Quantitative magnetic resonance techniques as surrogate markers of Alzheimer's disease

Hearing loss and dementia in older adults: A narrative review

The prevalence of hearing loss is high among older adults; globally, 65% of adults over 60 years have hearing loss. Over the past decade, evidence from epidemiologic studies has linked hearing loss to nearly two times greater risk of dementia. The hypothesized mechanistic pathways through which hearing loss could contribute to increased dementia risk include the effects of hearing on greater cognitive load, changes in brain structure and function, and decreased social engagement. These mechanistic pathways may be modified by management of hearing loss using existing intervention (eg, hearing aids). Hearing treatment may be an effective intervention for slowing cognitive decline in some older adults. In this review, we update existing reviews of the current epidemiologic research on the association between hearing loss and dementia risk and discuss hypothesized mechanisms of this association. We also discuss management of hearing loss as a potential intervention for slowing cognitive decline and reducing dementia risk.

Effects of Kami Guibi-tang in patients with mild cognitive impairment: study protocol for a phase III, randomized, double-blind, and placebo-controlled trial

BACKGROUND

Amnestic mild cognitive impairment (aMCI) is often considered a precursor to Alzheimer's disease (AD) and represents a key therapeutic target for early intervention of AD. However, no treatments have been approved for MCI at present. Our previous pilot study has shown that Kami Guibi-tang (KGT), a traditional herbal prescription widely used in Korean medicine for treating amnesia, might be beneficial for improving general cognitive function of aMCI patients. We will conduct a larger-scale clinical trial to validate the findings of our pilot study and further examine the efficacy and safety of KGT in aMCI.

METHODS

This trial is designed as a randomized, double-blind, placebo-controlled clinical trial. A total of 84 aMCI patients will be recruited and randomized into the treatment and control groups. Participants will be administered either KGT or placebo granules for 24 weeks, with a follow-up period of 12 weeks after the last treatment. Primary outcomes will include changes in cognitive performance assessed using a neuropsychological test battery, called the Seoul Neuropsychological Screening Battery, between the baseline, post-intervention visit, and follow-up visit (24th and 36th week, respectively). Secondary outcomes will involve the rate of progression to AD, changes in neuroimaging signals assessed using structural magnetic resonance imaging (MRI), resting-state functional MRI (rs-fMRI), and task-based fMRI, and changes in blood biomarkers measured by the ratio of plasma amyloid-β 42/40 levels (Aβ42/Aβ40) between the baseline and post-intervention visit (24th week). For safety assessments, blood chemistry tests and electrocardiograms (ECG) will also be performed.

DISCUSSION

This study aims to provide confirmatory evidence of the effect of the Korean herbal medicine, KGT, on improving cognitive function in patients with aMCI. We will identify the possible mechanisms underlying the effects of KGT using neuroimaging signals and blood biomarkers.

TRIAL REGISTRATION

Korean Clinical Trial Registry ( https://cris.nih.go.kr/cris/search/detailSearch.do/16918; Registration number: KCT0007039; Date of registration: February 24, 2022).

Saturation Transfer MRI for Detection of Metabolic and Microstructural Impairments Underlying Neurodegeneration in Alzheimer's Disease

Alzheimer's disease (AD) is one of the most common causes of dementia and difficult to study as the pool of subjects is highly heterogeneous. Saturation transfer (ST) magnetic resonance imaging (MRI) methods are quantitative modalities with potential for non-invasive identification and tracking of various aspects of AD pathology. In this review we cover ST-MRI studies in both humans and animal models of AD over the past 20 years. A number of magnetization transfer (MT) studies have shown promising results in human brain. Increased computing power enables more quantitative MT studies, while access to higher magnetic fields improves the specificity of chemical exchange saturation transfer (CEST) techniques. While much work remains to be done, results so far are very encouraging. MT is sensitive to patterns of AD-related pathological changes, improving differential diagnosis, and CEST is sensitive to particular pathological processes which could greatly assist in the development and monitoring of therapeutic treatments of this currently incurable disease.

Longitudinal associations of subclinical hearing loss with cognitive decline

BACKGROUND

Several studies have demonstrated that age-related hearing loss is associated with cognitive decline. We investigated whether subclinical hearing loss (SCHL), or imperfect hearing traditionally categorized as normal (pure tone average ≤25 dB), may be similarly linked to cognitive decline and risk of incident mild cognitive impairment (MCI)/dementia.

METHODS

Participants from the Baltimore Longitudinal Study of Aging were cognitively normal adults ≥50 years old with cognitive assessments from 1991-2019 and pure-tone average ≤25 dB measured between 1991-1994 (n=263). The exposure was hearing based on the better ear pure-tone average. Outcomes were test scores in various cognitive domains. Multivariable linear-mixed effects models modeled the association between hearing and change in cognition over time, adjusting for age, sex, education, vascular burden, and race. Kaplan-Meier survival curves and Cox proportional hazards models portrayed associations between hearing and incident MCI/dementia diagnosis based on predefined criteria.

RESULTS

Of 263 participants, 145 (55.1%) were female; mean age was 68.3 years (standard deviation, SD=8.9). Follow-up ranged up to 27.7 years (mean=11.7 years). Adjusting for multiple comparisons, a 10-dB increase in hearing loss was associated with an annual decline of -0.02 SDs (95% confidence interval, [CI]: -0.03, -0.01) in Letter Fluency. No significant relationships were observed between hearing and incident MCI/dementia.

CONCLUSIONS

A relationship between SCHL and cognitive decline was observed for the Letter Fluency test. Further studies are necessary to determine when in the spectrum of hearing loss there begins to be an observable relationship between hearing and cognitive decline.

Accelerating Structural Degeneration in Temporal Regions and Their Effects on Cognition in Aging of MCI Patients

Age is the major risk factor for Alzheimer's disease (AD) and for mild cognitive impairment (MCI). However, there is limited evidence about MCI-specific aging-related simultaneous changes of the brain structure and their impact on cognition. We analyzed the brain imaging data from 269 subjects (97 MCI patients and 172 cognitively normal [CN] elderly) using voxel-based morphometry and tract-based spatial statistics procedures to explore the special structural pattern during aging. We found that the patients with MCI showed accelerated age-related reductions in gray matter volume in the left planum temporale, thalamus, and posterior cingulate gyrus. The similar age×group interaction effect was found in the fractional anisotropy of the bilateral parahippocampal cingulum white matter tract, which connects the temporal regions. Importantly, the age-related temporal gray matter and white matter alterations were more significantly related to performance in memory and attention tasks in MCI patients. The accelerated degeneration patterns in the brain structure provide evidence for different neural mechanisms underlying aging in MCI patients. Temporal structural degeneration may serve as a potential imaging marker for distinguishing the progression of the preclinical AD stage from normal aging.

Entorhinal and Transentorhinal Atrophy in Preclinical Alzheimer's Disease

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

Age-related Hearing Loss and Dementia

Dementia is a devastating disease and global health challenge that is highly prevalent worldwide. A growing body of research has shown an independent association between age-related hearing loss (ARHL) and dementia, identifying ARHL as a compelling potential target in preventive strategies for dementia. However, a causal linkage between ARHL and dementia needs to be investigated before making definitive clinical guidelines and treatment recommendations regarding ARHL as a modifiable risk factor. In this review, we discuss the association between ARHL and dementia, the importance of addressing this finding, as well as common mechanisms (eg, microvascular disease) and causal mechanisms (eg, depletion of cognitive reserve and social isolation) that may explain the nature of this relationship. Future directions for research are also highlighted, including randomized controlled trials, developing high-resolution microvascular imaging, and further refining audiometric testing.

The effectiveness and safety of Kami Guibi-tang for mild cognitive impairment: study protocol of a pilot, randomized, placebo-controlled, double-blind trial

Background

Mild cognitive impairment (MCI) is an intermediate phase between normal aging and dementia. Since a majority of amnestic MCI (aMCI) cases progress to Alzheimer’s disease (AD), it is considered the prodromal stage of AD and, therefore, a treatment target for the prevention of further cognitive decline. However, there is no approved treatment for MCI at present. Kami Guibi-tang (KGT) is a herbal drug used in Korean medicine to treat amnesia, insomnia, loss of appetite, and depression. We will explore the effectiveness and safety of KGT in amnestic MCI in this trial.

Methods/design

The study will be a single-center, randomized, placebo-controlled, double-blind trial. Eligible participants diagnosed with amnestic MCI will be randomly allocated to a treatment or control group. Participants will take KGT or placebo granules, three times a day, for 24 weeks. The primary outcomes will be changes in Seoul Neuropsychological Screening Battery (SNSB) scores, and magnetic resonance imaging (MRI) measurements including those of brain metabolites, neurotransmitters, and cerebral blood flow. The secondary outcomes will include the safety assessment, measured by changes in blood chemistry, changes in blood protein and cholesterol levels related to AD pathology, and a comparison of MRI changes between the two groups, using age and genotype as covariates.

Discussion

This study will be the first clinical trial to identify the therapeutic potential of Kami Guibi-tang for amnestic MCI. The findings will provide insight into the feasibility of large-scale trials to gather evidence for KGT as a treatment for MCI.

Trial registration

Korean Clinical Trial Registry, ID: KCT0002407. Registered on 30 March 2017.

Electronic supplementary material

The online version of this article (10.1186/s13063-019-3567-1) contains supplementary material, which is available to authorized users.

Using deep Siamese neural networks for detection of brain asymmetries associated with Alzheimer's Disease and Mild Cognitive Impairment

In recent studies, neuroanatomical volume and shape asymmetries have been seen during the course of Alzheimer's Disease (AD) and could potentially be used as preclinical imaging biomarkers for the prediction of Mild Cognitive Impairment (MCI) and AD dementia. In this study, a deep learning framework utilizing Siamese neural networks trained on paired lateral inter-hemispheric regions is used to harness the discriminative power of whole-brain volumetric asymmetry. The method uses the MRICloud pipeline to yield low-dimensional volumetric features of pre-defined atlas brain structures, and a novel non-linear kernel trick to normalize these features to reduce batch effects across datasets and populations. By working with the low-dimensional features, Siamese networks were shown to yield comparable performance to studies that utilize whole-brain MR images, with the advantage of reduced complexity and computational time, while preserving the biological information density. Experimental results also show that Siamese networks perform better in certain metrics by explicitly encoding the asymmetry in brain volumes, compared to traditional prediction methods that do not use the asymmetry, on the ADNI and BIOCARD datasets.

Cortical thickness atrophy in the transentorhinal cortex in mild cognitive impairment

This study examines the atrophy rates of subjects with mild cognitive impairment (MCI) compared to controls in four regions within the medial temporal lobe: the transentorhinal cortex (TEC), entorhinal cortex (ERC), hippocampus, and amygdala. These regions were manually segmented and then corrected for undesirable longitudinal variability via Large Deformation Diffeomorphic Metric Mapping (LDDMM) based longitudinal diffeomorphometry. Diffeomorphometry techniques were used to compare thickness measurements in the TEC with the ERC. There were more significant changes in thickness atrophy rate in the TEC than medial regions of the entorhinal cortex. Volume measures were also calculated for all four regions. Classifiers were constructed using linear discriminant analysis to demonstrate that average thickness and atrophy rate of TEC together was the most discriminating measure compared to the thickness and volume measures in the areas examined, in differentiating MCI from controls. These findings are consistent with autopsy findings demonstrating that initial neuronal changes are found in TEC before spreading more medially in the ERC and to other regions in the medial temporal lobe. These findings suggest that the TEC thickness could serve as a biomarker for Alzheimer's disease in the prodromal phase of the disease.

Entorhinal and transentorhinal atrophy in mild cognitive impairment using longitudinal diffeomorphometry

INTRODUCTION

Autopsy findings have shown the entorhinal cortex and transentorhinal cortex are among the earliest sites of accumulation of pathology in patients developing Alzheimer's disease.

METHODS

Here, we study this region in subjects with mild cognitive impairment (n = 36) and in control subjects (n = 16). The cortical areas are manually segmented, and local volume and shape changes are quantified using diffeomorphometry, including a novel mapping procedure that reduces variability in anatomic definitions over time.

RESULTS

We find significant thickness and volume changes localized to the transentorhinal cortex through high field strength atlasing.

DISCUSSION

This demonstrates that in vivo neuroimaging biomarkers can detect these early changes among subjects with mild cognitive impairment.

A review of new insights on the association between hearing loss and cognitive decline in ageing

Age-related hearing loss (ARHL) has a multifactorial pathogenesis and it is an inevitable hearing impairment associated with reduction of communicative skills related to ageing. Increasing evidence has linked ARHL to more rapid progression of cognitive decline and incidental dementia. Many aspects of daily living of elderly people have been associated to hearing abilities, showing that hearing loss (HL) affects the quality of life, social relationships, motor skills, psychological aspects and function and morphology in specific brain areas. Epidemiological and clinical studies confirm the assumption of a relationship between these conditions. However, the mechanisms are still unclear and are reviewed herein. Long-term hearing deprivation of auditory inputs can impact cognitive performance by decreasing the quality of communication leading to social isolation and depression and facilitate dementia. On the contrary, the limited cognitive skills may reduce the cognitive resources available for auditory perception, increasing the effects of HL. In addition, hearing loss and cognitive decline may reflect a 'common cause' on the auditory pathway and brain. In fact, some pathogenetic factors are recongised in common microvascular disease factors such as diabetes, atherosclerosis and hypertension. Interdisciplinary efforts to investigate and address HL in the context of brain and cognitive ageing are needed. Surprisingly, few studies have been adressed on the effectiveness of hearing aids in changing the natural history of cognitive decline. Effective interventions with hearing aids or cochlear implant may improve social and emotional function, communication, cognitive function and positively impact quality of life. The aim of this review is to overview new insights on this challenging topic and provide new ideas for future research.

Magnetic Resonance Volumetry: Prediction of Subjective Memory Complaints and Mild Cognitive Impairment, and Associations with Genetic and Cardiovascular Risk Factors

Background/Aims

Subjective memory complaints (SMC) are strong predictors of mild cognitive impairment (MCI) and subsequent Alzheimer's disease. Our aims were to see if fully automated cerebral MR volume measurements could distinguish subjects with SMC and MCI from controls, and if probable parental late-onset Alzheimer's disease (LOAD), apolipoprotein E ε4 genotype, total plasma homocysteine, and cardiovascular risk factors were associated with MR volumetric findings.

Methods

198 stroke-free subjects comprised the control (n = 58), the SMC (n = 25) and the MCI (n = 115) groups. Analysis of covariance and receiver operating characteristic curve was used to see if MR volumetry distinguished subjects with SMC and MCI from controls.

Results

Subjects with SMC and MCI had significantly larger lateral ventricles and smaller hippocampal volumes than controls. The area under the curve in subjects with SMC and MCI compared to that of controls was less than 0.68 for all volumes of intracranial structures. There was an interaction between sex and probable parental LOAD for hippocampal volume, with a significant association between probable parental LOAD and hippocampal volume in women.

Conclusions

Fully automated MR volumetry can distinguish subjects with SMC and MCI from controls in a general population, but insufficiently to assume a clear clinical role. Research on sporadic LOAD might benefit from a sex-specific search for genetic risk factors.

Relationship of Hippocampal Volume to Amyloid Burden across Diagnostic Stages of Alzheimer's Disease

AIMS

To assess how hippocampal volume (HV) from volumetric magnetic resonance imaging (vMRI) is related to the amyloid status at different stages of Alzheimer's disease (AD) and its relevance to patient care.

METHODS

We evaluated the ability of HV to predict the florbetapir positron emission tomography (PET) amyloid positive/negative status by group in healthy controls (HC, n = 170) and early/late mild cognitive impairment (EMCI, n = 252; LMCI, n = 136), and AD dementia (n = 75) subjects from the Alzheimer's Disease Neuroimaging Initiative Grand Opportunity (ADNI-GO) and ADNI2. Logistic regression analyses, including elastic net classification modeling with 10-fold cross-validation, were used with age and education as covariates.

RESULTS

HV predicted amyloid status only in LMCI using either logistic regression [area under the curve (AUC) = 0.71, p < 0.001] or elastic net classification modeling [positive predictive value (PPV) = 72.7%]. In EMCI, age (AUC = 0.70, p < 0.0001) and age and/or education (PPV = 63.1%), but not HV, predicted amyloid status.

CONCLUSION

Using clinical neuroimaging, HV predicted amyloid status only in LMCI, suggesting that HV is not a biomarker surrogate for amyloid PET in clinical applications across the full diagnostic spectrum.

Hearing, Cognition, and Healthy Aging: Social and Public Health Implications of the Links between Age-Related Declines in Hearing and Cognition

Sensory input provides the signals used by the brain when listeners understand speech and participate in social activities with other people in a range of everyday situations. When sensory inputs are diminished, there can be short-term consequences to brain functioning, and long-term deprivation can affect brain neuroplasticity. Indeed, the association between hearing loss and cognitive declines in older adults is supported by experimental and epidemiologic evidence, although the causal mechanisms remain unknown. These interactions of auditory and cognitive aging play out in the challenges confronted by people with age-related hearing problems when understanding speech and engaging in social interactions. In the present article, we use the World Health Organization's International Classification of Functioning, Disability and Health and the Selective Optimization with Compensation models to highlight the importance of adopting a healthy aging perspective that focuses on facilitating active social participation by older adults. First, we examine epidemiologic evidence linking ARHL to cognitive declines and other health issues. Next, we examine how social factors influence and are influenced by auditory and cognitive aging and if they may provide a possible explanation for the association between ARHL and cognitive decline. Finally, we outline how audiologists could reposition hearing health care within the broader context of healthy aging.

Network Neurodegeneration in Alzheimer's Disease via MRI Based Shape Diffeomorphometry and High-Field Atlasing

This paper examines MRI analysis of neurodegeneration in Alzheimer’s Disease (AD) in a network of structures within the medial temporal lobe using diffeomorphometry methods coupled with high-field atlasing in which the entorhinal cortex is partitioned into eight subareas. The morphometry markers for three groups of subjects (controls, preclinical AD, and symptomatic AD) are indexed to template coordinates measured with respect to these eight subareas. The location and timing of changes are examined within the subareas as it pertains to the classic Braak and Braak staging by comparing the three groups. We demonstrate that the earliest preclinical changes in the population occur in the lateral most sulcal extent in the entorhinal cortex (alluded to as transentorhinal cortex by Braak and Braak), and then proceeds medially which is consistent with the Braak and Braak staging. We use high-field 11T atlasing to demonstrate that the network changes are occurring at the junctures of the substructures in this medial temporal lobe network. Temporal progression of the disease through the network is also examined via changepoint analysis, demonstrating earliest changes in entorhinal cortex. The differential expression of rate of atrophy with progression signaling the changepoint time across the network is demonstrated to be signaling in the intermediate caudal subarea of the entorhinal cortex, which has been noted to be proximal to the hippocampus. This coupled to the findings of the nearby basolateral involvement in amygdala demonstrates the selectivity of neurodegeneration in early AD.

Relationship of medial temporal lobe atrophy, APOE genotype, and cognitive reserve in preclinical Alzheimer's disease

This study evaluated the utility of baseline and longitudinal magnetic resonance imaging (MRI) measures of medial temporal lobe brain regions collected when participants were cognitively normal and largely in middle age (mean age 57 years) to predict the time to onset of clinical symptoms associated with mild cognitive impairment (MCI). Furthermore, we examined whether the relationship between MRI measures and clinical symptom onset was modified by apolipoprotein E (ApoE) genotype and level of cognitive reserve (CR). MRI scans and measures of CR were obtained at baseline from 245 participants who had been followed for up to 18 years (mean follow-up 11 years). A composite score based on reading, vocabulary, and years of education was used as an index of CR. Cox regression models showed that lower baseline volume of the right hippocampus and smaller baseline thickness of the right entorhinal cortex predicted the time to symptom onset independently of CR and ApoE-ɛ4 genotype, which also predicted the onset of symptoms. The atrophy rates of bilateral entorhinal cortex and amygdala volumes were also associated with time to symptom onset, independent of CR, ApoE genotype, and baseline volume. Only one measure, the left entorhinal cortex baseline volume, interacted with CR, such that smaller volumes predicted symptom onset only in individuals with lower CR. These results suggest that MRI measures of medial temporal atrophy, ApoE-ɛ4 genotype, and the protective effects of higher CR all predict the time to onset of symptoms associated with MCI in a largely independent, additive manner during the preclinical phase of Alzheimer's disease.

Amygdalar atrophy in symptomatic Alzheimer's disease based on diffeomorphometry: the BIOCARD cohort

This article examines the diffeomorphometry of magnetic resonance imaging-derived structural markers for the amygdala, in subjects with symptomatic Alzheimer's disease (AD). Using linear mixed-effects models we show differences between those with symptomatic AD and controls. Based on template centered population analysis, the distribution of statistically significant change is seen in both the volume and shape of the amygdala in subjects with symptomatic AD compared with controls. We find that high-dimensional vertex based markers are statistically more significantly discriminating (p < 0.00001) than lower-dimensional markers and volumes, consistent with comparable findings in presymptomatic AD. Using a high-field 7T atlas, significant atrophy was found to be centered in the basomedial and basolateral subregions, with no evidence of centromedial involvement.

Association of hearing impairment with brain volume changes in older adults

Hearing impairment in older adults is independently associated in longitudinal studies with accelerated cognitive decline and incident dementia, and in cross-sectional studies, with reduced volumes in the auditory cortex. Whether peripheral hearing impairment is associated with accelerated rates of brain atrophy is unclear. We analyzed brain volume measurements from magnetic resonance brain scans of individuals with normal hearing versus hearing impairment (speech-frequency pure tone average>25 dB) followed in the neuroimaging substudy of the Baltimore Longitudinal Study of Aging for a mean of 6.4 years after the baseline scan (n=126, age 56-86 years). Brain volume measurements were performed with semi-automated region-of-interest (ROI) algorithms, and brain volume trajectories were analyzed with mixed-effect regression models adjusted for demographic and cardiovascular factors. We found that individuals with hearing impairment (n=51) compared to those with normal hearing (n=75) had accelerated volume declines in whole brain and regional volumes in the right temporal lobe (superior, middle, and inferior temporal gyri, parahippocampus, p<.05). These results were robust to adjustment for multiple confounders and were consistent with voxel-based analyses, which also implicated right greater than left temporal regions. These findings demonstrate that peripheral hearing impairment is independently associated with accelerated brain atrophy in whole brain and regional volumes concentrated in the right temporal lobe. Further studies investigating the mechanistic basis of the observed associations are needed.

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

BACKGROUND

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

METHODS

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

RESULTS

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

COMPARISON WITH EXISTING METHOD(S)

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

CONCLUSION

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

Association of hearing impairment with brain volume changes in older adults

Hearing impairment in older adults is independently associated in longitudinal studies with accelerated cognitive decline and incident dementia, and in cross-sectional studies, with reduced volumes in the auditory cortex. Whether peripheral hearing impairment is associated with accelerated rates of brain atrophy is unclear. We analyzed brain volume measurements from magnetic resonance brain scans of individuals with normal hearing versus hearing impairment (speech-frequency pure tone average>25 dB) followed in the neuroimaging substudy of the Baltimore Longitudinal Study of Aging for a mean of 6.4 years after the baseline scan (n=126, age 56-86 years). Brain volume measurements were performed with semi-automated region-of-interest (ROI) algorithms, and brain volume trajectories were analyzed with mixed-effect regression models adjusted for demographic and cardiovascular factors. We found that individuals with hearing impairment (n=51) compared to those with normal hearing (n=75) had accelerated volume declines in whole brain and regional volumes in the right temporal lobe (superior, middle, and inferior temporal gyri, parahippocampus, p<.05). These results were robust to adjustment for multiple confounders and were consistent with voxel-based analyses, which also implicated right greater than left temporal regions. These findings demonstrate that peripheral hearing impairment is independently associated with accelerated brain atrophy in whole brain and regional volumes concentrated in the right temporal lobe. Further studies investigating the mechanistic basis of the observed associations are needed.

Quantitative imaging biomarkers: the application of advanced image processing and analysis to clinical and preclinical decision making

The importance of medical imaging for clinical decision making has been steadily increasing over the last four decades. Recently, there has also been an emphasis on medical imaging for preclinical decision making, i.e., for use in pharamaceutical and medical device development. There is also a drive towards quantification of imaging findings by using quantitative imaging biomarkers, which can improve sensitivity, specificity, accuracy and reproducibility of imaged characteristics used for diagnostic and therapeutic decisions. An important component of the discovery, characterization, validation and application of quantitative imaging biomarkers is the extraction of information and meaning from images through image processing and subsequent analysis. However, many advanced image processing and analysis methods are not applied directly to questions of clinical interest, i.e., for diagnostic and therapeutic decision making, which is a consideration that should be closely linked to the development of such algorithms. This article is meant to address these concerns. First, quantitative imaging biomarkers are introduced by providing definitions and concepts. Then, potential applications of advanced image processing and analysis to areas of quantitative imaging biomarker research are described; specifically, research into osteoarthritis (OA), Alzheimer's disease (AD) and cancer is presented. Then, challenges in quantitative imaging biomarker research are discussed. Finally, a conceptual framework for integrating clinical and preclinical considerations into the development of quantitative imaging biomarkers and their computer-assisted methods of extraction is presented.

Sex-specific risk of cardiovascular disease and cognitive decline: pregnancy and menopause

Understanding the biology of sex differences is integral to personalized medicine. Cardiovascular disease and cognitive decline are two related conditions, with distinct sex differences in morbidity and clinical manifestations, response to treatments, and mortality. Although mortality from all-cause cardiovascular diseases has declined in women over the past five years, due in part to increased educational campaigns regarding the recognition of symptoms and application of treatment guidelines, the mortality in women still exceeds that of men. The physiological basis for these differences requires further research, with particular attention to two physiological conditions which are unique to women and associated with hormonal changes: pregnancy and menopause. Both conditions have the potential to impact life-long cardiovascular risk, including cerebrovascular function and cognition in women. This review draws on epidemiological, translational, clinical, and basic science studies to assess the impact of hypertensive pregnancy disorders on cardiovascular disease and cognitive function later in life, and examines the effects of post-menopausal hormone treatments on cardiovascular risk and cognition in midlife women. We suggest that hypertensive pregnancy disorders and menopause activate vascular components, i.e., vascular endothelium and blood elements, including platelets and leukocytes, to release cell-membrane derived microvesicles that are potential mediators of changes in cerebral blood flow, and may ultimately affect cognition in women as they age. Research into specific sex differences for these disease processes with attention to an individual's sex chromosomal complement and hormonal status is important and timely.

Quantitative and qualitative assessment of structural magnetic resonance imaging data in a two-center study

BACKGROUND

Multi-center magnetic resonance imaging (MRI) studies present an opportunity to advance research by pooling data. However, brain measurements derived from MR-images are susceptible to differences in MR-sequence parameters. It is therefore necessary to determine whether there is an interaction between the sequence parameters and the effect of interest, and to minimise any such interaction by careful choice of acquisition parameters. As an exemplar of the issues involved in multi-center studies, we present data from a study in which we aimed to optimize a set of volumetric MRI-protocols to define a protocol giving data that are consistent and reproducible across two centers and over time.

METHODS

Optimization was achieved based on data quality and quantitative measures, in our case using FreeSurfer and Voxel Based Morphometry approaches. Our approach consisted of a series of five comparisons. Firstly, a single-center dataset was collected, using a range of candidate pulse-sequences and parameters chosen on the basis of previous literature. Based on initial results, a number of minor changes were implemented to optimize the pulse-sequences, and a second single-center dataset was collected. FreeSurfer data quality measures were compared between datasets in order to determine the best performing sequence(s), which were taken forward to the next stage of testing. We subsequently acquired short-term and long-term two-center reproducibility data, and quantitative measures were again assessed to determine the protocol with the highest reproducibility across centers. Effects of a scanner software and hardware upgrade on the reproducibility of the protocols at one of the centers were also evaluated.

RESULTS

Assessing the quality measures from the first two datasets allowed us to define artefact-free protocols, all with high image quality as assessed by FreeSurfer. Comparing the quantitative test and retest measures, we found high within-center reproducibility for all protocols, but lower between-center reproducibility for some protocols than others. The upgrade showed no important effects.

CONCLUSIONS

We were able to determine (for the scanners used in this study) an optimised protocol, which gave the highest within- and between-center reproducibility of those assessed, and give details of this protocol here. More generally, we discuss some of the issues raised by multi-center studies and describe a methodical approach to take towards optimization and standardization, and recommend performing this kind of procedure to other investigators.

Algorithms for characterizing brain metabolites in two-dimensional in vivo MR correlation spectroscopy

Traditional analyses of in vivo 1D MR spectroscopy of brain metabolites have been limited to the inspection of one-dimensional free induction decay (FID) signals from which only a limited number of metabolites are clearly observable. In this article we introduce a novel set of algorithms to process and characterize two-dimensional in vivo MR correlation spectroscopy (2D COSY) signals. 2D COSY data was collected from phantom solutions of topical metabolites found in the brain, namely glutamine, glutamate, and creatine. A statistical peak-detection and object segmentation algorithm is adapted for 2D COSY signals and applied to phantom solutions containing varied concentrations of glutamine and glutamate. Additionally, quantitative features are derived from peak and object structures, and we show that these measures are correlated with known phantom metabolite concentrations. These results are encouraging for future studies focusing on neurological disorders that induce subtle changes in brain metabolite concentrations and for which accurate quantitation is important.

Hippocampal atrophy in Alzheimer’s disease

SUMMARY New research criteria for Alzheimer’s disease (AD) and mild cognitive impairment (MCI) emphasize the use of imaging biomarkers in clinical diagnosis of these disorders. The volume loss of medial temporal lobe structures, especially hippocampal atrophy, is the best validated marker of AD. Manual tracing on MRI is the present gold standard for evaluating hippocampal volume; however, it is laborious and tracer-dependent. We categorized the most recent full- or semi-automated methods by the nature of the output of the method: size and shape of subcortical structures, cortical thickness, atrophy-rate and voxel- and region-based characteristics. The features of each method are introduced. The findings in structural MRI studies, especially in those studies utilizing the most recent methods, and the accuracies of those new methods in differentiating AD from healthy controls and stable MCI from progressive MCI are reviewed.

A longitudinal study of age- and gender-related annual rate of volume changes in regional gray matter in healthy adults

The aim of this study was to analyze correlations among the annual rate of gray matter volume change, age, gender, and cerebrovascular risk factors in 381 healthy community-dwelling subjects with a large age range by applying a longitudinal design over 6 years using brain magnetic resonance images (MRIs). Brain MRI data were processed with voxel-based morphometry using a custom template by applying diffeomorphic anatomical registration using the exponentiated lie algebra procedure. The annual rate of regional gray matter volume change showed significant positive correlations with age in several regions, including the bilateral temporal pole, caudate nucleus, ventral and dorsolateral prefrontal cortices, insula, hippocampus, and temporoparietal cortex, whereas significant negative correlations with age were observed in several regions including the bilateral cingulate gyri and anterior lobe of the cerebellum. Additionally, a significant age-by-gender interaction was found for the annual rate of regional gray matter volume change in the bilateral hippocampus. No significant correlations were observed between the annual rate of regional gray matter volume change and body mass index or systolic blood pressure. A significant positive correlation between the annual rate of gray matter volume change and age indicates that the region shows not linear but accelerated gray matter loss with age. Therefore, evaluating the annual rate of the gray matter volume change with age in healthy subjects is important in understanding how gray matter volume changes with aging in each brain region and in anticipating what cognitive functions are likely to show accelerated decline with aging.

Monitoring blood flow alterations in the Tg2576 mouse model of Alzheimer's disease by in vivo magnetic resonance angiography at 17.6 T

Many neurodegenerative diseases including Alzheimer's disease are linked to abnormalities in the vascular system. In AD, the deposition of amyloid β (Aβ) peptide in the cerebral vessel walls, known as cerebral amyloid angiopathy (CAA) is frequently observed, leading to blood flow abnormalities. Visualization of the changes in vascular structure is important for early diagnosis and treatment. Blood vessels can be imaged non-invasively by magnetic resonance angiography (MRA). In this study we optimized high resolution MRA at 17.6 T to longitudinally monitor morphological changes in cerebral arteries in a Tg2576 mouse model, a widely used model of AD. Our results at 17.6 T show that MRA significantly benefits from the ultra-high magnetic field strength especially to visualize smaller vessels. Visual and quantitative analysis of MRA results revealed severe blood flow defects in large and medium sized arteries in Tg2576 mice. In particular blood flow defects were observed in the middle cerebral artery (MCA) and in the anterior communicating artery (AComA) in Tg2576 mice. Histological data show that Aβ levels in the vessel wall may be responsible for impaired cerebral blood flow, thereby contributing to the early progression of AD. To our knowledge this is the first ultra-high field MRA study monitoring blood flow alterations longitudinally in living Tg2576 mice, consequently providing a powerful tool to test new therapeutic intervention related to CAA in a mouse model of AD.

In vivo human amyloid imaging

PET imaging agents such as Pittsburgh compound B (PiB) allow detection of fibrillar β-amyloid (Aβ) in vivo. In addition to quantification of Aβ deposition in mild cognitive impairment and Alzheimer's disease, PiB has also increased our understanding of Aβ deposition in older adults without cognitive impairment. In vivo Aβ deposition has been studied in relation to genotype, structural and functional brain changes, as well as alterations in biomarker levels. To date, several studies have reported changes in Aβ burden over time. This, together with investigation of the relationship between Aβ deposition and cognition, sets the stage for elucidation of the temporal sequence of the neurobiological events leading to cognitive decline. Furthermore, correlation of Aβ levels detected by PiB PET and those obtained from biopsy or postmortem specimens will allow more rigorous quantitative interpretation of PiB PET data in relation to neuropathological evaluation. Since the first human study in 2004, in vivo amyloid imaging has led to advances in our understanding of the role of Aβ deposition in human aging and cognitive decline, as well as provided new tools for patient selection and therapeutic monitoring in clinical trials.

Midlife obesity and trajectories of brain volume changes in older adults

Although obesity has been linked to structural brain changes, little is known about its associations with the rates of brain atrophy. We examined associations between global (BMI) and central (waist circumference) midlife obesity and subsequent trajectories of regional brain atrophy in 152 individuals [M (age) = 69 ± 7.8] prospectively followed through the Baltimore Longitudinal Study of Aging; 21 individuals became impaired during follow-up. We report no associations (P > 0.05) between either global or central midlife obesity and subsequent rates of regional brain volume changes against a background of age-related atrophy in older individuals who remained nondemented. When looking at the entire sample, greater decline was observed in the volume of gray matter, precuneus, cingulate and orbito-frontal gyri for globally obese (P < 0.03), even though only data up to the point of dementia diagnosis were included in the analyses (i.e., while still considered clinically normal). Moreover, when trajectories of regional volume changes were examined across the range of BMI and waist circumference values instead of employing a cut-off point to define obesity, a different pattern of results emerged. Overall, our results suggest that midlife obesity may be an important modifier of brain atrophy in individuals who are developing cognitive impairment and dementia, while it has little effect on structural brain integrity in nondemented older adults. Moreover, the discrepancies in findings between studies may be in part due to participant sampling and methodological differences.

Biomarkers in Alzheimer's disease drug development

Developing new therapies for Alzheimer's disease (AD) is critically important to avoid the impending public health disaster imposed by this common disorder. Means must be found to prevent, delay the onset, or slow the progression of AD. These goals will be achieved by identifying disease-modifying therapies and testing them in clinical trials. Biomarkers play an increasingly important role in AD drug development. In preclinical testing, they assist in decisions to develop an agent. Biomarkers in phase I provide insights into toxic responses and drug metabolism and in Phase II proof-of-concept trials they facilitate go/no-go decisions and dose finding. Biomarkers can play a role in identifying presymptomatic patients or specific patient subgroups. They can provide evidence of target engagement before clinical changes can be expected. Brain imaging can serve as a primary outcome in Phase II trials and as a key secondary outcome in Phase III trials. Magnetic resonance imaging is currently best positioned for use in large multicenter clinical trials. Cerebrospinal fluid (CSF) measures of amyloid beta protein (Aβ), tau protein, and hyperphosphorylated tau (p-tau) protein are sensitive and specific to the diagnosis of AD and may serve as inclusion criteria and possibly as outcomes in clinical trials targeting relevant pathways. Plasma measures of Aβ are of limited diagnostic value but may provide important information as a measure of treatment response. A wide variety of measures of detectable products of cellular processes are being developed as possible biomarkers accessible in the cerebrospinal fluid and plasma or serum. Surrogate markers that can function as outcomes in pivotal trials and reliably predict clinical outcomes are needed to facilitate primary prevention trials of asymptomatic persons where clinical measures may be of limited value. Fit-for-purpose biomarkers are increasingly available to guide AD drug development decisions.

Neuronal dysfunction and disconnection of cortical hubs in non-demented subjects with elevated amyloid burden

Disruption of functional connectivity between brain regions may represent an early functional consequence of β-amyloid pathology prior to clinical Alzheimer's disease. We aimed to investigate if non-demented older individuals with increased amyloid burden demonstrate disruptions of functional whole-brain connectivity in cortical hubs (brain regions typically highly connected to multiple other brain areas) and if these disruptions are associated with neuronal dysfunction as measured with fluorodeoxyglucose-positron emission tomography. In healthy subjects without cognitive symptoms and patients with mild cognitive impairment, we used positron emission tomography to assess amyloid burden and cerebral glucose metabolism, structural magnetic resonance imaging to quantify atrophy and novel resting state functional magnetic resonance imaging processing methods to calculate whole-brain connectivity. Significant disruptions of whole-brain connectivity were found in amyloid-positive patients with mild cognitive impairment in typical cortical hubs (posterior cingulate cortex/precuneus), strongly overlapping with regional hypometabolism. Subtle connectivity disruptions and hypometabolism were already present in amyloid-positive asymptomatic subjects. Voxel-based morphometry measures indicate that these findings were not solely a consequence of regional atrophy. Whole-brain connectivity values and metabolism showed a positive correlation with each other and a negative correlation with amyloid burden. These results indicate that disruption of functional connectivity and hypometabolism may represent early functional consequences of emerging molecular Alzheimer's disease pathology, evolving prior to clinical onset of dementia. The spatial overlap between hypometabolism and disruption of connectivity in cortical hubs points to a particular susceptibility of these regions to early Alzheimer's-type neurodegeneration and may reflect a link between synaptic dysfunction and functional disconnection.

Lack of association between 11C-PiB and longitudinal brain atrophy in non-demented older individuals

Amyloid-β plaques (Aβ) are a hallmark of Alzheimer's disease (AD), begin deposition decades before the incipient disease, and are thought to be associated with neuronal loss, brain atrophy and cognitive impairment. We examine associations between (11)C-PiB-PET measurement of Aβ burden and brain volume changes in the preceding years in 57 non-demented individuals (age 64-86; M=78.7). Participants were prospectively followed through the Baltimore Longitudinal Study of Aging, with up to 10 consecutive MRI scans (M=8.1) and an (11)C-PiB scan approximately 10 years after the initial MRI. Linear mixed effects models were used to determine whether mean cortical (11)C-PiB distribution volume ratios, estimated by fitting a reference tissue model to the measured time activity curves, were associated with longitudinal regional brain volume changes of the whole brain, ventricular CSF, frontal, temporal, parietal, and occipital white and gray matter, the hippocampus, orbito-frontal cortex, and the precuneus. Despite significant longitudinal declines in the volumes of all investigated regions (p<0.05), no associations were detected between current Aβ burden and regional brain volume decline trajectories in the preceding years, nor did the regional volume trajectories differ between those with highest and lowest Aβ burden. Consistent with a threshold model of disease, our findings suggest that Aβ load does not seem to affect brain volume changes in individuals without dementia.

Automatic analysis of medial temporal lobe atrophy from structural MRIs for the early assessment of Alzheimer disease

The purpose of this study is to develop a software for the extraction of the hippocampus and surrounding medial temporal lobe (MTL) regions from T1-weighted magnetic resonance (MR) images with no interactive input from the user, to introduce a novel statistical indicator, computed on the intensities in the automatically extracted MTL regions, which measures atrophy, and to evaluate the accuracy of the newly developed intensity-based measure of MTL atrophy to (a) distinguish between patients with Alzheimer disease (AD), patients with amnestic mild cognitive impairment (aMCI), and elderly controls by using established criteria for patients with AD and aMCI as the reference standard and (b) infer about the clinical outcome of aMCI patients. For the development of the software, the study included 61 patients with mild AD (17 men, 44 women; mean age +/- standard deviation (SD), 75.8 years +/- 7.8; Mini Mental State Examination (MMSE) score, 24.1 +/- 3.1), 42 patients with aMCI (11 men, 31 women; mean age +/- SD, 75.2 years +/- 4.9; MMSE score, 27.9 +/- 1.9), and 30 elderly healthy controls (10 men, 20 women; mean age +/- SD, 74.7 years +/- 5.2; MMSE score, 29.1 +/- 0.8). For the evaluation of the statistical indicator, 150 patients with mild AD (62 men, 88 women; mean age +/- SD, 76.3 years +/- 5.8; MMSE score, 23.2 +/- 4.1), 247 patients with aMCI (143 men, 104 women; mean age +/- SD, 75.3 years +/- 6.7; MMSE score, 27.0 +/- 1.8), and 135 elderly healthy controls (61 men, 74 women; mean age +/- SD, 76.4 years +/- 6.1). Fifty aMCI patients were evaluated every 6 months over a 3 year period to assess conversion to AD. For each participant, two subimages of the MTL regions were automatically extracted from T1-weighted MR images with high spatial resolution. An intensity-based MTL atrophy measure was found to separate control, MCI, and AD cohorts. Group differences were assessed by using two-sample t test. Individual classification was analyzed by using receiver operating characteristic (ROC) curves. Compared to controls, significant differences in the intensity-based MTL atrophy measure were detected in both groups of patients (AD vs controls, 0.28 +/- 0.03 vs 0.34 +/- 0.03, P < 0.001; aMCI vs controls, 0.31 +/- 0.03 vs 0.34 +/- 0.03, P < 0.001). Moreover, the subgroup of aMCI converters was significantly different from controls (0.27 +/- 0.034 vs 0.34 +/- 0.03, P < 0.001). Regarding the ROC curve for intergroup discrimination, the area under the curve was 0.863 for AD patients vs controls, 0.746 for all aMCI patients vs controls, and 0.880 for aMCI converters vs controls. With specificity set at 85%, the sensitivity was 74% for AD vs controls, 45% for aMCI vs controls, and 83% for aMCI converters vs controls. The automated analysis of MTL atrophy in the segmented volume is applied to the early assessment of AD, leading to the discrimination of aMCI converters with an average 3 year follow-up. This procedure can provide additional useful information in the early diagnosis of AD.

Longitudinal pattern of regional brain volume change differentiates normal aging from MCI

BACKGROUND

Neuroimaging measures have potential as surrogate markers of disease through identification of consistent features that occur prior to clinical symptoms. Despite numerous investigations, especially in relation to the transition to clinical impairment, the regional pattern of brain changes in clinically normal older adults has not been established. We predict that the regions that show early pathologic changes in association with Alzheimer disease will show accelerated volume loss in mild cognitive impairment (MCI) compared to normal aging.

METHODS

Through the Baltimore Longitudinal Study of Aging, we prospectively evaluated 138 nondemented individuals (age 64-86 years) annually for up to 10 consecutive years. Eighteen participants were diagnosed with MCI over the course of the study. Mixed-effects regression was used to compare regional brain volume trajectories of clinically normal individuals to those with MCI based on a total of 1,017 observations.

RESULTS

All investigated volumes declined with normal aging (p < 0.05). Accelerated change with age was observed for ventricular CSF (vCSF), frontal gray matter, superior, middle, and medial frontal, and superior parietal regions (p < or = 0.04). The MCI group showed accelerated changes compared to normal controls in whole brain volume, vCSF, temporal gray matter, and orbitofrontal and temporal association cortices, including the hippocampus (p < or = 0.04).

CONCLUSION

Although age-related regional volume loss is apparent and widespread in nondemented individuals, mild cognitive impairment is associated with a unique pattern of structural vulnerability reflected in differential volume loss in specific regions. Early identification of patterns of abnormality is of fundamental importance for detecting disease onset and tracking progression.

Mapping correlations between ventricular expansion and CSF amyloid and tau biomarkers in 240 subjects with Alzheimer's disease, mild cognitive impairment and elderly controls

We aimed to improve on the single-atlas ventricular segmentation method of (Carmichael, O.T., Thompson, P.M., Dutton, R.A., Lu, A., Lee, S.E., Lee, J.Y., Kuller, L.H., Lopez, O.L., Aizenstein, H.J., Meltzer, C.C., Liu, Y., Toga, A.W., Becker, J.T., 2006. Mapping ventricular changes related to dementia and mild cognitive impairment in a large community-based cohort. IEEE ISBI. 315-318) by using multi-atlas segmentation, which has been shown to lead to more accurate segmentations (Chou, Y., Leporé, N., de Zubicaray, G., Carmichael, O., Becker, J., Toga, A., Thompson, P., 2008. Automated ventricular mapping with multi-atlas fluid image alignment reveals genetic effects in Alzheimer's disease, NeuroImage 40(2): 615-630); with this method, we calculated minimal numbers of subjects needed to detect correlations between clinical scores and ventricular maps. We also assessed correlations between emerging CSF biomarkers of Alzheimer's disease pathology and localizable deficits in the brain, in 80 AD, 80 mild cognitive impairment (MCI), and 80 healthy controls from the Alzheimer's Disease Neuroimaging Initiative. Six expertly segmented images and their embedded parametric mesh surfaces were fluidly registered to each brain; segmentations were averaged within subjects to reduce errors. Surface-based statistical maps revealed powerful correlations between surface morphology and 4 variables: (1) diagnosis, (2) depression severity, (3) cognitive function at baseline, and (4) future cognitive decline over the following year. Cognitive function was assessed using the mini-mental state exam (MMSE), global and sum-of-boxes clinical dementia rating (CDR) scores, at baseline and 1-year follow-up. Lower CSF Abeta(1-42) protein levels, a biomarker of AD pathology assessed in 138 of the 240 subjects, were correlated with lateral ventricular expansion. Using false discovery rate (FDR) methods, 40 and 120 subjects, respectively, were needed to discriminate AD and MCI from normal groups. 120 subjects were required to detect correlations between ventricular enlargement and MMSE, global CDR, sum-of-boxes CDR and clinical depression scores. Ventricular expansion maps correlate with pathological and cognitive measures in AD, and may be useful in future imaging-based clinical trials.

MRI-derived measurements of human subcortical, ventricular and intracranial brain volumes: Reliability effects of scan sessions, acquisition sequences, data analyses, scanner upgrade, scanner vendors and field strengths

Automated MRI-derived measurements of in-vivo human brain volumes provide novel insights into normal and abnormal neuroanatomy, but little is known about measurement reliability. Here we assess the impact of image acquisition variables (scan session, MRI sequence, scanner upgrade, vendor and field strengths), FreeSurfer segmentation pre-processing variables (image averaging, B1 field inhomogeneity correction) and segmentation analysis variables (probabilistic atlas) on resultant image segmentation volumes from older (n=15, mean age 69.5) and younger (both n=5, mean ages 34 and 36.5) healthy subjects. The variability between hippocampal, thalamic, caudate, putamen, lateral ventricular and total intracranial volume measures across sessions on the same scanner on different days is less than 4.3% for the older group and less than 2.3% for the younger group. Within-scanner measurements are remarkably reliable across scan sessions, being minimally affected by averaging of multiple acquisitions, B1 correction, acquisition sequence (MPRAGE vs. multi-echo-FLASH), major scanner upgrades (Sonata-Avanto, Trio-TrioTIM), and segmentation atlas (MPRAGE or multi-echo-FLASH). Volume measurements across platforms (Siemens Sonata vs. GE Signa) and field strengths (1.5 T vs. 3 T) result in a volume difference bias but with a comparable variance as that measured within-scanner, implying that multi-site studies may not necessarily require a much larger sample to detect a specific effect. These results suggest that volumes derived from automated segmentation of T1-weighted structural images are reliable measures within the same scanner platform, even after upgrades; however, combining data across platform and across field-strength introduces a bias that should be considered in the design of multi-site studies, such as clinical drug trials. The results derived from the young groups (scanner upgrade effects and B1 inhomogeneity correction effects) should be considered as preliminary and in need for further validation with a larger dataset.

[Brain apparent diffusion coefficient: differences caused by age, sex, laterality, and distinct b value]

OBJECTIVE

To analyze the effects of age, sex, and b value on the apparent diffusion coefficient (ADC) in brain areas affected by neurodegenerative diseases.

MATERIAL AND METHODS

We studied the ADC of the genu and splenium of the corpus callosum and of the hippocampus in normal patients using diffusion magnetic resonance imaging (dMRI) with b1,000 s/mm2 and b3,000 s/mm2. We calculated the differences between the ADC (diffusion differential [DD]) with b1,000 and with b3,000 for each region. Patients were classified into the following age groups (<or=30 years old, 31-60 years old, >60 years old). We used a Kruskal-Wallis one-way ANOVA and the Bonferroni correction to analyze the differences in ADC and DD between age groups and between sexes. Pearson's chi-square test was used to correlate the ADC and DD with age.

RESULTS

In the right hippocampus, we observed differences in ADC (b1,000, p=0.011; b3,000, p=0.024) and DD (p=0.006) with age. Differences in ADC were observed between the 31-60 year-old age group and the >60 year-old age group (p=0.009) for b1,000, and between the<30 year-old age group and the 31-60 year-old age group (p=0.036) for b3,000. The DD in the >60 year-old age group was different from the rest. In the corpus callosum, there were significant differences between sexes in the DD of the genu (p=0.016). The DD was correlated with age in the right hippocampus (r=0.321, p=0.023).

CONCLUSIONS

Our data indicate greater stability in mean ADC values with b3000 during aging. It might be useful to analyze the ADC with a higher b in patients with neurodegenerative diseases.

Decreased cerebrospinal fluid Abeta(42) correlates with brain atrophy in cognitively normal elderly

OBJECTIVE

For therapies for Alzheimer's disease (AD) to have the greatest impact, it will likely be necessary to treat individuals in the "preclinical" (presymptomatic) stage. Fluid and neuroimaging measures are being explored as possible biomarkers of AD pathology that could aid in identifying individuals in this stage to target them for clinical trials and to direct and monitor therapy. The objective of this study was to determine whether cerebrospinal fluid (CSF) biomarkers for AD suggest the presence of brain damage in the preclinical stage of AD.

METHODS

We investigated the relation between structural neuroimaging measures (whole-brain volume) and levels of CSF amyloid-beta (Abeta)(40), Abeta(42), tau, and phosphorylated tau(181) (ptau(181)), and plasma Abeta(40) and Abeta(42) in well-characterized research subjects with very mild and mild dementia of the Alzheimer type (n = 29) and age-matched, cognitively normal control subjects (n = 69).

RESULTS

Levels of CSF tau and ptau(181), but not Abeta(42), correlated inversely with whole-brain volume in very mild and mild dementia of the Alzheimer type, whereas levels of CSF Abeta(42), but not tau or ptau(181), were positively correlated with whole-brain volume in nondemented control subjects.

INTERPRETATION

Reduction in CSF Abeta(42), likely reflecting Abeta aggregation in the brain, is associated with brain atrophy in the preclinical phase of AD. This suggests that there is toxicity associated with Abeta aggregation before the onset of clinically detectable disease. Increases in CSF tau (and ptau(181)) are later events that correlate with further structural damage and occur with clinical onset and progression.

The validity of biomarkers as surrogate endpoints in Alzheimer's disease by means of the Quantitative Surrogate Validation Level of Evidence Scheme (QSVLES)

OBJECTIVE

To evaluate the validity of biomarkers that are currently being proposed as potential surrogate endpoints in AD clinical trials with the aid of the "Quantitative Surrogate Validation Level of Evidence Schema" (QSVLES) proposed by Lassere et.al. (1).

PROCEDURE

A Pubmed literature search was conducted to identify AD biomarkers with SEP potential, and the QSVLES was applied to determine the extent of the SEP validity.

RESULTS

MRI, PET and MRS measures attained a total validity score of 4, NAA/Cre a total score of 5, and cerebral blood flow (SPECT), Abeta , Tau and APP a total score of 2. None of these biomarkers could fall into the rank of Levels 1 or 2, reserved for SEPs, according to the QSVLES criteria. This was mainly attributed to the lack of sufficient evidence that was derived from high ranking studies (RCT, prospective observational studies).

CONCLUSION

Though residing on SEPs as sole determinants of the benefit/risk ratio of AD medications seems to be pretty far, there could be certain cases where the use of SEPs may be beneficial, making efficient therapies available faster when there is a major public health interest involved. However, the potential risks of relying on invalid SEPs should not be underestimated and therefore the research on SEP validation and the development of specific validation guidance should be encouraged. The QSVLES, though not devoid of criticism, may be proposed as a starting point.

Magnetic resonance imaging traits in siblings discordant for Alzheimer disease

BACKGROUND

Magnetic resonance imaging (MRI) can aid clinical assessment of brain changes potentially correlated with Alzheimer disease (AD). MRI traits may improve our ability to identify genes associated with AD-outcomes. We evaluated semi-quantitative MRI measures as endophenotypes for genetic studies by assessing their association with AD in families from the Multi-Institutional Research in Alzheimer Genetic Epidemiology (MIRAGE) Study.

METHODS

Discordant siblings from multiple ethnicities were ascertained through a single affected proband. Semi-quantitative MRI measures were obtained for each individual. The association between continuous/ordinal MRI traits and AD were analyzed using generalized estimating equations. Medical history and Apolipoprotein E (APOE)epsilon4 status were evaluated as potential confounders.

RESULTS

Comparisons of 214 affected and 234 unaffected subjects from 229 sibships revealed that general cerebral atrophy, white matter hyperintensities (WMH), and mediotemporal atrophy differed significantly between groups (each at P < .0001) and varied by ethnicity. Age at MRI and duration of AD confounded all associations between AD and MRI traits. Among unaffected sibs, the presence of at least one APOEepsilon4 allele and MRI infarction was associated with more WMH after adjusting for age at MRI.

CONCLUSION

The strong association between MRI traits and AD suggests that MRI traits may be informative endophenotypes for basic and clinical studies of AD. In particular, WMH may be a marker of vascular disease that contributes to AD pathogenesis.

Alzheimer disease: postmortem neuropathologic correlates of antemortem 1H MR spectroscopy metabolite measurements

PURPOSE

To determine the neuropathologic correlates of antemortem hydrogen 1 ((1)H) magnetic resonance (MR) spectroscopy metabolite measurements in subjects with Alzheimer disease (AD)-type pathology.

MATERIALS AND METHODS

This study was approved by the institutional review board and was compliant with HIPAA regulations. Informed consent was obtained from each subject. The authors identified 54 subjects who underwent antemortem (1)H MR spectroscopy and were clinically healthy or had AD-type pathology with low to high likelihood of AD according to National Institute on Aging-Reagan neuropathologic criteria at autopsy. They investigated the associations between (1)H MR spectroscopy metabolite measurements and Braak neurofibrillary tangle stage (Braak stage), neuritic plaque score, and AD likelihood, with adjustments for subject age, subject sex, and time between (1)H MR spectroscopy and death.

RESULTS

Decreases in N-acetylaspartate-to-creatine ratio, an index of neuronal integrity, and increases in myo-inositol-to-creatine ratio were associated with higher Braak stage, higher neuritic plaque score, and greater likelihood of AD. The N-acetylaspartate-to-myo-inositol ratio proved to be the strongest predictor of the pathologic likelihood of AD. The strongest association observed was that between N-acetylaspartate-to-myo-inositol ratio and Braak stage (R(N)(2) = 0.47, P < .001).

CONCLUSION

Antemortem (1)H MR spectroscopy metabolite changes correlated with AD-type pathology seen at autopsy. The study findings validated (1)H MR spectroscopy metabolite measurements against the neuropathologic criteria for AD, and when combined with prior longitudinal (1)H MR spectroscopy findings, indicate that these measurements could be used as biomarkers for disease progression in clinical trials.

Hippocampal shape analysis of Alzheimer disease based on machine learning methods

BACKGROUND AND PURPOSE

Alzheimer disease (AD) is a neurodegenerative disease characterized by progressive dementia. The hippocampus is particularly vulnerable to damage at the very earliest stages of AD. This article seeks to evaluate critical AD-associated regional changes in the hippocampus using machine learning methods.

MATERIALS AND METHODS

High-resolution MR images were acquired from 19 patients with AD and 20 age- and sex-matched healthy control subjects. Regional changes of bilateral hippocampi were characterized using computational anatomic mapping methods. A feature selection method for support vector machine and leave-1-out cross-validation was introduced to determine regional shape differences that minimized the error rate in the datasets.

RESULTS

Patients with AD showed significant deformations in the CA1 region of bilateral hippocampi, as well as the subiculum of the left hippocampus. There were also some changes in the CA2-4 subregions of the left hippocampus among patients with AD. Moreover, the left hippocampal surface showed greater variations than the right compared with those in healthy control subjects. The accuracies of leave-1-out cross-validation and 3-fold cross-validation experiments for assessing the reliability of these subregions were more than 80% in bilateral hippocampi.

CONCLUSION

Subtle and spatially complex deformation patterns of hippocampus between patients with AD and healthy control subjects can be detected by machine learning methods.

Quantitative magnetization transfer imaging in Alzheimer disease

PURPOSE

To prospectively measure magnetization transfer (MT) parameters, along with established atrophy parameters, in patients with Alzheimer disease (AD) and in age- and sex-matched control subjects.

MATERIALS AND METHODS

Participants provided informed consent, and additional assent was obtained from next of kin of all patients with AD. The study was approved by the local ethics committee. Fourteen patients with AD (seven men; mean age, 67.2 years+/-6.5 [standard deviation]) and 14 control subjects (nine men; mean age, 65.5 years+/-9.4) underwent volumetric T1-weighted magnetic resonance and MT imaging. Whole-brain and total hippocampal volumes were adjusted for total intracranial volume. MT images were processed to derive four fundamental parameters in the hippocampal region by using the two-pool model of the MT phenomenon. Pearson correlation coefficients were used to assess the association between volumetric and MT parameters and Mini-Mental State Examination (MMSE) results. Logistic regression models were used to investigate whether combinations of parameters associated with MMSE could help provide better group discrimination.

RESULTS

Patients with AD had significantly reduced whole-brain (P=.001) and total hippocampal (P<.001) volumes compared with those of control subjects. Two MT parameters were significantly reduced in the hippocampal region of patients: 1/(RAT2A)--that is, ratio of relaxation times of free proton pool, where RA equals 1/T1A and is the inverse of the longitudinal relaxation time of the free proton pool (P=.01)--and f*b, which equals fb/[RA(1-fb)], where fb is the restricted proton fraction (P<.001). Among patients with AD, whole-brain volume and hippocampal were correlated with MMSE results. When both parameters were included in a logistic regression model, only hippocampal was significantly associated with case-control status (P=.03).

CONCLUSION

Certain MT parameters may serve as useful biomarkers of AD.

Biomarkers for Alzheimer's disease

Alzheimer's disease (AD) is a horribly debilitating disease that will increase in prevalence as the populations of the USA and Europe continue to age. It is expected that the USA alone will see some 16 million cases by 2050. At present, there is no cure for the disease and early diagnosis is all but impossible. The onset of disease is not manifested clinically and little is known regarding the cause of nonfamiliar AD. There is a need for biomarkers associated with AD to aid the diagnosis of this disease and to detect progression. Especially needed are biomarkers to monitor the effect of new drugs and therapeutic strategies as they are developed. A biomarker may be a genetic trait, a biochemical change, such as a protein, peptide or metabolite, or a change in a structural or functional feature detected using imaging technology. This review aims to cover the important field of biomarker research in association with AD.