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Objective The purpose of this study was to investigate the neuropathological substrates underlying in vivo hippocampal atrophy on magnetic resonance imaging (MRI) in autopsy confirmed neurodegenerative dementia cases. Methods Thirty-one neuropathologically verified cases (23 with Lewy body dementia (LBD) and eight with Alzheimer's disease (AD)) were included who had undergone an MRI scan close to death (mean 1.5 years). Manual volumetric measurements were undertaken for the hippocampus, entorhinal cortex and amygdala on MRI, along with quantitative neuropathological analysis of plaque, tangle and Lewy body pathology in the same regions. The relationship between neuropathology and MRI volumes was assessed using correlations and linear regression. Results Hippocampal and amygdala volumes were significantly smaller in cases with AD than with LBD, but there was no difference in entorhinal cortex volume. Analysing all cases together, a significant positive correlation was observed between normalised hippocampal volume and percent area of Lewy bodies in the hippocampus (r=0.449, p=0.017) but not with tangles (r=0.059, p=0.766) or plaques (r=−0.361, p=0.119). There were no other significant correlations between regional MRI volume and measures of neuropathology. Regression analysis showed that overall diagnosis of AD rather than burden of individual pathological changes was the most significant predictor of hippocampal volume loss in autopsy confirmed cases. Conclusion Our results suggest that (i) hippocampal and amygdala but not entorhinal cortex, volumes differ between AD and LBD and (ii) factors other than current markers of neurodegenerative pathological change are responsible for atrophy of medial temporal lobe structures in AD and LBD. Copyright © 2012 John Wiley & Sons, Ltd.

We describe a fully automated method for hippocampal segmentation. The method uses SPM5 (http://www.fil.ion.ucl.ac.uk/spm/) software to segment the brain into grey/white matter, and spatially normalize the images to standard space. Grey matter pixels within a predefined hippocampal region in standard space are identified to segment the hippocampi. The method was validated on 36 subjects (9 each of Alzheimer's disease, dementia with Lewy bodies, vascular dementia, and healthy controls). The mean absolute difference in volume compared with manual segmentation was 11% (SD 9%). Linear regression between manual and automated volume gave V(auto) = V(manual) × 0.83 + 401 ml. The method provides an acceptable automated alternative to manual segmentation which may be of value in large studies. Hum Brain Mapp 2008. © 2007 Wiley‐Liss, Inc.

Increased rates of brain atrophy are seen in Alzheimer's disease, but whether rates are similarly increased in other dementias such as Parkinson's disease dementia (PDD) has not been well examined. We determined the rates of brain atrophy using serial magnetic resonance imaging (MRI) in PDD and compared this finding to rates seen in cognitively intact Parkinson's disease (PD) patients and age-matched control subjects. Thirty-one patients (PD = 18, PDD = 13) and 24 age-matched controls underwent serial volumetric 1.5 T MRI scans, approximately 1 year apart. Baseline and repeat scans were registered and quantification of the brain boundary shift integral was used to determine whole-brain atrophy rates. Rates of brain atrophy were significantly increased in PDD (1.12 +/- 0.98%/year) compared to PD (0.31 +/- 0.69%/year; P = 0.018) and control subjects (0.34 +/- 0.76%/year; P = 0.015). There were no differences in atrophy rates between controls and PD (P = 0.79). No correlations between increased atrophy rates and age or dementia severity (Mini-Mental State Examination score) were observed. Serial MRI may be a useful tool for monitoring disease progression in PDD and further studies should investigate its utility for early diagnosis.

This paper examines the frequency of CIND, the profile of early cognitive deficits in stroke patients, the differences in the profile of cognitive impairment in people with CIND and those with vascular dementia, and the MRI associations of CIND in older stroke patients.

51.2(5.9), p 0.05) and AD women (37.1(4.5) vs. 35.2(3.5), p 0.03) compared to nondemented controls. Total lean mass was associated with dementia severity (beta -0.22, p 0.01), global cognitive performance (beta 0.23, p 0.23), and whole brain volume (beta 0.54, p 0.001) in the overall group. These relationships remained present when lean mass was indexed for height2 (lean mass index). Total and percent body fat were not related to cognition or brain atrophy measures. In separate within-group analyses, lean mass (beta 0.43, p 0.001) and lean mass index (beta 0.28, p 0.05) were associated with whole brain volume in early AD. A trend to better global cognitive performance in early AD subjects was present with increasing lean mass index (beta 0.23, p 0.06). Lean mass was not associated with brain atrophy or cognition in nondemented subjects. In AD, lean mass was associated with physical activity level (beta 0.17, p 0.04) and peripheral insulin levels (beta 0.18, p 0.04). Conclusions: Lean mass is reduced in early AD and associated with dementia severity, cognitive performance, and brain atrophy suggesting lean mass is lost in the early stages of AD. The mechanism of lean mass loss in AD may be related to declines in physical activity and loss of anabolic support.