a significant interaction between group and age highlighted an exacerbation of these connectivity changes with advancing age in J20 mice. In addition, significant reductions in fractional anisotropy (FA) were observed in the corpus callosum of J20 mice compared to WT, indicative of microstructural alterations consistent with white matter pathology. The observed alterations in brain connectivity and microstructure provide valuable insights into the spatiotemporal processes underlying AD-related decline and underscore the utility of multimodal neuroimaging in elucidating the neurobiological substrates of AD pathology in animal models.

Correlation of Cognitive Status and Atrophy Score in Alzheimer's Disease Among the Bangladeshi Population

BACKGROUND

Alzheimer's disease (AD) patients suffer from cognitive dysfunction. This study assessed the structural magnetic resonance imaging (MRI) scoring among Alzheimer's patients (age ≥18 years) to correlate with dementia severity according to mini-mental state exam (MMSE) scores.

METHODS

This cross-sectional study evaluated Bangladeshi adult AD patients from January 2018 to December 2022 who attended with subjective memory complaints and fulfilled the diagnostic and statistical manual of mental disorders criteria (DSM 5) for diagnosing dementia. The medial temporal lobe atrophy (MTA) and Koedam's score of the atrophy were measured utilising the 1.5 and 3 Tesla Magnetom symphony MRI systems.

RESULTS

Of the 62 patients enrolled, the majority (39 cases; 62.9%) were aged over 60 years. Males were more predominant than females, with a male-to-female ratio of 2.6:1, and the moderate MMSE group consisted of 35.6% males and 64.7% females (P = 0.01). Further, MTA score severity is paradoxically associated with the MMSE score (P = 0.005). Additionally, we found a statistically significant negative correlation between the severity of the MMSE and only MTA scores (r = -0.350; 95% CI -0.551 to -0.110; P = 0.005).

CONCLUSION

Structural magnetic resonance imaging among Alzheimer's patients is significantly correlated with the severity of dementia as per mini-mental state exam scores.

Tau Protein Alterations Induced by Hypobaric Hypoxia Exposure

Tauopathies are a group of neurodegenerative diseases whose central feature is dysfunction of the microtubule-associated protein tau (MAPT). Although the exact etiology of tauopathies is still unknown, it has been hypothesized that their onset may occur up to twenty years before the clear emergence of symptoms, which has led to questions about whether the prognosis of these diseases can be improved by, for instance, targeting the factors that influence tauopathy development. One such factor is hypoxia, which is strongly linked to Alzheimer's disease because of its association with obstructive sleep apnea and has been reported to affect molecular pathways related to the dysfunction and aggregation of tau proteins and other biomarkers of neurological damage. In particular, hypobaric hypoxia exposure increases the activation of several kinases related to the hyperphosphorylation of tau in neuronal cells, such as ERK, GSK3β, and CDK5. In addition, hypoxia also increases the levels of inflammatory molecules (IL-β1, IL-6, and TNF-α), which are also associated with neurodegeneration. This review discusses the many remaining questions regarding the influence of hypoxia on tauopathies and the contribution of high-altitude exposure to the development of these diseases.

Cognitive decline and hippocampal functional connectivity within older Black adults

While there has been a proliferation of neuroimaging studies on cognitive decline in older non-Hispanic White adults, there is a dearth of knowledge regarding neuroimaging correlates of cognitive decline in Black adults. Resting-state functional neuroimaging approaches may be particularly sensitive to early cognitive decline, but there are no studies that we know of that apply this approach to examining associations of brain function to cognition in older Black adults. We investigated the association of cognitive decline with whole-brain voxel-wise functional connectivity to the hippocampus, a key brain region functionally implicated in early Alzheimer's dementia, in 132 older Black adults without dementia participating in the Minority Aging Research Study and Rush Memory and Aging Project, two longitudinal studies of aging that include harmonized annual cognitive assessments and magnetic resonance imaging brain imaging. In models adjusted for demographic factors (age, education, sex), global cognitive decline was associated with functional connectivity of the hippocampus to three clusters in the right and left frontal regions of the dorsolateral prefrontal cortex. In domain-specific analyses, decline in semantic memory was associated with functional connectivity of the hippocampus to bilateral clusters in the precentral gyrus, and decline in perceptual speed was inversely associated with connectivity of the hippocampus to the bilateral intracalcarine cortex and the right fusiform gyrus. These findings elucidate neurobiological mechanisms underlying cognitive decline in older Black adults and may point to specific targets of intervention for Alzheimer's disease.

Association Between Motor Task Performance and Hippocampal Atrophy Across Cognitively Unimpaired, Amnestic Mild Cognitive Impairment, and Alzheimer's Disease Individuals

Hippocampal atrophy is a widely used biomarker for Alzheimer's disease (AD), but the cost, time, and contraindications associated with magnetic resonance imaging (MRI) limit its use. Recent work has shown that a low-cost upper extremity motor task has potential in identifying AD risk. Fifty-four older adults (15 cognitively unimpaired, 24 amnestic mild cognitive impairment, and 15 AD) completed six motor task trials and a structural MRI. Several measures of motor task performance significantly predicted bilateral hippocampal volume, controlling for age, sex, education, and memory. Thus, this motor task may be an affordable, non-invasive screen for AD risk and progression.

Diffusion tension imaging is a good tool for assessing patients with dementia and behavioral problems and discriminating them from other dementia patients

Background

Dementia is one of the leading public health concerns as the world’s population ages. Although Alzheimer’s disease (AD) is the most common dementia diagnosis among older patients, some patients have additional behavioral symptoms. It is therefore important to provide an exact diagnosis, both to provide the best possible treatment for patients and to facilitate better understanding.

Purpose

To investigate whether magnetic resonance imaging (MRI) with fractional anisotropy (FA) can accurately find patients with behavioral symptoms within a group of AD patients.

Material and Methods

Forty-five patients from the geriatric outpatient clinic were recruited consecutively to form a group of patients with AD and behavioral symptoms (AD + BS) and a control group of 50 patients with established AD. All patients had a full assessment for dementia to establish the diagnosis according to ICD-10. MRI included 3D anatomical recordings for morphometric measurements, DTI for fiber tracking, and quantitative assessment of regional white matter integrity. The DTI analyses included computing of the diffusion tensor and its derived FA index.

Results

We found a significant difference in FA values between the patient groups’ frontal lobes. The FA was greater in the study group in both left (0.39 vs 0.09, p < 0.05) and right (0.40 vs 0.16, p < 0.05) frontal lobes.

Conclusion

MRI with FA will find damage in frontal tracts and may be used as a diagnostic tool and be considered a robust tool for the recognizing different types of dementia in the future.

Neural Correlates of Cognitive Performance in Alzheimer's Disease- and Lewy Bodies-Related Cognitive Impairment

BACKGROUND

Clinicopathological studies have demonstrated that the neuropsychological profiles and outcomes are different between two dementia subtypes, namely Alzheimer's disease (AD) and Lewy bodies-related disease.

OBJECTIVE

We investigated the neural correlates of cognitive dysfunction in patients with AD-related cognitive impairment (ADCI) and those with Lewy bodies-related cognitive impairment (LBCI).

METHODS

We enrolled 216 ADCI patients, 183 LBCI patients, and 30 controls. Cortical thickness and diffusion tensor imaging analyses were performed to correlate gray matter and white matter (WM) abnormalities to cognitive composite scores for memory, visuospatial, and attention/executive domains in the ADCI spectrum (ADCI patients and controls) and the LBCI spectrum (LBCI patients and controls) separately.

RESULTS

Memory dysfunction correlated with cortical thinning and increased mean diffusivity in the AD-prone regions, particularly the medial temporal region, in ADCI. Meanwhile, it only correlated with increased mean diffusivity in the WM adjacent to the anteromedial temporal, insula, and basal frontal cortices in LBCI. Visuospatial dysfunction correlated with cortical thinning in posterior brain regions in ADCI, while it correlated with decreased fractional anisotropy in the corpus callosum and widespread WM regions in LBCI. Attention/executive dysfunction correlated with cortical thinning and WM abnormalities in widespread brain regions in both disease spectra; however, ADCI had more prominent correlation with cortical thickness and LBCI did with fractional anisotropy values.

CONCLUSIONS

Our study demonstrated that ADCI and LBCI have different neural correlates with respect to cognitive dysfunction. Cortical thinning had greater effects on cognitive dysfunction in the ADCI, while WM disruption did in the LBCI.

The Causal Role of Lipoxidative Damage in Mitochondrial Bioenergetic Dysfunction Linked to Alzheimer's Disease Pathology

Current shreds of evidence point to the entorhinal cortex (EC) as the origin of the Alzheimer’s disease (AD) pathology in the cerebrum. Compared with other cortical areas, the neurons from this brain region possess an inherent selective vulnerability derived from particular oxidative stress conditions that favor increased mitochondrial molecular damage with early bioenergetic involvement. This alteration of energy metabolism is the starting point for subsequent changes in a multitude of cell mechanisms, leading to neuronal dysfunction and, ultimately, cell death. These events are induced by changes that come with age, creating the substrate for the alteration of several neuronal pathways that will evolve toward neurodegeneration and, consequently, the development of AD pathology. In this context, the present review will focus on description of the biological mechanisms that confer vulnerability specifically to neurons of the entorhinal cortex, the changes induced by the aging process in this brain region, and the alterations at the mitochondrial level as the earliest mechanism for the development of AD pathology. Current findings allow us to propose the existence of an altered allostatic mechanism at the entorhinal cortex whose core is made up of mitochondrial oxidative stress, lipid metabolism, and energy production, and which, in a positive loop, evolves to neurodegeneration, laying the basis for the onset and progression of AD pathology.

Brain Metabolite, N-Acetylaspartate Is a Potent Protein Aggregation Inhibitor

Deposition of toxic protein inclusions is a common hallmark of many neurodegenerative disorders including Alzheimer's disease, Parkinson disease etc. N-acetylaspartate (NAA) is an important brain metabolite whose levels got altered under various neurodegenerative conditions. Indeed, NAA has been a widely accepted biological marker for various neurological disorders. We have also reported that NAA is a protein stabilizer. In the present communication, we investigated the role of NAA in modulating the aggregation propensity on two model proteins (carbonic anhydrase and catalase). We discovered that NAA suppresses protein aggregation and could solubilize preformed aggregates.

Neither Excessive Nitric Oxide Accumulation nor Acute Hyperglycemia Affects the N-Acetylaspartate Network in Wistar Rat Brain Cells

The N-acetylaspartate network begins in neurons with N-acetylaspartate production catalyzed by aspartate N-acetyltransferase from acetyl-CoA and aspartate. Clinical studies reported a significant depletion in N-acetylaspartate brain level in type 1 diabetic patients. The main goal of this study was to establish the impact of either hyperglycemia or oxidative stress on the N-acetylaspartate network. For the in vitro part of the study, embryonic rat primary neurons were treated by using a nitric oxide generator for 24 h followed by 6 days of post-treatment culture, while the neural stem cells were cultured in media with 25–75 mM glucose. For the in vivo part, male adult Wistar rats were injected with streptozotocin (65 mg/kg body weight, ip) to induce hyperglycemia (diabetes model) and euthanized 2 or 8 weeks later. Finally, the biochemical profile, NAT8L protein/Nat8l mRNA levels and enzymatic activity were analyzed. Ongoing oxidative stress processes significantly affected energy metabolism and cholinergic neurotransmission. However, the applied factors did not affect the N-acetylaspartate network. This study shows that reduced N-acetylaspartate level in type 1 diabetes is not related to oxidative stress and that does not trigger N-acetylaspartate network fragility. To reveal why N-acetylaspartate is reduced in this pathology, other processes should be considered.

Entorhinal and Transentorhinal Atrophy in Preclinical Alzheimer's Disease

This study examines the atrophy patterns in the entorhinal and transentorhinal cortices of subjects that converted from normal cognition to mild cognitive impairment. The regions were manually segmented from 3T MRI, then corrected for variability in boundary definition over time using an automated approach called longitudinal diffeomorphometry. Cortical thickness was calculated by deforming the gray matter-white matter boundary surface to the pial surface using an approach called normal geodesic flow. The surface was parcellated based on four atlases using large deformation diffeomorphic metric mapping. Average cortical thickness was calculated for (1) manually-defined entorhinal cortex, and (2) manually-defined transentorhinal cortex. Group-wise difference analysis was applied to determine where atrophy occurred, and change point analysis was applied to determine when atrophy started to occur. The results showed that by the time a diagnosis of mild cognitive impairment is made, the transentorhinal cortex and entorhinal cortex was up to 0.6 mm thinner than a control with normal cognition. A change point in atrophy rate was detected in the transentorhinal cortex 9–14 years prior to a diagnosis of mild cognitive impairment, and in the entorhinal cortex 8–11 years prior. The findings are consistent with autopsy findings that demonstrate neuronal changes in the transentorhinal cortex before the entorhinal cortex.

Gray Matter Densities in Limbic Areas and APOE4 Independently Predict Cognitive Decline in Normal Brain Aging

Cross-sectional magnetic resonance imaging (MRI) studies reported significant associations between gray matter (GM) density changes in various limbic and neocortical areas and worst cognitive performances in elderly controls. Longitudinal studies in this field remain scarce and led to conflicting data. We report a clinico-radiological investigation of 380 cognitively preserved individuals who undergo neuropsychological assessment at baseline and after 18 months. All cases were assessed using a continuous cognitive score taking into account the global evolution of neuropsychological performances. The vast majority of Mini Mental State Examination (MMSE) 29 and 30 cases showed equal or worst performance at follow-up due to a ceiling effect. GM densities, white matter hyperintensities and arterial spin labeling (ASL) values were assessed in the hippocampus, amygdala, mesial temporal and parietal cortex at inclusion using 3 Tesla MRI Scans. Florbetapir positron emission tomography (PET) amyloid was available in a representative subsample of 64 cases. Regional amyloid uptake ratios (SUVr), mean cortical SUVr values (mcSUVr) and corresponding z-scores were calculated. Linear regression models were built to explore the association between the continuous cognitive score and imaging variables. The presence of an APOE-ε4 allele was negatively related to the continuous cognitive score. Among the areas studied, significant associations were found between GM densities in the hippocampus and amygdala but not mesial temporal and parietal areas and continuous cognitive score. Neither ASL values, Fazekas score nor mean and regional PET amyloid load was related to the cognitive score. In multivariate models, the presence of APOE-ε4 allele and GM densities in the hippocampus and amygdala were independently associated with worst cognitive evolution at follow-up. Our data support the idea that early GM damage in the hippocampus and amygdala occur long before the emergence of the very first signs of cognitive failure in brain aging.

Untold New Beginnings: Adult Hippocampal Neurogenesis and Alzheimer's Disease

Neurogenesis occurs in a limited number of brain regions during adulthood. Of these, the hippocampus has attracted great interest due to its involvement in memory processing. Moreover, both the hippocampus and the main area that innervates this structure, namely the entorhinal cortex, show remarkable atrophy in patients with Alzheimer's disease (AD). Adult hippocampal neurogenesis is a process that continuously gives rise to newborn granule neurons in the dentate gyrus. These cells coexist with developmentally generated granule neurons in this structure, and both cooperative and competition phenomena regulate the communication between these two types of cells. Importantly, it has been revealed that GSK-3β and tau proteins, which are two of the main players driving AD pathology, are cornerstones of adult hippocampal neurogenesis regulation. We have shown that alterations either promoting or impeding the actions of these two proteins have detrimental effects on the structural plasticity of granule neurons. Of note, these impairments occur both under basal conditions and in response to detrimental and neuroprotective stimuli. Thus, in order to achieve the full effectiveness of future therapies for AD, we propose that attention be turned toward identifying the pathological and physiological actions of the proteins involved in the pathogenesis of this condition.

The effects of exercise on the structure of cognitive related brain regions: a meta-analysis of functional neuroimaging data

OBJECTIVE

Numerous previous studies have suggested that physical activity or exercise may play an important role in both structural integrity of the brain and cognitive function. However, it is unclear what effect exercise has on cognitive related brain structure. The present study comprehensively reviews the effect of exercise on cognitive related brain regions of the healthy elderly by using activation likelihood estimation (ALE).

MATERIALS AND METHODS

Seven electronic databases were searched for randomized controlled trials published up to September 2017. The quality of the selected studies was evaluated using the Cochrane Collaboration's tool for assessing the risk of bias. GingerALE version 2.3.6 was used to perform the coordinate-based ALE meta-analysis.

RESULTS AND CONCLUSIONS

Nine randomized controlled trials (RCTs) with 50 distinct foci were analyzed for structural changes, containing 412 healthy older subjects. ALE showed significant regional increases in regions including the left superior temporal gyrus, left medial temporal gyrus, left inferior frontal gyrus, right medial frontal gyrus, right and left superior frontal gyrus, left cingulate gyrus, right anterior cingulate and left lentiform nucleus in subjects with the exercise intervention compared to controls. However, considering the quantity and limitations of the included studies, the conclusion could not yet be drawn. Additional randomized controlled trials with rigorous designs and longer intervention periods are needed in the future.

Body mass index and its relation to neuropsychological functioning and brain volume in healthy older adults

Obesity is a growing concern worldwide because of its adverse health effects, including its negative impact on cognitive functioning. This concern is especially relevant for older adults, who are already likely to experience some cognitive decline and loss of brain volume due to aging, (Gea et al., 2002). However, there is some evidence that higher body mass index (BMI) may actually be protective in later life (Hughes et al., 2009; Luchsinger et al., 2007; Nilsson and Nilsson, 2009; Sturman et al., 2008). Therefore, the purpose of the current study was to assess the relationship between BMI and neuropsychological functioning in older adults, and concurrently the relationship between BMI and brain volume. Older adults (N = 88) reported height and weight to determine BMI (M = 26.5) based on Centers for Disease Control and Prevention (CDC) guidelines. Cognitive function was assessed with the Repeatable Battery for Assessment of Neuropsychological Status (RBANS). Brain volume measurements were evaluated via structural MRI. Results indicated no association between BMI and neuropsychological functioning. There was a significant association between BMI and total grey matter volume while controlling for age and years of education (β = 0.208, p = .026, ΔR² = 0.043), indicating that as BMI increased, brain volume in these areas modestly increased. However, these results did not survive multiple comparison corrections and were further attenuated to near significance when sex was explicitly added as an additional covariate. Nevertheless, while replication is clearly needed, these results suggest that moderately greater BMI in later life may modestly attenuate concomitant grey matter volume decline.

Automated versus manual segmentation of brain region volumes in former football players

Objectives

To determine whether or not automated FreeSurfer segmentation of brain regions considered important in repetitive head trauma can be analyzed accurately without manual correction.

Materials and methods

3 T MR neuroimaging was performed with automated FreeSurfer segmentation and manual correction of 11 brain regions in former National Football League (NFL) players with neurobehavioral symptoms and in control subjects. Automated segmentation and manually-corrected volumes were compared using an intraclass correlation coefficient (ICC). Linear mixed effects regression models were also used to estimate between-group mean volume comparisons and to correlate former NFL player brain volumes with neurobehavioral factors.

Results

Eighty-six former NFL players (55.2 ± 8.0 years) and 22 control subjects (57.0 ± 6.6 years) were evaluated. ICC was highly correlated between automated and manually-corrected corpus callosum volumes (0.911), lateral ventricular volumes (right 0.980, left 0.967), and amygdala-hippocampal complex volumes (right 0.713, left 0.731), but less correlated when amygdalae (right -0.170, left -0.090) and hippocampi (right 0.539, left 0.637) volumes were separately delineated and also less correlated for cingulate gyri volumes (right 0.639, left 0.351). Statistically significant differences between former NFL player and controls were identified in 8 of 11 regions with manual correction but in only 4 of 11 regions without such correction. Within NFL players, manually corrected brain volumes were significantly associated with 3 neurobehavioral factors, but a different set of 3 brain regions and neurobehavioral factor correlations was observed for brain region volumes segmented without manual correction.

Conclusions

Automated FreeSurfer segmentation of the corpus callosum, lateral ventricles, and amygdala-hippocampus complex may be appropriate for analysis without manual correction. However, FreeSurfer segmentation of the amygdala, hippocampus, and cingulate gyrus need further manual correction prior to performing group comparisons and correlations with neurobehavioral measures.

Phenotype-Dependent Interactions between N-acetyl-L-Aspartate and Acetyl-CoA in Septal SN56 Cholinergic Cells Exposed to an Excess of Zinc

Pyruvate dehydrogenase reaction utilizing glucose-derived pyruvate is an almost exclusive source of acetyl-CoA in different cell mitochondrial compartments of the brain. In neuronal mitochondria, the largest fraction of acetyl-CoA is utilized for energy production and the much smaller one for N-acetyl-L-aspartate (NAA) synthesis. Cholinergic neurons, unlike others, require additional amounts of acetyl-CoA for acetylcholine synthesis. Therefore, several neurotoxic signals, which inhibit pyruvate dehydrogenase, generate deeper shortages of acetyl-CoA and greater mortality of cholinergic neurons than noncholinergic ones. NAA is considered to be a marker of neuronal energy status in neuropathic brains. However, there is no data on putative differential fractional distribution of the acetyl-CoA pool between energy producing and NAA or acetylcholine synthesizing pathways in noncholinergic and cholinergic neurons, respectively. Therefore, the aim of this study was to investigate whether zinc-excess, a common excitotoxic signal, may evoke differential effects on the NAA metabolism in neuronal cells with low and high expression of the cholinergic phenotype. Differentiated SN56 neuronal cells, displaying a high activity of choline acetyltransferase and rates of acetylcholine synthesis, contained lower levels of acetyl-CoA and NAA, being more susceptible to ZnCl2 exposition that the nondifferentiated SN56 or differentiated dopaminergic SHSY5Y neuronal and astroglial C6 cells. Differentiated SN56 accumulated greater amounts of Zn2 + from extracellular space than the other ones, and displayed a stronger suppression of pyruvate dehydrogenase complex activity and acetyl-CoA, NAA, ATP, acetylcholine levels, and loss of viability. These data indicate that the acetyl-CoA synthesizing system in neurons constitutes functional unity with energy generating and NAA or acetylcholine pathways of its utilization, which are uniformly affected by neurotoxic conditions.

[Perspectives of the diagnosis of Alzheimer's disease using optic coherent tomography]

There is a constant search for new possibilities of the diagnosis of neurodegenerative diseases that cause dementia. The problem is important because of the growing prevalence of dementia, 60-80% of which are caused by Alzheimer's disease (AD). Over the last years, changes in the retina are thought to be a marker neurodegeneration. Assessment of these changes is performed using a method of optical coherent tomography (OCT) that allows taking cross-sectional imaging of a tissue. OCT is considered a potential biomarker of the early stage of AD. Identification of the relationship of the changes in retina and the optic nerve with cognitive impairment open new possibilities for the diagnosis of AD.

BIOMARKER CHANGE-POINT ESTIMATION WITH RIGHT CENSORING IN LONGITUDINAL STUDIES

We consider in this paper a statistical two-phase regression model in which the change point of a disease biomarker is measured relative to another point in time, such as the manifestation of the disease, which is subject to right-censoring (i.e., possibly unobserved over the entire course of the study). We develop point estimation methods for this model, based on maximum likelihood, and bootstrap validation methods. The effectiveness of our approach is illustrated by numerical simulations, and by the estimation of a change point for amygdalar atrophy in the context of Alzheimer's disease, wherein it is related to the cognitive manifestation of the disease.

When are metabolic ratios superior to absolute quantification? A statistical analysis

Metabolite levels measured using magnetic resonance spectroscopy (MRS) are often expressed as ratios rather than absolute concentrations. However, the inter-subject variability of the denominator metabolite can introduce uncertainty into a metabolite ratio. In a clinical setting, there are no guidelines on whether ratios or absolute quantification should be used for a more accurate classification of normal versus abnormal results based on their statistical properties. In a research setting, the choice of one over the other can have significant implications on sample size, which must be factored in at the study design stage. Herein, we derive the probability distribution function for the ratio of two normally distributed random variables, and present analytical expressions for the comparison of ratios with absolute quantification in terms of both sample size and area under the receiver operator characteristic curve. The two approaches are compared for typical metabolite values found in the literature, and their respective merits are illustrated using previously acquired clinical MRS data in two pathologies: mild traumatic brain injury and multiple sclerosis. Our analysis shows that the decision between ratios and absolute quantification is non-trivial: in some cases, ratios might offer a reduction in sample size, whereas, in others, absolute quantification might prove more desirable for individual (i.e. clinical) use. The decision is straightforward and exact guidelines are provided in the text, given that population means and standard deviations of numerator and denominator can be reliably estimated.

Hippocampal and Amygdala Gray Matter Loss in Elderly Controls with Subtle Cognitive Decline

In contrast to the idea that hippocampal and amygdala volume loss occur in late phases of neurodegeneration, recent contributions point to the relevance of preexisting structural deficits that are associated with aging and are independent of amyloid deposition in preclinical Alzheimer disease cases. The present work explores GM hippocampal and amygdala volumes in elderly controls displaying the first signs of cognitive decline. 455 subjects (263 females), including 374 controls (228 females) and 81 middle cognitive impairment subjects (35 females), underwent two neuropsychological evaluations (baseline and 18 months follow-up) and a MRI-T1 examination (only baseline). Clinical assessment included Mini-Mental State Examination (MMSE), Clinical Dementia Rating scale, Hospitalized Anxiety and Depression scale, the Consortium to Establish a Registry for Alzheimer’s Disease neuropsychological battery and RI-48 Cued Recall Test (RI-48) for episodic memory. Based on their cognitive performance, we defined the controls as stable controls (sCON) and deteriorating controls (dCONs). Analyses included volumetric assessment, shape analyses and linear regressions between GM volume loss and differences in clinical scores between baseline and follow-up. Significant GM volume decrease in hippocampus bilaterally and right amygdala was found in dCON compared to sCON (p < 0.05). Lower right amygdala volumes were measured in mild cognitive impairment (MCI) compared to sCON (p < 0.05). Shape analyses revealed that atrophy was more pronounced at the superior- posterior lateral side of the hippocampus and amygdala. Significant correlations were found between GM volume of left hippocampus and the delta of MMSE and RI-48 scores in dCON and MCI groups separately. Decreased hippocampal and right amygdala volumes precede the first signs of cognitive decline in healthy elderly controls at the pre-MCI state. Left hippocampus volume may also predict short-term changes of overall cognition in these vulnerable cases.

Advancing research diagnostic criteria for Alzheimer's disease: the IWG-2 criteria

In the past 8 years, both the International Working Group (IWG) and the US National Institute on Aging-Alzheimer's Association have contributed criteria for the diagnosis of Alzheimer's disease (AD) that better define clinical phenotypes and integrate biomarkers into the diagnostic process, covering the full staging of the disease. This Position Paper considers the strengths and limitations of the IWG research diagnostic criteria and proposes advances to improve the diagnostic framework. On the basis of these refinements, the diagnosis of AD can be simplified, requiring the presence of an appropriate clinical AD phenotype (typical or atypical) and a pathophysiological biomarker consistent with the presence of Alzheimer's pathology. We propose that downstream topographical biomarkers of the disease, such as volumetric MRI and fluorodeoxyglucose PET, might better serve in the measurement and monitoring of the course of disease. This paper also elaborates on the specific diagnostic criteria for atypical forms of AD, for mixed AD, and for the preclinical states of AD.

Mild cognitive impairment. Part 2: Biological markers for diagnosis and prediction of dementia in Alzheimer's disease

OBJECTIVE

To present a critical review of publications reporting on the rationale and clinical implications of the use of biomarkers for the early diagnosis of Alzheimer's disease (AD).

METHODS

We conducted a systematic search of the PubMed and Web of Science electronic databases, limited to articles published in English between 1999 and 2012, and based on the following terms: mild cognitive impairment, Alzheimer's disease OR dementia, biomarkers. We retrieved 1,130 articles, of which 175 were reviews. Overall, 955 original articles were eligible.

RESULTS

The following points were considered relevant for the present review: a) rationale for biomarkers research in AD and mild cognitive impairment (MCI); b) usefulness of distinct biomarkers for the diagnosis and prediction of AD; c) the role of multimodality biomarkers for the diagnosis and prediction of AD; d) the role of biomarkers in clinical trials of patients with AD and MCI; and e) current limitations to the widespread use of biomarkers in research and clinical settings.

CONCLUSION

Different biomarkers are useful for the early diagnosis and prediction of AD in at-risk subjects. Nonetheless, important methodological limitations need to be overcome for widespread use of biomarkers in research and clinical settings.

Inferring changepoint times of medial temporal lobe morphometric change in preclinical Alzheimer's disease

This paper uses diffeomorphometry methods to quantify the order in which statistically significant morphometric change occurs in three medial temporal lobe regions, the amygdala, entorhinal cortex (ERC), and hippocampus among subjects with symptomatic and preclinical Alzheimer's disease (AD). Magnetic resonance imaging scans were examined in subjects who were cognitively normal at baseline, some of whom subsequently developed clinical symptoms of AD. The images were mapped to a common template, using shape-based diffeomorphometry. The multidimensional shape markers indexed through the temporal lobe structures were modeled using a changepoint model with explicit parameters, specifying the number of years preceding clinical symptom onset. Our model assumes that the atrophy rate of a considered brain structure increases years before detectable symptoms.

The results demonstrate that the atrophy changepoint in the ERC occurs first, indicating significant change 8–10 years prior to onset, followed by the hippocampus, 2–4 years prior to onset, followed by the amygdala, 3 years prior to onset. The ERC is significant bilaterally, in both our local and global measures, with estimates of ERC surface area loss of 2.4% (left side) and 1.6% (right side) annually. The same changepoint model for ERC volume gives 3.0% and 2.7% on the left and right sides, respectively. Understanding the order in which changes in the brain occur during preclinical AD may assist in the design of intervention trials aimed at slowing the evolution of the disease.

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We use diffeomorphometry to quantify the order in which statistically significant morphometric change occurs in three medial temporal lobe regions, the amygdala, entorhinal cortex (ERC), and hippocampus among subjects with symptomatic and preclinical Alzheimer's disease (AD).

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We introduce a model on anatomical shape change in which changepoint is inferred, taking place some period of time before cognitive onset of AD.

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The analysis uses a dataset arising from the BIOCARD study, in which all subjects were cognitively normal at baseline, some of whom subsequently developed clinical symptoms of AD.

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The results demonstrate that the atrophy changepoint in the ERC occurs first, indicating significant change 8-10 years prior to onset, followed by hippocampus, 2-4 years prior to onset, followed by amygdala, 3 years prior to onset.

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The ERC is significant bilaterally, in both our local and global measures, with estimates of ERC surface area loss of 2.4% (left side) and 1.6% (right side) annually.

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Understanding the order in which changes in the brain occur during preclinical AD may assist in the design of intervention trials aimed at slowing the evolution of the disease.

Automated algorithm to measure changes in medial temporal lobe volume in Alzheimer disease

BACKGROUND

The change in volume of anatomic structures is as a sensitive indicator of Alzheimer disease (AD) progression. Although several methods are available to measure brain volumes, improvements in speed and automation are required. Our objective was to develop a fully automated, fast, and reliable approach to measure change in medial temporal lobe (MTL) volume, including primarily hippocampus.

METHODS

The MTL volume defined in an atlas image was propagated onto each baseline image and a level set algorithm was applied to refine the shape and smooth the boundary. The MTL of the baseline image was then mapped onto the corresponding follow-up image to measure volume change (ΔMTL). Baseline and 24 months 3D T1-weighted images from the Alzheimer Disease Neuroimaging Initiative (ADNI) were randomly selected for 50 normal elderly controls (NECs), 50 subjects with mild cognitive impairment (MCI) and 50 subjects with AD to test the algorithm. The method was compared to the FreeSurfer segmentation tools.

RESULTS

The average ΔMTL (mean±SEM) was 68±35mm(3) in NEC, 187±38mm(3) in MCI and 300±34mm(3) in the AD group and was significantly different (p<0.0001) between all three groups. The ΔMTL was correlated with cognitive decline.

COMPARISON WITH EXISTING METHOD(S)

Results for the FreeSurfer software were similar but did not detect significant differences between the MCI and AD groups.

CONCLUSION

This novel segmentation approach is fully automated and provides a robust marker of brain atrophy that shows different rates of atrophy over 2 years between NEC, MCI, and AD groups.

Sensitivity and specificity of diagnostic accuracy in Alzheimer's disease: a synthesis of existing evidence

PURPOSE OF THE STUDY

This report synthesizes existing evidence to compare the accuracy of various Alzheimer's disease (AD) diagnostic approaches.

DESIGN AND METHODS

Meta-analyses and reviews of diagnostic accuracy of AD were identified through a search of the PubMed and Cochrane Library databases using the keyword combinations of "sensitivity specificity Alzheimer's disease diagnosis" and "accuracy of Alzheimer's disease diagnosis."

RESULTS

From 507 abstracts initially identified, 41 systematic reviews or meta-analyses were selected. Cerebrospinal fluid-tau demonstrated variable sensitivity (range 73.3%-100%) and specificity (range 70.0%-92.4%) in diagnosing AD when compared to neuropathological verification of clinical criteria for AD. Various positron emission tomography approaches showed a similar range of sensitivity (range 80.0%-100%) and specificity (range 62.0%-90%) as diagnostic protocols.

IMPLICATIONS

Issues that remain in the study of AD diagnosis include the need to determine the comparative effectiveness of diagnostic approaches. Variations in study quality make empirically derived conclusions about the diagnostic accuracy of existing approaches tenuous.

Changes in cerebral morphometry and amplitude of low-frequency fluctuations of BOLD signals during healthy aging: correlation with inhibitory control

Aging is known to be associated with changes in cerebral morphometry and in regional activations during resting or cognitive challenges. Here, we investigated the effects of age on cerebral gray matter (GM) volumes and fractional amplitude of low-frequency fluctuation (fALFF) of blood oxygenation level-dependent signals in 111 healthy adults, 18-72 years of age. GM volumes were computed using voxel-based morphometry as implemented in Statistical Parametric Mapping, and fALFF maps were computed for task-residuals as described in Zhang and Li (Neuroimage 49:1911-1918, 2010) for individual participants. Across participants, a simple regression against age was performed for GM volumes and fALFF, respectively, with quantity of recent alcohol use as a covariate. At cluster level p < 0.05, corrected for family-wise error of multiple comparisons, GM volumes declined with age in prefrontal/frontal regions, bilateral insula, and left inferior parietal lobule (IPL), suggesting structural vulnerability of these areas to aging. FALFF was negatively correlated with age in the supplementary motor area (SMA), pre-SMA, anterior cingulate cortex, bilateral dorsal lateral prefrontal cortex (DLPFC), right IPL, and posterior cingulate cortex, indicating that spontaneous neural activities in these areas during cognitive performance decrease with age. Notably, these age-related changes overlapped in the prefrontal/frontal regions including the pre-SMA, SMA, and DLPFC. Furthermore, GM volumes and fALFF of the pre-SMA/SMA were negatively correlated with the stop signal reaction time, in accord with our earlier work. Together, these results describe anatomical and functional changes in prefrontal/frontal regions and how these changes are associated with declining inhibitory control during aging.

The relationship between cortical blood flow and sub-cortical white-matter health across the adult age span

Degeneration of cerebral white matter is commonly observed in aging, and the associated degradation in neural connectivity contributes to cognitive decline in older adults. Vascular dysfunction has been implicated as a potential mechanism for general age-related neural tissue deterioration; however, no prior study has examined the direct relationship between cortical vascular health and subcortical white-matter integrity. In this work, we aimed to determine whether blood supply to the brain is associated with microstructural integrity of connective tissue, and whether such associations are regionally specific and mainly accounted for by aging. We examined the association between cerebral blood flow (CBF) in the cortical mantle, measured using arterial spin labeling (ASL), and subcortical white-matter integrity, measured using diffusion tensor imaging (DTI), in a group of healthy adults spanning early to late adulthood. We found cortical CBF to be significantly associated with white-matter integrity throughout the brain. In addition, these associations were only partially tied to aging, as they remained even when statistically controlling for age, and when restricting the analyses to a young subset of the sample. Furthermore, vascular risk was not a prominent determinant of these effects. These findings suggest that the overall blood supply to the brain is an important indicator of white-matter health in the normal range of variations amongst adults, and that the decline in CBF with advancing age may potentially exacerbate deterioration of the connective anatomy of the brain.

The Framingham Brain Donation Program: neuropathology along the cognitive continuum

The Framingham Heart Study has enrolled 3 generations of participants, the original cohort (gen 1) enrolled in 1948, the offspring cohort (gen 2) enrolled in 1971 and the third generation enrolled in 2002. Participants have been undergoing prospective surveillance for incident stroke and dementia and embedded within this cohort is the voluntary Framingham Brain Donation Program that was begun in 1997. Participants who register to become brain donors have had one or more brain MR and cognitive test batteries administered. In addition, they undergo neurological evaluation as indicated, record review and post-mortem next-of-kin interview to determine the presence, type and extent of antemortem, clinical neurological diagnoses and to assign a retrospective clinical dementia rating (CDR) Scale score. Between 1997 and 2009 there were 1806 deaths, 186 of which were among registered brain donors and of these 139 brains could be examined. 58% were deemed cognitively normal at death. We present results for 3 projects; the first was to examine the sensitivity and specificity of our clinical diagnosis against the gold standard of pathological AD in 59 persons who underwent detailed cognitive assessment in the two years prior to death; we observed a 77.3% sensitivity (2 persons with AD were diagnosed clinically as Lewy body dementia) and a 91.9% specificity. The second examined the correlation of regional Alzheimer-type pathology to cognitive status at death among 34 persons who were over the age of 75 and without any significant vascular or alternative neurodegenerative pathology and found that neurofibrillary tangle counts distinguished between persons who were controls, had mild cognitive impairment, mild or moderate dementia; tangles in dorsolateral frontal cortex best distinguished MCI and controls. The third project examined the extent and severity of vascular pathology, again in a larger sample of varying cognitive abilities and in a subsample of persons with either amnestic or nonamnestic MCI. We observed that an aggregate ischemic injury score was significantly higher in persons with a CDR score of 0.5 than in normal controls.

The diagnosis and evaluation of dementia and mild cognitive impairment with emphasis on SPECT perfusion neuroimaging

As the world population ages, the incidence of dementing illnesses will dramatically increase. The number of people afflicted with dementia is expected to quadruple in the next 50 years. Since the neuropathology of the dementias precedes clinical symptoms often by several years, earlier detection and intervention could be key steps to mitigating the progression and burden of these diseases. This review will explore methods of evaluating, differentiating, and diagnosing the multiple forms of dementia. Particular emphasis will be placed on the diagnosis of mild cognitive impairment-the precursor to dementia. Anatomical imaging; cerebrospinal fluid markers; functional neuroimaging, such as positron emission tomography and single photon emission tomography; and molecular imaging, such as amyloid marker imaging, will be assessed in terms of sensitivity and specificity. Cost will also be a consideration, as the growing population afflicted with dementia represents an increasingly large financial encumbrance to the healthcare systems of every nation. In the face of expensive new markers and limited availability of cyclotrons, single photon emission computer tomography (SPECT) provides relatively high sensitivity and specificity at a comparatively low overall cost.

Feed-forward hierarchical model of the ventral visual stream applied to functional brain image classification

Functional brain imaging is a common tool in monitoring the progression of neurodegenerative and neurological disorders. Identifying functional brain imaging derived features that can accurately detect neurological disease is of primary importance to the medical community. Research in computer vision techniques to identify objects in photographs have reported high accuracies in that domain, but their direct applicability to identifying disease in functional imaging is still under investigation in the medical community. In particular, Serre et al. (: In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR-05). pp 994-1000) introduced a biophysically inspired filtering method emulating visual processing in striate cortex which they applied to perform object recognition in photographs. In this work, the model described by Serre et al. [2005] is extended to three-dimensional volumetric images to perform signal detection in functional brain imaging (PET, SPECT). The filter outputs are used to train both neural network and logistic regression classifiers and tested on two distinct datasets: ADNI Alzheimer's disease 2-deoxy-D-glucose (FDG) PET and National Football League players Tc99m HMPAO SPECT. The filtering pipeline is analyzed to identify which steps are most important for classification accuracy. Our results compare favorably with other published classification results and outperform those of a blinded expert human rater, suggesting the utility of this approach.

Prediction of conversion from mild cognitive impairment to Alzheimer's disease dementia based upon biomarkers and neuropsychological test performance

The current study tested the accuracy of primary MRI and cerebrospinal fluid (CSF) biomarker candidates and neuropsychological tests for predicting the conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia. In a cross-validation paradigm, predictor models were estimated in the training set of AD (N = 81) and elderly control subjects (N = 101). A combination of CSF t-tau/Aβ(1-4) ratio and MRI biomarkers or neuropsychological tests (free recall and trail making test B (TMT-B)) showed the best statistical fit in the AD vs. HC comparison, reaching a classification accuracy of up to 64% when applied to the prediction of MCI conversion (3.3-year observation interval, mean = 2.3 years). However, several single-predictor models showed a predictive accuracy of MCI conversion comparable to that of any multipredictor model. The best single predictors were right entorhinal cortex (prediction accuracy = 68.5% (95% CI (59.5, 77.4))) and TMT-B test (prediction accuracy 64.6% (95% CI (55.5, 73.4%))). In conclusion, short-term conversion to AD is predicted by single marker models to a comparable degree as by multimarker models in amnestic MCI subjects.

Structural and functional neuroimaging methods in the diagnosis of dementias: a retrospective chart and brain imaging review

OBJECTIVE

Assess the contribution of structural and functional neuroimaging methods to the diagnosis of dementia.

METHODS

This was a retrospective chart and imaging review. Participants were 24 inpatient dementia cases from a general hospital-based, university medical psychiatry unit. Data from clinical charts and imaging results were reviewed.

RESULTS

Most common initial diagnoses were dementia NOS and vascular dementia (VD); most common discharge diagnoses were VD, Alzheimer's, Dementia NOS and dementia with Lewy bodies. Most diagnostic changes occurred following family meetings or SPECT/PET, with fewer changes after CT/MRI.

CONCLUSIONS

Diagnostic steps that contributed the most to the final diagnosis were the family meeting and the functional neuroimaging evaluation.

Alzheimer's disease: a clinical practice-oriented review

Investigation in the field of Alzheimer's disease (AD), the commonest cause of dementia, has been very active in recent years and it may be difficult for the clinician to keep up with all the innovations and to be aware of the implications they have in clinical practice. The authors, thus, reviewed recent literature on the theme in order to provide the clinician with an updated overview, intended to support decision-making on aspects of diagnosis and management. This article begins to focus on the concept of AD and on its pathogenesis. Afterward, epidemiology and non-genetic risk factors are approached. Genetics, including genetic risk factors and guidelines for genetic testing, are mentioned next. Recommendations for diagnosis of AD, including recently proposed criteria, are then reviewed. Data on the variants of AD is presented. First approach to the patient is dealt with next, followed by neuropsychological evaluation. Biomarkers, namely magnetic resonance imaging, single photon emission tomography, FDG PET, PiB PET, CSF tau, and Aβ analysis, as well as available data on their diagnostic accuracy, are also discussed. Factors predicting rate of disease progression are briefly mentioned. Finally, non-pharmacological and pharmacological treatments, including established and emerging drugs, are addressed.

Label fusion strategy selection

Label fusion is used in medical image segmentation to combine several different labels of the same entity into a single discrete label, potentially more accurate, with respect to the exact, sought segmentation, than the best input element. Using simulated data, we compared three existing label fusion techniques—STAPLE, Voting, and Shape-Based Averaging (SBA)—and observed that none could be considered superior depending on the dissimilarity between the input elements. We thus developed an empirical, hybrid technique called SVS, which selects the most appropriate technique to apply based on this dissimilarity. We evaluated the label fusion strategies on two- and three-dimensional simulated data and showed that SVS is superior to any of the three existing methods examined. On real data, we used SVS to perform fusions of 10 segmentations of the hippocampus and amygdala in 78 subjects from the ICBM dataset. SVS selected SBA in almost all cases, which was the most appropriate method overall.

The PREVENT study: a prospective cohort study to identify mid-life biomarkers of late-onset Alzheimer's disease

INTRODUCTION

Epidemiological studies indicate that significant decreases in the incidence of Alzheimer's disease (AD) may be obtained by targeting multiple middle-age risk factors. However, as dementia is unlikely to be diagnosed for decades, short-term outcome measures are required. AD biomarker changes precede clinical symptoms by many years, but their sensitivity to mid-life change remains unknown.

METHODS AND ANALYSIS

PREVENT is a prospective cohort study examining biomarker status at mid-life in at least 150 individuals genetically at high, medium or low risk of late-onset AD. Participants are children of individuals with or without a diagnosed AD allocated to high, medium and low-risk groups according to parental clinical status and ApoE genotype. The biomarkers examined over 2 years are plasma and CSF Aβ42 amyloid, Tau and pTau, proinflammatory cytokines, acute-phase proteins, medial temporal-lobe atrophy, white matter lesion volume, cognitive performance related to transentorhinal and hippocampal functioning and hypothalamic-pituitary-adrenal and sympathetic axes regulation.

ETHICS AND DISSEMINATION

Detected pathologies are communicated to the participant's general practitioner with their permission. Risk status by genotype would not be revealed. The results of the study would be published in peer-reviewed journals and validated biomarkers used to construct a randomised controlled intervention study.

Is Alzheimer's disease amyloidosis the result of a repair mechanism gone astray?

Here, we synthesize several lines of evidence supporting the hypothesis that at least one function of amyloid-β is to serve as a part of the acute response to brain hemodynamic disturbances intended to seal vascular leakage. Given the resilient and adhesive physicochemical properties of amyloid, an abluminal hemostatic repair system might be highly advantageous, if deployed on a limited and short-term basis, in young individuals. However, in the aged, inevitable cardiovascular dysfunction combined with brain microvascular lesions may yield global chronic hypoperfusion that may lead to continuous amyloid deposition and consequential negative effects on neuronal viability. A large body of experimental evidence supports the hypothesis of an amyloid-β rescue function gone astray. Preventing or inducing the removal of amyloid in Alzheimer's disease (AD) has been simultaneously successful and disappointing. Amyloid deposits clearly play major roles in AD, but they may not represent the preeminent factor in dementia pathogenesis. Successful application of AD preventative approaches may hinge on an accurate and comprehensive view of comorbidities, including cardiovascular disease, diabetes, and head trauma.

Nuclear medicine imaging in dementia: a practical overview for hospitalists

Dementia is a clinical syndrome with diverse presentation, a challenging differential diagnosis, and time-sensitive therapy. The most common cause of dementia in patients aged > 65 years is Alzheimer's disease, which now affects 4 million people in the United States, but is often underrecognized, especially in the inpatient population. The hospitalist may have the opportunity to evaluate a patient's initial presentation of dementia. Addressing the inpatient's dementia symptoms can improve overall care and outcomes, so it is imperative that the hospitalist is abreast of recent developments in the dementia workup. The focus of this article is to overview how nuclear medicine imaging of the brain can aid in this process, with perfusion single-photon emission computed tomography (SPECT) and fludeoxyglucose F 18 ((18)F-FDG) positron emission tomography (PET) as the 2 most common modalities. Our discussion focuses on Alzheimer's disease, as this the most common etiology of dementia in patients aged > 65 years; however, we also touch on the other common neurodegenerative dementias (eg, dementia with Lewy bodies, vascular dementia, and frontotemporal dementia) for completeness. We begin with a summary of the most recent published guidelines for each of these neurodegenerative diseases, and then expand on the role that nuclear imaging plays in each. We provide a basic overview of the principles of these nuclear medicine techniques, and then illustrate findings in perfusion SPECT and (18)F-FDG PET for typical patterns of dementia, with emphasis on evidence regarding diagnostic accuracy of each modality, in comparison with accepted gold standards. Finally, we outline some future research topics within the field of nuclear medicine in dementia, including amyloid plaque imaging and dopamine transporter imaging.

The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease

The National Institute on Aging and the Alzheimer's Association charged a workgroup with the task of developing criteria for the symptomatic predementia phase of Alzheimer's disease (AD), referred to in this article as mild cognitive impairment due to AD. The workgroup developed the following two sets of criteria: (1) core clinical criteria that could be used by healthcare providers without access to advanced imaging techniques or cerebrospinal fluid analysis, and (2) research criteria that could be used in clinical research settings, including clinical trials. The second set of criteria incorporate the use of biomarkers based on imaging and cerebrospinal fluid measures. The final set of criteria for mild cognitive impairment due to AD has four levels of certainty, depending on the presence and nature of the biomarker findings. Considerable work is needed to validate the criteria that use biomarkers and to standardize biomarker analysis for use in community settings.