Search

Introduction: White matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-β 1-42 (Aβ42)-positive status., Methods: Individual patient data (n = 3,132; mean age 71.5 ± 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and Aß42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume., Results: VRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p < 0.001), external capsule (B = 0.052, p < 0.001), and middle cerebellar peduncle (B = 0.067, p < 0.001), and Aß42-positive status with WMH in posterior thalamic radiation (B = 0.097, p < 0.001) and splenium (B = 0.103, p < 0.001)., Discussion: Vascular risk factors and Aß42 pathology have distinct signature WMH patterns. This regional vulnerability may incite future studies into how arteriolosclerosis and Aß42 pathology affect the brain's white matter., Highlights: Key dementia etiologies may be associated with specific patterns of white matter hyperintensities (WMH). We related WMH locations to vascular risk and cerebral Aβ42 status in 11 memory clinic cohorts. Aβ42 positive status was associated with posterior WMH in splenium and posterior thalamic radiation. Vascular risk was associated with anterior and infratentorial WMH. Amyloid pathology and vascular risk have distinct signature WMH patterns., (© 2024 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Background: Although age is the biggest known risk factor for dementia, there remains uncertainty about other factors over the life course that contribute to a person's risk for cognitive decline later in life. Furthermore, the pathological processes leading to dementia are not fully understood. The main goals of Insight 46-a multi-phase longitudinal observational study-are to collect detailed cognitive, neurological, physical, cardiovascular, and sensory data; to combine those data with genetic and life-course information collected from the MRC National Survey of Health and Development (NSHD; 1946 British birth cohort); and thereby contribute to a better understanding of healthy ageing and dementia., Methods/design: Phase 1 of Insight 46 (2015-2018) involved the recruitment of 502 members of the NSHD (median age = 70.7 years; 49% female) and has been described in detail by Lane and Parker et al. 2017. The present paper describes phase 2 (2018-2021) and phase 3 (2021-ongoing). Of the 502 phase 1 study members who were invited to a phase 2 research visit, 413 were willing to return for a clinic visit in London and 29 participated in a remote research assessment due to COVID-19 restrictions. Phase 3 aims to recruit 250 study members who previously participated in both phases 1 and 2 of Insight 46 (providing a third data time point) and 500 additional members of the NSHD who have not previously participated in Insight 46., Discussion: The NSHD is the oldest and longest continuously running British birth cohort. Members of the NSHD are now at a critical point in their lives for us to investigate successful ageing and key age-related brain morbidities. Data collected from Insight 46 have the potential to greatly contribute to and impact the field of healthy ageing and dementia by combining unique life course data with longitudinal multiparametric clinical, imaging, and biomarker measurements. Further protocol enhancements are planned, including in-home sleep measurements and the engagement of participants through remote online cognitive testing. Data collected are and will continue to be made available to the scientific community., (© 2024. The Author(s).)

Importance: Midlife vascular risk burden is associated with late-life dementia. Less is known about if and how risk exposure in early adulthood influences late-life brain health., Objective: To determine the associations between vascular risk in early adulthood, midlife, and late life with late-life brain structure and pathology using measures of white matter-hyperintensity volume, β-amyloid load, and whole-brain and hippocampal volumes., Design, Setting, and Participants: This prospective longitudinal cohort study, Insight 46, is part of the Medical Research Council National Survey of Health and Development, which commenced in 1946. Participants had vascular risk factors evaluated at ages 36 years (early adulthood), 53 years (midlife), and 69 years (early late life). Participants were assessed with multimodal magnetic resonance imaging and florbetapir-amyloid positron emission tomography scans between May 2015 and January 2018 at University College London. Participants with at least 1 available imaging measure, vascular risk measurements at 1 or more points, and no dementia were included in analyses., Exposures: Office-based Framingham Heart study-cardiovascular risk scores (FHS-CVS) were derived at ages 36, 53, and 69 years using systolic blood pressure, antihypertensive medication usage, smoking, diabetic status, and body mass index. Analysis models adjusted for age at imaging, sex, APOE genotype, socioeconomic position, and, where appropriate, total intracranial volume., Main Outcomes and Measures: White matter-hyperintensity volume was generated from T1/fluid-attenuated inversion recovery scans using an automated technique and whole-brain volume and hippocampal volume were generated from automated in-house pipelines; β-amyloid status was determined using a gray matter/eroded subcortical white matter standardized uptake value ratio threshold of 0.61., Results: A total of 502 participants were assessed as part of Insight 46, and 463 participants (236 male [51.0%]) with at least 1 available imaging measure (mean [SD] age at imaging, 70.7 [0.7] years; 83 β-amyloid positive [18.2%]) who fulfilled eligibility criteria were included. Among them, FHS-CVS increased with age (36 years: median [interquartile range], 2.7% [1.5%-3.6%]; 53 years: 10.9% [6.7%-15.6%]; 69 years: 24.3% [14.9%-34.9%]). At all points, these scores were associated with smaller whole-brain volumes (36 years: β coefficient per 1% increase, -3.6 [95% CI, -7.0 to -0.3]; 53 years: -0.8 [95% CI, -1.5 to -0.08]; 69 years: -0.6 [95% CI, -1.1 to -0.2]) and higher white matter-hyperintensity volume (exponentiated coefficient: 36 years, 1.09 [95% CI, 1.01-1.18]; 53 years, 1.02 [95% CI, 1.00-1.04]; 69 years, 1.01 [95% CI, 1.00-1.02]), with largest effect sizes at age 36 years. At no point were FHS-CVS results associated with β-amyloid status., Conclusions and Relevance: Higher vascular risk is associated with smaller whole-brain volume and greater white matter-hyperintensity volume at age 69 to 71 years, with the strongest association seen with early adulthood vascular risk. There was no evidence that higher vascular risk influences amyloid deposition, at least up to age 71 years. Reducing vascular risk with appropriate interventions should be considered from early adulthood to maximize late-life brain health.

Introduction: We aimed to assess the value of a second MR scan in the radiological diagnosis of dementia., Methods: One hundred twenty subjects with clinical follow-up of at least 1 year with two scans were selected from a cognitive disorders clinic. Scans were reviewed as a single first scan (method A), two unregistered scans presented side-by-side (method B) and a registered pair (method C). Scans were presented to two neuroradiologists and a clinician together with approximate scan interval (if applicable) and age. Raters decided on a main and subtype diagnosis., Results: There was no evidence that differences between methods (expressed as relative odds of a correct response) differed between reviewers (p = 0.17 for degenerative condition or not, p = 0.5 for main diagnosis, p = 0.16 for subtype). Accordingly, results were pooled over reviewers. For distinguishing normal/non-progressors from degenerative conditions, the proportions correctly diagnosed were higher with methods B and C than with A (p = 0.001, both tests). The difference between method B and C was not statistically significant (p = 0.18). For main diagnosis, the proportion of correct diagnoses were highest with method C for all three reviewers; however, this was not statistically significant comparing with method A (p = 0.23) or with method B (p = 0.16). For subtype diagnosis, there was some evidence that method C was better than method A (p = 0.01) and B (p = 0.048)., Conclusions: Serial MRI and registration may improve visual diagnosis in dementia.

Hippocampal atrophy is a characteristic and early feature of Alzheimer's disease. Volumetry of the hippocampus using T1-weighted magnetic resonance imaging (MRI) has been used not only to assess hippocampal involvement in different neurodegenerative diseases as a potential diagnostic biomarker, but also to understand the natural history of diseases, and to track changes in volume over time. Assessing change in structure circumvents issues surrounding interindividual variability and allows assessment of disease progression. Disease-modifying effects of putative therapies are important to assess in clinical trials and are difficult using clinical scales. As a result, there is increasing use of serial MRI in trials to detect potential slowing of atrophy rates as an outcome measure. Automated and yet reliable methods of quantifying such change in the hippocampus would therefore be very valuable. Algorithms capable of measuring such changes automatically have been developed and may be applicable to predict decline to a diagnosis of dementia in the future. This article details the progress in using MRI to understand hippocampal changes in the degenerative dementias and also describes attempts to automate hippocampal segmentation in these diseases., (2009 Wiley-Liss, Inc.)

Background: A 55-year-old woman was followed over a 13-year period as part of a longitudinal study of people at risk for familial dementia. She was a member of a family with an autosomal dominant familial dementia that fulfilled consensus criteria for frontotemporal lobar degeneration. The patient was initially asymptomatic but developed progressive behavioral and cognitive decline characterized by apathy, impaired emotion recognition, mixed aphasia and parietal lobe dysfunction., Investigations: Clinical assessments, neuropsychometry, volumetric brain MRI, and genetic mutation screening., Diagnosis: Progranulin-associated frontotemporal lobar degeneration., Management: Explanation of the patient's condition and genetic counseling for her family.

This study explores the diagnostic utility of atrophy rates of the cingulate gyrus, its subdivisions and the hippocampus in Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD). Regions were manually outlined on MR images of a group of pathologically or genetically confirmed patients with AD (n=19), FTLD (n=8) and age-matched controls (n=11). Mean (S.D.) atrophy rates (%year(-1)) in the cingulate in controls, AD and FTLD were -0.3 (1.2), 5.9 (3.5), and 8.6 (4.1), respectively. Hippocampal atrophy rates in controls, AD and FTLD were -0.1 (0.8), 3.4 (2.2), and 5.2 (5.4), respectively. Atrophy rates were significantly higher in the cingulate and hippocampi in AD and FTLD compared with controls (p<0.01). There was evidence of a difference in trends of atrophy in the cingulate (more anterior in FTLD and more posterior in AD) between the disease groups (p=0.03). Cingulate atrophy rates discriminated perfectly between FTLD and controls. Significantly better discrimination between AD and controls was obtained by hippocampal rather than cingulate rates. In conclusion, cingulate atrophy is as significant a feature of AD and FTLD as hippocampal atrophy.

Background: Differentiating between Alzheimer disease (AD) and frontotemporal lobar degeneration (FTLD) can be difficult, particularly in the earliest stages of the diseases. Patterns of atrophy on magnetic resonance imaging may help distinguish these diseases and aid diagnosis., Objective: To assess the diagnostic utility of magnetic resonance imaging-derived amygdala and hippocampal volumes from patients with pathologically proved AD and FTLD., Design: Cross-sectional volumetric magnetic resonance imaging study of the hippocampus and amygdala., Setting: Specialist cognitive disorders clinic. Subjects Thirty-seven subjects, including 10 patients with pathologically proved AD, 17 patients with pathologically proved FTLD, and 10 age-matched control subjects., Main Outcome Measures: Hippocampal and amygdala volumes., Results: Geometric mean amygdala and hippocampal volumes were, respectively, 15.0% (95% confidence interval [CI], 4.2%-24.5%) and 16.4% (95% CI, 5.9%-25.6%) lower in the AD than in the control group. In FTLD, the equivalent differences were 43.1% (95% CI, 31.9%-52.6%) in the amygdala and 36.1% (95% CI, 27.5%-43.7%) in the hippocampus. Volumes were significantly lower in the FTLD than in the AD group (P<.01 in both regions). Within the FTLD clinical subgroups, there was evidence of a difference in pattern of atrophy with greater asymmetry (left smaller than right) in semantic dementia compared with frontal variant FTLD (P<.001). On average, the left hippocampus was 14% smaller in semantic dementia than in frontal variant FTLD, whereas the right hippocampus was 37% larger. On average, the left amygdala was 39% smaller in semantic dementia than in frontal variant FTLD, whereas the right amygdala was only 1% smaller., Conclusions: Hippocampal atrophy is not specific to AD or FTLD. However, severe or asymmetrical amygdala atrophy should suggest FTLD. Atrophy patterns follow clinical syndromes rather than pathology.

IntroductionThe spatial distribution of white matter hyperintensities (WMH) on MRI is often considered in the diagnostic evaluation of patients with cognitive problems. In some patients, clinicians may classify WMH patterns as "unusual", but this is largely based on expert opinion, because detailed quantitative information about WMH distribution frequencies in a memory clinic setting is lacking. Here we report voxel wise 3D WMH distribution frequencies in a large multicenter dataset and also aimed to identify individuals with unusual WMH patterns.MethodsIndividual participant data (N = 3525, including 777 participants with subjective cognitive decline, 1389 participants with mild cognitive impairment and 1359 patients with dementia) from eleven memory clinic cohorts, recruited through the Meta VCI Map Consortium, were used. WMH segmentations were provided by participating centers or performed in Utrecht and registered to the Montreal Neurological Institute (MNI)-152 brain template for spatial normalization. To determine WMH distribution frequencies, we calculated WMH probability maps at voxel level. To identify individuals with unusual WMH patterns, region-of-interest (ROI) based WMH probability maps, rule-based scores, and a machine learning method (Local Outlier Factor (LOF)), were implemented.ResultsWMH occurred in 82% of voxels from the white matter template with large variation between subjects. Only a small proportion of the white matter (1.7%), mainly in the periventricular areas, was affected by WMH in at least 20% of participants. A large portion of the total white matter was affected infrequently. Nevertheless, 93.8% of individual participants had lesions in voxels that were affected in less than 2% of the population, mainly located in subcortical areas. Only the machine learning method effectively identified individuals with unusual patterns, in particular subjects with asymmetric WMH distribution or with WMH at relatively rarely affected locations despite common locations not being affected.DiscussionAggregating data from several memory clinic cohorts, we provide a detailed 3D map of WMH lesion distribution frequencies, that informs on common as well as rare localizations. The use of data-driven analysis with LOF can be used to identify unusual patterns, which might serve as an alert that rare causes of WMH should be considered.

IntroductionAlzheimer's Disease Neuroimaging Initiative (ADNI) is now in its 10th year. The primary objective of the magnetic resonance imaging (MRI) core of ADNI has been to improve methods for clinical trials in Alzheimer's disease (AD) and related disorders.MethodsWe review the contributions of the MRI core from present and past cycles of ADNI (ADNI-1, -Grand Opportunity and -2). We also review plans for the future-ADNI-3.ResultsContributions of the MRI core include creating standardized acquisition protocols and quality control methods; examining the effect of technical features of image acquisition and analysis on outcome metrics; deriving sample size estimates for future trials based on those outcomes; and piloting the potential utility of MR perfusion, diffusion, and functional connectivity measures in multicenter clinical trials.DiscussionOver the past decade the MRI core of ADNI has fulfilled its mandate of improving methods for clinical trials in AD and will continue to do so in the future.

INTRODUCTION: White matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid‐β1‐42 (Aβ42)‐positive status. METHODS: Individual patient data (n = 3,132; mean age 71.5 ± 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and Aß42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume. RESULTS: VRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p < 0.001), external capsule (B = 0.052, p < 0.001), and middle cerebellar peduncle (B = 0.067, p < 0.001), and Aß42‐positive status with WMH in posterior thalamic radiation (B = 0.097, p < 0.001) and splenium (B = 0.103, p < 0.001). DISCUSSION: Vascular risk factors and Aß42 pathology have distinct signature WMH patterns. This regional vulnerability may incite future studies into how arteriolosclerosis and Aß42 pathology affect the brain's white matter. Highlights: Key dementia etiologies may be associated with specific patterns of white matter hyperintensities (WMH).We related WMH locations to vascular risk and cerebral Aβ42 status in 11 memory clinic cohorts.Aβ42 positive status was associated with posterior WMH in splenium and posterior thalamic radiation.Vascular risk was associated with anterior and infratentorial WMH.Amyloid pathology and vascular risk have distinct signature WMH patterns. [ABSTRACT FROM AUTHOR]

Objectives: To investigate whether APOE ε4 carriers have higher hippocampal atrophy rates than non-carriers in Alzheimer's disease (AD), mild cognitive impairment (MCI) and controls, and if so, whether higher hippocampal atrophy rates are still observed after adjusting for concurrent whole-brain atrophy rates. Methods: MRI scans from all available visits in ADNI (148 AD, 307 MCI, 167 controls) were used. MCI subjects were divided into “progressors” (MCI-P) if diagnosed with AD within 36 months or “stable” (MCI-S) if a diagnosis of MCI was maintained. A joint multi-level mixed-effect linear regression model was used to analyse the effect of ε4 carrier-status on hippocampal and whole-brain atrophy rates, adjusting for age, gender, MMSE and brain-to-intracranial volume ratio. The difference in hippocampal rates between ε4 carriers and non-carriers after adjustment for concurrent whole-brain atrophy rate was then calculated. Results: Mean adjusted hippocampal atrophy rates in ε4 carriers were significantly higher in AD, MCI-P and MCI-S (p≤0.011, all tests) compared with ε4 non-carriers. After adjustment for whole-brain atrophy rate, the difference in mean adjusted hippocampal atrophy rate between ε4 carriers and non-carriers was reduced but remained statistically significant in AD and MCI-P. Conclusions: These results suggest that the APOE ε4 allele drives atrophy to the medial-temporal lobe region in AD. [ABSTRACT FROM AUTHOR]

Multi-atlas segmentation has been widely used to segment various anatomical structures. The success of this technique partly relies on the selection of atlases that are best mapped to a new target image after registration. Recently, manifold learning has been proposed as a method for atlas selection. Each manifold learning technique seeks to optimize a unique objective function. Therefore, different techniques produce different embeddings even when applied to the same data set. Previous studies used a single technique in their method and gave no reason for the choice of the manifold learning technique employed nor the theoretical grounds for the choice of the manifold parameters. In this study, we compare side-by-side the results given by 3 manifold learning techniques (Isomap, Laplacian Eigenmaps and Locally Linear Embedding) on the same data set. We assess the ability of those 3 different techniques to select the best atlases to combine in the framework of multi-atlas segmentation. First, a leave-one-out experiment is used to optimize our method on a set of 110 manually segmented atlases of hippocampi and find the manifold learning technique and associated manifold parameters that give the best segmentation accuracy. Then, the optimal parameters are used to automatically segment 30 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). For our dataset, the selection of atlases with Locally Linear Embedding gives the best results. Our findings show that selection of atlases with manifold learning leads to segmentation accuracy close to or significantly higher than the state-of-the-art method and that accuracy can be increased by fine tuning the manifold learning process. [ABSTRACT FROM AUTHOR]

There is considerable interest in designing therapeutic studies of individuals at risk of Alzheimer disease (AD) to prevent the onset of symptoms. Cortical β-amyloid plaques, the first stage of AD pathology, can be detected in vivo using positron emission tomography (PET), and several studies have shown that ∼1/3 of healthy elderly have significant β-amyloid deposition. Here we assessed whether asymptomatic amyloid-PET-positive controls have increased rates of brain atrophy, which could be harnessed as an outcome measure for AD prevention trials. We assessed 66 control subjects (age = 73.5±7.3 yrs; MMSE = 29±1.3) from the Australian Imaging Biomarkers & Lifestyle study who had a baseline Pittsburgh Compound B (PiB) PET scan and two 3T MRI scans ∼18-months apart. We calculated PET standard uptake value ratios (SUVR), and classified individuals as amyloid-positive/negative. Baseline and 18-month MRI scans were registered, and brain, hippocampal, and ventricular volumes and annualized volume changes calculated. Increasing baseline PiB-PET measures of β-amyloid load correlated with hippocampal atrophy rate independent of age (p = 0.014). Twenty-two (1/3) were PiB-positive (SUVR>1.40), the remaining 44 PiB-negative (SUVR≤1.31). Compared to PiB-negatives, PiB-positive individuals were older (76.8±7.5 vs. 71.7±7.5, p<0.05) and more were APOE4 positive (63.6% vs. 19.2%, p<0.01) but there were no differences in baseline brain, ventricle or hippocampal volumes, either with or without correction for total intracranial volume, once age and gender were accounted for. The PiB-positive group had greater total hippocampal loss (0.06±0.08 vs. 0.02±0.05 ml/yr, p = 0.02), independent of age and gender, with non-significantly higher rates of whole brain (7.1±9.4 vs. 4.7±5.5 ml/yr) and ventricular (2.0±3.0 vs. 1.1±1.0 ml/yr) change. Based on the observed effect size, recruiting 384 (95%CI 195–1080) amyloid-positive subjects/arm will provide 80% power to detect 25% absolute slowing of hippocampal atrophy rate in an 18-month treatment trial. We conclude that hippocampal atrophy may be a feasible outcome measure for secondary prevention studies in asymptomatic amyloidosis. [ABSTRACT FROM AUTHOR]

Background: Possession of one or more apolipoprotein E (APOE) ε4 alleles may influence the distribution of atrophy and clinical phenotype. We aimed to assess the influence of APOE genotype on cortical thickness and regional brain volumes in AD (Alzheimer’s disease). Methods: We included 38 patients (9 ε4 non-carriers, 23 ε4 heterozygotes, 6 ε4 homozygotes) and 23 controls. Each subject had 2 magnetic resonance imaging (MRI) scans and a neuropsychological battery. Cortical thickness and isthmus cingulate volume were measured using FreeSurfer; the volumes of the hippocampus, whole brain, and lateral ventricles were calculated using manual and semi-automated volumetry. Results: Compared with controls, cortical thickness was significantly lower: in the bilateral temporal, posterior parietal and occipital regions in non-carriers, in the medial temporal and left parietal regions in heterozygotes, and in the medial temporal lobe in homozygotes. Comparisons between AD subgroups did not show significant differences. A trend for larger brain and isthmus cingulate volumes and smaller hippocampal and ventricular volumes with increasing ε4 dose were seen. These differences were supported by neuropsychological profiles. Conclusion: These results suggest that APOE genotype may influence the topography of regional atrophy and cortical thinning in AD. Copyright © 2009 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Both cognitive tests and MRI-based measures have been suggested as outcomes in trials assessing disease-modifying therapies in Alzheimer's disease (AD). To compare changes in longitudinal MRI measures with changes in performance on cognitive tests routinely used in AD clinical trials. Fifty-two subjects from the placebo-arm of a clinical trial in mild-to-moderate AD had volumetric T1-weighted scans and cognitive tests including the Mini-Mental State Examination (MMSE), AD Assessment Scale-Cognitive Subscale, Disability Assessment for Dementia, AD Cooperative Study-Clinical Global Impression of Change and Clinical Dementia Rating at baseline and one-year later. Rates of brain atrophy and ventricular enlargement were measured using the boundary shift integral. Hippocampal (Hc) atrophy was calculated from manual volume measurements. The relationships between MRI and cognitive measures were investigated. Rates of brain atrophy and/or ventricular enlargement were correlated with declining performance on cognitive scales. The strongest association was between brain atrophy rate and MMSE decline (r = 0.59, p < 0.0001). Hc atrophy rate was not significantly correlated with any of the cognitive scales. The lack of correlation between Hc atrophy and cognitive scales may reflect a combination of: the extensive functional damage to the Hc by the time AD is clinically established, the greater influence of ongoing cortical degeneration, and errors in Hc outlining. The strong correlations between brain atrophy and ventricular enlargement, and cognitive scales probably reflect the correspondence between these measures of overall cerebral loss and global cognitive measures in the moderate stages of AD. [ABSTRACT FROM AUTHOR]

Objective: To determine whether Alzheimer’s disease (AD) is associated with preferential atrophy of either the left or right hippocampus. Methods: We examined right-left asymmetry in hippocampal volume and atrophy rates in 32 subjects with probable AD and 50 age-matched controls. Hippocampi were measured on two serial volumetric MRI scans using a technique that minimizes laterality bias. Results: We found a non-significant trend for right > left (R > L) asymmetry in controls at both time points (R > L: 1.7%; CI: –0.3–3.7%; p = 0.1). AD subjects showed a similar non-significant trend for R > L asymmetry at baseline (R > L: 1.8%; CI: –1.9–5.5%; p = 0.32), but not at repeat (p = 0.739). Change in R/L ratio between visits in AD patients was significant (p = 0.02). The AD group had significantly higher variance in these ratios than the controls at baseline (p = 0.02), but not repeat (p = 0.06). AD patients had higher atrophy rates than controls (p < 0.001). Mean (CI) annualized atrophy rates for left and right hippocampi were 1.2% (0.5–1.8%) and 1.1% (0.5–1.8%) for the controls, and 4.6% (3.3–6.0%) and 6.3% (4.9–7.8%) for AD subjects. There was no significant asymmetry in atrophy rates in controls (p = 0.9), but borderline significantly higher atrophy rates in the right hippocampus of the AD group (p = 0.05) compared to the left. Presence of an APOEε4 allele had no significant effect on the size, asymmetry or atrophy rates in AD (p > 0.20). Conclusions: We report minor R > L asymmetry in hippocampal volumes in controls and present some evidence to suggest that there is a change in the natural R > L asymmetry during the progression of AD. Copyright © 2005 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Abstract: Medial temporal lobe atrophy (MTA) is a recognized marker of Alzheimer''s disease (AD), however, it can be prominent in frontotemporal lobar degeneration (FTLD). There is an increasing awareness that posterior atrophy (PA) is important in AD and may aid the differentiation of AD from FTLD. Visual rating scales are a convenient way of assessing atrophy in a clinical setting. In this study, 2 visual rating scales measuring MTA and PA were used to compare atrophy patterns in 62 pathologically-confirmed AD and 40 FTLD patients. Anatomical correspondence of MTA and PA was assessed using manually-delineated regions of the hippocampus and posterior cingulate gyrus, respectively. Both MTA and PA scales showed good inter- and intrarater reliabilities (kappa > 0.8). MTA scores showed a good correspondence with manual hippocampal volumes. Thirty percent of the AD patients showed PA in the absence of MTA. Adding the PA to the MTA scale improved discrimination of AD from FTLD, and early-onset AD from normal aging. These results underline the importance of considering PA in AD diagnosis, particularly in younger patients where medial temporal atrophy may be less conspicuous. [Copyright &y& Elsevier]

Abstract: Alzheimer''s disease (AD) and semantic dementia (SD) are characterized by different patterns of global and temporal lobe atrophy which can be studied using magnetic resonance imaging (MRI). Manual delineation of regions of interest is time-consuming. FreeSurfer is a freely available automated technique which has a facility to label cortical and subcortical brain regions automatically. As with all automated techniques comparison with existing methods is important. Eight temporal lobe structures in each hemisphere were delineated using FreeSurfer and compared with manual segmentations in 10 control, 10 AD, and 10 SD subjects. The reproducibility errors for the manual segmentations ranged from 3% to 6%. Differences in protocols between the two methods led to differences in absolute volumes with the greatest differences between methods found bilaterally in the hippocampus, entorhinal cortex and fusiform gyrus (p < 0.005). However, good correlations between the methods were found for most regions, with the highest correlations shown for the ventricles, whole brain and left medial–inferior temporal gyrus (r > 0.9), followed by the bilateral amygdala and hippocampus, left superior temporal gyrus, right medial–inferior temporal gyrus and left temporal lobe (r >0.8). Overlap ratios differed between methods bilaterally in the amygdala, superior temporal gyrus, temporal lobe, left fusiform gyrus and right parahippocampal gyrus (p <0.01). Despite differences in protocol and volumes, both methods showed similar atrophy patterns in the patient groups compared with controls, and similar right–left differences, suggesting that both methods accurately distinguish between the three groups. [Copyright &y& Elsevier]