Volumetric MRI vs clinical predictors of Alzheimer disease in mild cognitive impairment

Brain imaging of mild cognitive impairment and Alzheimer's disease

The rapidly increasing prevalence of cognitive impairment and Alzheimer's disease has the potential to create a major worldwide healthcare crisis. Structural MRI studies in patients with Alzheimer's disease and mild cognitive impairment are currently attracting considerable interest. It is extremely important to study early structural and metabolic changes, such as those in the hippocampus, entorhinal cortex, and gray matter structures in the medial temporal lobe, to allow the early detection of mild cognitive impairment and Alzheimer's disease. The microstructural integrity of white matter can be studied with diffusion tensor imaging. Increased mean diffusivity and decreased fractional anisotropy are found in subjects with white matter damage. Functional imaging studies with positron emission tomography tracer compounds enable detection of amyloid plaques in the living brain in patients with Alzheimer's disease. In this review, we will focus on key findings from brain imaging studies in mild cognitive impairment and Alzheimer's disease, including structural brain changes studied with MRI and white matter changes seen with diffusion tensor imaging, and other specific imaging methodologies will also be discussed.

Potential Clinical Applications of PET/MR Imaging in Neurodegenerative Diseases

Neurodegenerative disorders such as Alzheimer disease are among today's most alarming health problems in our aging society. The clinical assessment of neurodegenerative disorders benefits from recent innovations in the field of imaging technology. These innovations include emerging tracers for molecular imaging of neurodegenerative pathology and the introduction of novel integrated PET/MR imaging instruments. Because both PET and MR imaging procedures have shown critical value in the diagnostic work-up of neurodegenerative disorders, the combination of both imaging modalities in the form of an integrated PET/MR imaging system may be of value. This combination includes practical methodologic advantages and an improved workflow facilitated by the combined acquisition of dual-modality data. It offers clinical advantages because of the systematic combination of complementary information, potentially allowing the creation of novel integrated imaging biomarkers. The effectiveness of new disease-modifying treatments may depend on the timely initiation of therapy before irreversible neuronal damage in slowly progressive neurodegenerative disorders. Integrated PET/MR imaging may be able to improve such early diagnosis through both structural and functional information.

Value of serum nonceruloplasmin copper for prediction of mild cognitive impairment conversion to Alzheimer disease

OBJECTIVE

Meta-analyses show that nonbound ceruloplasmin (non-Cp) copper (also known as free or labile copper) in serum is higher in patients with Alzheimer disease (AD). It differentiates subjects with mild cognitive impairment (MCI) from healthy controls. However, a longitudinal study on an MCI cohort has not yet been performed to assess the accuracy of non-Cp copper for the prediction of conversion from MCI to AD during a long-term follow-up.

METHODS

The study included 42 MCI converters and 99 stable MCI subjects. We assessed levels of copper, ceruloplasmin, non-Cp copper, iron, transferrin, ferritin, and APOE genotype. A multiple Cox regression analysis-with age, sex, baseline Mini-Mental State Examination, APOE4, iron, non-Cp copper, transferrin, ferritin, hypercholesterolemia, and hypertension as covariates-was applied to predict the conversion from MCI to AD.

RESULTS

Among the evaluated parameters, the only significant predictor of conversion to AD was non-Cp copper (hazard ratio = 1.23, 95% confidence interval = 1.03-1.47, p = 0.022); for each additional micromole per liter unit (μmol/l) of non-Cp copper, the hazard increased by ~20%. Subjects with non-Cp copper levels >1.6 μmol/l had a hazard conversion rate (50% of conversion in 4 years) that was ~3× higher than those with values ≤1.6 μmol/l (<20% in 4 years). The rate of conversion was similar between APOE4 carriers and noncarriers (p = 0.321), indicating that the non-Cp copper association was independent of APOE4.

INTERPRETATION

Non-Cp copper appears to predict conversion from MCI to AD. These results encourage healthy life style choices and dietary intervention to modify this risk.

Ventricular enlargement and its clinical correlates in the imaging cohort from the ADCS MCI donepezil/vitamin E study

We analyzed the baseline and 3-year T1-weighted magnetic resonance imaging data of 110 amnestic mild cognitive impairment (MCI) participants with minimal hippocampal atrophy at baseline from the Alzheimer's Disease Cooperative Study group MCI Donepezil/Vitamin E trial. Forty-six subjects converted to Alzheimer disease (AD) (MCIc), whereas 64 remained stable (MCInc). We used the radial distance technique to examine the differences in lateral ventricle shape and size between MCIc and MCInc and the associations between ventricular enlargement and cognitive decline. MCIc group had significantly larger frontal and right body/occipital horns relative to MCInc at baseline and significantly larger bilateral frontal, body/occipital, and left temporal horns at follow-up. Global cognitive decline measured with AD Assessment scale cognitive subscale and Mini-Mental State Examination and decline in activities of daily living (ADL) were associated with posterior lateral ventricle enlargement. Decline in AD Assessment scale cognitive subscale and ADL were associated with left temporal and decline in Mini-Mental State Examination with right temporal horn enlargement. After correction for baseline hippocampal volume, decline in ADL showed a significant association with right frontal horn enlargement. Executive decline was associated with right frontal and left temporal horn enlargement.

The value of hippocampal and temporal horn volumes and rates of change in predicting future conversion to AD

Hippocampal pathology occurs early in Alzheimer disease (AD), and atrophy, measured by volumes and volume changes, may predict which subjects will develop AD. Measures of the temporal horn (TH), which is situated adjacent to the hippocampus, may also indicate early changes in AD. Previous studies suggest that these metrics can predict conversion from amnestic mild cognitive impairment (MCI) to AD with conversion and volume change measured concurrently. However, the ability of these metrics to predict future conversion has not been investigated. We compared the abilities of hippocampal, TH, and global measures to predict future conversion from MCI to AD. TH, hippocampi, whole brain, and ventricles were measured using baseline and 12-month scans. Boundary shift integral was used to measure the rate of change. We investigated the prediction of conversion between 12 and 24 months in subjects classified as MCI from baseline to 12 months. All measures were predictive of future conversion. Local and global rates of change were similarly predictive of conversion. There was evidence that the TH expansion rate is more predictive than the hippocampal atrophy rate (P=0.023) and that the TH expansion rate is more predictive than the TH volume (P=0.036). Prodromal atrophy rates may be useful predictors of future conversion to sporadic AD from amnestic MCI.

Dementia in Down's syndrome: an MRI comparison with Alzheimer's disease in the general population

BACKGROUND

Down's syndrome (DS) is the most common genetic cause of intellectual disability. People with DS are at an increased risk of Alzheimer's disease (AD) compared to the general population. Neuroimaging studies of AD have focused on medial temporal structures; however, to our knowledge, no in vivo case-control study exists comparing the anatomy of dementia in DS to people with AD in the general population. We therefore compared the in vivo brain anatomy of people with DS and dementia (DS+) to those with AD in the general population.

METHOD

Using MRI in 192 adults, we compared the volume of whole brain matter, lateral ventricles, temporal lobes and hippocampus in DS subjects with and without dementia (DS+, DS-), to each other and to three non-DS groups. These included one group of individuals with AD and two groups of controls (each age-matched for their respective DS and general population AD cohorts).

RESULTS

AD and DS+ subjects showed significant reductions in the volume of the whole brain, hippocampus and temporal lobes and a significant elevation in the volume of the lateral ventricle, compared to their non-demented counterparts. People with DS+ had a smaller reduction in temporal lobe volume compared to individuals with AD.

CONCLUSIONS

DS+ and AD subjects have a significant reduction in volume of the same brain regions. We found preliminary evidence that DS individuals may be more sensitive to tissue loss than others and have less 'cognitive reserve'.

Recent advances in imaging Alzheimer's disease

Advances in brain imaging technology in the past five years have contributed greatly to the understanding of Alzheimer's disease (AD). Here, we review recent research related to amyloid imaging, new methods for magnetic resonance imaging analyses, and statistical methods. We also review research that evaluates AD risk factors and brain imaging, in the context of AD prediction and progression. We selected a variety of illustrative studies, describing how they advanced the field and are leading AD research in promising new directions.

Selected findings from the Religious Orders Study and Rush Memory and Aging Project

The Religious Orders Study and the Rush Memory and Aging Project are both cohort studies of aging and dementia that include organ donation at death. Together, more than 2,700 persons have agreed to annual clinical evaluation and brain donation at death. A subset of participants also participated in a substudy that included ante-mortem imaging. We highlight recent findings that have been highly cited over the past five years. The findings fall into three general categories. The first relates to the neuropathology of probable Alzheimer's disease, mild cognitive impairment, and those without dementia or mild cognitive impairment. The second relates to risk factors for Alzheimer's disease and neuropathology. The third are clinical and imaging studies of mild cognitive impairment. The findings illustrate the range of insights that can be gained into cognitive aging by incorporating neuropathologic indices into well designed, prospective cohort studies.

Correlation between gray matter volume in the temporal lobe and depressive symptoms in patients with Alzheimer's disease

Recent studies have suggested that depression might be an aggravating factor in Alzheimer's disease (AD). The aim of the study was to compare depressive symptoms and gray matter volume between AD patients with comorbid depression and patients with dementia only. Forty-nine patients with AD, 57 with mild cognitive impairment (MCI), and 50 healthy control subjects were assessed using the Consortium to Establish a Registry for Alzheimer's disease (CERAD) and the Geriatric Depression Scale (GDS). All magnetic resonance imaging (MRI)s were analyzed using voxel-based morphometry (VBM). Seventeen AD patients with depression versus 32 patients with dementia only showed decreased immediate recall for a word list (8.7±1.1 vs. 10.1±1.5, z=3.6, p<0.01) and constructional praxis scores (3.7±0.9 vs. 5.3±2.1, z=2.5, p=0.01). Compared to 32 patients with dementia, seventeen AD patients with depression showed decreased gray matter volume in the left inferior temporal gyrus (-56, -19, -31; KE=578, t=3.80, Puncorr<0.001). The MCI group showed decreased gray matter volume in the right hippocampal gyrus compared to healthy control group. Our results suggest that depressive symptoms may be associated with the volume changes of frontal and temporal lobe in patients with AD.

Meta-analysis of functional network alterations in Alzheimer's disease: toward a network biomarker

The increasing prevalence of Alzheimer's disease (AD) emphasizes the need for sensitive biomarkers. Memory, a core deficit in AD, involves the interaction of distributed brain networks. We propose that biomarkers should be sought at the level of disease-specific disturbances in large-scale neural networks instead of alterations in a single brain region. This is the first voxel-level quantitative meta-analysis of default mode connectivity and task-related activation in 1196 patients and 1255 controls to detect robust changes in components of large-scale neural networks. We show that with disease progression, specific components of networks are widespread altered. The medial parietal regions and the subcortical areas are differentially affected depending on the disease stage. Specific compensatory mechanisms are only seen in the earliest stages, before symptoms are evident, and could become a functional network biomarker or target for interventions. These results underline the need to further fine-grain these networks spatially and temporally across disease stages. To conclude, AD should indeed be considered as a syndrome involving neural network disruption before cognitive deficits are detectable.

Association of parental stroke with brain injury and cognitive measures in offspring: the Framingham Heart Study

BACKGROUND AND PURPOSE

Parental stroke has been related to an increased risk of stroke in the offspring. This study examines whether parental stroke is also associated with increased vascular brain injury and poorer cognitive performance among offspring free of clinical stroke.

METHODS

Multivariable regression analyses were used to relate parental stroke to cross-sectional and change in brain magnetic resonance imaging measures and cognitive function among the offspring, with and without adjustment for vascular risk factors.

RESULTS

Stroke- and dementia-free Framingham Offspring (n=1297, age, 61±9 years, 54% women) were studied. Parental stroke by age 65 years was associated with a higher baseline white matter hyperintensity volume (β=0.17±0.08; P=0.027) and with lower visual memory performance (β= -0.80±0.34; P=0.017). During a 6-year follow-up, parental stroke was also associated with increase in white matter hyperintensity volume (odds ratio [OR], 1.87; 95% confidence interval [CI], 1.03-3.38) and decline in executive function (Trails B-A; OR, 1.81; 95% CI, 1.06-3.09). The associations with white matter hyperintensity volume and visual memory attenuated after additional adjustment for concomitant vascular risk factors.

CONCLUSIONS

Parental stroke by age 65 years is associated with increased vascular brain injury and lower memory in offspring equivalent to 3 and 7 years of brain aging, respectively. This may be partly attributed to inheritance of vascular risk factors.

Visual ratings of atrophy in MCI: prediction of conversion and relationship with CSF biomarkers

Medial temporal lobe atrophy (MTA) and cerebrospinal fluid (CSF) markers of Alzheimer's disease (AD) pathology may aid the early detection of AD in mild cognitive impairment (MCI). However, the relationship between structural and pathological markers is not well understood. Furthermore, while posterior atrophy (PA) is well recognized in AD, its value in predicting conversion from late-onset amnestic MCI to AD is unclear. In this study we used visual ratings of MTA and PA to assess their value in predicting conversion to AD in 394 MCI patients. The relationship of atrophy patterns with CSF Aβ1-42, tau, and p-tau(181) was further investigated in 114 controls, 192 MCI, and 99 AD patients. There was a strong association of MTA ratings with conversion to AD (p < 0.001), with a weaker association for PA ratings (p = 0.047). Specific associations between visual ratings and CSF biomarkers were found; MTA was associated with lower levels of Aβ1-42 in MCI, while PA was associated with elevated levels of tau in MCI and AD, which may reflect widespread neuronal loss including posterior regions. These findings suggest both that posterior atrophy may predict conversion to AD in late-onset MCI, and that there may be differential relationships between CSF biomarkers and regional atrophy patterns.

Variation in Variables that Predict Progression from MCI to AD Dementia over Duration of Follow-up

The purpose of this paper is to investigate the relative utility of using neuroimaging, genetic, cerebrospinal fluid (CSF), and cognitive measures to predict progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia over a follow-up period. The studied subjects were 139 persons with MCI enrolled in the Alzheimer's Disease Neuroimaging Initiative. Predictors of progression to AD included brain volume, ventricular volume, hippocampal volume, APOE ε4 two alleles, Aβ₄₂, p-tau₁₈₁, p-tau₁₈₁/Aβ₄₂, memory, language, and executive function. We employ a combination of Cox regression analyses and time-dependent receiver operating characteristic (ROC) methods to assess the prognostic utility and performance stability of candidate biomarkers. In a demographic-adjusted multivariable Cox model, seven measures- brain volume, hippocampal volume, ventricular volume, APOE ε4 two alleles, Aβ₄₂, Memory composite, Executive function composite - predicted progression to AD. Time-dependent ROC revealed that this multivariable model had an area under the curve of 0.832, 0.788, 0.794, and 0.757 at 12, 18, 24, and 36 months respectively. Supplemental Cox models with time of origin set differentially at 12, 18, 24 and 36 months showed that six measures were significant predictors at 12 months whereas only memory and executive function predicted progression to AD at 18 and 24 months. The authors concluded that baseline volumetric MRI and cognitive measures selectively predict progression from MCI to AD, with cognitive measures remaining predictive even late in the follow-up period. These findings may inform case selection for AD clinical trials.

Apolipoprotein ε4-allele as a significant risk factor for conversion from mild cognitive impairment to Alzheimer's disease: a meta-analysis of prospective studies

Recent studies of the relationship between progression from mild cognitive impairment (MCI) to Alzheimer disease (AD) and APOE ε4-allele revealed inconsistent results. To estimate the risk posed by APOE ε4-allele for developing AD in MCI subjects using meta-analysis and identify possible sources of heterogeneity between studies, we reviewed longitudinal epidemiological studies of the presence of APOE ε4-allele on risk for progression to dementia in MCI subjects, and conducted meta-analyses of the results from these studies. Our study was derived from 315 positive-outcome events and 461 negative-outcome events from 8 prospective studies. The pooled RR was statistically significant (pooled RR = 2.09; 95 % CI, 1.52-2.88). The Q statistics indicated high heterogeneity across studies (Q = 14.21, p = 0.003). RR were significantly related to the ethnicity of the sample (z = 3.58, p = 0.024). No significant heterogeneity was observed after stratification in four European-population studies (χ² = 0.67, p = 0.880), but it remained in four American-population studies (χ² = 18.52, p = 0.003). Heterogeneity markedly reduced after excluding one specific study (Q = 4.9, p = 0.009; I² = 39 %). APOE ε4-allele conferred increased risk for progression to dementia in MCI subjects. Ethnicity is a critical factor to yield heterogeneity. Further studies using larger sample sizes are required.

Outcome of mild cognitive impairment comparing early memory profiles

BACKGROUND

: Finding variables that predict decline or stability in persons with amnestic mild cognitive impairment (aMCI) is an important step in identifying subjects in prodromal stages of dementia. This study tests a clinical observation suggesting that aMCI cases with better-preserved recognition skills, despite similar delayed recall deficits, are more likely to remain functionally stable.

METHODS

: A cohort of 210 cases with aMCI, diagnosed with standardized criteria that had been followed up for 48 ± 12 months (range: 36-100), were divided into two groups according to their initial recognition memory discrimination index (DI) on the Hopkins Verbal Learning Test (DI ≥ or <8). We compared the two groups according to demographic and neuropsychological variables, cerebral small vessel disease, and outcome (progression to dementia versus stability as aMCI).

RESULTS

: Thirty-seven percent progressed to dementia. In the group with the higher DI scores (n = 107), only 21.5% of the cases converted, compared with 52.4% of lower scorers (n = 103; Fisher's test: p < 0.0001). Progression to dementia occurred significantly later in cases with higher DI (50 ± 17 versus 26 ± 11 months in cases with impaired DI, Mann-Whitney test, U statistic = 1092.5, p < 0.0001). The group with lower DI showed a threefold-increased rate of progression to dementia. A multivariate regression model revealed DI, delayed recall, age, and family history of dementia as the strongest predictors of dementia, in this order.

CONCLUSIONS

: The aMCI patients with better-preserved recognition at baseline have a more benign prognosis. Detection of these cases may aid in isolating other aMCI cases that are already in prodromal stages of AD and in selecting more homogeneous groups for clinical trials.

A two-year follow-up of cognitive deficits and brain perfusion in mild cognitive impairment and mild Alzheimer's disease

The 15-Objects Test (15-OT) provides useful gradation of visuoperceptual impairment from normal aging through Alzheimer's disease (AD) and correlates with temporo-parietal perfusion. The objectives of this study were to analyze progression of 15-OT performance in mild cognitive impairment (MCI) and AD, and its correlates with cognition and single photon emission computerized tomography (SPECT), as well as to examine neuropsychological and SPECT differences between the MCI patients who developed AD and those who did not. From the initial 126 participants (42/group), 38 AD, 39 MCI, and 38 elderly controls (EC) were reassessed (SPECT: 35 AD, 33 MCI, 35 EC) after two years. The progression of cognitive and SPECT scores during this period was compared between groups, and baseline data between converters and non-converters. The 15-OT was the only measure of progression that differed between the three groups; worsening scores on 15-OT were associated with worsening in verbal and visual retention, and decreased perfusion on left postsubicular area. In the MCI patients, cerebral perfusion fell over the two years in medial-posterior cingulate and fronto-temporo-parietal regions; AD showed extensive changes involving almost all cerebral regions. No SPECT changes were detected in controls. At baseline, the MCI patients who developed AD differed from non-converters in verbal recognition memory, but not in SPECT perfusion. In conclusion, SPECT and 15-OT appear to provide a potential measure to differentiate between normal aging, MCI, and AD. Worsening on 15-OT was related to decreased perfusion in postsubicular area; but further longitudinal studies are needed to determine the contribution of 15-OT as a predictor of AD from MCI.

Measuring clinical progression in MCI and pre-MCI populations: enrichment and optimizing clinical outcomes over time

Recent biomarker research has improved the identification of individuals with very early stages of Alzheimer's disease (AD) and has demonstrated that biomarkers are sensitive for measuring progression in the pre-dementia or mild cognitive impairment (MCI) stage and even pre-symptomatic or pre-MCI stage of AD. Because there are no validated biomarkers in AD, it is important to seek out clinical outcomes that are also sensitive for measuring progression in these very early stages of disease. Clinical outcomes are more subjective and more affected by measurement error than biomarkers but represent the core aspects of the disease and are critical for validation of biomarkers and for evaluation of clinical relevance. Identification of individuals with pre-MCI stages of AD will need to continue to rely on biomarkers, but the identification of individuals with MCI who will progress to AD can be achieved with biomarkers or clinical criteria. Although standard clinical outcomes have been shown to be less sensitive to progression than biomarker outcomes in MCI and pre-MCI populations, non-standard scoring has improved the performance of the Alzheimer's Disease Assessment Scale cognitive subscale, making it more sensitive to progression. Neuropsychological cognitive testing items are optimal for measuring progression in pre-MCI populations, and current research is exploring the best ways to combine these items into a composite cognitive score with maximum responsiveness. In an MCI stage, cognitive, functional, and global items all change, and the best single composite score for measuring progression may involve all of these aspects of the disease. The best chance of success in demonstrating treatment effects in clinical trials will be achieved in a well-defined pre-MCI or MCI population and with an outcome that tracks well with clinical progression over time and with time. A partial least squares model can be used to identify these optimal weighted combinations.

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

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

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Sports concussions and aging: a neuroimaging investigation

Recent epidemiological and experimental studies suggest a link between cognitive decline in late adulthood and sports concussions sustained in early adulthood. In order to provide the first in vivo neuroanatomical evidence of this relation, the present study probes the neuroimaging profile of former athletes with concussions in relation to cognition. Former athletes who sustained their last sports concussion >3 decades prior to testing were compared with those with no history of traumatic brain injury. Participants underwent quantitative neuroimaging (optimized voxel-based morphometry [VBM], hippocampal volume, and cortical thickness), proton magnetic resonance spectroscopy ((1)H MRS; medial temporal lobes and prefrontal cortices), and neuropsychological testing, and they were genotyped for APOE polymorphisms. Relative to controls, former athletes with concussions exhibited: 1) Abnormal enlargement of the lateral ventricles, 2) cortical thinning in regions more vulnerable to the aging process, 3) various neurometabolic anomalies found across regions of interest, 4) episodic memory and verbal fluency decline. The cognitive deficits correlated with neuroimaging findings in concussed participants. This study unveiled brain anomalies in otherwise healthy former athletes with concussions and associated those manifestations to the long-term detrimental effects of sports concussion on cognitive function. Findings from this study highlight patterns of decline often associated with abnormal aging.

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.

Test sequence of CSF and MRI biomarkers for prediction of AD in subjects with MCI

Our aim was to identify the best diagnostic test sequence for predicting Alzheimer's disease (AD)-type dementia in subjects with mild cognitive impairment (MCI) using cerebrospinal fluid (CSF) and magnetic resonance imaging (MRI) biomarkers. We selected 153 subjects with mild cognitive impairment from a multicenter memory clinic-based cohort. We tested the CSF beta amyloid (Aβ)1-42/tau ratio using enzyme-linked immunosorbent assay (ELISA) and hippocampal volumes (HCVs) using the atlas-based learning embeddings for atlas propagation (LEAP) method. Outcome measure was progression to AD-type dementia in 2 years. At follow-up, 48 (31%) subjects converted to AD-type dementia. In multivariable analyses, CSF Aβ1-42/tau and HCV predicted AD-type dementia regardless of apolipoprotein E (APOE) genotype and cognitive scores. Test sequence analyses showed that CSF Aβ1-42/tau increased predictive accuracy in subjects with normal HCV (p < 0.001) and abnormal HCV (p = 0.025). HCV increased predictive accuracy only in subjects with normal CSF Aβ1-42/tau (p = 0.014). Slope analyses for annual cognitive decline yielded similar results. For selection of subjects for a prodromal AD trial, the best balance between sample size and number of subjects needed to screen was obtained with CSF markers. These results provide further support for the use of CSF and magnetic resonance imaging biomarkers to identify prodromal AD.

A role for interleukin-1β in determining the lineage fate of embryonic rat hippocampal neural precursor cells

Neurogenesis occurs in the hippocampus of the developing and adult brain due to the presence of multipotent stem cells and restricted precursor cells at different stages of differentiation. It has been proposed that they may be of potential benefit for use in cell transplantation approaches for neurodegenerative disorders and trauma. Prolonged release of interleukin-1β (IL-1β) from activated microglia has a deleterious effect on hippocampal neurons and is implicated in the impaired neurogenesis and cognitive dysfunction associated with aging, Alzheimer's disease and depression. This study assessed the effect of IL-1β on the proliferation and differentiation of embryonic rat hippocampal NPCs in vitro. We show that IL-1R1 is expressed on proliferating NPCs and that IL-1β treatment decreases cell proliferation and neurosphere growth. When NPCs were differentiated in the presence of IL-1β, a significant reduction in the percentages of newly-born neurons and post-mitotic neurons and a significant increase in the percentage of astrocytes was observed in these cultures. These effects were attenuated by IL-1 receptor antagonist. These data reveal that IL-1β exerts an anti-proliferative, anti-neurogenic and pro-gliogenic effect on embryonic hippocampal NPCs, which is mediated by IL-1R1. The present results emphasise the consequences of an inflammatory environment during NPC development, and indicate that strategies to inhibit IL-1β signalling may be necessary to facilitate effective cell transplantation approaches or in conditions where endogenous hippocampal neurogenesis is impaired.

Alliance for aging research AD biomarkers work group: structural MRI

Biomarkers of Alzheimer's disease (AD) are increasingly important. All modern AD therapeutic trials employ AD biomarkers in some capacity. In addition, AD biomarkers are an essential component of recently updated diagnostic criteria for AD from the National Institute on Aging--Alzheimer's Association. Biomarkers serve as proxies for specific pathophysiological features of disease. The 5 most well established AD biomarkers include both brain imaging and cerebrospinal fluid (CSF) measures--cerebrospinal fluid Abeta and tau, amyloid positron emission tomography (PET), fluorodeoxyglucose (FDG) positron emission tomography, and structural magnetic resonance imaging (MRI). This article reviews evidence supporting the position that MRI is a biomarker of neurodegenerative atrophy. Topics covered include methods of extracting quantitative and semiquantitative information from structural MRI; imaging-autopsy correlation; and evidence supporting diagnostic and prognostic value of MRI measures. Finally, the place of MRI in a hypothetical model of temporal ordering of AD biomarkers is reviewed.

Hippocampal subregions are differentially affected in the progression to Alzheimer's disease

Atrophy within the hippocampus (HP) as measured by magnetic resonance imaging (MRI) is a promising biomarker for the progression to Alzheimer's disease (AD). Subregions of the HP along the longitudinal axis have been found to demonstrate unique function, as well as undergo differential changes in the progression to AD. Little is known of relationships between such HP subregions and other potential biomarkers, such as neuropsychological (NP), genetic, and cerebral spinal fluid (CSF) beta amyloid and tau measures. The purpose of this study was to subdivide the hippocampus to determine how the head, body, and tail were affected in normal control, mild cognitively impaired, and AD subjects, and investigate relationships with HP subregions and other potential biomarkers. MRI scans of 120 participants of the Alzheimer's Disease Neuroimaging Initiative were processed using FreeSurfer, and the HP was subdivided using 3D Slicer. Each subregion was compared among groups, and correlations were used to determine relationships with NP, genetic, and CSF measures. Results suggest that HP subregions are undergoing differential atrophy in AD, and demonstrate unique relationships with NP and CSF data. Discriminant function analyses revealed that these regions, when combined with NP and CSF measures, were able to classify by diagnostic group, and classify MCI subjects who would and would not progress to AD within 12 months.

A new model using routinely available clinical parameters to predict significant liver fibrosis in chronic hepatitis B

Objective

We developed a predictive model for significant fibrosis in chronic hepatitis B (CHB) based on routinely available clinical parameters.

Methods

237 treatment-naïve CHB patients [58.4% hepatitis B e antigen (HBeAg)-positive] who had undergone liver biopsy were randomly divided into two cohorts: training group (n = 108) and validation group (n = 129). Liver histology was assessed for fibrosis. All common demographics, viral serology, viral load and liver biochemistry were analyzed.

Results

Based on 12 available clinical parameters (age, sex, HBeAg status, HBV DNA, platelet, albumin, bilirubin, ALT, AST, ALP, GGT and AFP), a model to predict significant liver fibrosis (Ishak fibrosis score ≥3) was derived using the five best parameters (age, ALP, AST, AFP and platelet). Using the formula log(index+1) = 0.025+0.0031(age)+0.1483 log(ALP)+0.004 log(AST)+0.0908 log(AFP+1)−0.028 log(platelet), the PAPAS (Platelet/Age/Phosphatase/AFP/AST) index predicts significant fibrosis with an area under the receiving operating characteristics (AUROC) curve of 0.776 [0.797 for patients with ALT <2×upper limit of normal (ULN)] The negative predictive value to exclude significant fibrosis was 88.4%. This predictive power is superior to other non-invasive models using common parameters, including the AST/platelet/GGT/AFP (APGA) index, AST/platelet ratio index (APRI), and the FIB-4 index (AUROC of 0.757, 0.708 and 0.723 respectively). Using the PAPAS index, 67.5% of liver biopsies for patients being considered for treatment with ALT <2×ULN could be avoided.

Conclusion

The PAPAS index can predict and exclude significant fibrosis, and may reduce the need for liver biopsy in CHB patients.

Steps to standardization and validation of hippocampal volumetry as a biomarker in clinical trials and diagnostic criterion for Alzheimer's disease

BACKGROUND

The promise of Alzheimer's disease biomarkers has led to their incorporation in new diagnostic criteria and in therapeutic trials; however, significant barriers exist to widespread use. Chief among these is the lack of internationally accepted standards for quantitative metrics. Hippocampal volumetry is the most widely studied quantitative magnetic resonance imaging measure in Alzheimer's disease and thus represents the most rational target for an initial effort at standardization.

METHODS AND RESULTS

The authors of this position paper propose a path toward this goal. The steps include the following: (1) Establish and empower an oversight board to manage and assess the effort, (2) adopt the standardized definition of anatomic hippocampal boundaries on magnetic resonance imaging arising from the European Alzheimer's Disease Centers-Alzheimer's Disease Neuroimaging Initiative hippocampal harmonization effort as a reference standard, (3) establish a scientifically appropriate, publicly available reference standard data set based on manual delineation of the hippocampus in an appropriate sample of subjects (Alzheimer's Disease Neuroimaging Initiative), and (4) define minimum technical and prognostic performance metrics for validation of new measurement techniques using the reference standard data set as a benchmark.

CONCLUSIONS

Although manual delineation of the hippocampus is the best available reference standard, practical application of hippocampal volumetry will require automated methods. Our intent was to establish a mechanism for credentialing automated software applications to achieve internationally recognized accuracy and prognostic performance standards that lead to the systematic evaluation and then widespread acceptance and use of hippocampal volumetry. The standardization and assay validation process outlined for hippocampal volumetry was envisioned as a template that could be applied to other imaging biomarkers.

Neuroimaging measures as endophenotypes in Alzheimer's disease

Late onset Alzheimer's disease (AD) is moderately to highly heritable. Apolipoprotein E allele ε4 (APOE4) has been replicated consistently as an AD risk factor over many studies, and recently confirmed variants in other genes such as CLU, CR1, and PICALM each increase the lifetime risk of AD. However, much of the heritability of AD remains unexplained. AD is a complex disease that is diagnosed largely through neuropsychological testing, though neuroimaging measures may be more sensitive for detecting the incipient disease stages. Difficulties in early diagnosis and variable environmental contributions to the disease can obscure genetic relationships in traditional case-control genetic studies. Neuroimaging measures may be used as endophenotypes for AD, offering a reliable, objective tool to search for possible genetic risk factors. Imaging measures might also clarify the specific mechanisms by which proposed risk factors influence the brain.

Longitudinal MRI atrophy biomarkers: relationship to conversion in the ADNI cohort

Atrophic changes in early Alzheimer's disease (AD) and amnestic mild cognitive impairment (MCI) have been proposed as biomarkers for detection and monitoring. We analyzed magnetic resonance imaging (MRI) atrophy rate from baseline to 1 year in 4 groups of participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI): AD (n = 152), converters from MCI to probable AD (MCI-C, n = 60), stable MCI (MCI-S, n = 261), and healthy controls (HC, n = 200). Scans were analyzed using multiple methods, including voxel-based morphometry (VBM), regions of interest (ROIs), and automated parcellation, permitting comparison of annual percent change (APC) in neurodegeneration markers. Effect sizes and the sample required to detect 25% reduction in atrophy rates were calculated. The influence of APOE genotype on APC was also evaluated. AD patients and converters from MCI to probable AD demonstrated high atrophy APCs across regions compared with minimal change in healthy controls. Stable MCI subjects showed intermediate atrophy rates. APOE genotype was associated with APC in key regions. In sum, APC rates are influenced by APOE genotype, imminent MCI to AD conversion, and AD-related neurodegeneration.

Ventricular maps in 804 ADNI subjects: correlations with CSF biomarkers and clinical decline

Ideal biomarkers of Alzheimer's disease (AD) should correlate with accepted measures of pathology in the cerebrospinal fluid (CSF); they should also correlate with, or predict, future clinical decline, and should be readily measured in hundreds to thousands of subjects. Here we explored the utility of automated 3D maps of the lateral ventricles as a possible biomarker of AD. We used our multi-atlas fluid image alignment (MAFIA) method, to compute ventricular models automatically, without user intervention, from 804 brain MRI scans with 184 AD, 391 mild cognitive impairment (MCI), and 229 healthy elderly controls (446 men, 338 women; age: 75.50 +/- 6.81 [SD] years). Radial expansion of the ventricles, computed pointwise, was strongly correlated with current cognition, depression ratings, Hachinski Ischemic scores, language scores, and with future clinical decline after controlling for any effects of age, gender, and educational level. In statistical maps ranked by effect sizes, ventricular differences were highly correlated with CSF measures of Abeta(1-42), and correlated with ApoE4 genotype. These statistical maps are highly automated, and offer a promising biomarker of AD for large-scale studies.

Characterizing Alzheimer's disease using a hypometabolic convergence index

This article introduces a hypometabolic convergence index (HCI) for the assessment of Alzheimer's disease (AD); compares it to other biological, cognitive and clinical measures; and demonstrates its promise to predict clinical decline in mild cognitive impairment (MCI) patients using data from the AD Neuroimaging Initiative (ADNI). The HCI is intended to reflect in a single measurement the extent to which the pattern and magnitude of cerebral hypometabolism in an individual's fluorodeoxyglucose positron emission tomography (FDG-PET) image correspond to that in probable AD patients, and is generated using a fully automated voxel-based image-analysis algorithm. HCIs, magnetic resonance imaging (MRI) hippocampal volume measurements, cerebrospinal fluid (CSF) assays, memory test scores, and clinical ratings were compared in 47 probable AD patients, 21 MCI patients who converted to probable AD within the next 18months, 76 MCI patients who did not, and 47 normal controls (NCs) in terms of their ability to characterize clinical disease severity and predict conversion rates from MCI to probable AD. HCIs were significantly different in the probable AD, MCI converter, MCI stable and NC groups (p=9e-17) and correlated with clinical disease severity. Using retrospectively characterized threshold criteria, MCI patients with either higher HCIs or smaller hippocampal volumes had the highest hazard ratios (HRs) for 18-month progression to probable AD (7.38 and 6.34, respectively), and those with both had an even higher HR (36.72). In conclusion, the HCI, alone or in combination with certain other biomarker measurements, has the potential to help characterize AD and predict subsequent rates of clinical decline. More generally, our conversion index strategy could be applied to a range of imaging modalities and voxel-based image-analysis algorithms.

MR imaging texture analysis of the corpus callosum and thalamus in amnestic mild cognitive impairment and mild Alzheimer disease

BACKGROUND AND PURPOSE

TA is a branch of image processing that seeks to reduce image information by extracting texture descriptors from the image. TA of MR images of anatomic structures in mild AD and aMCI is not well-studied. Our objective was to attempt to find differences among patients with aMCI and mild AD and normal-aging subjects, by using TA applied to the MR images of the CC and the thalami of these groups of subjects.

MATERIALS AND METHODS

TA was applied to the MR images of 17 patients with aMCI, 16 patients with mild AD, and 16 normal-aging subjects. The TA approach was based on the GLCM. MR images were T1-weighted and were obtained in the sagittal and axial planes. The CC and thalami were manually segmented for each subject, and 44 texture parameters were computed for each of these structures.

RESULTS

TA parameters showed differences among the 3 groups for the CC and thalamus. A pair-wise comparison among groups showed differences for AD-control and aMCI-AD for the CC; and for AD-control, aMCI-AD, and aMCI-control for the thalamus.

CONCLUSIONS

TA is a useful technique to aid in the detection of tissue alterations in MR images of mild AD and aMCI and has the potential to become a helpful tool in the diagnosis and understanding of these pathologies.

Brain perfusion correlates of visuoperceptual deficits in mild cognitive impairment and mild Alzheimer's disease

Visuoperceptual processing is impaired early in the clinical course of Alzheimer's disease (AD). The 15-Objects Test (15-OT) detects such subtle performance deficits in mild cognitive impairment (MCI) and mild AD. Reduced brain perfusion in the temporal, parietal, and prefrontal regions have been found in early AD and MCI patients. The objectives of this study were to confirm the role of the 15-OT in the diagnosis of MCI and AD and to investigate the brain perfusion correlates of visuoperceptual dysfunction (15-OT) in subjects with MCI, AD, and normal aging. Forty-two AD, 42 MCI, and 42 healthy elderly control subjects underwent a brain Single Photon Emission Tomography (SPECT) and separately completed the 15-OT. An analysis of variance compared 15-OT scores between groups. SPM5 was used to analyse the SPECT data. 15-OT performance was impaired in the MCI and AD patients. In terms of the SPECT scans, AD patients showed reduced perfusion in temporal-parietal regions, while the MCI subjects had decreased perfusion in the middle and posterior cingulate. When MCI and AD groups were compared, a significant brain perfusion reduction was found in temporo-parietal regions. In the whole sample, 15-OT performance was significantly correlated with the clinical dementia rating scores, and with the perfusion in the bilateral posterior cingulate and the right temporal pole, with no significant correlation in each separate group. Our findings suggest that the 15-OT performance provides a useful gradation of impairment from normal aging to AD, and it seems to be related to perfusion in the bilateral posterior cingulate and the right temporal pole.

Influence of apolipoprotein E varepsilon4 on rates of cognitive and functional decline in mild cognitive impairment

BACKGROUND

Apolipoprotein E varepsilon4 (APOE varepsilon4) allele carrier status has been well established as a risk factor for developing Alzheimer's disease. However, the specific influence of APOE varepsilon4 allele status on cognitive and functional rates of decline in mild cognitive impairment (MCI) is poorly understood. We examine the prospective association of APOE varepsilon4 allele status on measures of cognitive and functional decline in subjects with amnestic MCI (aMCI).

METHODS

A total of 516 aMCI participants aged 55-90 years who received placebo or vitamin E from the Alzheimer's Disease Cooperative Study's MCI treatment trial were evaluated. During the 36-month study period, neurocognitive and functional measures were collected. These measures were assessed over time for change and association with APOE varepsilon4 status. Generalized Estimating Equations were performed to model each outcome measure over the study period.

RESULTS

APOE varepsilon4 status had a significant impact on cognitive and functional decline on multiple measures; those who were APOE varepsilon4 positive had significantly more rapid decline in performance on all cognitive and functional measures except Number Cancellation and Maze tracing (P < .05). The greatest decline was seen in global measures of cognition and function including the Clinical Diagnostic Rating scale, followed by the Mini-Mental State Examination, Global Deterioration scale, and the Alzheimer's Disease Assessment Scale-Cognitive Subscale.

CONCLUSIONS

These findings demonstrate that APOE varepsilon4 genotype is predictive of increased general rates of decline with global measures of cognition and function most affected. With accelerated declines in common clinical trial primary efficacy measures, APOE varepsilon4 status needs to be accounted for in treatment trials of MCI.

New developments in the diagnosis of dementia

BACKGROUND

The terms "dementia" and "Alzheimer's disease" are often wrongly used as if they were synonyms. Dementia is a clinical syndrome whose main element is memory impairment; it is due to Alzheimer's disease in more than 75% of cases. Alzheimer's disease, on the other hand, is a neuropathological entity that is characterized by a protracted preclinical phase followed by the onset of slowly progressive dementia.

METHODS

We here review relevant literature that we retrieved by a selective Medline search (2005-2009), paying special attention to the early diagnosis of Alzheimer's disease, its clinical manifestations, and its relevance in primary care.

RESULTS

The early clinical manifestations of a dementing illness can be detected in primary care through the use of simple screening tests such as the mini mental state examination, clock drawing tests, and DemTect. A diminished concentration of Abeta-peptide and an increase of (phospho-)tau in the cerebrospinal fluid can suggest the presence of Alzheimer's disease even before the onset of dementia: these substances are components of amyloid plaques and neurofibrillary tangles, which are the characteristic neuropathological lesions of Alzheimer's disease. New types of morphological magnetic resonsance imaging (MRI), and automated analysis of the images obtained, can improve the consistency of radiological assessment over the traditional visual method and thus enable more secure diagnosis.

CONCLUSION

The early, preclinical phase of Alzheimer's disease involves what has been termed mild cognitive impairment and may last as long as five years until the onset of dementia. With the aid of the new biomarkers described here, the likelihood of diagnosing Alzheimer's disease correctly in this phase can be raised above 80%. Early detection of Alzheimer's disease before the onset of dementia provides an opportunity to study potential approaches for secondary prevention, which are now an object of intense clinical research.

Disease progression model for cognitive deterioration from Alzheimer's Disease Neuroimaging Initiative database

BACKGROUND

A mathematical model was developed to describe the longitudinal response in Alzheimer's Disease Assessment Scale-cognitive (ADAS-cog) obtained from the Alzheimer's Disease Neuroimaging Initiative.

METHODS

The model was fit to the longitudinal ADAS-cog scores from 817 patients. Risk factors (age, apolipoprotein ɛ4 [APOE ɛ4] genotype, gender, family history of AD, years of education) and baseline severity were tested as covariates.

RESULTS

Rate of disease progression increased with baseline severity. Age, APOE ɛ4 genotype, and gender were identified as potential covariates influencing disease progression. The rate of disease progression in patients with mild to moderate AD was estimated as approximately 5.5 points/yr.

CONCLUSIONS

A disease progression model adequately described the natural decline of ADAS-cog observed in Alzheimer's Disease Neuroimaging Initiative. Baseline severity is an important covariate to predict a curvilinear rate of disease progression in normal elderly, mild cognitive impairment, and AD patients. Age, APOE ɛ4 genotype, and gender also influence the rate of disease progression.

Boosting power for clinical trials using classifiers based on multiple biomarkers

Machine learning methods pool diverse information to perform computer-assisted diagnosis and predict future clinical decline. We introduce a machine learning method to boost power in clinical trials. We created a Support Vector Machine algorithm that combines brain imaging and other biomarkers to classify 737 Alzheimer's disease Neuroimaging initiative (ADNI) subjects as having Alzheimer's disease (AD), mild cognitive impairment (MCI), or normal controls. We trained our classifiers based on example data including: MRI measures of hippocampal, ventricular, and temporal lobe volumes, a PET-FDG numerical summary, CSF biomarkers (t-tau, p-tau, and Abeta(42)), ApoE genotype, age, sex, and body mass index. MRI measures contributed most to Alzheimer's disease (AD) classification; PET-FDG and CSF biomarkers, particularly Abeta(42), contributed more to MCI classification. Using all biomarkers jointly, we used our classifier to select the one-third of the subjects most likely to decline. In this subsample, fewer than 40 AD and MCI subjects would be needed to detect a 25% slowing in temporal lobe atrophy rates with 80% power--a substantial boosting of power relative to standard imaging measures.

Cerebrospinal fluid abnormalities and rate of decline in everyday function across the dementia spectrum: normal aging, mild cognitive impairment, and Alzheimer disease

OBJECTIVE

To investigate the effect of cerebrospinal fluid (CSF) abnormalities on the rate of decline in everyday function in normal aging, mild cognitive impairment (MCI), and mild Alzheimer disease (AD).

DESIGN

Immunoassays of total tau (t-tau), tau phosphorylated at threonine 181 (p-tau(181)), and beta-amyloid 1-42 (Abeta(42)) concentrations were performed in CSF obtained from participants in the Alzheimer's Disease Neuroimaging Initiative. Random effects regressions were used to examine the relationship among CSF abnormalities, cognitive impairment (assessed with the Alzheimer Disease Assessment Scale-cognitive subscale [ADAS-Cog]), and functional decline (assessed with the Pfeffer Functional Activities Questionnaire) and to determine whether the impact of CSF abnormalities on functional decline is mediated by cognitive impairment.

SETTING

Fifty-eight sites in the United States and Canada.

PARTICIPANTS

One hundred fourteen cognitively intact adults, 195 patients with MCI, and 100 patients with mild AD. Main Outcome Measure Decline in the Pfeffer Functional Activities Questionnaire score.

RESULTS

Abnormalities in all CSF analytes were associated with functional decline in MCI, and all but the t-tau:Abeta(42) ratio were associated with functional decline in controls. No abnormal CSF analyte was associated with functional decline in AD. Among controls, p-tau(181) concentration was the most sensitive to functional decline, whereas in MCI it was Abeta(42) concentration. Cerebrospinal fluid biomarkers were uniformly more sensitive to functional decline than the ADAS-Cog score among controls and variably so in MCI, whereas the ADAS-Cog score was unequivocally more sensitive than CSF biomarkers in AD. The impact of CSF abnormalities on functional decline in MCI was partially mediated by their effect on cognitive status. Across all diagnostic groups, persons with both tau and Abeta(42) abnormalities exhibited the steepest rate of functional decline.

CONCLUSIONS

Abnormalities in CSF are associated with functional decline and thus with future development of AD in controls and patients with MCI. However, they do not predict further functional degradation in patients with AD. Persons with comorbid tau and Abeta(42) abnormalities are at greatest risk of functional loss.

Automated MRI measures predict progression to Alzheimer's disease

The prediction of individuals with mild cognitive impairment (MCI) destined to develop Alzheimer's disease (AD) is of increasing clinical importance. In this study, using baseline T1-weighted MRI scans of 324 MCI individuals from two cohorts and automated software tools, we employed factor analyses and Cox proportional hazards models to identify a set of neuroanatomic measures that best predicted the time to progress from MCI to AD. For comparison, cerebrospinal fluid (CSF) assessments of cellular pathology and positron emission tomography (PET) measures of metabolic activity were additionally examined. By 3 years follow-up, 60 MCI individuals from the first cohort and 58 MCI individuals from the second cohort had progressed to a diagnosis of AD. Cox models on the first cohort demonstrated significant effects for the medial temporal factor [Hazards Ratio (HR) = 0.43{95% confidence interval (CI), 0.32-0.55}, p < 0.0001], the fronto-parietoccipital factor [HR = 0.59{95% CI, 0.48-0.80}, p < 0.001], and the lateral temporal factor [HR = 0.67 {95% CI, 0.52-0.87}, p < 0.01]. When applied to the second cohort, these Cox models showed significant effects for the medial temporal factor [HR = 0.44 {0.32-0.61}, p < 0.001] and lateral temporal factor [HR = 0.49 {0.38-0.62}, p < 0.001]. In a combined Cox model, consisting of individual CSF, PET, and MRI measures that best predicted disease progression, only the medial temporal factor [HR = 0.53 {95% CI, 0.34-0.81}, p < 0.001] demonstrated a significant effect. These findings illustrate that automated MRI measures of the medial temporal cortex accurately and reliably predict time to disease progression, outperform cellular and metabolic measures as predictors of clinical decline, and can potentially serve as a predictive marker for AD.

Dementia risk prediction in the population: are screening models accurate?

Early identification of individuals at risk of dementia will become crucial when effective preventative strategies for this condition are developed. Various dementia prediction models have been proposed, including clinic-based criteria for mild cognitive impairment, and more-broadly constructed algorithms, which synthesize information from known dementia risk factors, such as poor cognition and health. Knowledge of the predictive accuracy of such models will be important if they are to be used in daily clinical practice or to screen the entire older population (individuals aged >or=65 years). This article presents an overview of recent progress in the development of dementia prediction models for use in population screening. In total, 25 articles relating to dementia risk screening met our inclusion criteria for review. Our evaluation of the predictive accuracy of each model shows that most are poor at discriminating at-risk individuals from not-at-risk cases. The best models incorporate diverse sources of information across multiple risk factors. Typically, poor accuracy is associated with single-factor models, long follow-up intervals and the outcome measure of all-cause dementia. A parsimonious and cost-effective consensus model needs to be developed that accurately identifies individuals with a high risk of future dementia.

3D comparison of low, intermediate, and advanced hippocampal atrophy in MCI

We applied the hippocampal radial atrophy mapping technique to the baseline and follow-up magnetic resonance image data of 169 amnestic mild cognitive impairment (MCI) participants in the imaging arm of the Alzheimer's Disease Cooperative Study MCI Donepezil/Vitamin E trial. Sixty percent of the subjects with none to mild hippocampal atrophy rated with the visual medial temporal atrophy rating scale (MTA score < 2) and 33.8% of the subjects with moderate to severe (MTA > or = 2) hippocampal atrophy converted to Alzheimer's disease (AD) during 3-year follow-up. MTA > or = 2 showed a trend for greater left sided hippocampal atrophy versus MTA < 2 groups at baseline (P(corrected) = 0.08). Higher MTA scores were associated with progressive atrophy of the subiculum and the CA1-3 subregions. The MTA < 2 group demonstrated significant bilateral atrophy progression at follow-up (left P(corrected) = 0.008; right P(corrected) = 0.05). Relative to MTA < 2 nonconverters, MTA < 2 converters showed further involvement of the subiculum and CA1 and additional involvement of CA2-3 at follow-up. Right CA1 atrophy was significantly associated with conversion to dementia (for 1 mm greater right CA1 radial distance subjects had 50% reduced hazard for conversion). Greater CA1 and subicular atrophy can be demonstrated early and is predictive of future conversion to AD, whereas CA2-3 involvement becomes more evident as the disease progresses.

Modeling screening, prevention, and delaying of Alzheimer's disease: an early-stage decision analytic model

Background

Alzheimer's Disease (AD) affects a growing proportion of the population each year. Novel therapies on the horizon may slow the progress of AD symptoms and avoid cases altogether. Initiating treatment for the underlying pathology of AD would ideally be based on biomarker screening tools identifying pre-symptomatic individuals. Early-stage modeling provides estimates of potential outcomes and informs policy development.

Methods

A time-to-event (TTE) simulation provided estimates of screening asymptomatic patients in the general population age ≥55 and treatment impact on the number of patients reaching AD. Patients were followed from AD screen until all-cause death. Baseline sensitivity and specificity were 0.87 and 0.78, with treatment on positive screen. Treatment slowed progression by 50%. Events were scheduled using literature-based age-dependent incidences of AD and death.

Results

The base case results indicated increased AD free years (AD-FYs) through delays in onset and a reduction of 20 AD cases per 1000 screened individuals. Patients completely avoiding AD accounted for 61% of the incremental AD-FYs gained. Total years of treatment per 1000 screened patients was 2,611. The number-needed-to-screen was 51 and the number-needed-to-treat was 12 to avoid one case of AD. One-way sensitivity analysis indicated that duration of screening sensitivity and rescreen interval impact AD-FYs the most. A two-way sensitivity analysis found that for a test with an extended duration of sensitivity (15 years) the number of AD cases avoided was 6,000-7,000 cases for a test with higher sensitivity and specificity (0.90,0.90).

Conclusions

This study yielded valuable parameter range estimates at an early stage in the study of screening for AD. Analysis identified duration of screening sensitivity as a key variable that may be unavailable from clinical trials.

Neuropsychological profile of prodromal Alzheimer's disease (Prd-AD) and their radiological correlates

This study describes the cognitive profile of Prd-AD, the neuropsychological tests that may predict progression to dementia, and to study their brain structural correlates. We enrolled 24 stable amnesics who did not develop dementia after two years follow-up; 27 patients were considered as Prd-AD, in the initial visit, since they fulfilled NINCDS-ADRDA criteria after two years; 31 Alzheimer's disease (AD) patients and 27 controls (CTR). Structural magnetic resonance imaging (MRI), as well as a neuropsychological battery was performed at the initial visit. The key findings were: Prd-AD patients were characterized by prominent episodic memory dysfunction and minimal semantic memory and executive dysfunction. Semantic fluency test (Sem-Flu), delayed text memory test (Del-text-mem) and memory alteration test (M@T) (including both episodic and semantic memory), together with trail making test A (TMT-A), resulted significant predictors for dementia development in this group of amnesic patients. This optimal predictive model obtained an estimated accuracy of 53% after two years follow-up. M@T and semantic Sem-Flu test performance presented high correlation with decreased gray matter density in the left lateral temporal lobe. We conclude that Prd-AD is characterized by prominent episodic memory dysfunction and minimal semantic memory and executive dysfunction which are related with left medial, inferior and lateral temporal density loss, predominantly in the left side.

VENTRICULAR MAPS IN 804 SUBJECTS CORRELATE WITH COGNITIVE DECLINE, CSF PATHOLOGY, AND IMMINENT ALZHEIMER'S DISEASE

There is an urgent need for neuroimaging biomarkers of Alzheimer's disease (AD) that correlate with cognitive decline, and with accepted measures of pathology detectable in cerebrospinal fluid (CSF). Ideal biomarkers should also be able to predict future decline, and should be computable automatically from hundreds to thousands of images without user intervention. Here we used our multi-atlas fluid image alignment method (MAFIA [1]), to automatically segment parametric 3D surface models of the lateral ventricles in brain MRI scans from 184 AD, 391 MCI, and 229 healthy elderly controls. Radial expansion of the ventricles, computed pointwise, was correlated with measures of (1) clinical decline, (2) pathology from CSF, and (3) future deterioration. Surface-based correlation maps were assessed using a cumulative distribution function method to rank influential covariates according to their effect sizes. The resulting approach is highly automated, and boosts the power of fluid image registration by integrating multiple independent registrations to reduce segmentation errors.

Manual validation of FreeSurfer's automated hippocampal segmentation in normal aging, mild cognitive impairment, and Alzheimer Disease subjects

Hippocampal volume is reduced in Alzheimer Disease (AD) and has been proposed as a possible surrogate biomarker to aid early diagnosis. Whilst automated methods to segment the hippocampus from magnetic resonance images are available, manual segmentation, in spite of being time-consuming and unsuitable for large samples, is still the standard. In order to study the validity of FreeSurfer's automated method, we compared hippocampal automated measures with manual tracing in a sample composed of healthy elderly (N=41), Mild Cognitive Impairment (MCI) (N=23), and AD (N=25) subjects. Percent volume overlap, percent volume difference, correlations, and Bland-Altman plots were studied. Automated measures were slightly larger than hand tracing ones (mean difference 10%). Percent volume overlap showed good results, but was far from perfect (78%). Manual and automated volume correlations were approximately 0.84 and the Bland-Altman analysis showed acceptable interchangeability of methods. Within-group analysis demonstrated that patient samples obtained smaller values in validity indexes than controls. Globally, FreeSurfer's automated hippocampal volumetry showed adequate validity when compared to manual tracing, with a tendency to overestimation. Nevertheless, the greater difference between automated and manual segmentation in atrophic brains suggests that studies in AD based on this software could be more likely to produce false negatives.

Decreased levels of PSD95 and two associated proteins and increased levels of BCl2 and caspase 3 in hippocampus from subjects with amnestic mild cognitive impairment: Insights into their potential roles for loss of synapses and memory, accumulation of Abeta, and neurodegeneration in a prodromal stage of Alzheimer's disease

Alzheimer's disease (AD) is the most common form of dementia and is pathologically characterized by senile plaques, neurofibrillary tangles, synaptic disruption and loss, and progressive neuronal deficits. The exact mechanism(s) of AD pathogenesis largely remain unknown. With advances in technology diagnosis of a pre-AD stage referred to as amnestic mild cognitive impairment (MCI) has become possible. Amnestic MCI is characterized clinically by memory deficit, but normal activities of daily living and no dementia. In the present study, compared to controls, we observed in hippocampus from subjects with MCI a significantly decreased level of PSD95, a key synaptic protein, and also decreased levels of two proteins associated with PSD95, the N-methyl-D-aspartate receptor, subunit 2A (NR2A) and the low-density lipoprotein receptor-1 (LRP1). PSD95 and NR2A are involved in long-term potentiation, a key component of memory formation, and LRP1 is involved in efflux of amyloid beta-peptide (1-42). Abeta (1-42) conceivably is critical to the pathogenesis of MCI and AD, including the oxidative stress under which brain in both conditions exist. The data obtained from the current study suggest a possible involvement of these proteins in synaptic alterations, apoptosis and consequent decrements in learning and memory associated with the progression of MCI to AD.