Volume 31, Supplement 3, September 2012 - "Biomarkers for Alzheimer's Disease Using Multi-Model Imaging Research" (Guest Editor: Pravat K Mandal)
Pravat K. Mandal
Predictive Biomarkers for Alzheimer’s Disease using State-of-the-Art Brain Imaging Techniques
Nicolás Fayed, Pedro J Modrego, Gulillermo Rojas Salinas, José Gazulla
Magnetic Resonance Imaging Based Clinical Research in Alzheimer's Disease
Abstract: Alzheimer's disease (AD) is the most common cause of dementia in elderly people in western countries. However important goals are unmet in the issue of early diagnosis and the development of new drugs for treatment. Magnetic resonance imaging (MRI) and volumetry of the medial temporal lobe structures are useful tools for diagnosis. Positron emission tomography is one of the most sensitive tests for making an early diagnosis of AD but the cost and limited availability are important caveats for its utilization. The importance of magnetic resonance techniques has increased gradually to the extent that most clinical works based on AD use these techniques as the main aid to diagnosis. However, the accuracy of structural MRI as biomarker of early AD generally reaches an accuracy of 80%, so additional biomarkers should be used to improve predictions. Other structural MRI (diffusion weighted, diffusion-tensor MRI) and functional MRI have also added interesting contribution to the understanding of the pathophysiology of AD. Magnetic resonance spectroscopy has proven useful to monitor progression and response to treatment in AD, as well as a biomarker of early AD in mild cognitive impairment.
Brian T. Gold, Yang Jiang, David K. Powell, Charles D. Smith
Multimodal Imaging Evidence for Axonal and Myelin Deterioration in Amnestic Mild Cognitive Impairment
Abstract: White matter (WM) microstructural declines have been demonstrated in Alzheimer’s disease and amnestic mild cognitive impairment (aMCI). However, the pattern of WM microstructural changes in aMCI after controlling for WM atrophy is unknown. Here, we address this issue through joint consideration of aMCI alterations in fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity, as well as macrostructural volume in WM and gray matter compartments. Participants were 18 individuals with aMCI and 24 healthy seniors. Voxelwise analyses of diffusion tensor imaging data was carried out using tract-based spatial statistics (TBSS) and voxelwise analyses of high-resolution structural data was conducted using voxel based morphometry. After controlling for WM atrophy, the main pattern of TBSS findings indicated reduced fractional anisotropy with only small alterations in mean diffusivity/radial diffusivity/axial diffusivity. These WM microstructural declines bordered and/or were connected to gray matter structures showing volumetric declines. However, none of the potential relationships between WM integrity and volume in connected gray matter structures was significant, and adding fractional anisotropy information improved the classificatory accuracy of aMCI compared to the use of hippocampal atrophy alone. These results suggest that WM microstructural declines provide unique information not captured by atrophy measures that may aid the magnetic resonance imaging contribution to aMCI detection.
Stefan J. Teipel, Martin Wegrzyn, Thomas Meindl, Giovanni Frisoni, Arun L.W. Bokde, Andreas Fellgiebel, Massimo Filippi, Harald Hampel, Stefan Klöppel, Karlheinz Hauenstein, Michael Ewers, and the EDSD study group
Anatomical MRI and DTI in the Diagnosis of Alzheimer’s Disease: a European Multicenter Study
Abstract: Diffusion tensor imaging (DTI) detects microstructural changes of the cerebral white matter in Alzheimer’s disease (AD). The use of DTI for the diagnosis of AD in a multicenter setting has not yet been investigated. We used voxel-based analysis of fractional anisotropy, mean diffusivity, and grey matter volumes from multimodal magnetic resonance imaging data of 137 AD patients and 143 healthy elderly controls collected across 9 different scanners. We compared different univariate analysis approaches to model the effect of scanner, including a linear model across all scans with a scanner covariate, a random effects model with scanner as a random variable as well as a voxel-based meta-analysis. We found significant reduction of fractional anisotropy and significant increase of mean diffusivity in core areas of AD pathology including corpus callosum, medial and lateral temporal lobes, as well as fornix, cingulate gyrus, precuneus, and prefrontal lobe white matter. Grey matter atrophy was most pronounced in medial and lateral temporal lobe as well as parietal and prefrontal association cortex. The effects of group were spatially more restricted with random effects modeling of scanner effects compared to simple pooled analysis. All three analysis approaches yielded similar accuracy of group separation in block-wise cross-validated logistic regression. Our results suggest similar effects of center on group separation based on different analysis approaches and confirm a typical pattern of cortical and subcortical microstructural changes in AD using a large multimodal multicenter data set.
Supplementary Data for Teipel et al. article (PDF)
Charles D. Smith, Anders H. Andersen, Brian T. Gold for the Alzheimer’s Disease Neuroimaging Initiative
Structural Brain Alterations before Mild Cognitive Impairment in ADNI: Validation of Volume Loss in a Predefined Antero-Temporal Region
Abstract: Volume losses in the medial temporal lobe, posterior cingulated, and orbitofrontal region have been observed in Alzheimer’s disease (AD). Smaller reductions in similar regions have also been reported in amnestic mild cognitive impairment (aMCI), a canonical precursor to AD. We previously demonstrated that volume loss in bilateral anteromedial temporal lobe is present at baseline in longitudinally followed normal subjects who later developed MCI or AD. In this study we compared grey matter volumes within this predefined anteromedial temporal region (AMTR) at baseline between: 1) normal subjects enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) who subsequently developed cognitive complaints as reflected in a CDR memory box score of 0.5; and 2) normal subjects who remained normal over a median of 48 months of follow-up (CDR sum of boxes 0). We found significantly decreased volume within AMTR in the ADNI memory complainers. To relate AMTR results to those from conventional anatomy, we demonstrate that volumes extracted with the ICBM amygdala region had the best correspondence with AMTR volumes. In contrast, regions that have demonstrated volume loss in frank MCI and AD in ADNI, e.g., the posterior cingulate, did not show volume loss. These findings provide independent confirmation that volume changes preceding MCI occur in AMTR, a region of overlap between amygdala and anterior hippocampus.
Katherine J. Bangen, Khaled Restom, Thomas T. Liu, Christina E. Wierenga, Amy J. Jak, David P. Salmon, Mark W. Bondi
Assessment of Alzheimer’s Disease Risk with Functional Magnetic Resonance Imaging: An Arterial Spin Labeling Study
Abstract: Functional magnetic resonance imaging (fMRI) of older adults at risk for Alzheimer’s disease (AD) by virtue of their cognitive (i.e., mild cognitive impairment [MCI]) and/or genetic (i.e., apolipoprotein E [APOE] ε4 allele) status demonstrate divergent brain response patterns during memory encoding across studies. Using arterial spin labeling MRI, we examined the influence of AD risk on resting cerebral blood flow (CBF) as well as the CBF and blood oxygenation level dependent (BOLD) signal response to memory encoding in the medial temporal lobes (MTL) in 45 older adults (29 cognitively normal [14 APOE ε4 carriers and 15 noncarriers]; 16 MCI [8 APOE ε4 carriers, 8 noncarriers]). Risk groups were comparable in terms of mean age, years of education, gender distribution, and vascular risk burden. Individuals at genetic risk for AD by virtue of the APOE ε4 allele demonstrated increased MTL resting state CBF relative to ε4 noncarriers, whereas individuals characterized as MCI showed decreased MTL resting state CBF relative to their cognitively normal peers. For percent change CBF, there was a trend toward a cognitive status by genotype interaction. In the cognitively normal group, there was no difference in percent change CBF based on APOE genotype. In contrast, in the MCI group, APOE ε4 carriers demonstrated significantly greater percent change in CBF relative to ε4 noncarriers. No group differences were found for BOLD response. Findings suggest that abnormal resting state CBF and CBF response to memory encoding may be early indicators of brain dysfunction in individuals at risk for developing AD.
Pravat K. Mandal, Himanshu Akolkar, Manjari Tripathi
Mapping of Hippocampal pH and Neurochemicals from in vivo Multi-voxel 31P Experiments in Healthy Normal Young Male/Female, Mild Cognitive Impairment, and Alzheimer’s Patients
Abstract: Magnetic resonance spectroscopy (MRS) plays an important role in the understanding crucial membrane and energy metabolism. The outcome of MRS experiments helps to derive important cellular conditions (e.g., intracellular pH, energy, membrane metabolism, etc.), which are directly related to neuronal health. We present a novel multi-voxel 31P MRS imaging experimental scheme along with an advanced 31P signal processing technique to determine the pH and neurochemicals from both hippocampal areas of healthy young male/female, mild cognitive impairment (MCI) and Alzheimer’s disease (AD) subjects in 13.2 minutes for both hippocampal areas. Significant (p=0.005) decrease of phosphomonoester (PME) and increase of phosphodiester (PDE) (p<0.001), γ-ATP (0.008), and PCr (p=0.001) levels in left hippocampus of AD patients (n=6) compared to control group (n=12) were found based on post-hoc ANOVA. On the other hand, in the right hippocampus, decrease in PME (p=0.008) and increase in PDE (p<0.001) were significant between AD and controls. In case of AD subjects, pH in the left hippocampus is increased towards alkaline side compared to MCI but did not reach statistical significance level. The pH (left hippocampus) in AD is found to be negatively correlated (r=-0.829, p=0.042) with PCr level of (left hippocampus) AD subjects. In the left hippocampus, the increase in pH to alkaline range (normal aging pH is decreased to acidic range) along with statistically significant increments of PCr, γ-ATP, and PDE as well as decrease of PME in AD subjects provide extremely crucial clinical information, which can be used as biomarker.
Vladimír Mlynárik, Matthias Cacquevel, Lili Sun-Reimer, Sharon Janssens, Cristina Cudalbu, Hongxia Lei, Bernard L. Schneider, Patrick Aebischer, Rolf Gruetter
Proton and Phosphorus Magnetic Resonance Spectroscopy of a Mouse Model of Alzheimer’s Disease
Abstract: The development of new diagnostic criteria for Alzheimer’s disease (AD) requires new in vivo markers reflecting early pathological changes in the brain of patients. Magnetic resonance (MR) spectroscopy has been shown to provide useful information about the biochemical changes occurring in AD brain in vivo. The development of numerous transgenic mouse models of AD has facilitated the evaluation of early biomarkers, allowing researchers to perform longitudinal studies starting before the onset of the pathology. In addition, the recent development of high-field animal scanners enables the measurement of brain metabolites that cannot be reliably quantified at lower magnetic fields. In this report, we studied a new transgenic mouse model of AD, the 5xFAD model, by in vivo proton and phosphorus MR spectroscopy. This model, which is characterized by an early-onset and a robust amyloid pathology, developed changes in the neurochemical profile, which are typical in the human disease, i.e., an increase in myo-inositol and a decrease in N-acetylaspartate concentrations, as early as in the 40th week of age. In addition, a significant decrease in the γ-aminobutyrate concentration was observed in transgenic mice at this age compared to controls. The pseudo-first-order rate constant of the creatine kinase reaction as well as relative concentrations of phosphorus-containing metabolites were not changed significantly in the 36 and 72-week old transgenic mice. Overall, these results suggest that mitochondrial activity in the 5xFAD mice is not substantially affected but that the model is relevant for studying early biomarkers of AD.
Cristina Cudalbu, Vladimir Mlynárik, Rolf Gruetter
Handling Macromolecule Signals in the Quantification of the Neurochemical Profile
Abstract: In vivo localized proton magnetic resonance spectroscopy (1H MRS) became a powerful and unique technique to non-invasively investigate brain metabolism of rodents and humans. The main goal of 1H MRS is the reliable quantification of concentrations of metabolites (neurochemical profile) in a well-defined region of the brain. The availability of very high magnetic field strengths combined with the possibility of acquiring spectra at very short echo time have dramatically increased the number of constituents of the neurochemical profile. The quantification of spectra measured at short echo times is complicated by the presence of macromolecule signals of particular importance at high magnetic fields. An error in the macromolecule estimation can lead to substantial errors in the obtained neurochemical profile. The purpose of the present review is to overview methods of high field 1H MRS with a focus on the metabolite quantification, in particular in handling signals of macromolecules. Three main approaches of handling signals of macromolecules are described, namely mathematical estimation of macromolecules, measurement of macromolecules in vivo, and direct acquisition of the in vivo spectrum without the contribution of macromolecules.
Pravat K Mandal, Jitesh Joshi, Sumiti Saharan
Visuospatial Perception: An Emerging Biomarker for Alzheimer's Disease
Abstract: In recent years, the focus of research on Alzheimer’s disease (AD) has shifted toward finding reliable diagnostic biomarkers that enable accurate detection of mild cognitive impairment (MCI) as well as AD. Functional magnetic resonance imaging (fMRI) has the potential to identify functional changes in the preclinical stages of AD. In addition to the cardinal deficits in memory, deficits in visuospatial cognition are pervasive in AD. Recent neurophysiological and imaging studies have revealed that changes in visuospatial perception (VSP) functions can be detected in the early stages of AD. This review highlights the scope of VSP functional alterations as a biomarker for AD. We describe the neuroanatomical regions involved in the processing of various VSP tasks, and discuss the effect of AD on these regions from a pathological as well as a functional point of view. A comprehensive synopsis of the existing fMRI literature that has assessed VSP in patients with MCI and AD has been provided. The diagnostic scope of monitoring the brain activation correlates of VSP processing in AD is discussed in terms of the key advantages of utilizing VSP-related deficits in AD for early detection and longitudinal tracking of AD.
Takao Yamasaki, Shizuka Horie, Hiroyuki Muranaka, Yumiko Kaseda, Yasuyo Mimori, Shozo Tobimatsu
Relevance of in vivo Neurophysiological Biomarkers for Mild Cognitive Impairment and Alzheimer’s Disease
Abstract: Visuospatial dysfunction including defects in motion perception in Alzheimer’s disease (AD) and mild cognitive impairment (MCI) are clues to search for potential in vivo biomarkers. In this review, we focus on the clinical relevance of non-invasive neurophysiological findings in event-related potentials (ERPs) and functional magnetic resonance imaging (fMRI) to assess visual dysfunction in AD and MCI. We first summarize the current concept of the parallel visual pathways in primates and humans. Next, we outline the results of previous electrophysiological and fMRI studies on visual function in AD and MCI. Finally, we present the recent findings of our systematic ERP and fMRI approach to visual perception in AD and MCI. Our overview strongly indicates that visual impairments in patients with AD and MCI are mainly caused by dysfunction in higher-level parallel visual pathways. In particular, a deficit in ventro-dorsal stream function related to optic flow perception is responsible for the earliest and most prominent visual symptoms in MCI. Therefore, we conclude that ERP and fMRI measurements for visual perception can be used as in vivo biomarkers for early functional brain changes in MCI and AD patients.
Jasmeer P. Chhatwal, Reisa A. Sperling
Functional MRI of Mnemonic Networks Across the Spectrum of Normal Aging, Mild Cognitive Impairment, and Alzheimer’s Disease
Abstract: Functional magnetic resonance imaging (fMRI) is a non-invasive technique that has come into common use to examine neural network function in normal and impaired cognitive states. Using this promising type of analysis, researchers have identified the presence of anatomically distributed regions operating as large-scale neural networks, which are observed both during the performance of associative memory tasks and in the resting state. The assembly of these anatomically distinct regions into functional ensembles and their choreographed activation and deactivation sets the stage for complex behaviors such as the formation and retrieval of associative memories. We review progress in the use of task-related and task-free MRI to elucidate the changes in neural activity in normal older individuals, patients with mild cognitive impairment, and those with Alzheimer’s disease, focusing on the altered activity of the default mode network and medial temporal lobe. We place task-free fMRI studies into the larger context of more traditional, task-based fMRI studies of human memory, which have firmly established the critical role of the medial temporal lobe in associative encoding. Lastly, we discuss the data from our group and others that suggests task-free MRI and task-based fMRI may prove useful as non-invasive biomarkers in studying the progression of memory failure over the course of Alzheimer’s disease.
Pravat K Mandal, Rashima Mahajan, Ivo D. Dinov
Structural Brain Atlases: Design, Rationale, and Applications in Normal and Pathological Cohorts
Abstract: Structural magnetic resonance imaging (MRI) provides anatomical information of the brain (e.g., white matter, grey matter, cerebrospinal fluid, etc.) in healthy as well as in diseased conditions. On the other hand, functional MRI (fMRI) provides information on the brain regions involved during the performance of a specific task. Serial fMRI studies have found a significant place in modern clinical neurology in monitoring therapeutic medical interventions and in pre- and post-surgery patients. Its scope as a research tool is expanding, with the ever-increasing challenges posed by the steady progressive research in neuroscience. Analysis of fMRI data requires the registration of the data to a reference brain template to identify the activated brain regions. Brain template also finds application in other neuroimaging modalities (e.g., multi-voxel spectroscopy). As there are certain differences (e.g., brain shape and size) in the brains between populations of different origin and during diseased conditions like in Alzheimer’s disease (AD), population-specific and disease-specific brain templates may be considered crucial for accurate registration and subsequent analysis of fMRI data. The chronological view of the development of brain template design, starting from the Talairach and Tournoux atlas to the Chinese brain template (to date), along with their respective detailed construction protocols provides the backdrop to this manuscript. The manuscript also provides the automated workflow-based protocol for designing a population-specific brain atlas from structural MRI data using LONI Pipeline graphical workflow environment. Applications of deterministic and probabilistic brain atlases in AD are also discussed.
Hervé Abdi, Lynne J. Williams, Derek Beaton, Mette T. Posamentier, Thomas S. Harris, Anjali Krishnan, Michael D. Devous, Sr.
Analysis of Regional Cerebral Blood Flow Data to Discriminate among Alzheimer's Disease, Frontotemporal Dementia, and Elderly Controls: A Multi-Block Barycentric Discriminant Analysis (MUBADA) Methodology
Abstract: We present a generalization of mean-centered partial least squares correlation called multiblock barycentric discriminant analysis (MUBADA) that integrates multiple regions of interest (ROIs) to analyze functional brain images of cerebral blood flow or metabolism obtained with SPECT or PET. To illustrate MUBADA we analyzed data from 104 participants comprising Alzheimer’s disease (AD) patients, frontotemporal dementia (FTD) patients, and elderly normal controls. Brain images were analyzed via 28 ROIs (59,845 voxels) selected for clinical relevance. This is a discriminant analysis (DA) question with several blocks (one per ROI) and with more variables than observations, a configuration that precludes using DA. MUBADA revealed two factors explaining 74% and 26% of the total variance: Factor 1 isolated FTD, and Factor 2 isolated AD. A random effects model correctly classified 64% (chance = 33%) of “new” participants (p < 0.0001). MUBADA identified ROIs that best discriminated groups: ROIs separating FTD were bilateral inferior, middle frontal, left inferior, and middle temporal gyri, while ROIs separating AD were bilateral thalamus, inferior parietal gyrus, inferior temporal gyrus, left precuneus, middle frontal, and middle temporal gyri. MUBADA classified participants at levels comparable to standard methods (i.e., SVM, PCA-LDA, and PLS-DA) but provided information (e.g., discriminative ROIs and voxels) not easily accessible to these methods.
Supplementary Data for Abdi et al. article (PDF)
Edo Richard, Ben Schmand, Piet Eikelenboom, Rudi G. Westendorp, Willem A. Van Gool
The Alzheimer Myth and Biomarker Research in Dementia
Abstract: The focus of most of the research on Alzheimer’s disease in the last decades has been on senile plaques and neurofibrillary tangles. The vast majority of patients with Alzheimer’s disease are over 75 years of age, whereas most of the research focuses on younger subjects. To consider old-age dementia as a homogenous well-defined condition ignores the complexity of this condition and limits the development of new diagnostic methods, preventive strategies, or treatment strategies that could be widely applicable in daily practice in the majority of the older patients. The current research on biomarkers focuses on correlates of plaques and tangles, which are poor markers in older dementia subjects. Acknowledging that dementia in old age is an essentially different condition from dementia at relatively younger age is needed and should lead to new approaches in dementia research.
Giulia Liberati, Josué Luiz Dalboni da Rocha, Linda van der Heiden Antonino Raffone , Niels Birbaumer, Marta Olivetti Belardinelli, Ranganatha Sitaram
Toward a Brain-Computer Interface for Alzheimer’s Disease Patients by Combining Classical Conditioning and Brain State Classification
Abstract: Brain-computer interfaces (BCIs) provide alternative methods for communicating and acting on the world, since messages or commands are conveyed from the brain to an external device without using the normal output pathways of peripheral nerves and muscles. Alzheimer’s disease (AD) patients in the most advanced stages, who have lost the ability to communicate verbally, could benefit from a BCI that may allow them to convey basic thoughts (e.g., “yes” and “no”) and emotions. There is currently no report of such research, mostly because the cognitive deficits in AD patients pose serious limitations to the use of traditional BCIs, which are normally based on instrumental learning and require users to self-regulate their brain activation. Recent studies suggest that not only self-regulated brain signals, but also involuntary signals, for instance related to emotional states, may provide useful information about the user, opening up the path for so-called “affective BCIs”. These interfaces do not necessarily require users to actively perform a cognitive task, and may therefore be used with patients who are cognitively challenged. In the present hypothesis paper, we propose a paradigm shift from instrumental learning to classical conditioning, with the aim of discriminating “yes” and “no” thoughts after associating them to positive and negative emotional stimuli respectively. This would represent a first step in the development of a BCI that could be used by AD patients, lending a new direction not only for communication, but also for rehabilitation and diagnosis.
Liam Zaidel, Greg Allen, C. Munro Cullum, Richard W. Briggs, Linda S. Hynan, Myron F. Weiner, Roderick McColl, Kaundinya S. Gopinath, Elizabeth McDonald, Craig D. Rubin
Donepezil Effects on Hippocampal and Prefrontal Functional Connectivity in Alzheimer’s Disease: Preliminary Report
Abstract: We used functional connectivity magnetic resonance imaging (fcMRI) to investigate changes in interhemispheric brain connectivity in 11 patients with mild Alzheimer’s disease (AD) following eight weeks of treatment with the cholinesterase inhibitor donepezil. We examined functional connectivity between four homologous temporal, frontal, and occipital regions. These regions were selected to represent sites of AD neuropathology, sites of donepezil-related brain activation change in prior studies, and sites that are minimally affected by the pathologic changes of AD. Based on previous findings of selective, localized frontal responses to donepezil, we predicted that frontal connectivity would be most strongly impacted by treatment. Of the areas examined, we found that treatment had a significant effect only on functional connectivity between right and left dorsolateral prefrontal cortices. Implications for understanding the impact of donepezil treatment on brain functioning and behavior in patients with AD are discussed. This preliminary report suggests that fcMRI may provide a useful index of treatment outcome in diseases affecting brain connectivity. Future research should investigate these treatment-related changes in larger samples of patients and age-matched controls.