Comparison of prefrontal atrophy and episodic memory performance in dysexecutive Alzheimer’s disease and behavioural-variant frontotemporal dementia

Alzheimer’s disease (AD) sometimes presents with prominent executive dysfunction and associated prefrontal cortex atrophy. The impact of such executive deficits on episodic memory performance as well as their neural correlates in AD, however, remains unclear. The aim of the current study was to investigate episodic memory and brain atrophy in AD patients with relatively spared executive functioning (SEF-AD; n = 12) and AD patients with relatively impaired executive functioning (IEF-AD; n = 23). We also compared the AD subgroups with a group of behavioral-variant frontotemporal dementia patients (bvFTD; n = 22), who typically exhibit significant executive deficits, and age-matched healthy controls (n = 38). On cognitive testing, the three patient groups showed comparable memory profiles on standard episodic memory tests, with significant impairment relative to controls. Voxel-based morphometry analyses revealed extensive prefrontal and medial temporal lobe atrophy in IEF-AD and bvFTD, whereas this was limited to the middle frontal gyrus and hippocampus in SEF-AD. Moreover, the additional prefrontal atrophy in IEF-AD and bvFTD correlated with memory performance, whereas this was not the case for SEF-AD. These findings indicate that IEF-AD patients show prefrontal atrophy in regions similar to bvFTD, and suggest that this contributes to episodic memory performance. This has implications for the differential diagnosis of bvFTD and subtypes of AD

Integrating longitudinal information in hippocampal volume measurements for the early detection of Alzheimer's disease

Background: Structural MRI measures for monitoring Alzheimer's Disease (AD) progression are becoming instrumental in the clinical practice, and more so in the context of longitudinal studies. This investigation addresses the impact of four image analysis approaches on the longitudinal performance of the hippocampal volume. Methods: We present a hippocampal segmentation algorithm and validate it on a gold-standard manual tracing database. We segmented 460 subjects from ADNI, each subject having been scanned twice at baseline, 12-month and 24month follow-up scan (1.5T, T1 MRI). We used the bilateral hippocampal volume v and its variation, measured as the annualized volume change Λ=δv/year(mm3/y). Four processing approaches with different complexity are compared to maximize the longitudinal information, and they are tested for cohort discrimination ability. Reference cohorts are Controls vs. Alzheimer's Disease (CTRL/AD) and CTRL vs. Mild Cognitive Impairment who subsequently progressed to AD dementia (CTRL/MCI-co). We discuss the conditions on v and the added value of Λ in discriminating subjects. Results: The age-corrected bilateral annualized atrophy rate (%/year) were: -. 1.6 (0.6) for CTRL, -. 2.2 (1.0) for MCI-. nc, -. 3.2 (1.2) for MCI-. co and -. 4.0 (1.5) for AD. Combined (. v, Λ) discrimination ability gave an Area under the ROC curve (. auc). =. 0.93 for CTRL vs AD and auc=. 0.88 for CTRL vs MCI-. co. Conclusions: Longitudinal volume measurements can provide meaningful clinical insight and added value with respect to the baseline provided the analysis procedure embeds the longitudinal information

A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI.

AbstractAutomated analysis of MRI data of the subregions of the hippocampus requires computational atlases built at a higher resolution than those that are typically used in current neuroimaging studies. Here we describe the construction of a statistical atlas of the hippocampal formation at the subregion level using ultra-high resolution, ex vivo MRI. Fifteen autopsy samples were scanned at 0.13mm isotropic resolution (on average) using customized hardware. The images were manually segmented into 13 different hippocampal substructures using a protocol specifically designed for this study; precise delineations were made possible by the extraordinary resolution of the scans. In addition to the subregions, manual annotations for neighboring structures (e.g., amygdala, cortex) were obtained from a separate dataset of in vivo, T1-weighted MRI scans of the whole brain (1mm resolution). The manual labels from the in vivo and ex vivo data were combined into a single computational atlas of the hippocampal formation with a novel atlas building algorithm based on Bayesian inference. The resulting atlas can be used to automatically segment the hippocampal subregions in structural MRI images, using an algorithm that can analyze multimodal data and adapt to variations in MRI contrast due to differences in acquisition hardware or pulse sequences. The applicability of the atlas, which we are releasing as part of FreeSurfer (version 6.0), is demonstrated with experiments on three different publicly available datasets with different types of MRI contrast. The results show that the atlas and companion segmentation method: 1) can segment T1 and T2 images, as well as their combination, 2) replicate findings on mild cognitive impairment based on high-resolution T2 data, and 3) can discriminate between Alzheimer's disease subjects and elderly controls with 88% accuracy in standard resolution (1mm) T1 data, significantly outperforming the atlas in FreeSurfer version 5.3 (86% accuracy) and classification based on whole hippocampal volume (82% accuracy)

Medial Temporal Lobe Does Not Tell The Whole Story: Episodic Memory In ‘atypical’ Variants Of Alzheimer’s Disease

Alzheimer’s disease is the most common form of dementia, which is globally epidemic and well-known by the general public. Episodic memory, a conscious recollection of a particular event in spatial and temporal context, is the most prominent deficit in the early stage of clinical amnestic AD, and reflected by the shrinkage of structures in medial temporal lobe (MTL), including the hippocampus. According to Braak staging, tangles begin in the transentorhinal cortex of the MTL, which then spreads to hippocampal subfields, and later to neocortical areas. Cases that are less recognized by the general public are patients with the atypical variants of AD. Interestingly, many of the atypical cases of AD appear to share the same histopathological features with clinical amnestic AD. According to the diagnostic criteria for these atypical variants of AD, episodic memory should be relatively preserved. However, inconsistent reports on the episodic memory performance and the hippocampal involvement in these atypical cases pose challenges for accurately diagnosing these patients. The two kinds of atypical variants of AD that I focused here are logopenic variant of Primary Progressive Aphasia (lvPPA) and posterior cortical atrophy (PCA). The overarching theme of my thesis is to examine 1) whether the atypical cases of AD have episodic memory difficulty, and if so, 2) what brain areas are responsible for this difficulty. Chapter 2 and 3 of the current thesis show that 1) episodic memory difficulty is observed in lvPPA and PCA cases and 2) this impairment is modulated by deficit in other cognitive domains and associated with disease in non-MTL brain regions. This would be consistent with the ‘hippocampal-sparing’ hypothesis that not all AD histopathology begins in the MTL, and these hippocampal-sparing conditions suggest that additional mechanisms must be considered in the genesis of spreading pathology in AD