On the multivariate nature of brain metabolic impairment in Alzheimer's disease

Cerebral glucose metabolism in Alzheimer's disease

18F-fluoro-deoxy-glucose positron emission tomography (FDG-PET) is a useful paraclinical exam for the diagnosis of Alzheimer's disease (AD). In this narrative review, we report seminal studies in clinically probable AD that have shown the importance of posterior brain metabolic decrease and the paradoxical variability of the hippocampal metabolism. The FDG-PET pattern was a sensitive indicator of AD in pathologically confirmed cases and it was used for differential diagnosis of dementia conditions. In prodromal AD, the AD FDG-PET pattern was observed in converters and predicted conversion. Automated data analysis techniques provided variable accuracy according to the reported indices and machine learning methods showed variable reliability of results. FDG-PET could confirm AD clinical heterogeneity and image data driven analyses identified hypometabolic subtypes with variable involvement of the hippocampus, reminiscent if the paradoxical FDG uptake. In studies dedicated to clinical and metabolic correlations, episodic memory was related to metabolism in the default mode network (and Papez's circuit) in prodromal and mild AD stages, and specific cognitive processes were associated to precisely distributed brain metabolism. Cerebral metabolic correlates of anosognosia could also be related to current neuropsychological models. AD FDG-PET pattern was reported in preclinical AD stages and related to cognition or to conversion to mild cognitive impairment (MCI). Using other biomarkers, the AD FDG-PET pattern was confirmed in AD participants with positive PET-amyloid. Intriguing observations reported increased metabolism related to brain amyloid and/or tau deposition. Preserved glucose metabolism sometimes appear as a compensation, but it was frequently detrimental and the nature of such a preservation of glucose metabolism remains an open question. Limbic metabolic involvement was frequently related to non-AD biomarkers profile and clinical stability, and it was reported in non-AD pathologies, such as the limbic predominant age-related encephalopathy (LATE). FDG-PET abnormalities observed in the absence of classical AD proteinopathies can be useful to search for pathological mechanisms and differential diagnosis of AD.

Principal component analysis of synaptic density measured with [11C]UCB-J PET in early Alzheimer's disease

BACKGROUND

Synaptic loss is considered an early pathological event and major structural correlate of cognitive impairment in Alzheimer's disease (AD). We used principal component analysis (PCA) to identify regional patterns of covariance in synaptic density using [11C]UCB-J PET and assessed the association between principal components (PC) subject scores with cognitive performance.

METHODS

[11C]UCB-J binding was measured in 45 amyloid + participants with AD and 19 amyloid- cognitively normal participants aged 55-85. A validated neuropsychological battery assessed performance across five cognitive domains. PCA was applied to the pooled sample using distribution volume ratios (DVR) standardized (z-scored) by region from 42 bilateral regions of interest (ROI).

RESULTS

Parallel analysis determined three significant PCs explaining 70.2% of the total variance. PC1 was characterized by positive loadings with similar contributions across the majority of ROIs. PC2 was characterized by positive and negative loadings with strongest contributions from subcortical and parietooccipital cortical regions, respectively, while PC3 was characterized by positive and negative loadings with strongest contributions from rostral and caudal cortical regions, respectively. Within the AD group, PC1 subject scores were positively correlated with performance across all cognitive domains (Pearson r = 0.24-0.40, P = 0.06-0.006), PC2 subject scores were inversely correlated with age (Pearson r = -0.45, P = 0.002) and PC3 subject scores were significantly correlated with CDR-sb (Pearson r = 0.46, P = 0.04). No significant correlations were observed between cognitive performance and PC subject scores in CN participants.

CONCLUSIONS

This data-driven approach defined specific spatial patterns of synaptic density correlated with unique participant characteristics within the AD group. Our findings reinforce synaptic density as a robust biomarker of disease presence and severity in the early stages of AD.

The identification and cognitive correlation of perfusion patterns measured with arterial spin labeling MRI in Alzheimer's disease

BACKGROUND

Vascular dysfunction, including cerebral hypoperfusion, plays an important role in the pathogenesis and progression of Alzheimer's disease (AD), independent of amyloid and tau pathology. We established an AD-related perfusion pattern (ADRP) measured with arterial spin labeling (ASL) MRI using multivariate spatial covariance analysis.

METHODS

We obtained multimodal MRI including pseudo-continuous ASL and neurocognitive testing in a total of 55 patients with a diagnosis of mild to moderate AD supported by amyloid PET and 46 normal controls (NCs). An ADRP was established from an identification cohort of 32 patients with AD and 32 NCs using a multivariate analysis method based on scaled subprofile model/principal component analysis, and pattern expression in individual subjects was quantified for both the identification cohort and a validation cohort (23 patients with AD and 14 NCs). Subject expression score of the ADRP was then used to assess diagnostic accuracy and cognitive correlations in AD patients and compared with global and regional cerebral blood flow (CBF) in specific areas identified from voxel-based univariate analysis.

RESULTS

The ADRP featured negative loading in the bilateral middle and posterior cingulate and precuneus, inferior parietal lobule, and frontal areas, and positive loading in the right cerebellum and bilateral basal areas. Subject expression score of the ADRP was significantly elevated in AD patients compared with NCs (P < 0.001) and showed good diagnostic accuracy for AD with area under receiver-operator curve of 0.87 [95% CI (0.78-0.96)] in the identification cohort and 0.85 in the validation cohort. Moreover, there were negative correlations between subject expression score and global cognitive function and performance in various cognitive domains in patients with AD. The characteristics of the ADRP topography and subject expression scores were supported by analogous findings obtained with regional CBF.

CONCLUSIONS

We have reported a characteristic perfusion pattern associated with AD using ASL MRI. Subject expression score of this spatial covariance pattern is a promising MRI biomarker for the identification and monitoring of AD.

Evaluation of in vivo staging of amyloid deposition in cognitively unimpaired elderly aged 78-94

Amyloid-beta (Aβ) deposition is common in cognitively unimpaired (CU) elderly >85 years. This study investigated amyloid distribution and evaluated three published in vivo amyloid-PET staging schemes from a cognitively unimpaired (CU) cohort aged 84.9 ± 4.3 years (n = 75). SUV-based principal component analysis (PCA) was applied to 18F-flutemetamol PET data to determine an unbiased regional covariance pattern of tracer uptake across grey matter regions. PET staging schemes were applied to the data and compared to the PCA output. Concentration of p-tau181 was measured in blood plasma. The PCA revealed three distinct components accounting for 91.2% of total SUV variance. PC1 driven by the large common variance of uptake in neocortical and striatal regions was significantly positively correlated with global SUVRs, APOE4 status and p-tau181 concentration. PC2 represented mainly non-specific uptake in typical amyloid-PET reference regions, and PC3 the occipital lobe. Application of the staging schemes demonstrated that the majority of the CU cohort (up to 93%) were classified as having pathological amount and distribution of Aβ. Good correspondence existed between binary (+/-) classification and later amyloid stages, however, substantial differences existed between schemes for low stages with 8-17% of individuals being unstageable, i.e., not following the sequential progression of Aβ deposition. In spite of the difference in staging outcomes there was broad spatial overlap between earlier stages and PC1, most prominently in default mode network regions. This study critically evaluated the utility of in vivo amyloid staging from a single PET scan in CU elderly and found that early amyloid stages could not be consistently classified. The majority of the cohort had pathological Aβ, thus, it remains an open topic what constitutes abnormal brain Aβ in the oldest-old and what is the best method to determine that.

Going round in circles-The Papez circuit in Alzheimer's disease

The hippocampus is regarded as the pivotal structure for episodic memory symptoms associated with Alzheimer's disease (AD) pathophysiology. However, what is often overlooked is that the hippocampus is 'only' one part of a network of memory critical regions, the Papez circuit. Other Papez circuit regions are often regarded as less relevant for AD as they are thought to sit 'downstream' of the hippocampus. However, this notion is oversimplistic, and increasing evidence suggests that other Papez regions might be affected before or concurrently with the hippocampus. In addition, AD research has mostly focused on episodic memory deficits, whereas spatial navigation processes are also subserved by the Papez circuit with increasing evidence supporting its valuable potential as a diagnostic measure of incipient AD pathophysiology. In the current review, we take a step forward analysing recent evidence on the structural and functional integrity of the Papez circuit across AD disease stages. Specifically, we will review the integrity of specific Papez regions from at-genetic-risk (APOE4 carriers), to mild cognitive impairment (MCI), to dementia stage of sporadic AD and autosomal dominant AD (ADAD). We related those changes to episodic memory and spatial navigation/orientation deficits in AD. Finally, we provide an overview of how the Papez circuit is affected in AD diseases and their specific symptomology contributions. This overview strengthened the need for moving away from a hippocampal-centric view to a network approach on how the whole Papez circuit is affected in AD and contributes to its symptomology, informing future research and clinical approaches.

Principal components of tau positron emission tomography and longitudinal tau accumulation in Alzheimer's disease

Background

We aimed to investigate the clinical correlates of principal components (PCs) of tau positron emission tomography (PET) and their predictability for longitudinal changes in tau accumulation in Alzheimer’s disease (AD).

Methods

We enrolled 272 participants who underwent two PET scans [¹⁸F-flortaucipir for tau and ¹⁸F-florbetaben for amyloid-β (Aβ)], brain magnetic resonance imaging, and neuropsychological tests as baseline assessments. Among them, 187 participants underwent the same follow-up assessments after an average of 2 years. Using Aβ-positive AD dementia-specific PCs obtained from the baseline scans of 56 Aβ-positive patients with AD dementia, we determined the expression of the first two PCs (PC1 and PC2) in all participants. We assessed the correlation of PC expression with baseline clinical characteristics and tau accumulation rates. Moreover, we investigated the predictability of PCs for the longitudinal tau accumulation in training and test sets.

Results

PC1 corresponded to the tau distribution pattern in AD, while the two PC2 extremes reflected the parietal or temporal predominance of tau distribution. PC1 expression increased with tau burden and decreased with cognitive impairment, while PC2 expression decreased with advanced age and visuospatial and attention function deterioration. The tau accumulation rate was positively correlated with PC1 expression (greater tau burden) and negatively correlated with PC2 expression (temporal predominance). A regression model using both PCs could predict longitudinal changes in the tau burden (intraclass correlation coefficient = 0.775, R² = 0.456 in test set).

Conclusions

PC analysis of tau PET could be useful for evaluating disease progression, characterizing the tau distribution pattern, and predicting longitudinal tau accumulation.

Characterization of a temporoparietal junction subtype of Alzheimer's disease

Alzheimer's disease (AD) subtypes have been described according to genetics, neuropsychology, neuropathology, and neuroimaging. Thirty-one patients with clinically probable AD were selected based on perisylvian metabolic decrease on FDG-PET. They were compared to 25 patients with a typical pattern of decreased posterior metabolism. Tree-based machine learning was used on those 56 images to create a classifier that was subsequently applied to 207 Alzheimer's Disease Neuroimaging Initiative (ADNI) patients with AD. Machine learning was also used to discriminate between the two ADNI groups based on neuropsychological scores. Compared to AD patients with a typical precuneus metabolic decrease, the new subtype showed stronger hypometabolism in the temporoparietal junction. The classifier was able to distinguish the two groups in the ADNI population. Both groups could only be distinguished cognitively by Trail Making Test-A scores. This study further confirms that there is more than a typical metabolic pattern in probable AD with amnestic presentation.

Metabolic regional and network changes in Alzheimer's disease subtypes

Clinical variants of Alzheimer's disease (AD) include the common amnestic subtype as well as subtypes characterised by leading visual processing impairments or by multimodal neurocognitive deficits. We investigated regional metabolic patterns and networks between AD subtypes. The study comprised 9 age-matched controls and 25 patients with mild to moderate AD. Methods included clinical and neuropsychological assessment, high-resolution FDG PET and T1-weighted 3D MR imaging with PET-MR coregistration, grey matter segmentation, atlas-based regions-of-interest, linear mixed effects and regional correlation analysis. Regional metabolic patterns differed significantly between groups, but significant hypometabolism in the posterior cingulate cortex (PCC) was common to all subtypes. The most distinctive regional abnormality was occipital hypometabolism in the visual subtype. In controls, two large clusters of positive regional metabolic correlations were observed. The most pronounced breakdown of the normal correlation pattern was found in amnestic patients who, in contrast, showed the least regional focal metabolic deficits. The normal positive correlation between PCC and hippocampus was lost in all subtypes. In conclusion, PCC hypometabolism and metabolic correlation breakdown between PCC and hippocampus are the common functional core of all AD subtypes. Network alterations exceed focal regional impairment and are most prominent in the amnestic subtype.

Clinical validity of brain fluorodeoxyglucose positron emission tomography as a biomarker for Alzheimer's disease in the context of a structured 5-phase development framework

The use of Alzheimer's disease (AD) biomarkers is supported in diagnostic criteria, but their maturity for clinical routine is still debated. Here, we evaluate brain fluorodeoxyglucose positron emission tomography (FDG PET), a measure of cerebral glucose metabolism, as a biomarker to identify clinical and prodromal AD according to the framework suggested for biomarkers in oncology, using homogenous criteria with other biomarkers addressed in parallel reviews. FDG PET has fully achieved phase 1 (rational for use) and most of phase 2 (ability to discriminate AD subjects from healthy controls or other forms of dementia) aims. Phase 3 aims (early detection ability) are partly achieved. Phase 4 studies (routine use in prodromal patients) are ongoing, and only preliminary results can be extrapolated from retrospective observations. Phase 5 studies (quantify impact and costs) have not been performed. The results of this study show that specific efforts are needed to complete phase 3 evidence, in particular comparing and combining FDG PET with other biomarkers, and to properly design phase 4 prospective studies as a basis for phase 5 evaluations.

Predicting the neural effect of switching from donepezil to galantamine based on single-photon emission computed tomography findings in patients with Alzheimer's disease

BACKGROUND

A number of neuroimaging studies have addressed the specific effect of treatment with cholinesterase inhibitors on the frontal lobe in patients with Alzheimer's disease (AD). However, the neural effects of cholinesterase inhibitors on both apathy and executive dysfunction remain unclear. We examined whether baseline regional cerebral blood flow, as determined by using single-photon emission computed tomography, is capable of predicting changes in apathy and executive dysfunction in response to AD patients switching from donepezil to galantamine therapy.

METHODS

We conducted a 24-week, prospective, open-label study of AD patients treated with galantamine who did not respond to previous treatment with donepezil. Single-photon emission computed tomography was performed at baseline, and behaviour and cognitive assessments including the Mini-Mental State Examination, the Japanese version of the Alzheimer's Disease Assessment Scale-cognitive subscale, the Frontal Assessment Battery, the Neuropsychiatry Inventory Brief Questionnaire Form, and the Dysexecutive Questionnaire were conducted at three time points (baseline and after 12 and 24 weeks of galantamine therapy).

RESULTS

After galantamine therapy, the Neuropsychiatry Inventory Brief Questionnaire Form scores (apathy, irritability, and aberrant motor symptoms) and the Dysexecutive Questionnaire score improved significantly. The single-photon emission computed tomography findings showed that lower baseline regional cerebral blood flow values in several frontal areas, including the dorsolateral and ventrolateral prefrontal cortex, the anterior cingulate, and the orbitofrontal cortex, predicted greater reductions in the score for apathy (distress) on the Neuropsychiatry Inventory Brief Questionnaire Form and the Dysexecutive Questionnaire score after patients switched from donepezil to galantamine therapy.

CONCLUSIONS

Our study suggests that galantamine therapy, unlike donepezil, is characterized by a dual mechanism of action that may increase acetylcholine and the nicotinic receptor-modulation effect within the frontal lobe, both of which are associated with apathy and executive dysfunction in AD patients.

Hierarchical multivariate covariance analysis of metabolic connectivity

Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI).

Associative memory and its cerebral correlates in Alzheimer׳s disease: evidence for distinct deficits of relational and conjunctive memory

This study investigated the impact of Alzheimer׳s disease (AD) on conjunctive and relational binding in episodic memory. Mild AD patients and controls had to remember item-color associations by imagining color either as a contextual association (relational memory) or as a feature of the item to be encoded (conjunctive memory). Patients׳ performance in each condition was correlated with cerebral metabolism measured by FDG-PET. The results showed that AD patients had an impaired capacity to remember item-color associations, with deficits in both relational and conjunctive memory. However, performance in the two kinds of associative memory varied independently across patients. Partial Least Square analyses revealed that poor conjunctive memory was related to hypometabolism in an anterior temporal-posterior fusiform brain network, whereas relational memory correlated with metabolism in regions of the default mode network. These findings support the hypothesis of distinct neural systems specialized in different types of associative memory and point to heterogeneous profiles of memory alteration in Alzheimer׳s disease as a function of damage to the respective neural networks.

Glucose metabolism during resting state reveals abnormal brain networks organization in the Alzheimer's disease and mild cognitive impairment

This paper aims to study the abnormal patterns of brain glucose metabolism co-variations in Alzheimer disease (AD) and Mild Cognitive Impairment (MCI) patients compared to Normal healthy controls (NC) using the Alzheimer Disease Neuroimaging Initiative (ADNI) database. The local cerebral metabolic rate for glucose (CMRgl) in a set of 90 structures belonging to the AAL atlas was obtained from Fluro-Deoxyglucose Positron Emission Tomography data in resting state. It is assumed that brain regions whose CMRgl values are significantly correlated are functionally associated; therefore, when metabolism is altered in a single region, the alteration will affect the metabolism of other brain areas with which it interrelates. The glucose metabolism network (represented by the matrix of the CMRgl co-variations among all pairs of structures) was studied using the graph theory framework. The highest concurrent fluctuations in CMRgl were basically identified between homologous cortical regions in all groups. Significant differences in CMRgl co-variations in AD and MCI groups as compared to NC were found. The AD and MCI patients showed aberrant patterns in comparison to NC subjects, as detected by global and local network properties (global and local efficiency, clustering index, and others). MCI network's attributes showed an intermediate position between NC and AD, corroborating it as a transitional stage from normal aging to Alzheimer disease. Our study is an attempt at exploring the complex association between glucose metabolism, CMRgl covariations and the attributes of the brain network organization in AD and MCI.

Cognitive and neuroimaging evidence of impaired interaction between self and memory in Alzheimer's disease

In human cognition, self and memory processes strongly interact, as evidenced by the memory advantage for self-referential materials [Self-Reference Effect (SRE) and Self-Reference Recollection Effect (SRRE)]. The current study examined this interaction at the behavioural level and its neural correlates in patients with Alzheimer's disease (AD). Healthy older controls (HC) and AD patients performed trait-adjectives judgements either for self-relevance or for other-relevance (encoding phase). In a first experiment, the encoding and subsequent yes-no recognition phases were administrated in a Magnetic Resonance Imaging (MRI) scanner. Brain activation as measured by functional MRI (fMRI) was examined during self-relevance judgements and anatomical images were used to search for correlation between the memory advantage for self-related items and grey matter density (GMD). In a second experiment, participants described the retrieval experience that had driven their recognition decisions (familiarity vs recollective experience). The behavioural results revealed that the SRE and SRRE were impaired in AD patients compared to HC participants. Furthermore, verbal reports revealed that the retrieval of self-related information was preferentially associated with the retrieval of contextual details, such as source memory in the HC participants, but less so in the AD patients. Our imaging findings revealed that both groups activated the medial prefrontal cortex (MPFC) at encoding during self-relevance judgements. However, the variable and limited memory advantage for self-related information was associated with GMD in the lateral prefrontal cortex in the AD patients, a region supporting high-order processes linking self and memory. These findings suggest that even if AD patients engage MPFC during self-referential judgements, the retrieval of self-related memories is qualitatively and quantitatively impaired in relation with altered high-order processes in the lateral PFC.

Age-dependent effects of environmental enrichment on brain networks and spatial memory in Wistar rats

We assessed the effect of 3h of environmental enrichment (EE) exposure per day started at different ages (3 and 18months old) on the performance in a spatial memory task and on brain regions involved in the spatial learning (SPL) process using the principal component analysis (PCA). The animals were tested in the four-arm radial water maze (4-RAWM) for 4days, with six daily trials. We used cytochrome c oxidase (COx) histochemistry to determine the brain oxidative metabolic changes related to age, SPL and EE. Behavioural results showed that the enriched groups, regardless of their age, achieved better performance in the spatial task. Interestingly, in the case of the distance travelled in the 4-RAWM, the effect of the EE was dependent on the age, so the young enriched group travelled a shorter distance compared to the aged enriched group. Respect to COx histochemistry results, we found that different brain mechanisms are triggered in aged rats to solve the spatial task, compared to young rats. PCA revealed the same brain functional network in both age groups, but the contribution of the brain regions involved in this network was slightly different depending on the age of the rats. Thus, in the aged group, brain regions involved in anxiety-like behaviour, such as the amygdala or the bed nucleus of the stria terminalis had more relevance; whereas in the young enriched group the frontal and the hippocampal subregions had more contribution.

Neuroimaging insights into network-based neurodegeneration

PURPOSE OF REVIEW

Convergent evidence from a number of neuroscience disciplines supports the hypothesis that Alzheimer's disease and other neurodegenerative disorders progress along brain networks. This review considers the role of neuroimaging in strengthening the case for network-based neurodegeneration and elucidating potential mechanisms.

RECENT FINDINGS

Advances in functional and structural MRI have recently enabled the delineation of multiple large-scale distributed brain networks. The application of these network-imaging modalities to neurodegenerative disease has shown that specific disorders appear to progress along specific networks. Recent work applying theoretical measures of network efficiency to in-vivo network imaging has allowed for the development and evaluation of models of disease spread along networks. Novel MRI acquisition and analysis methods are paving the way for in-vivo assessment of the layer-specific microcircuits first targeted by neurodegenerative diseases. These methodological advances coupled with large, longitudinal studies of subjects progressing from healthy aging into dementia will enable a detailed understanding of the seeding and spread of these disorders.

SUMMARY

Neuroimaging has provided ample evidence that neurodegenerative disorders progress along brain networks, and is now beginning to elucidate how they do so.

Metabolic and structural connectivity within the default mode network relates to working memory performance in young healthy adults

Studies of functional connectivity suggest that the default mode network (DMN) might be relevant for cognitive functions. Here, we examined metabolic and structural connectivity between major DMN nodes, the posterior cingulate (PCC) and medial prefrontal cortex (MPFC), in relation to normal working memory (WM). DMN was captured using independent component analysis of [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) data from 35 young healthy adults (27.1 ± 5.1 years). Metabolic connectivity, a correlation between FDG uptake in PCC and MPFC, was examined in groups of subjects with (relative to median) low (n=18) and high (n=17) performance on digit span backward test as an index of verbal WM. In addition, fiber tractography based on PCC and MPFC nodes as way points was performed in a subset of subjects. FDG uptake in the DMN nodes did not differ between high and low performers. However, significantly (p=0.01) lower metabolic connectivity was found in the group of low performers. Furthermore, as compared to high performers, low performers showed lower density of the left superior cingulate bundle. Verbal WM performance is related to metabolic and structural connectivity within the DMN in young healthy adults. Metabolic connectivity as quantified with FDG-PET might be a sensitive marker of the normal variability in some cognitive functions.

Voxel-based classification of FDG PET in dementia using inter-scanner normalization

Statistical mapping of FDG PET brain images has become a common tool in differential diagnosis of patients with dementia. We present a voxel-based classification system of neurodegenerative dementias based on partial least squares (PLS). Such a classifier relies on image databases of normal controls and dementia cases as training data. Variations in PET image characteristics can be expected between databases, for example due to differences in instrumentation, patient preparation, and image reconstruction. This study evaluates (i) the impact of databases from different scanners on classification accuracy and (ii) a method to improve inter-scanner classification. Brain FDG PET databases from three scanners (A, B, C) at two clinical sites were evaluated. Diagnostic categories included normal controls (NC, nA=26, nB=20, nC=24 for each scanner respectively), Alzheimer's disease (AD, nA=44, nB=11, nC=16), and frontotemporal dementia (FTD, nA=13, nB=13, nC=5). Spatially normalized images were classified as NC, AD, or FTD using partial least squares. Supervised learning was employed to determine classifier parameters, whereby available data is sub-divided into training and test sets. Four different database setups were evaluated: (i) "in-scanner": training and test data from the same scanner, (ii) "x-scanner": training and test data from different scanners, (iii) "train other": train on both x-scanners, and (iv) "train all": train on all scanners. In order to moderate the impact of inter-scanner variations on image evaluation, voxel-by-voxel scaling was applied based on "ratio images". Good classification accuracy of on average 94% was achieved for the in-scanner setups. Accuracy deteriorated for setups with mismatched scanners (79-91%). Ratio-image normalization improved all results with mismatched scanners (85-92%). In conclusion, automatic classification of individual FDG PET in differential diagnosis of dementia is feasible. Accuracy can vary with respect to scanner or acquisition characteristics of the training image data. The adopted approach of ratio-image normalization has been demonstrated to effectively moderate these effects.

Association between cerebral metabolism and Rey-Osterrieth Complex Figure Test performance in Alzheimer's disease

The copy condition of the Rey-Osterrieth Complex Figure (ROCF) is sensitive to Alzheimer's disease (AD) pathology, but its neural correlates remain unclear. We used fluorodeoxyglucose positron emission tomography (FDG-PET) to elucidate this association in 77 patients with probable AD. We observed a correlation between ROCF and metabolic rate of bilateral temporal-parietal cortex and occipital lobe, and right frontal lobe. Global and local elements of the ROCF correlated with metabolic rate of these same regions. The copy approach correlated with right lateral temporal cortex. The ROCF appears reflective of posterior temporal-parietal cortex functioning, highlighting the role of visuospatial processing in constructional abilities in AD.

Item familiarity and controlled associative retrieval in Alzheimer's disease: an fMRI study

Typical Alzheimer's disease (AD) is characterized by an impaired form of associative memory, recollection, that includes the controlled retrieval of associations. In contrast, familiarity-based memory for individual items may sometimes be preserved in the early stages of the disease. This is the first study that directly examines whole-brain regional activity during one core aspect of the recollection function: associative controlled episodic retrieval (CER), contrasted to item familiarity in AD patients. Cerebral activity related to associative CER and item familiarity in AD patients and healthy controls (HCs) was measured with functional magnetic resonance imaging during a word-pair recognition task to which the process dissociation procedure was applied. Some patients had null CER estimates (AD-), whereas others did show some CER abilities (AD+), although significantly less than HC. In contrast, familiarity estimates were equivalent in the three groups. In AD+, as in controls, associative CER activated the inferior precuneus/posterior cingulate cortex (PCC). When performing group comparisons, no region was found to be significantly more activated during CER in HC than AD+ and vice versa. However, during associative CER, functional connectivity between this region and the hippocampus, the inferior parietal and dorsolateral prefrontal cortex (DLPFC) was significantly higher in HC than in AD+. In all three groups, item familiarity was related to activation along the intraparietal sulcus (IPS). In conclusion, whereas the preserved automatic detection of an old item (without retrieval of accurate word association) is related to parietal activation centred on the IPS, the inferior precuneus/PCC supports associative CER ability in AD patients, as in HC. However, AD patients have deficient functional connectivity during associative CER, suggesting that the residual recollection function in these patients might be impoverished by the lack of some recollection-related aspects such as autonoetic quality, episodic details and verification.

APOE and neuroenergetics: an emerging paradigm in Alzheimer's disease

APOE is the major known genetic risk factor for late-onset Alzheimer's disease. Though relationships between APOE-encoded apolipoprotein E and β-amyloid are increasingly well described, mounting evidence supports wide-ranging effects of APOE on the brain. Specifically, APOE appears to affect brain network activity and closely related neuroenergetic functions that might be involved in vulnerability to neurodegenerative pathophysiology. These effects highlight the salience of further investigation into the diverse influences of APOE. Therefore, this article reviews the interplay between APOE and neuroenergetics and proposes areas for further investigation. This research might lead to the identification of novel therapeutic targets for the treatment and/or prevention of Alzheimer's disease.

Bilateral symmetry aspects in computer-aided Alzheimer's disease diagnosis by single-photon emission-computed tomography imaging

OBJECTIVE

This paper explores the importance of the latent symmetry of the brain in computer-aided systems for diagnosing Alzheimer's disease (AD). Symmetry and asymmetry are studied from two points of view: (i) the development of an effective classifier within the scope of machine learning techniques, and (ii) the assessment of its relevance to the AD diagnosis in the early stages of the disease.

METHODS

The proposed methodology is based on eigenimage decomposition of single-photon emission-computed tomography images, using an eigenspace extension to accommodate odd and even eigenvectors separately. This feature extraction technique allows for support-vector-machine classification and image analysis.

RESULTS

Identification of AD patterns is improved when the latent symmetry of the brain is considered, with an estimated 92.78% accuracy (92.86% sensitivity, 92.68% specificity) using a linear kernel and a leave-one-out cross validation strategy. Also, asymmetries may be used to define a test for AD that is very specific (90.24% specificity) but not especially sensitive.

CONCLUSIONS

Two main conclusions are derived from the analysis of the eigenimage spectrum. Firstly, the recognition of AD patterns is improved when considering only the symmetric part of the spectrum. Secondly, asymmetries in the hypo-metabolic patterns, when present, are more pronounced in subjects with AD.

Functional networks involved in spatial learning strategies in middle-aged rats

Our aim was to assess the way that middle-aged rats solve spatial learning tasks that can be performed using different strategies. We assessed the brain networks involved in these spatial learning processes using Principal Component Analysis. Two tasks were performed in a complex context, a four-arm radial maze, in which each group must use either an allocentric or an egocentric strategy. Another task was performed in a simple T-maze in which rats must use an egocentric strategy. Brain metabolic activity was quantified to evaluate neural changes related to spatial learning in the described tasks. Our findings revealed that two functional networks are involved in spatial learning in aged rats. One of the networks, spatial processing, is composed of brain regions involved in the integration of sensory and motivational information. The other network, context-dependent processing, mainly involves the dorsal hippocampus and is related to the processing of contextual information from the environment. Both networks work together to solve spatial tasks in a complex spatial environment.

Resting metabolic connectivity in prodromal Alzheimer's disease. A European Alzheimer Disease Consortium (EADC) project

We explored resting-state metabolic connectivity in prodromal Alzheimer's disease (pAD) patients and in healthy controls (CTR), through a voxel-wise interregional correlation analysis of 18F-fluorodeoxyglucose (FDG)-positron emission tomography (PET) by means of statistical parametric mapping. Baseline 18F-fluorodeoxyglucose-positron emission tomography of 36 patients with amnestic mild cognitive impairment who converted to Alzheimer's disease (AD) dementia after an average time of 2 years (pAD) and of 105 CTR were processed. The area of hypometabolism in pAD showed less metabolic connectivity in patients than in CTR (autocorrelation and correlation with large temporal and frontal areas, respectively). pAD patients showed limited correlation even in selected nonhypometabolic areas, including the hippocampi and the dorsolateral prefrontal cortex (DLFC). On the contrary, in CTR group correlation was highlighted between hippocampi and precuneus/posterior cingulate and frontal cortex, and between dorsolateral prefrontal cortex and caudate nuclei and parietal cortex. The reduced metabolic connections both in hypometabolic and nonhypometabolic areas in pAD patients suggest that metabolic disconnection (reflecting early diaschisis) may antedate remote hypometabolism (early sign of synaptic degeneration).

Executive deficits are related to the inferior frontal junction in early dementia

Executive functions describe a wide variety of higher order cognitive processes that allow the flexible modification of thought and behaviour in response to changing cognitive or environmental contexts. Their impairment is common in neurodegenerative disorders. Executive deficits negatively affect everyday activities and hamper the ability to cope with other deficits, such as memory impairment in Alzheimer's disease or behavioural disorders in frontotemporal lobar degeneration. Our study aimed to characterize the neural correlates of executive functions by relating respective deficits to regional hypometabolism in early dementia. Executive functions were assessed with two classical tests, the Stroop and semantic fluency test and various subtests of the behavioural assessment of the dysexecutive syndrome test battery capturing essential aspects of executive abilities relevant to daily living. Impairments in executive functions were correlated with reductions in brain glucose utilization as measured by [(18)F]fluorodeoxyglucose positron emission tomography and analysed voxelwise using statistical parametric mapping in 54 subjects with early dementia, mainly Alzheimer's disease and frontotemporal lobar degeneration, and its prodromal stages: subjective and mild cognitive impairment. Although the analysis revealed task-specific frontoparietal networks, it consistently showed that hypometabolism in one region in the left lateral prefrontal cortex-the inferior frontal junction area-was related to performance in the various neuropsychological tests. This brain region has recently been related to the three component processes of cognitive control-working memory, task switching and inhibitory control. Group comparisons additionally showed hypometabolism in this area in Alzheimer's disease and frontotemporal lobar degeneration. Our study underlines the importance of the inferior frontal junction area for cognitive control in general and for executive deficits in early dementia.

New computer-aided diagnosis of dementia using positron emission tomography: brain regional sensitivity-mapping method

PURPOSE

We devised a new computer-aided diagnosis method to segregate dementia using one estimated index (Total Z score) derived from the Brodmann area (BA) sensitivity map on the stereotaxic brain atlas. The purpose of this study is to investigate its accuracy to differentiate patients with Alzheimer's disease (AD) or mild cognitive impairment (MCI) from normal adults (NL).

METHODS

We studied 101 adults (NL: 40, AD: 37, MCI: 24) who underwent (18)FDG positron emission tomography (PET) measurement. We divided NL and AD groups into two categories: a training group with (Category A) and a test group without (Category B) clinical information. In Category A, we estimated sensitivity by comparing the standard uptake value per BA (SUVR) between NL and AD groups. Then, we calculated a summated index (Total Z score) by utilizing the sensitivity-distribution maps and each BA z-score to segregate AD patterns. To confirm the validity of this method, we examined the accuracy in Category B. Finally, we applied this method to MCI patients.

RESULTS

In Category A, we found that the sensitivity and specificity of differentiation between NL and AD were all 100%. In Category B, those were 100% and 95%, respectively. Furthermore, we found this method attained 88% to differentiate AD-converters from non-converters in MCI group.

CONCLUSIONS

The present automated computer-aided evaluation method based on a single estimated index provided good accuracy for differential diagnosis of AD and MCI. This good differentiation power suggests its usefulness not only for dementia diagnosis but also in a longitudinal study.

Cerebral metabolism, cognition, and functional abilities in Alzheimer disease

Patients with Alzheimer disease (AD) exhibit profound difficulties in completing instrumental activities of daily living (IADLs), such as managing finances, organizing medications, and food preparation. It is unclear which brain areas underlie IADL deficits in AD. To address this question, we used voxel-based analysis to correlate the performance of IADLs with resting cerebral metabolism as measured during [(18)F] fluorodeoxyglucose-positron emission tomography (FDG-PET) imaging in 44 patients with AD. Poorer ability to complete IADLs was associated with hypometabolism in right-sided cortical regions, including the parietal lobe, posterior temporal cortex, dorsolateral prefrontal cortex, and frontal pole. Follow-up path analyses examining anatomically defined regions of interest (ROI) demonstrated that the association between metabolism and IADLs was mediated by global cognition in frontal ROIs, and partially mediated by global cognition in the parietal ROI. Findings suggest that hypometabolism of right sided brain regions involved in executive functioning, visuospatial processing, attention, and working memory underlie functional impairments in patients with AD.

Combined Imaging Markers Dissociate Alzheimer's Disease and Frontotemporal Lobar Degeneration - An ALE Meta-Analysis

To compare and dissociate the neural correlates of Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD), we combine and synthesize here recent comprehensive meta-analyses. Systematic and quantitative meta-analyses were conducted according to the QUOROM statement by calculating anatomical likelihood estimates (ALE). AD (n = 578) and the three subtypes of FTLD, frontotemporal dementia, semantic dementia (SD), and progressive non-fluent aphasia (n = 229), were compared in conjunction analyses, separately for atrophy and reductions in glucose metabolism. Atrophy coincided in the amygdala and hippocampal head in AD and the FTLD subtype SD. The other brain regions did not show any overlap between AD and FTLD subtypes for both atrophy and changes in glucose metabolism. For AD alone (n = 826), another conjunction analysis revealed a regional dissociation between atrophy and hypoperfusion/hypometabolism, whereby hypoperfusion and hypometabolism coincided in the angular/supramarginal gyrus and inferior precuneus/posterior cingulate gyrus. Our data together with other imaging studies suggest a specific dissociation of AD and FTLD if, beside atrophy, additional imaging markers in AD such as abnormally low parietal glucose utilization and perfusion are taken into account. Results support the incorporation of standardized imaging inclusion criteria into future diagnostic systems, which is crucial for early individual diagnosis and treatment in the future.

[Neuroimaging in Alzheimer's disease: a synthesis and a contribution to the understanding of physiopathological mechanisms]

Alzheimer's disease has become a major public health issue for occidental societies. Since animal models of Alzheimer's disease currently fail to perfectly mimic pathophysiological mechanisms or the manifestations of the disease, in vivo neuroimaging has a key role in better understanding the pathophysiology of Alzheimer's disease. The diversity of anatomical and functional neuroimaging techniques - anatomical (T1-MRI), functional (fMRI) and diffusion tensor imaging (DTI) via magnetic resonance imaging (MRI) as well as position emission tomography coupled to fluorodeoxyglucose ((18)FDG-PET) - offers a large possibility of investigation of brain alterations in Alzheimer's disease. These techniques have thus provided morphological and functional brain alterations mapping of Alzheimer's disease: on one hand grey matter atrophy first concerns the medial temporal lobe before extending to the temporal neocortex and then other neocortical areas; on the other hand, metabolic alterations are first located within the posterior cingulate cortex and then reach the temporo-parietal area as well as the prefrontal cortex, especially in its medial part. Assessments of white matter alterations with DTI have highlighted a variety of tract alterations including the cingulum bundle, a white matter tract connecting the medial temporal lobe to the posterior cingulate cortex. Finally fMRI activation studies have evidenced compensatory mechanisms through hyperactivations in Alzheimer's disease patients. Altogether these results have led to the hypothesis of two major pathophysiological mechanisms in Alzheimer's disease: on one hand compensatory mechanisms in regions where atrophy exceeds metabolic alterations, on the other disconnection between medial temporal lobe and posterior cingulate cortex through the cingulum bundle, accounting for higher metabolic than structural alterations in the posterior cingulate cortex. Our work has extensively contributed to this disconnection hypothesis thanks to the use of cross-sectional and longitudinal multi-modal neuroimaging approaches. It has underlined the relevance of distant over local mechanisms in the pathophysiology of Alzheimer's disease and offers new perspectives to the exploration of the neural bases of cognitive impairments in this disorder.

Performance of FDG PET for detection of Alzheimer's disease in two independent multicentre samples (NEST-DD and ADNI)

AIM

We investigated the performance of FDG PET using an automated procedure for discrimination between Alzheimer's disease (AD) and controls, and studied the influence of demographic and technical factors.

METHODS

FDG PET data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) [102 controls (76.0 +/- 4.9 years) and 89 AD patients (75.7 +/- 7.6 years, MMSE 23.5 +/- 2.1) and the Network for Standardisation of Dementia Diagnosis (NEST-DD) [36 controls (62.2 +/- 5.0 years) and 237 AD patients (70.8 +/- 8.3 years, MMSE 20.9 +/- 4.4). The procedure created t-maps of abnormal voxels. The sum of t-values in predefined areas that are typically affected by AD (AD t-sum) provided a measure of scan abnormality associated with a preset threshold for discrimination between patients and controls.

RESULTS

AD patients had much higher AD t-sum scores compared to controls (p < 0.01), which were significantly related to dementia severity (ADNI: r = -0.62, p < 0.01; NEST-DD: r = -0.59, p < 0.01). Early-onset AD patients had significantly higher AD t-sum scores than late-onset AD patients (p < 0.01). Differences between databases were mainly due to different age distributions. The predefined AD t-sum threshold yielded a sensitivity and specificity of 83 and 78% in ADNI and 78 and 94% in NEST-DD, respectively.

CONCLUSION

The automated FDG PET analysis procedure provided good discrimination power, and was most accurate for early-onset AD.

Principal component analysis in mild and moderate Alzheimer's disease--a novel approach to clinical diagnosis

Principal component analysis (PCA) provides a method to explore functional brain connectivity. The aim of this study was to identify regional cerebral blood flow (rCBF) distribution differences between Alzheimer's disease (AD) patients and controls (CTR) by means of volume of interest (VOI) analysis and PCA. Thirty-seven CTR, 30 mild AD (mildAD) and 27 moderate AD (modAD) subjects were investigated using single photon emission computed tomography with (99m)Tc-hexamethylpropylene amine oxime. Analysis of covariance (ANCOVA), PCA, and discriminant analysis (DA) were performed on 54 VOIs. VOI analysis identified in both mildAD and modAD subjects a decreased rCBF in six regions. PCA in mildAD subjects identified four principal components (PCs) in which the correlated VOIs showed a decreased level of rCBF, including regions that are typically affected early in the disease. In five PCs, including parietal-temporal-limbic cortex, and hippocampus, a significantly lower rCBF in correlated VOIs was found in modAD subjects. DA significantly discriminated the groups. The percentage of subjects correctly classified was 95, 70, and 81 for CTR, mildAD and modAD groups, respectively. PCA highlighted, in mildAD and modAD, relationships not evident when brain regions are considered as independent of each other, and it was effective in discriminating groups. These findings may allow neurophysiological inferences to be drawn regarding brain functional connectivity in AD that might not be possible with univariate analysis.

Robustness of multivariate image analysis assessed by resampling techniques and applied to FDG-PET scans of patients with Alzheimer's disease

For finite and noisy samples extraction of robust features or patterns which are representative of the population is a formidable task in which over-interpretation is not uncommon. In this work, resampling techniques have been applied to a sample of 42 FDG PET brain images of 19 healthy volunteers (HVs) and 23 Alzheimer's disease (AD) patients to assess the robustness of image features extracted through principal component analysis (PCA) and Fisher discriminant analysis (FDA). The objective of this work is to: 1) determine the relative variance described by the PCA to the population variance; 2) assess the robustness of the PCA to the population sample using the largest principal angle between PCA subspaces; 3) assess the robustness and accuracy of the FDA. Since the sample does not have histopathological data the impact of possible clinical misdiagnosis on the discrimination analysis is investigated. The PCA can describe up to 40% of the total population variability. Not more than the first three or four PCs can be regarded as robust on which a robust FDA can be build. Standard error images showed that regions close to the falx and around ventricles are less stable. Using the first three PCs, sensitivity and specificity were 90.5% and 96.9% respectively. The use of resampling techniques in the evaluation of the robustness of many multivariate image analysis methods enables researchers to avoid over-analysis when using these methods applied to many different neuroimaging studies often with small sample sizes.