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Apostolova, L. G. et al. Conversion of mild cognitive impairment to Alzheimer disease predicted by hippocampal atrophy maps. Arch. Neurol. 63, 693-699

Laboratory of Neuro Imaging, Department of Neurology, The David Geffen School of Medicine at UCLA, University of California-Los Angeles, Los Angeles, CA, USA.
JAMA Neurology (Impact Factor: 7.01). 06/2006; 63(5):693-9. DOI: 10.1001/archneur.63.5.693
Source: PubMed

ABSTRACT While most patients with mild cognitive impairment (MCI) transition to Alzheimer disease (AD), others develop non-AD dementia, remain in the MCI state, or improve.
To test the following hypotheses: smaller hippocampal volumes predict conversion of MCI to AD, whereas larger hippocampal volumes predict cognitive stability and/or improvement; and patients with MCI who convert to AD have greater atrophy in the CA1 hippocampal subfield and subiculum.
Prospective longitudinal cohort study.
University of California-Los Angeles Alzheimer's Disease Research Center.
We followed up 20 MCI subjects clinically and neuropsychologically for 3 years.
Baseline regional hippocampal atrophy was analyzed with region-of-interest and 3-dimensional hippocampal mapping techniques.
During the 3-year study, 6 patients developed AD (MCI-c), 7 remained stable (MCI-nc), and 7 improved (MCI-i). Patients with MCI-c had 9% smaller left and 13% smaller right mean hippocampal volumes compared with MCI-nc patients. Radial atrophy maps showed greater atrophy of the CA1 subregion in MCI-c. Patients with MCI-c had significantly smaller hippocampi than MCI-i patients (left, 24%; right, 27%). Volumetric analyses showed a trend for greater hippocampal atrophy in MCI-nc relative to MCI-i patients (eg, 16% volume loss). After permutation tests corrected for multiple comparison, the atrophy maps showed a significant difference on the right. Subicular differences were seen between MCI-c and MCI-i patients, and MCI-nc and MCI-i patients. Multiple linear regression analysis confirmed the group effect to be highly significant and independent of age, hemisphere, and Mini-Mental State Examination scores at baseline.
Smaller hippocampi and specifically CA1 and subicular involvement are associated with increased risk for conversion from MCI to AD. Patients with MCI-i tend to have larger hippocampal volumes and relative preservation of both the subiculum and CA1.

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    • "*P < 0.05; **P < 0.01; ***P < 0.001. r Hippocampal Subfields Volumetry r r 9 r [Apostolova et al., 2006; Ch etelat et al., 2008; La Joie et al., 2013; Mueller et al., 2010; Pluta et al., 2012] "
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    ABSTRACT: Growing interest has developed in hippocampal subfield volumetry over the past few years and an increasing number of studies use the automatic segmentation algorithm implemented in FreeSurfer. However, this approach has not been validated on standard resolution T1-weighted magnetic resonance (MR) as used in most studies. We aimed at comparing hippocampal subfield segmentation using FreeSurfer on standard T1-weighted images versus manual delineation on dedicated high-resolution hippocampal scans. Hippocampal subfields were segmented in 133 individuals including 98 cognitively normal controls aged 19-84 years, 17 mild cognitive impairment and 18 Alzheimer's disease (AD) patients using both methods. Intraclass correlation coefficients (ICC) and Bland-Altman plots were computed to assess the consistency between both methods, and the effects of age and diagnosis were assessed from both measures. Low to moderate ICC (0.31-0.74) were found for the subiculum and other subfields as well as for the whole hippocampus, and the correlations were very low for cornu ammonis (CA)1 (<0.1). FreeSurfer CA1 volume estimates were found to be much lower than those obtained from manual segmentation, and this bias was proportional to the volume of this structure so that no effect of age or AD could be detected on FreeSurfer CA1 volumes. This study points to the differences in the anatomic definition of the subfields between FreeSurfer and manual delineation, especially for CA1, and provides clue for improvement of this automatic technique for potential clinical application on standard T1-weighted MR. Hum Brain Mapp, 2014. © 2014 Wiley Periodicals, Inc.
    Human Brain Mapping 07/2014; 36(2). DOI:10.1002/hbm.22640 · 6.92 Impact Factor
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    • "The decaying hippocampus is a biomarker of MCI [10] [11] and a good predictor of conversion from MCI to AD [11] [12] [13] [14] [15] [16] [17] [18], as well as of AD onset [19]. Loss of entorhinal cortex volume can predict the development of AD as well [13] [15] [18] [20] and its combination with hippocampal pathology is associated with memory decline [14] [21] [22]. There is growing evidence that timely interventions in MCI can restore cognition in affected individuals [23]. "
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    ABSTRACT: The present article is based on the premise that the risk of developing Alzheimer's disease (AD) from its prodromal phase (mild cognitive impairment; MCI) is higher when adverse factors (e.g., stress, depression, and metabolic syndrome) are present and accumulate. Such factors augment the likelihood of hippocampal damage central in MCI/AD aetiology, as well as compensatory mechanisms failure triggering a switch toward neurodegeneration. Because of the devastating consequences of AD, there is a need for early interventions that can delay, perhaps prevent, the transition from MCI to AD. We hypothesize that Mindfulness-Based Interventions (MBI) show promise with regard to this goal. The present review discusses the associations between modifiable adverse factors and MCI/AD decline, MBI's impacts on adverse factors, and the mechanisms that could underlie the benefits of MBI. A schematic model is proposed to illustrate the course of neurodegeneration specific to MCI/AD, as well as the possible preventive mechanisms of MBI. Whereas regulation of glucocorticosteroids, inflammation, and serotonin could mediate MBI's effects on stress and depression, resolution of the metabolic syndrome might happen through a reduction of inflammation and white matter hyperintensities, and normalization of insulin and oxidation. The literature reviewed in this paper suggests that the main reach of MBI over MCI/AD development involves the management of stress, depressive symptoms, and inflammation. Future research must focus on achieving deeper understanding of MBI's mechanisms of action in the context of MCI and AD. This necessitates bridging the gap between neuroscientific subfields and a cross-domain integration between basic and clinical knowledge.
    Behavioural Brain Research 06/2014; In press. DOI:10.1016/j.bbr.2014.05.058 · 3.39 Impact Factor
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    • "The computated automated imaging field has opened a new avenue to analyze the Grey matter (GM), white matter (WM) and Cerebrospinal fluid (CSF) volume and thickness. Quantitative MRI studies have revealed differences in the volume of particular brain structures in several neurological & psychiatric conditions including depression [1], posttraumatic stress disorder [2] [3], schizophrenia [4] [5], Alzheimer's disease [6] [7], Obsessive Compulsive disorder [8] [9]. Our study is focused on Traumatic brain injury (TBI), which is a heterogeneous disorder resulting from a variety of causes, extending from trivial and transient injuries to catastrophic damage and ranging from focal to diffuse injuries, with patients having varied outcomes. "
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    ABSTRACT: Aim: To assess Surface Based Morphometry (SBM) and Voxel Based Morphometry (VBM), the automated computation methods to demonstrate volume and thickness changes in brain among early Traumatic Brain Injury (TBI) and their correlation with cognitive test scores. Methods: 22 mild to moderate TBI patients and 20 age, gender matched healthy individuals were recruited (mean ± SD, age range: 27.7 ± 6.5 years). MRI scans were acquired in the Siemens 3T Magnetom Skyra Scanner. TheT1-weighted magnetization preparation rapid acquisition gradient echo (MP-RAGE) sequence used for morphometric analysis provided excellent gray-white matter contrast. The structural data was processed using SBM and VBM methods with statistical significance of P<0.05 corrected for multiple comparisons. Results: both methods did not show any significant changes in brain measures after correcting for false discovery rate. However, on correlating neuropsychological score with structural changes, SBM demonstrated significant voxels survived in animal naming and Token Test after correcting for multiple comparisons. No significant change was found while using VBM. Conclusion: The study emphasizes the similarities in the results obtained after using different automatedmethods. Our findings suggest that SBM is more sensitive as compared to VBM in detecting structural changes correlated with Neuropsychological scores during early phase of TBI.
    02/2014; 2. DOI:10.11131/2014/101069
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