George Pengas

Focal posterior cingulate atrophy in incipient Alzheimer's disease

Severe posterior cingulate cortex hypometabolism is a feature of incipient, sporadic Alzheimers disease (AD). The aim was to test the hypothesis that this region is focally atrophic in very early disease by studying AD patients at the mild cognitive impairment (MCI) stage, and, if so, to determine whether the amount of atrophy was comparable to that of the hippocampus. Twenty-four patients meeting criteria for amnestic MCI, who all subsequently progressed to fulfil AD criteria, and 28 age-matched controls, were imaged with volumetric MRI. Four regions of interest were manually traced in each hemisphere: two posterior cingulate regions (BA 23 and BA 29/30), the hippocampus (as a positive control) and the anterior cingulate (as a negative control). BA 23 and BA 29/30 were both significantly atrophic and this atrophy was comparable to that found in the hippocampus, in the absence of anterior cingulate cortex (ACC) atrophy. Contrary to previous reports, there was no evidence that posterior cingulate atrophy is specifically associated with early-onset AD. The results indicate that posterior cingulate cortex atrophy is present from the earliest clinical stage of sporadic AD and that this region is as vulnerable to neurodegeneration as the hippocampus.

Atrophy patterns in histologic vs clinical groupings of frontotemporal lobar degeneration

Objective: Predictable patterns of atrophy are associated with the clinical subtypes of frontotemporal dementia (FTD): behavioral variant (bvFTD), semantic dementia (SEMD), and progressive nonfluent aphasia (PNFA). Some studies of pathologic subtypes have also suggested specific atrophy patterns; however, results are inconsistent. Our aim was to test the hypothesis that clinical, but not pathologic, classification (FTD with ubiquitin inclusions [FTD-U] and FTD with tau inclusions [FTD-T]) is associated with predictable patterns of regional atrophy. Methods: Magnetic resonance scans of nine FTD-U and six FTD-T patients (histologically confirmed) were compared with 25 controls using voxel-based morphometry (VBM). Analyses were conducted with the patient group classified according to histologic or clinical variant. Additionally, three Alzheimer pathology patients who had the syndrome of SEMD in life (FTD-A) were analyzed. Results: The VBM studies in clinical variants confirmed established patterns of atrophy (SEMD, rostral temporal; bvFTD, mesial frontal; PNFA, left insula). FTD-U and FTD-T VBM results were very similar, showing severe atrophy in the temporal poles, mesial frontal lobe, and insulae. A conjunction analysis confirmed this similarity. Subgroup analysis found that SEMD associated with either FTD-T or FTD-U was associated with similar rostral temporal atrophy; however, FTD-A had a qualitatively different pattern of left hippocampal atrophy. Conclusions: While there is predictable atrophy for clinical variants of frontotemporal dementia (FTD), histologic FTD variants show no noticeable differences. Reports of specific atrophy profiles are likely the result of idiosyncrasies in small groups. Semantic dementia associated with Alzheimer pathology, however, presented a distinct atrophy pattern.

The impact of skull-stripping and radio-frequency bias correction on grey-matter segmentation for voxel-based morphometry

This study evaluates the application of (i) skull-stripping methods (hybrid watershed algorithm (HWA), brain surface extractor (BSE) and brain-extraction tool (BET2)) and (ii) bias correction algorithms (nonparametric nonuniform intensity normalisation (N3), bias field corrector (BFC) and FMRIBs automated segmentation tool (FAST)) as pre-processing pipelines for the technique of voxel-based morphometry (VBM) using statistical parametric mapping v.5 (SPM5). The pipelines were evaluated using a BrainWeb phantom, and those that performed consistently were further assessed using artificial-lesion masks applied to 10 healthy controls compared to the original unlesioned scans, and finally, 20 Alzheimers disease (AD) patients versus 23 controls. In each case, pipelines were compared to each other and to those from default SPM5 methodology. The BET2+N3 pipeline was found to produce the least miswarping to template induced by real abnormalities, and performed consistently better than the other methods for the above experiments. Occasionally, the clusters of significant differences located close to the boundary were dragged out of the glass-brain projections -- this could be corrected by adding background noise to low-probability voxels in the grey matter segments. This method was confirmed in a one-dimensional simulation and was preferable to threshold and explicit (simple) masking which excluded true abnormalities.

Comparative Reliability of Total Intracranial Volume Estimation Methods and the Influence of Atrophy in a Longitudinal Semantic Dementia Cohort

Total intracranial volume (TIV) as a measure of premorbid brain size is often used to correct volumes of interest for interindividual differences in magnetic resonance imaging (MRI) studies. We directly compared the reliability of different TIV estimation methods to address whether such methods are influenced by brain atrophy in the neurodegenerative disease, semantic dementia.

Registration accuracy for VBM studies varies according to region and degenerative disease grouping

Voxel-based morphometry studies are frequently cited as having the advantage of being objective compared to region-of-interest methods. This statement assumes, however, that all regions are treated equally both in controls and diseased cohorts. This study aimed to test whether this statement is correct by analyzing fiducial landmarks in controls, Alzheimers disease (as a model of mild generalized atrophy model); Frontotemporal Dementia (focal atrophy model) and Semantic Dementia (extreme focal atrophy model). Standard SPM5 and DARTEL were evaluated using either raw or skull-stripped/bias corrected scans. The results indicated that with all methods there was variability in the degree of misregistration across regions and that there was a disease grouping interaction-most severely in the extreme focal atrophy model (Semantic Dementia). Preprocessing improved VBM outputs both with standard SPM and DARTEL. In the latter case, this occurred to an extreme degree-DARTEL using raw data was grossly insensitive to a ground truth (manually verified hippocampal atrophy in AD) whereas DARTEL after preprocessing yielded excellent results with respect to this yardstick.

Diffusion tensor metrics as biomarkers in Alzheimer's disease.

Background Although diffusion tensor imaging has been a major research focus for Alzheimer’s disease in recent years, it remains unclear whether it has sufficient stability to have biomarker potential. To date, frequently inconsistent results have been reported, though lack of standardisation in acquisition and analysis make such discrepancies difficult to interpret. There is also, at present, little knowledge of how the biometric properties of diffusion tensor imaging might evolve in the course of Alzheimer’s disease. Methods The biomarker question was addressed in this study by adopting a standardised protocol both for the whole brain (tract-based spatial statistics), and for a region of interest: the midline corpus callosum. In order to study the evolution of tensor changes, cross-sectional data from very mild (N = 21) and mild (N = 22) Alzheimer’s disease patients were examined as well as a longitudinal cohort (N = 16) that had been rescanned at 12 months. Findings and Significance The results revealed that increased axial and mean diffusivity are the first abnormalities to occur and that the first region to develop such significant differences was mesial parietal/splenial white matter; these metrics, however, remained relatively static with advancing disease indicating they are suitable as ‘state-specific’ markers. In contrast, increased radial diffusivity, and therefore decreased fractional anisotropy–though less detectable early–became increasingly abnormal with disease progression, and, in the splenium of the corpus callosum, correlated significantly with dementia severity; these metrics therefore appear ‘stage-specific’ and would be ideal for monitoring disease progression. In addition, the cross-sectional and longitudinal analyses showed that the progressive abnormalities in radial diffusivity and fractional anisotropy always occurred in areas that had first shown an increase in axial and mean diffusivity. Given that the former two metrics correlate with dementia severity, but the latter two did not, it would appear that increased axial diffusivity represents an upstream event that precedes neuronal loss.

Lost and found: bespoke memory testing for Alzheimer's disease and semantic dementia.

The neural network activated during Topographical Memory (TM) tasks in controls overlaps with the earliest affected regions in Alzheimers disease (AD) but not with those of Semantic Dementia (SD). This suggests that clinical TM tests could be more bespoke to neural dysfunction in early AD and therefore more sensitive and specific. We hypothesized that TM impairment would be characteristic of AD but not of SD making it useful both for early diagnosis and differential diagnosis. TM was assessed in 69 patients (22 mild AD, 15 SD, 32 with mild cognitive impairment (MCI)) and 35 controls, using three tasks: the four mountains test and two novel tests in a virtual town (the Virtual Route Learning Test (VRLT) and the Heading Orientation Test). AD patients were impaired on all TM tasks. The VRLT was the most discriminatory; had the highest correlation with caregiver reports of navigation problems; and correlated strongly with memory, attention/executive function, and to a lesser degree, visuospatial ability. In contrast, SD patients performed well on the TM battery only becoming abnormal with very advanced dementia and performance correlated exclusively with attention/executive function. The VRLT achieved 95% sensitivity and 94% specificity in discriminating AD patients from controls; at the same cutoff, 70% of MCI patients were impaired. When combined with either naming performance or global dementia severity, there was complete separation of AD from SD. The VRLT is ecologically valid, highly sensitive to early AD, and useful in discriminating AD from the non-Alzheimer dementia, SD.

The relationship of topographical memory performance to regional neurodegeneration in Alzheimer's disease

The network activated during normal route learning shares considerable homology with the network of degeneration in the earliest symptomatic stages of Alzheimers disease (AD). This inspired the virtual route learning test (VRLT) in which patients learn routes in a virtual reality environment. This study investigated the neural basis of VRLT performance in AD to test whether impairment was underpinned by a network or by the widely held explanation of hippocampal degeneration. VRLT score in a mild AD cohort was regressed against gray matter (GM) density and diffusion tensor metrics of white matter (WM) (n = 30), and, cerebral glucose metabolism (n = 26), using a mass univariate approach. GM density and cerebral metabolism were then submitted to a multivariate analysis [support vector regression (SVR)] to examine whether there was a network associated with task performance. Univariate analyses of GM density, metabolism and WM axial diffusion converged on the vicinity of the retrosplenial/posterior cingulate cortex, isthmus and, possibly, hippocampal tail. The multivariate analysis revealed a significant, right hemisphere-predominant, network level correlation with cerebral metabolism; this comprised areas common to both activation in normal route learning and early degeneration in AD (retrosplenial and lateral parietal cortices). It also identified right medio-dorsal thalamus (part of the limbic-diencephalic hypometabolic network of early AD) and right caudate nucleus (activated during normal route learning). These results offer strong evidence that topographical memory impairment in AD relates to damage across a network, in turn offering complimentary lesion evidence to previous studies in healthy volunteers for the neural basis of topographical memory. The results also emphasize that structures beyond the mesial temporal lobe (MTL) contribute to memory impairment in AD—it is too simplistic to view memory impairment in AD as a synonym for hippocampal degeneration.

MRI detection of tissue pathology beyond atrophy in Alzheimer's disease: Introducing T2-VBM

Voxel-based morphometry (VBM) of T1-weighted magnetic resonance (MR) images has been widely used to identify regional atrophy in neurodegenerative conditions such as Alzheimers disease (AD). In theory, however, T2-weighting should be more sensitive to tissue pathology, though until recently, volumetric T2-weighted images were unavailable. We tested the hypothesis that T2-VBM would be more sensitive to grey matter pathology in AD than T1-VBM using the recently-developed SPACE acquisition, which provides true-3D, high-resolution T2-weighted images. This was contrasted to conventional T1-weighted MPRAGE images acquired at the same session and resolution. All of the atrophic regions identified with T1-VBM were also identified with T2-VBM. Additional abnormalities were, however, identified with T2-VBM and the distribution of these bore a striking resemblance to the distribution of amyloid plaque deposition in AD, suggesting that T2-VBM detects signal changes due to histopathology over and above those attributable to atrophy. In keeping with this hypothesis, the relevant statistical tests demonstrated that the difference in sensitivity was caused by an apparent change in T2-weighted signal intensity that was not present in T1-weighted images. These results suggest that T2-VBM has the potential to advance VBM beyond atrophy detection to more expansive applications in tissue pathology mapping.

VBM with viscous fluid registration of gray matter segments in SPM

Improved registration of gray matter segments in SPM has been achieved with the DARTEL algorithm. Previous work from our group suggested, however, that such improvements may not translate to studies of clinical groups. To address the registration issue in atrophic brains, this paper relaxed the condition of diffeomorphism, central to DARTEL, and made use of a viscous fluid registration model with limited regularization constraints to register the modulated gray matter probability maps to an intra-population template. Quantitative analysis of the registration results after the additional viscous fluid step showed no worsening of co-localization of fiducials compared to DARTEL or unified segmentation methods, and the resulting voxel based morphometry (VBM) analyses were able to better identify atrophic regions and to produce results with fewer apparent false positives. DARTEL showed great sensitivity to atrophy, but the resulting VBM maps presented broad, amorphous regions of significance that are hard to interpret. We propose that the condition of diffeomorphism is not necessary for basic VBM studies in atrophic populations, but also that it has disadvantages that must be taken into consideration before a study. The presented viscous fluid registration method is proposed for VBM studies to enhance sensitivity and localizing power.