Local amygdala structural differences with 3T MRI in patients with Alzheimer disease

Histologic studies show that the amygdala is affected by Alzheimer disease (AD) pathology, and its medial aspect is the most involved. We aimed to assess in vivo local structural differences in the amygdala of patients with AD using high-field MRI

Operationalizing protocol differences for EADC-ADNI manual hippocampal segmentation

Hippocampal volumetry on magnetic resonance imaging is recognized as an Alzheimer's disease (AD) biomarker, and manual segmentation is the gold standard for measurement. However, a standard procedure is lacking. We operationalize and quantitate landmark differences to help a Delphi panel converge on a set of landmarks

Mapping local hippocampal changes in Alzheimer's disease and normal ageing with MRI at 3 Tesla

Histological studies have suggested differing involvement of the hippocampal subfields in ageing and in Alzheimer's disease. The aim of this study was to assess in vivo local hippocampal changes in ageing and Alzheimer's disease based on high resolution MRI at 3 Tesla. T(1)-weighted images were acquired from 19 Alzheimer's disease patients [age 76 +/- 6 years, three males, Mini-Mental State Examination 13 +/- 4] and 19 controls (age 74 +/- 5 years, 11 males, Mini-Mental State Examination 29 +/- 1). The hippocampal formation was isolated by manual tracing. Radial atrophy mapping was used to assess group differences and correlations by averaging hippocampal shapes across subjects using 3D parametric surface mesh models. Percentage difference, Pearson's r, and significance maps were produced. Hippocampal volumes were inversely correlated with age in older healthy controls (r = 0.56 and 0.6 to the right and left, respectively, P < 0.05, corresponding to 14% lower volume for every 10 years of older age from ages 65 to 85 years). Ageing-associated atrophy mapped to medial and lateral areas of the tail and body corresponding to the CA1 subfield and ventral areas of the head corresponding to the presubiculum. Significantly increased volume with older age mapped to a few small spots mainly located to the CA1 sector of the right hippocampus. Volumes were 35% and 30% smaller in Alzheimer's disease patients to the right and left (P < 0.0005). Alzheimer's disease-associated atrophy mapped not only to CA1 areas of the body and tail corresponding to those also associated with age, but also to dorsal CA1 areas of the head unaffected by age. Regions corresponding to the CA2-3 fields were relatively spared in both ageing and Alzheimer's disease. Hippocampal atrophy in Alzheimer's disease maps to areas in the body and tail that partly overlap those affected by normal ageing. Specific areas in the anterior and dorsal CA1 subfield involved in Alzheimer's disease were not in normal ageing. These patterns might relate to differential neural systems involved in Alzheimer's disease and ageing

Harmonized benchmark labels of the hippocampus on magnetic resonance: The EADC-ADNI project

A globally harmonized protocol (HarP) for manual hippocampal segmentation based on magnetic resonance has been recently developed by a task force from European Alzheimer's Disease Consortium (EADC) and Alzheimer's Disease Neuroimaging Initiative (ADNI). Our aim was to produce benchmark labels based on the HarP for manual segmentation

Manual segmentation qualification platform for the EADC-ADNI harmonized protocol for hippocampal segmentation project

The use of hippocampal volumetry as a biomarker for Alzheimer's disease (AD) requires that tracers from different laboratories comply with the same segmentation method. Here we present a platform for training and qualifying new tracers to perform the manual segmentation of the hippocampus on magnetic resonance images (MRI) following the European Alzheimer's Disease Consortium and Alzheimer's Disease Neuroimaging Initiative (EADC-ADNI) Harmonized Protocol (HarP). Our objective was to demonstrate that the training process embedded in the platform leads to increased compliance and qualification with the HarP

The new Alzheimer\u2019s criteria in a naturalistic series of patients with mild cognitive impairment

To test the validity of the new diagnostic criteria for Alzheimer\u2019s disease (AD) in a naturalistic series of patients with mild cognitive impairment (MCI). Ninety consecutive MCI patients were enrolled in a longitudinal study on the natural history of cognitive impairment. Medial temporal (MT) atrophy on MRI was defined as hippocampal volume below the fifth percentile of the distribution in healthy elders, abnormal CSF was based on Sjogren\u2019s cutoffs for Abeta42 and tau, and temporoparietal hypometabolism on 18F-FDG PET based on Herholz\u2019s t sum score. Patients were followed clinically to detect conversion to AD (MCI-AD), non-AD dementia (MCI-nAD), or no conversion (MCI-NC). The 24 MCI-AD and 15 MCI-nAD patients had sociodemo-graphic, clinical, and neuropsychological baseline features similar to the 51 MCI-NC patients. All MCI patients with MT atrophy converted to AD, as did all those with abnormal CSF, but only 48 and 35% of those without MT atrophy or abnormal CSF converted (p on logrank test = 0.0007 and 0.001). Prediction of AD conversion was enhanced when positivity to either MT atrophy or abnormal CSF was considered, with only 15% of those MCI patients negative on both converting to AD (p<0.0005). Markers were not predictive of non-AD dementia conversion. The accuracy of either MT atrophy or abnormal CSF in discriminating MCI-AD from MCI-NC was good (AUC 0.82, 95% CI 0.70\u20130.95). MT atrophy and abnormal CSF are the single most robust predictors of conversion to AD in MCI patients, and their combination enhances prediction. AD markers are not predictive of conversion to non-AD dementia

Training labels for hippocampal segmentation based on the EADC-ADNI harmonized hippocampal protocol

The European Alzheimer's Disease Consortium and Alzheimer's Disease Neuroimaging Initiative (ADNI) Harmonized Protocol (HarP) is a Delphi definition of manual hippocampal segmentation from magnetic resonance imaging (MRI) that can be used as the standard of truth to train new tracers, and to validate automated segmentation algorithms. Training requires large and representative data sets of segmented hippocampi. This work aims to produce a set of HarP labels for the proper training and certification of tracers and algorithms