Alzheimer disease: quantitative structural neuroimaging for detection and prediction of clinical and structural changes in mild cognitive impairment

Semi-supervised pattern classification of medical images: application to mild cognitive impairment (MCI)

Many progressive disorders are characterized by unclear or transient diagnoses for specific subgroups of patients. Commonly used supervised pattern recognition methodology may not be the most suitable approach to deriving image-based biomarkers in such cases, as it relies on the availability of categorically labeled data (e.g., patients and controls). In this paper, we explore the potential of semi-supervised pattern classification to provide image-based biomarkers in the absence of precise diagnostic information for some individuals. We employ semi-supervised support vector machines (SVM) and apply them to the problem of classifying MR brain images of patients with uncertain diagnoses. We examine patterns in serial scans of ADNI participants with mild cognitive impairment (MCI), and propose that in the absence of sufficient follow-up evaluations of individuals with MCI, semi-supervised strategy is potentially more appropriate than the fully-supervised paradigm employed up to date.

Functional imaging of hippocampal dysfunction among persons with Alzheimer's disease: a proof-of-concept study

Cholinergic deficits are an early and functionally significant manifestation of Alzheimer's disease (AD). These deficits contribute to impairment of hippocampally mediated information processing, including declarative memory impairments and abnormal auditory sensory gating. A functional imaging technique that facilitates identification of changes in cholinergically dependent hippocampal information processing would be of considerable use in the study and clinical evaluation of persons with this condition. Techniques that interrogate hippocampal function passively, ie, in a manner requiring no cognitive effort or novel task learning during the neuroimaging procedure, would also be especially useful in this cognitively impaired population. The functional magnetic resonance imaging sensory gating paradigm developed at the University of Colorado, CO, USA, is a functional neuroimaging technique that possesses both of these characteristics. We developed a demonstration project using this paradigm in which we passively interrogated hippocampal function in two subjects with probable AD of mild severity. Imaging data were quick and easy in these subjects and served usefully as an initial demonstration of the feasibility of using this neuroimaging method in this population. Preliminary analyses of the data obtained from these subjects identified abnormal blood oxygen level-dependent responses when compared with four healthy comparators, and the pattern of these responses was consistent with impaired function of the auditory sensory gating network. The strengths and limitations of this neuroimaging paradigm and the additional issues that require investigation in order to continue its development into a research and clinical technique for use in this population are discussed.

Characterizing the regional structural difference of the brain between tau transgenic (rTg4510) and wild-type mice using MRI

rTg4510 transgenic mouse model demonstrates features resembling Alzheimer's disease including neurofibrillary degeneration and progressive neuronal loss. We investigated the volumetric differences of brain structures between transgenic and wild-type mice using MR images of fourteen 5.5 month old female mice. Tensor-based morphometry and atlas-based segmentation were applied to MRI images. Severe atrophy of hippocampus and neocortex as well as ventricular dilatation were observed in the transgenic mice. These findings were confirmed by histopathologic evaluation of the same mice. The results suggest that MRI should be useful for evaluating disease-modifying therapies for Alzheimer's disease in the rTg4510 model and comparing treatment responses in mice and humans.

Structural brain changes in aging: courses, causes and cognitive consequences

The structure of the brain is constantly changing from birth throughout the lifetime, meaning that normal aging, free from dementia, is associated with structural brain changes. This paper reviews recent evidence from magnetic resonance imaging (MRI) studies about age-related changes in the brain. The main conclusions are that (1) the brain shrinks in volume and the ventricular system expands in healthy aging. However, the pattern of changes is highly heterogeneous, with the largest changes seen in the frontal and temporal cortex, and in the putamen, thalamus, and accumbens. With modern approaches to analysis of MRI data, changes in cortical thickness and subcortical volume can be tracked over periods as short as one year, with annual reductions of between 0.5% and 1.0% in most brain areas. (2) The volumetric brain reductions in healthy aging are likely only to a minor extent related to neuronal loss. Rather, shrinkage of neurons, reductions of synaptic spines, and lower numbers of synapses probably account for the reductions in grey matter. In addition, the length of myelinated axons is greatly reduced, up to almost 50%. (3) Reductions in specific cognitive abilities--for instance processing speed, executive functions, and episodic memory--are seen in healthy aging. Such reductions are to a substantial degree mediated by neuroanatomical changes, meaning that between 25% and 100% of the differences between young and old participants in selected cognitive functions can be explained by group differences in structural brain characteristics.

Brain beta-amyloid measures and magnetic resonance imaging atrophy both predict time-to-progression from mild cognitive impairment to Alzheimer's disease

Biomarkers of brain Aβ amyloid deposition can be measured either by cerebrospinal fluid Aβ42 or Pittsburgh compound B positron emission tomography imaging. Our objective was to evaluate the ability of Aβ load and neurodegenerative atrophy on magnetic resonance imaging to predict shorter time-to-progression from mild cognitive impairment to Alzheimer’s dementia and to characterize the effect of these biomarkers on the risk of progression as they become increasingly abnormal. A total of 218 subjects with mild cognitive impairment were identified from the Alzheimer’s Disease Neuroimaging Initiative. The primary outcome was time-to-progression to Alzheimer’s dementia. Hippocampal volumes were measured and adjusted for intracranial volume. We used a new method of pooling cerebrospinal fluid Aβ42 and Pittsburgh compound B positron emission tomography measures to produce equivalent measures of brain Aβ load from either source and analysed the results using multiple imputation methods. We performed our analyses in two phases. First, we grouped our subjects into those who were ‘amyloid positive’ (n = 165, with the assumption that Alzheimer's pathology is dominant in this group) and those who were ‘amyloid negative’ (n = 53). In the second phase, we included all 218 subjects with mild cognitive impairment to evaluate the biomarkers in a sample that we assumed to contain a full spectrum of expected pathologies. In a Kaplan–Meier analysis, amyloid positive subjects with mild cognitive impairment were much more likely to progress to dementia within 2 years than amyloid negative subjects with mild cognitive impairment (50 versus 19%). Among amyloid positive subjects with mild cognitive impairment only, hippocampal atrophy predicted shorter time-to-progression (P < 0.001) while Aβ load did not (P = 0.44). In contrast, when all 218 subjects with mild cognitive impairment were combined (amyloid positive and negative), hippocampal atrophy and Aβ load predicted shorter time-to-progression with comparable power (hazard ratio for an inter-quartile difference of 2.6 for both); however, the risk profile was linear throughout the range of hippocampal atrophy values but reached a ceiling at higher values of brain Aβ load. Our results are consistent with a model of Alzheimer’s disease in which Aβ deposition initiates the pathological cascade but is not the direct cause of cognitive impairment as evidenced by the fact that Aβ load severity is decoupled from risk of progression at high levels. In contrast, hippocampal atrophy indicates how far along the neurodegenerative path one is, and hence how close to progressing to dementia. Possible explanations for our finding that many subjects with mild cognitive impairment have intermediate levels of Aβ load include: (i) individual subjects may reach an Aβ load plateau at varying absolute levels; (ii) some subjects may be more biologically susceptible to Aβ than others; and (iii) subjects with mild cognitive impairment with intermediate levels of Aβ may represent individuals with Alzheimer’s disease co-existent with other pathologies.

Relative capability of MR imaging and FDG PET to depict changes associated with prodromal and early Alzheimer disease

PURPOSE

To quantify the effect sizes of regional metabolic and morphometric measures in patients with preclinical and mild Alzheimer disease (AD) to aid in the identification of noninvasive biomarkers for the early detection of AD.

MATERIALS AND METHODS

The study was conducted with institutional review board approval and in compliance with HIPAA regulations. Written informed consent was obtained from each participant or participant's legal guardian. Fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET) and magnetic resonance (MR) imaging data were analyzed from 80 healthy control (HC) subjects, 68 individuals with AD, and 156 with amnestic mild cognitive impairment (MCI), 69 of whom had single-domain amnestic MCI. Regions of interest (ROIs) were derived after coregistering FDG PET and MR images by using high-throughput, subject-specific procedures. The Cohen d effect sizes were calculated for 42 predefined ROIs across the brain. Statistical comparison of the largest overall effect sizes for MR imaging and PET was performed. Metabolic effect sizes were determined with and without accounting for regional atrophy. Discriminative accuracy of ROIs showing the largest effect sizes were compared by calculating receiver operating characteristic curves.

RESULTS

For all disease groups, the hippocampus showed the largest morphometric effect size and the entorhinal cortex showed the largest metabolic effect size. In mild AD, the Cohen d effect size for hippocampal volume (1.92) was significantly larger (P < .05) than that for entorhinal metabolism (1.43). Regression of regional atrophy substantially reduced most metabolic effects. For all group comparisons, the areas under the receiver operating characteristic curves were significantly larger for hippocampal volume than for entorhinal metabolism.

CONCLUSION

The current results show no evidence that FDG PET is more sensitive than MR imaging to the degeneration occurring in preclinical and mild AD, suggesting that an MR imaging finding may be a more practical clinical biomarker for early detection of AD.

Multivariate analysis of MRI data for Alzheimer's disease, mild cognitive impairment and healthy controls

We have used multivariate data analysis, more specifically orthogonal partial least squares to latent structures (OPLS) analysis, to discriminate between Alzheimer's disease (AD), mild cognitive impairment (MCI) and elderly control subjects combining both regional and global magnetic resonance imaging (MRI) volumetric measures. In this study, 117 AD patients, 122 MCI patients and 112 control subjects (from the AddNeuroMed study) were included. High-resolution sagittal 3D MP-RAGE datasets were acquired from each subject. Automated regional segmentation and manual outlining of the hippocampus were performed for each image. Altogether this yielded volumes of 24 different anatomically defined structures which were used for OPLS analysis. 17 randomly selected AD patients, 12 randomly selected control subjects and the 22 MCI subjects who converted to AD at 1-year follow up were excluded from the initial OPLS analysis to provide a small external test set for model validation. Comparing AD with controls we found a sensitivity of 87% and a specificity of 90% using hippocampal measures alone. Combining both global and regional measures resulted in a sensitivity of 90% and a specificity of 94%. This increase in sensitivity and specificity resulted in an increase of the positive likelihood ratio from 9 to 15. From the external test set, the model predicted 82% of the AD patients and 83% of the control subjects correctly. Finally, 73% of the MCI subjects which converted to AD at 1 year follow-up were shown to resemble AD patients more closely than controls. This method shows potential for distinguishing between different patient groups. Combining the different MRI measures together resulted in a significantly better classification than using them separately. OPLS also shows potential for predicting conversion from MCI to AD.

Six-month atrophy in MTL structures is associated with subsequent memory decline in elderly controls

Neurodegeneration precedes the onset of dementias such as Alzheimer's by several years. Recent advances in volumetric imaging allow quantification of subtle neuroanatomical change over time periods as short as six months. This study investigates whether neuroanatomical change in medial temporal lobe subregions is associated with later memory decline in elderly controls. Using high-resolution, T1-weighted magnetic resonance images acquired at baseline and six-month follow-up, change in cortical thickness and subcortical volumes was measured in 142 healthy elderly subjects (aged 59-90 years) from the ADNI cohort. Regression analysis was used to identify whether change in fourteen subregions, selected a priori, was associated with declining performance on memory tests from baseline to two-year follow-up. Percent thickness change in the right fusiform and inferior temporal cortices and expansion of the right inferior lateral ventricle were found to be significant predictors of subsequent decline on memory-specific neuropsychological measures. These results demonstrate that six-month regional neurodegeneration can be quantified in the healthy elderly and might help identify those at risk for subsequent cognitive decline.

Relationship between regional atrophy rates and cognitive decline in mild cognitive impairment

We investigated the relationship between regional atrophy rates and 2-year cognitive decline in a large cohort of patients with mild cognitive impairment (MCI; n = 103) and healthy controls (n = 90). Longitudinal magnetic resonance image (MRI) scans were analyzed using high-throughput image analysis procedures. Atrophy rates were derived by calculating percent cortical volume loss between baseline and 24 month scans. Stepwise regressions were performed to investigate the contribution of atrophy rates to language, memory, and executive functioning decline, controlling for age, gender, baseline performances, and disease progression. In MCI, left temporal lobe atrophy rates were associated with naming decline, whereas bilateral temporal, left frontal, and left anterior cingulate atrophy rates were associated with semantic fluency decline. Left entorhinal atrophy rate was associated with memory decline and bilateral frontal atrophy rates were associated with executive function decline. These data provide evidence that regional atrophy rates in MCI contribute to domain-specific cognitive decline, which appears to be partially independent of disease progression. MRI measures of regional atrophy can provide valuable information for understanding the neural basis of cognitive impairment in MCI.

Integrating ADNI results into Alzheimer's disease drug development programs

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is providing critical new information on biomarkers in cognitively normal elderly, persons with mild cognitive impairment (MCI), and patients with mild Alzheimer's disease (AD). The data provide insights into the progression of the pathology of AD over time, assist in understanding which biomarkers might be most useful in clinical trials, and facilitate development of disease-modifying treatments. ADNI results are intended to support new AD treatment development; this report considers how ADNI information can be integrated in AD drug development programs. Cerebrospinal fluid (CSF) amyloid beta protein (Abeta) measures can be used in Phase I studies to detect any short term effects on Abeta levels in the CSF. Phase II studies may benefit most from biomarker measures that can inform decisions about Phase III. CSF Abeta levels, CSF total tau and phospho-tau measures, fluorodeoxyglucose positron emission tomography (FDG PET), Pittsburgh Compound B (PIB) amyloid imaging, or magnetic resonance imaging (MRI) may be employed to select patients in enriched trials or as outcomes for specific disease-modifying interventions. Use of biomarkers may allow Phase II trials to be conducted more efficiently with smaller populations of patients or shorted treatment times. New drug applications (NDAs) may include biomarker outcomes of phase III trials. ADNI patients are highly educated and are nearly all of Caucasian ethnicity limiting the generalizability of the results to other populations commonly included in global clinical trials. ADNI has inspired or collaborates with biomarker investigations worldwide and together these studies will provide biomarker information that can reduce development times and costs, improve drug safety, optimize drug efficacy, and bring new treatments to patients with or at risk for AD.

Automated MR morphometry to predict Alzheimer's disease in mild cognitive impairment

PURPOSE

Prediction of progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is challenging but essential for early treatment. This study aims to investigate the use of hippocampal atrophy markers for the automatic detection of MCI converters and to compare the predictive value to manually obtained hippocampal volume and temporal horn width.

METHODS

A study was performed with 15 patients with Alzheimer and 18 patients with MCI (ten converted, eight remained stable in a 3-year follow-up) as well as 15 healthy subjects. MRI scans were obtained at baseline and evaluated with an automated system for scoring of hippocampal atrophy. The predictive value of the automated system was compared with manual measurements of hippocampal volume and temporal horn width in the same subjects.

RESULTS

The conversion to AD was correctly predicted in 77.8% of the cases (sensitivity 70%, specificity 87.5%) in the MCI group using automated morphometry and a plain linear classifier that was trained on the AD and healthy groups. Classification was improved by limiting analysis to the left cerebral hemisphere (accuracy 83.3%, sensitivity 70%, specificity 100%). The manual linear and volumetric approaches reached rates of 66.7% (40/100%) and 72.2% (60/87.5%), respectively.

CONCLUSION

The automatic approach fulfills many important preconditions for clinical application. Contrary to the manual approaches, it is not observer-dependent and reduces human resource requirements. Automated assessment may be useful for individual patient assessment and for predicting progression to dementia.

The Alzheimer's disease neuroimaging initiative: progress report and future plans

The Alzheimer's Disease Neuroimaging Initiative (ADNI) beginning in October 2004, is a 6-year research project that studies changes of cognition, function, brain structure and function, and biomarkers in elderly controls, subjects with mild cognitive impairment, and subjects with Alzheimer's disease (AD). A major goal is to determine and validate MRI, PET images, and cerebrospinal fluid (CSF)/blood biomarkers as predictors and outcomes for use in clinical trials of AD treatments. Structural MRI, FDG PET, C-11 Pittsburgh compound B (PIB) PET, CSF measurements of amyloid beta (Abeta) and species of tau, with clinical/cognitive measurements were performed on elderly controls, subjects with mild cognitive impairment, and subjects with AD. Structural MRI shows high rates of brain atrophy, and has high statistical power for determining treatment effects. FDG PET, C-11 Pittsburgh compound B PET, and CSF measurements of Abeta and tau were significant predictors of cognitive decline and brain atrophy. All data are available at UCLA/LONI/ADNI, without embargo. ADNI-like projects started in Australia, Europe, Japan, and Korea. ADNI provides significant new information concerning the progression of AD.

Update on the magnetic resonance imaging core of the Alzheimer's disease neuroimaging initiative

Functions of the Alzheimer's Disease Neuroimaging Initiative (ADNI) magnetic resonance imaging (MRI) core fall into three categories: (1) those of the central MRI core laboratory at Mayo Clinic, Rochester, Minnesota, needed to generate high quality MRI data in all subjects at each time point; (2) those of the funded ADNI MRI core imaging analysis groups responsible for analyzing the MRI data; and (3) the joint function of the entire MRI core in designing and problem solving MR image acquisition, pre-processing, and analyses methods. The primary objective of ADNI was and continues to be improving methods for clinical trials in Alzheimer's disease. Our approach to the present ("ADNI-GO") and future ("ADNI-2," if funded) MRI protocol will be to maintain MRI methodological consistency in the previously enrolled "ADNI-1" subjects who are followed up longitudinally in ADNI-GO and ADNI-2. We will modernize and expand the MRI protocol for all newly enrolled ADNI-GO and ADNI-2 subjects. All newly enrolled subjects will be scanned at 3T with a core set of three sequence types: 3D T1-weighted volume, FLAIR, and a long TE gradient echo volumetric acquisition for micro hemorrhage detection. In addition to this core ADNI-GO and ADNI-2 protocol, we will perform vendor-specific pilot sub-studies of arterial spin-labeling perfusion, resting state functional connectivity, and diffusion tensor imaging. One of these sequences will be added to the core protocol on systems from each MRI vendor. These experimental sub-studies are designed to demonstrate the feasibility of acquiring useful data in a multicenter (but single vendor) setting for these three emerging MRI applications.

Brain substrates of learning and retention in mild cognitive impairment diagnosis and progression to Alzheimer's disease

Understanding the underlying qualitative features of memory deficits in mild cognitive impairment (MCI) can provide critical information for early detection of Alzheimer's disease (AD). This study sought to investigate the utility of both learning and retention measures in (a) the diagnosis of MCI, (b) predicting progression to AD, and (c) examining their underlying brain morphometric correlates. A total of 607 participants were assigned to three MCI groups (high learning-low retention; low learning-high retention; low learning-low retention) and one control group (high learning-high retention) based on scores above or below a 1.5 SD cutoff on learning and retention indices of the Rey Auditory Verbal Learning Test. Our results demonstrated that MCI individuals with predominantly a learning deficit showed a widespread pattern of gray matter loss at baseline, whereas individuals with a retention deficit showed more focal gray matter loss. Moreover, either learning or retention measures provided good predictive value for longitudinal clinical outcome over two years, although impaired learning had modestly better predictive power than impaired retention. As expected, impairments in both measures provided the best predictive power. Thus, the conventional practice of relying solely on the use of delayed recall or retention measures in studies of amnestic MCI misses an important subset of older adults at risk of developing AD. Overall, our results highlight the importance of including learning measures in addition to retention measures when making a diagnosis of MCI and for predicting clinical outcome.

CSF biomarkers in prediction of cerebral and clinical change in mild cognitive impairment and Alzheimer's disease

Brain atrophy and altered CSF levels of amyloid beta (Abeta(42)) and the microtubule-associated protein tau are potent biomarkers of Alzheimer's disease (AD)-related pathology. However, the relationship between CSF biomarkers and brain morphometry is poorly understood. Thus, we addressed the following questions. (1) Can CSF biomarker levels explain the morphometric differences between normal controls (NC) and patients with mild cognitive impairment (MCI) or AD? (2) How are CSF biomarkers related to atrophy across the brain? (3) How closely are CSF biomarkers and morphometry related to clinical change [clinical dementia rating sum of boxes (CDR-sb)]? Three hundred seventy participants (105 NC, 175 MCI, 90 AD) from the Alzheimer's Disease Neuroimaging Initiative were studied, of whom 309 were followed for 1 year and 176 for 2 years. Analyses were performed across the entire cortical surface, as well as for 30 cortical and subcortical regions of interest. Results showed that CSF biomarker levels could not account for group differences in brain morphometry at baseline but that CSF biomarker levels showed moderate relationships to longitudinal atrophy rates in numerous brain areas, not restricted to medial temporal structures. Baseline morphometry was at least as predictive of atrophy as were CSF biomarkers. Even MCI patients with levels of Abeta(42) comparable with controls and of p-tau lower than controls showed more atrophy than the controls. Morphometry predicted change in CDR-sb better than did CSF biomarkers. These results indicate that morphometric changes in MCI and AD are not secondary to CSF biomarker changes and that the two types of biomarkers yield complementary information.

Combining MR imaging, positron-emission tomography, and CSF biomarkers in the diagnosis and prognosis of Alzheimer disease

BACKGROUND AND PURPOSE

Different biomarkers for AD may potentially be complementary in diagnosis and prognosis of AD. Our aim was to combine MR imaging, FDG-PET, and CSF biomarkers in the diagnostic classification and 2-year prognosis of MCI and AD, by examining the following: 1) which measures are most sensitive to diagnostic status, 2) to what extent the methods provide unique information in diagnostic classification, and 3) which measures are most predictive of clinical decline.

MATERIALS AND METHODS

ADNI baseline MR imaging, FDG-PET, and CSF data from 42 controls, 73 patients with MCI, and 38 patients with AD; and 2-year clinical follow-up data for 36 controls, 51 patients with MCI, and 25 patients with AD were analyzed. The hippocampus and entorhinal, parahippocampal, retrosplenial, precuneus, inferior parietal, supramarginal, middle temporal, lateral, and medial orbitofrontal cortices were used as regions of interest. CSF variables included Abeta42, t-tau, p-tau, and ratios of t-tau/Abeta42 and p-tau/Abeta42. Regression analyses were performed to determine the sensitivity of measures to diagnostic status as well as 2-year change in CDR-SB, MMSE, and delayed logical memory in MCI.

RESULTS

Hippocampal volume, retrosplenial thickness, and t-tau/Abeta42 uniquely predicted diagnostic group. Change in CDR-SB was best predicted by retrosplenial thickness; MMSE, by retrosplenial metabolism and thickness; and delayed logical memory, by hippocampal volume.

CONCLUSIONS

All biomarkers were sensitive to the diagnostic group. Combining MR imaging morphometry and CSF biomarkers improved diagnostic classification (controls versus AD). MR imaging morphometry and PET were largely overlapping in value for discrimination. Baseline MR imaging and PET measures were more predictive of clinical change in MCI than were CSF measures.

Brain atrophy in healthy aging is related to CSF levels of Aβ1-42

Reduced levels of beta-amyloid(1-42) (Abeta1-42) and increased levels of tau proteins in the cerebrospinal fluid (CSF) are found in Alzheimer's disease (AD), likely reflecting Abeta deposition in plaques and neuronal and axonal damage. It is not known whether these biomarkers are associated with brain atrophy also in healthy aging. We tested the relationship between CSF levels of Abeta1-42 and tau (total tau and tau phosphorylated at threonine 181) proteins and 1-year brain atrophy in 71 cognitively normal elderly individuals. Results showed that under a certain threshold value, levels of Abeta1-42 correlated highly with 1-year change in a wide range of brain areas. The strongest relationships were not found in the regions most vulnerable early in AD. Above the threshold level, Abeta1-42 was not related to brain changes, but significant volume reductions as well as ventricular expansion were still seen. It is concluded that Abeta1-42 correlates with brain atrophy and ventricular expansion in a subgroup of cognitively normal elderly individuals but that reductions independent of CSF levels of Abeta1-42 is common. Further research and follow-up examinations over several years are needed to test whether degenerative pathology will eventually develop in the group of cognitively normal elderly individuals with low levels of Abeta1-42.

Remote sites of structural atrophy predict later amyloid formation in a mouse model of Alzheimer's disease

Magnetic resonance (MR) imaging can provide a longitudinal view of neurological disease through repeated imaging of patients at successive stages of impairment. Until recently, the difficulty of manual delineation has limited volumetric analyses of MR data sets to a few select regions and a small number of subjects. Increased throughput offered by faster imaging methods, automated segmentation, and deformation-based morphometry have recently been applied to overcome this limitation with mouse models of neurological conditions. We use automated analyses to produce an unbiased view of volumetric changes in a transgenic mouse model for Alzheimer's disease (AD) at two points in the progression of disease: immediately before and shortly after the onset of amyloid formation. In addition to the cortex and hippocampus, where atrophy has been well documented in AD patients, we identify volumetric losses in the pons and substantia nigra where neurodegeneration has not been carefully examined. We find that deficits in cortical volume precede amyloid formation in this mouse model, similar to presymptomatic atrophy seen in patients with familial AD. Unexpectedly, volumetric losses identified by MR outside of the forebrain predict locations of future amyloid formation, such as the inferior colliculus and spinal nuclei, which develop pathology at very late stages of disease. Our work provides proof-of-principle that MR microscopy can expand our view of AD by offering a complete and unbiased examination of volumetric changes that guide us in revisiting the canonical neuropathology.

One-year brain atrophy evident in healthy aging

An accurate description of changes in the brain in healthy aging is needed to understand the basis of age-related changes in cognitive function. Cross-sectional magnetic resonance imaging (MRI) studies suggest thinning of the cerebral cortex, volumetric reductions of most subcortical structures, and ventricular expansion. However, there is a paucity of detailed longitudinal studies to support the cross-sectional findings. In the present study, 142 healthy elderly participants (60-91 years of age) were followed with repeated MRI, and were compared with 122 patients with mild to moderate Alzheimer's disease (AD). Volume changes were measured across the entire cortex and in 48 regions of interest. Cortical reductions in the healthy elderly were extensive after only 1 year, especially evident in temporal and prefrontal cortices, where annual decline was approximately 0.5%. All subcortical and ventricular regions except caudate nucleus and the fourth ventricle changed significantly over 1 year. Some of the atrophy occurred in areas vulnerable to AD, while other changes were observed in areas less characteristic of the disease in early stages. This suggests that the changes are not primarily driven by degenerative processes associated with AD, although it is likely that preclinical changes associated with AD are superposed on changes due to normal aging in some subjects, especially in the temporal lobes. Finally, atrophy was found to accelerate with increasing age, and this was especially prominent in areas vulnerable to AD. Thus, it is possible that the accelerating atrophy with increasing age is due to preclinical AD.

Humanin and the receptors for humanin

Alzheimer's disease (AD) is a prevalent dementia-causing neurodegenerative disease. Neuronal death is closely linked to the progression of AD-associated dementia. Accumulating evidence has established that a 24-amino-acid bioactive peptide, Humanin, protects neurons from AD-related neuronal death. A series of studies using various murine AD models including familial AD gene-expressing transgenic mice have shown that Humanin is effective against AD-related neuronal dysfunction in vivo. Most recently, it has been shown that Humanin inhibits neuronal cell death and dysfunction by binding to a novel IL-6-receptor-related receptor(s) on the cell surface involving CNTFRalpha, WSX-1, and gp130. These findings suggest that endogenous Humanin [or a Humanin-like substance(s)] may suppress the onset of AD-related dementia by inhibiting both AD-related neuronal cell death and dysfunction.

Cognitive phenotypes, brain morphometry and the detection of cognitive decline in preclinical AD

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

Structural neuroimaging in the detection and prognosis of pre-clinical and early AD

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

Subregional neuroanatomical change as a biomarker for Alzheimer's disease

Regions of the temporal and parietal lobes are particularly damaged in Alzheimer's disease (AD), and this leads to a predictable pattern of brain atrophy. In vivo quantification of subregional atrophy, such as changes in cortical thickness or structure volume, could lead to improved diagnosis and better assessment of the neuroprotective effects of a therapy. Toward this end, we have developed a fast and robust method for accurately quantifying cerebral structural changes in several cortical and subcortical regions using serial MRI scans. In 169 healthy controls, 299 subjects with mild cognitive impairment (MCI), and 129 subjects with AD, we measured rates of subregional cerebral volume change for each cohort and performed power calculations to identify regions that would provide the most sensitive outcome measures in clinical trials of disease-modifying agents. Consistent with regional specificity of AD, temporal-lobe cortical regions showed the greatest disease-related changes and significantly outperformed any of the clinical or cognitive measures examined for both AD and MCI. Global measures of change in brain structure, including whole-brain and ventricular volumes, were also elevated in AD and MCI, but were less salient when compared to changes in normal subjects. Therefore, these biomarkers are less powerful for quantifying disease-modifying effects of compounds that target AD pathology. The findings indicate that regional temporal lobe cortical changes would have great utility as outcome measures in clinical trials and may also have utility in clinical practice for aiding early diagnosis of neurodegenerative disease.

A six stage approach for the diagnosis of the Alzheimer's disease based on fMRI data

The aim of this work is to present an automated method that assists in the diagnosis of Alzheimer's disease and also supports the monitoring of the progression of the disease. The method is based on features extracted from the data acquired during an fMRI experiment. It consists of six stages: (a) preprocessing of fMRI data, (b) modeling of fMRI voxel time series using a Generalized Linear Model, (c) feature extraction from the fMRI data, (d) feature selection, (e) classification using classical and improved variations of the Random Forests algorithm and Support Vector Machines, and (f) conversion of the trees, of the Random Forest, to rules which have physical meaning. The method is evaluated using a dataset of 41 subjects. The results of the proposed method indicate the validity of the method in the diagnosis (accuracy 94%) and monitoring of the Alzheimer's disease (accuracy 97% and 99%).

CSF biomarker pathology correlates with a medial temporo-parietal network affected by very mild to moderate Alzheimer's disease but not a fronto-striatal network affected by healthy aging

It is suggested that reductions in a medial temporo-parietal episodic memory network characterize Alzheimer's disease (AD), while changes in a fronto-striatal executive network characterize healthy aging. In the present study, magnetic resonance imaging (MRI) was used to test this directly. MRI scans of 372 participants from two samples were analyzed: Sample 1 consisted of 96 very mild to moderate AD patients, 93 healthy elderly (HE), and 137 young (HY), all with available MR scans, while Sample 2 consisted of 46 MCI patients, with available MR scans and measures of CSF biomarkers Abeta42 and tau protein. Substantial morphometric reductions of the medial temporo-parietal network were found in AD, while the fronto-striatal network was less affected. Both networks were affected by healthy aging, but the fronto-striatal to a greater degree than the medial temporo-parietal. Further exploratory analyses of 49 cortical and subcortical structures indicated no overlap between predictors of AD vs. HE and predictors of HE vs. HY. CSF biomarker pathology correlated with the medial temporo-parietal but not fronto-striatal network. Likewise, the AD-prone structures from the exploratory analyses were related to CSF biomarkers, while the aging-prone structures were not. It is concluded that the pattern of macrostructural brain changes in very mild to moderate AD can be clearly delineated from that of healthy aging.

Level of executive function influences verbal memory in amnestic mild cognitive impairment and predicts prefrontal and posterior cingulate thickness

This study aims to investigate the relationship between executive function and verbal memory and to explore the underlying neuroanatomical correlates in 358 individuals with amnestic mild cognitive impairment (MCI) and 222 healthy controls (HCs). The MCI participants were divided into 2 groups (high vs. low) based on executive function task performance. Results demonstrated that although both MCI groups were impaired on all memory measures relative to HCs, MCI individuals with higher executive function (HEF) demonstrated better verbal memory performance than those with lower executive function (LEF), particularly on measures of learning. The 2 MCI groups did not differ in mesial temporal morphometric measures, but the MCI LEF group showed significant thinning in dorsolateral prefrontal and posterior cingulate cortices bilaterally compared with the MCI HEF and HCs. Further, thickness in numerous regions of frontal cortex, and bilateral posterior cingulate, was significantly associated with memory performance in all MCI participants above and beyond the contribution of the mesial temporal regions known to be associated with episodic memory. Overall, these results demonstrate the importance of evaluating executive function in individuals with MCI to predict involvement of brain areas beyond the mesial temporal lobe.

Does Alzheimer's disease begin in the brainstem?

Although substantial evidence indicates that the progression of pathological changes of the neuronal cytoskeleton is crucial in determining the severity of dementia in Alzheimer's disease (AD), the exact causes and evolution of these changes, the initial site at which they begin, and the neuronal susceptibility levels for their development are poorly understood. The current clinical criteria for diagnosis of AD are focused mostly on cognitive deficits produced by dysfunction of hippocampal and high-order neocortical areas, whereas noncognitive, behavioural and psychological symptoms of dementia such as disturbances in mood, emotion, appetite, and wake-sleep cycle, confusion, agitation and depression have been less considered. The early occurrence of these symptoms suggests brainstem involvement, and more specifically of the serotonergic nuclei. In spite of the fact that the Braak and Braak staging system and National Institutes of Aging - Reagan Institute (NIA-RI) criteria do not include their evaluation, several recent reports drew attention to the possibility of selective and early involvement of raphe nuclei, particularly the dorsal raphe nucleus (DRN), in the pathogenesis of AD. Based on these findings of differential susceptibility and anatomical connectivity, a novel pathogenetic scheme of AD progression was proposed. Although the precise mechanisms of neurofibrillary degeneration still await elucidation, we speculated that cumulative oxidative damage may be the main cause of DRN alterations, as the age is the main risk factor for sporadic AD. Within such a framework, beta-amyloid production is considered only as one of the factors (although a significant one in familial cases) that promotes molecular series of events underlying AD-related neuropathological changes.