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Age is not only the greatest risk factor for Alzheimer's disease (AD) but also a key modifier of disease presentation and progression. Here, we investigate how longitudinal atrophy patterns vary with age in mild cognitive impairment (MCI) and AD. Data comprised serial longitudinal 1.5-T magnetic resonance imaging scans from 153 AD, 339 MCI, and 191 control subjects. Voxel-wise maps of longitudinal volume change were obtained and aligned across subjects. Local volume change was then modeled in terms of diagnostic group and an interaction between group and age, adjusted for total intracranial volume, white-matter hyperintensity volume, and apolipoprotein E genotype. Results were significant at p < 0.05 with family-wise error correction for multiple comparisons. An age-by-group interaction revealed that younger AD patients had significantly faster atrophy rates in the bilateral precuneus, parietal, and superior temporal lobes. These results suggest younger AD patients have predominantly posterior progressive atrophy, unexplained by white-matter hyperintensity, apolipoprotein E, or total intracranial volume. Clinical trials may benefit from adapting outcome measures for patient groups with lower average ages, to capture progressive atrophy in posterior cortices., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

This study investigates relationships between white matter hyperintensity (WMH) volume, cerebrospinal fluid (CSF) Alzheimer's disease (AD) pathology markers, and brain and hippocampal volume loss. Subjects included 198 controls, 345 mild cognitive impairment (MCI), and 154 AD subjects with serial volumetric 1.5-T MRI. CSF Aβ 42 and total tau were measured (n = 353). Brain and hippocampal loss were quantified from serial MRI using the boundary shift integral (BSI). Multiple linear regression models assessed the relationships between WMHs and hippocampal and brain atrophy rates. Models were refitted adjusting for (a) concurrent brain/hippocampal atrophy rates and (b) CSF Aβ 42 and tau in subjects with CSF data. WMH burden was positively associated with hippocampal atrophy rate in controls (P = 0.002) and MCI subjects (P = 0.03), and with brain atrophy rate in controls (P = 0.03). The associations with hippocampal atrophy rate remained following adjustment for concurrent brain atrophy rate in controls and MCIs, and for CSF biomarkers in controls (P = 0.007). These novel results suggest that vascular damage alongside AD pathology is associated with disproportionately greater hippocampal atrophy in nondemented older adults. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc., (© 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc.)

Posterior cortical atrophy (PCA) is a neurodegenerative syndrome characterized by predominant visual deficits and parieto-occipital atrophy, and is typically associated with Alzheimer's disease (AD) pathology. In AD, assessment of hippocampal atrophy is widely used in diagnosis, research, and clinical trials; its utility in PCA remains unclear. Given the posterior emphasis of PCA, we hypothesized that hippocampal shape measures may give additional group differentiation information compared with whole-hippocampal volume assessments. We investigated hippocampal volume and shape in subjects with PCA (n = 47), typical AD (n = 29), and controls (n = 48). Hippocampi were outlined on MRI scans and their 3D meshes were generated. We compared hippocampal volume and shape between disease groups. Mean adjusted hippocampal volumes were ∼ 8% smaller in PCA subjects (P < 0.001) and ∼ 22% smaller in tAD subject (P < 0.001) compared with controls. Significant inward deformations in the superior hippocampal tail were observed in PCA compared with controls even after adjustment for hippocampal volume. Inward deformations in large areas of the hippocampus were seen in tAD subjects compared with controls and PCA subjects, but only localized shape differences remained after adjusting for hippocampal volume. The shape differences observed, even allowing for volume differences, suggest that PCA and tAD are each associated with different patterns of hippocampal tissue loss that may contribute to the differential range and extent of episodic memory dysfunction in the two groups., (© 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.)

Background: An international Delphi panel has defined a harmonized protocol (HarP) for the manual segmentation of the hippocampus on MR. The aim of this study is to study the concurrent validity of the HarP toward local protocols, and its major sources of variance., Methods: Fourteen tracers segmented 10 Alzheimer's Disease Neuroimaging Initiative (ADNI) cases scanned at 1.5 T and 3T following local protocols, qualified for segmentation based on the HarP through a standard web-platform and resegmented following the HarP. The five most accurate tracers followed the HarP to segment 15 ADNI cases acquired at three time points on both 1.5 T and 3T., Results: The agreement among tracers was relatively low with the local protocols (absolute left/right ICC 0.44/0.43) and much higher with the HarP (absolute left/right ICC 0.88/0.89). On the larger set of 15 cases, the HarP agreement within (left/right ICC range: 0.94/0.95 to 0.99/0.99) and among tracers (left/right ICC range: 0.89/0.90) was very high. The volume variance due to different tracers was 0.9% of the total, comparing favorably to variance due to scanner manufacturer (1.2), atrophy rates (3.5), hemispheric asymmetry (3.7), field strength (4.4), and significantly smaller than the variance due to atrophy (33.5%, P < .001), and physiological variability (49.2%, P < .001)., Conclusions: The HarP has high measurement stability compared with local segmentation protocols, and good reproducibility within and among human tracers. Hippocampi segmented with the HarP can be used as a reference for the qualification of human tracers and automated segmentation algorithms., (Copyright © 2015 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)

Background: This study aimed to have international experts converge on a harmonized definition of whole hippocampus boundaries and segmentation procedures, to define standard operating procedures for magnetic resonance (MR)-based manual hippocampal segmentation., Methods: The panel received a questionnaire regarding whole hippocampus boundaries and segmentation procedures. Quantitative information was supplied to allow evidence-based answers. A recursive and anonymous Delphi procedure was used to achieve convergence. Significance of agreement among panelists was assessed by exact probability on Fisher's and binomial tests., Results: Agreement was significant on the inclusion of alveus/fimbria (P = .021), whole hippocampal tail (P = .013), medial border of the body according to visible morphology (P = .0006), and on this combined set of features (P = .001). This definition captures 100% of hippocampal tissue, 100% of Alzheimer's disease-related atrophy, and demonstrated good reliability on preliminary intrarater (0.98) and inter-rater (0.94) estimates., Discussion: Consensus was achieved among international experts with respect to hippocampal segmentation using MR resulting in a harmonized segmentation protocol., (Copyright © 2015 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)

Hippocampal volumetric measures may be useful for Alzheimer's disease (AD) diagnosis and disease tracking; however, manual segmentation of the hippocampus is labour-intensive. Therefore, automated techniques are necessary for large studies and to make hippocampal measures feasible for clinical use. As large studies and clinical centres are moving from using 1.5 Tesla (T) scanners to higher field strengths it is important to assess whether specific image processing techniques can be used at these field strengths. This study investigated whether an automated hippocampal segmentation technique (HMAPS: hippocampal multi-atlas propagation and segmentation) and volume change measures (BSI: boundary shift integral) were as accurate at 3T as at 1.5T. Eighteen Alzheimer's disease patients and 18 controls with 1.5T and 3T scans at baseline and 12-month follow-up were used from the Alzheimer's Disease Neuroimaging Initiative cohort. Baseline scans were segmented manually and using HMAPS and their similarity was measured by the Jaccard index. BSIs were calculated for serial image pairs. We calculated pair-wise differences between manual and HMAPS rates at 1.5T and 3T and compared the SD of these differences at each field strength. The difference in mean Jaccards (manual and HMAPS) between 1.5T and 3T was small with narrow confidence intervals (CIs) and did not appear to be segmentor dependent. The SDs of the difference between volumes from manual and automated segmentations were similar at 1.5T and 3T, with a relatively narrow CI for their ratios. The SDs of the difference between BSIs from manual and automated segmentations were also similar at 1.5T and 3T but with a wider CI for their ratios. This study supports the use of our automated hippocampal voluming methods, developed using 1.5T images, with 3T images.

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.

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.

Anatomical segmentation of structures of interest is critical to quantitative analysis in medical imaging. Several automated multi-atlas based segmentation propagation methods that utilise manual delineations from multiple templates appear promising. However, high levels of accuracy and reliability are needed for use in diagnosis or in clinical trials. We propose a new local ranking strategy for template selection based on the locally normalised cross correlation (LNCC) and an extension to the classical STAPLE algorithm by Warfield et al. (2004), which we refer to as STEPS for Similarity and Truth Estimation for Propagated Segmentations. It addresses the well-known problems of local vs. global image matching and the bias introduced in the performance estimation due to structure size. We assessed the method on hippocampal segmentation using a leave-one-out cross validation with optimised model parameters; STEPS achieved a mean Dice score of 0.925 when compared with manual segmentation. This was significantly better in terms of segmentation accuracy when compared to other state-of-the-art fusion techniques. Furthermore, due to the finer anatomical scale, STEPS also obtains more accurate segmentations even when using only a third of the templates, reducing the dependence on large template databases. Using a subset of Alzheimer's Disease Neuroimaging Initiative (ADNI) scans from different MRI imaging systems and protocols, STEPS yielded similarly accurate segmentations (Dice=0.903). A cross-sectional and longitudinal hippocampal volumetric study was performed on the ADNI database. Mean±SD hippocampal volume (mm(3)) was 5195 ± 656 for controls; 4786 ± 781 for MCI; and 4427 ± 903 for Alzheimer's disease patients and hippocampal atrophy rates (%/year) of 1.09 ± 3.0, 2.74 ± 3.5 and 4.04 ± 3.6 respectively. Statistically significant (p<10(-3)) differences were found between disease groups for both hippocampal volume and volume change rates. Finally, STEPS was also applied in a multi-label segmentation propagation scenario using a leave-one-out cross validation, in order to parcellate 83 separate structures of the brain. Comparisons of STEPS with state-of-the-art multi-label fusion algorithms showed statistically significant segmentation accuracy improvements (p<10(-4)) in several key structures., (Copyright © 2013 Elsevier B.V. All rights reserved.)

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.

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 © 2012 Elsevier Inc. All rights reserved.)

Volume and change in volume of the hippocampus are both important markers of Alzheimer's disease (AD). Delineation of the structure on MRI is time-consuming and therefore reliable automated methods are required. We describe an improvement (multiple-atlas propagation and segmentation (MAPS)) to our template library-based segmentation technique. The improved technique uses non-linear registration of the best-matched templates from our manually segmented library to generate multiple segmentations and combines them using the simultaneous truth and performance level estimation (STAPLE) algorithm. Change in volume over 12months (MAPS-HBSI) was measured by applying the boundary shift integral using MAPS regions. Methods were developed and validated against manual measures using subsets from Alzheimer's Disease Neuroimaging Initiative (ADNI). The best method was applied to 682 ADNI subjects, at baseline and 12-month follow-up, enabling assessment of volumes and atrophy rates in control, mild cognitive impairment (MCI) and AD groups, and within MCI subgroups classified by subsequent clinical outcome. We compared our measures with those generated by Surgical Navigation Technologies (SNT) available from ADNI. The accuracy of our volumes was one of the highest reported (mean(SD) Jaccard Index 0.80(0.04) (N=30)). Both MAPS baseline volume and MAPS-HBSI atrophy rate distinguished between control, MCI and AD groups. Comparing MCI subgroups (reverters, stable and converters): volumes were lower and rates higher in converters compared with stable and reverter groups (p< or =0.03). MAPS-HBSI required the lowest sample sizes (78 subjects) for a hypothetical trial. In conclusion, the MAPS and MAPS-HBSI methods give accurate and reliable volumes and atrophy rates across the clinical spectrum from healthy aging to AD., (Copyright 2010 Elsevier Inc. All rights reserved.)

Identifying mild cognitive impairment (MCI) subjects who will convert to clinical Alzheimer's disease (AD) is important for therapeutic decisions, patient counselling and clinical trials. Hippocampal volume and rate of atrophy predict clinical decline at the MCI stage and progression to AD. In this paper, we create p-maps from the differences in the shape of the hippocampus between 60 normal controls and 60 AD subjects using statistical shape models, and generate different regions of interest (ROI) by thresholding the p-maps at different significance levels. We demonstrate increased statistical power to classify 86 MCI converters and 128 MCI stable subjects using the hippocampal atrophy rates calculated by the boundary shift integral within these ROIs.

Hippocampal atrophy rates are useful in both diagnosing and tracking Alzheimer's disease (AD). However, cohorts and methods used to determine such rates are heterogeneous, leading to differences in reported annualised rates. We performed a meta-analysis of hippocampal atrophy rates in AD patients and matched controls from studies reported in the peer-reviewed literature. Studies reporting longitudinal volume change in hippocampi in AD subjects together with controls were systematically identified and appraised. All authors were contacted either to confirm the results or to provide missing data. Meta-analysis and meta-regression were then performed on this data. Nine studies were included from seven centres, with data from a total of 595 AD and 212 matched controls. Mean (95% CIs) annualised hippocampal atrophy rates were found to be 4.66% (95% CI 3.92, 5.40) for AD subjects and 1.41% (0.52, 2.30) for controls. The difference between AD and control subject in this rate was 3.33% (1.73, 4.94).

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.)

Objective: To assess hippocampal atrophy rates calculated from fluid registration methods., Methods: Hippocampi were segmented on baseline and registered-repeat scans of 32 probable Alzheimer disease (AD) subjects and 55 controls. Fluid-based atrophy rates were calculated., Results: In AD patients, the mean (SD) atrophy rates for manual, fluidly propagated, and Jacobian methods were 5.09 (3.59), 5.34 (3.43), and 3.55 (2.70) (percentage per year). In controls, atrophy rates were 1.31 (2.00), 0.89 (0.75), and 0.56 (1.12) (percentage per year). In AD, fluid propagation and manual rates were similar in means (P = 0.55) and variances (P = 0.71). Jacobian rates were smaller in mean (P = 0.002) and variance (P = 0.026) than in manual rates. In controls, fluid-propagated rates were similar in mean to manual rates (P = 0.12), but less variable (P < 0.0001). Jacobian rates were smaller in mean (P = 0.014) and less variable (P < 0.0001) than in manual rates. Both fluid methods were superior to manual measures in separating AD from controls (P < 0.0001)., Conclusions: Fluid-based methods may be useful in large serial hippocampal studies.

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.

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 APOEepsilon4 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.

Manual segmentation of the hippocampus is the gold standard in volumetric hippocampal magnetic resonance imaging (MRI) analysis; however, this is difficult to achieve reproducibly. This study explores whether application of local registration and calculation of the hippocampal boundary shift integral (HBSI) can reduce random variation compared with manual measures. Hippocampi were outlined on the baseline and registered-repeat MRIs of 32 clinically diagnosed Alzheimer's disease (AD) patients and 47 matched controls (37-86 years) with a wide range of scanning intervals (175-1173 days). The scans were globally registered using 9 degrees of freedom and subsequently locally registered using 6 degrees of freedom and HBSI was then calculated automatically. HBSI significantly reduced the mean rate (P < 0.01) and variation in controls (P < 0.001) and increased group separation between AD cases and controls. When comparing HBSI atrophy rates with manually derived atrophy rates at 90% sensitivity, specificities were 98% and 81%, respectively. From logistic regression models, a 1% increase in HBSI atrophy rates was associated with an 11-fold (CI 3, 36) increase in the odds of a diagnosis of AD. For manually derived atrophy rates, the equivalent odds ratio was 3 (CI 2,4). We conclude that HBSI-derived atrophy rates reduce operator time and error, and are at least as effective as the manual equivalent as a diagnostic marker and are a potential marker of progression in longitudinal studies and trials.

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]