Mapping hippocampal and ventricular change in Alzheimer disease

Laboratory of Neuro Imaging, Brain Mapping Division, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095, USA.
NeuroImage (Impact Factor: 6.36). 09/2004; 22(4):1754-66. DOI: 10.1016/j.neuroimage.2004.03.040
Source: PubMed


We developed an anatomical mapping technique to detect hippocampal and ventricular changes in Alzheimer disease (AD). The resulting maps are sensitive to longitudinal changes in brain structure as the disease progresses. An anatomical surface modeling approach was combined with surface-based statistics to visualize the region and rate of atrophy in serial MRI scans and isolate where these changes link with cognitive decline. Sixty-two [corrected] high-resolution MRI scans were acquired from 12 AD patients (mean [corrected] age +/- SE at first scan: 68.7 +/- 1.7 [corrected] years) and 14 matched controls (age: 71.4 +/- 0.9 years) [corrected] each scanned twice (1.9 +/- 0.2 [corrected] years apart, when all subjects are pooled [corrected] 3D parametric mesh models of the hippocampus and temporal horns were created in sequential scans and averaged across subjects to identify systematic patterns of atrophy. As an index of radial atrophy, 3D distance fields were generated relating each anatomical surface point to a medial curve threading down the medial axis of each structure. Hippocampal atrophic rates and ventricular expansion were assessed statistically using surface-based permutation testing and were faster in AD than in controls. Using color-coded maps and video sequences, these changes were visualized as they progressed anatomically over time. Additional maps localized regions where atrophic changes linked with cognitive decline. Temporal horn expansion maps were more sensitive to AD progression than maps of hippocampal atrophy, but both maps correlated with clinical deterioration. These quantitative, dynamic visualizations of hippocampal atrophy and ventricular expansion rates in aging and AD may provide a promising measure to track AD progression in drug trials.

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    • "These various techniques (e.g. large deformation high-dimensional brain mapping (Csernansky et al., 2000; Wang et al., 2003), radial atrophy (Thompson et al., 2004; Frisoni et al., 2006; Apostolova et al., 2006a) or spherical harmonics (Gerardin et al., 2009; Sarazin et al., 2010; Lindberg et al., 2012)), are generally based on four main steps: (1) (manual or automated) segmentation of the whole hippocampus , (2) surface reconstruction, i.e. converting segmentations to surface meshes, (3) across subject alignment of the surfaces, (4) between subject comparison of hippocampal surfaces, usually through the computation of displacement vectors indicating the difference between each subject and a reference (either an average surface or a template). Eventually, these methods provide images showing local areas of inward or outward displacement of the surface in relation to age, disease, or cognitive performance. "
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    ABSTRACT: Hippocampal atrophy, as evidenced using magnetic resonance imaging (MRI), is one of the most validated, easily accessible and widely used biomarkers of Alzheimer's disease (AD). However, its imperfect sensitivity and specificity have highlighted the need to improve the analysis of MRI data. Based on neuropathological data showing a differential vulnerability of hippocampal subfields to AD processes, neuroimaging researchers have tried to capture corresponding morphological changes within the hippocampus. The present review provides an overview of the methodological developments that allow the assessment of hippocampal subfield morphology in vivo, and summarizes the results of studies looking at the effects of AD and normal aging on these structures. Most studies highlighted a focal atrophy of the CA1 subfield in the early (predementia or even preclinical) stages of AD, before atrophy becomes more widespread at the dementia stage, consistent with the pathological literature. Preliminary studies have indicated that looking at this focal atrophy pattern rather than standard whole hippocampus volumetry improves diagnostic accuracy at the Mild Cognitive Impairment (MCI) stage. However, controversies remain regarding changes in hippocampal subfield structure in normal aging and regarding correlations between specific subfield volume and memory abilities, very likely because of the strong methodological variability between studies. Overall, hippocampal subfield analysis has proven to be a promising technique in the study of AD. However, harmonization of segmentation protocols and studies on larger samples are needed to enable accurate comparisons between studies and to confirm the clinical utility of these techniques. Copyright © 2015. Published by Elsevier Ltd.
    Neuroscience 08/2015; 309. DOI:10.1016/j.neuroscience.2015.08.033 · 3.36 Impact Factor
    • "The changes in the distance between the mitral cell layers on both sides of the bulb also show a correlation to the degeneration level with an increase in distance. This is a result of changes in the OB shape in mutant mice, but can also suggest a small ventricle volume increase as can be seen qualitatively in the MEMRI images, which can be similar to reported ventricle enlargement in studies of AD and MCI patients (Thompson et al., 2004; Tang et al., 2014). However, the possible increase in the ventricular volume needs to be quantitatively measured in future studies. "
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    ABSTRACT: Manganese Enhanced MRI (MEMRI) was used to detect specific laminar changes in the olfactory bulb (OB) to follow the progression of amyloid precursor protein (APP)-induced neuronal pathology and its recovery in a reversible olfactory based Alzheimer's disease (AD) mouse model. Olfactory dysfunction is an early symptom of AD, which suggests that olfactory sensory neurons (OSNs) may be more sensitive to AD related factors than neurons in other brain areas. Previously a transgenic mouse model was established that causes degeneration of OSNs by overexpressing humanized APP (hAPP), which results in a disruption of olfactory circuitry with changes in glomerular structure. In the present work, OB volume and manganese enhancement of the glomerular layer in OB were decreased in mutant mice. Turning off APP overexpression with doxycycline produced a significant increase in manganese enhancement of the glomerular layer after only 1 week, and further recovery after 3 weeks, while treatment with Aβ antibody produced modest improvement with MRI measurements. Thus, MEMRI enables a direct tracking of laminar specific neurodegeneration through a non-invasive in vivo measurement. The use of MRI will enable assessment of the ability of different pharmacological reagents to block olfactory neuronal loss and can serve as a unique in vivo screening tool to both identify potential therapeutics and test their efficacy. Copyright © 2015. Published by Elsevier Inc.
    NeuroImage 05/2015; 118. DOI:10.1016/j.neuroimage.2015.05.045 · 6.36 Impact Factor
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    • "This finding implies the difference of atrophy in terms of its extension and hemisphere dominance at different stages of AD. A closer inspection of the results shows that the top-ranked significant volumetric variables, e.g., hippocampus [30]–[32], ventricular [26], [33], cortical [30], [32], [34] and amygdala [33], [35] are all regions that have been proven to be effective predictors of AD and/or MCI by other research groups. The convergence of these findings comes in support of the merits and usability of the ranking system developed in this study. "
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    ABSTRACT: This paper proposes to combine MRI data with a neuropsychological test, mini-mental state examination (MMSE), as input to a multi-dimensional space for the classification of Alzheimer's disease (AD) and it's prodromal stages—mild cognitive impairment (MCI) including amnestic MCI (aMCI) and nonamnestic MCI (naMCI). The decisional space is constructed using those features deemed statistically significant through an elaborate feature selection and ranking mechanism. FreeSurfer was used to calculate 55 volumetric variables, which were then adjusted for intracranial volume, age and education. The classification results obtained using support vector machines are based on twofold cross validation of 50 independent and randomized runs. The study included 59 AD, 67 aMCI, 56 naMCI, and 127 cognitively normal (CN) subjects. The study shows that MMSE scores contain the most discriminative power of AD, aMCI, and naMCI. For AD versus CN, the two most discriminative volumetric variables (right hippocampus and left inferior lateral ventricle), when combined with MMSE scores, provided an average accuracy of 92.4% (sensitivity: 84.0%; specificity: 96.1%). MMSE scores are found to improve all classifications with accuracy increments of 8.2% and 12% for aMCI versus CN and naMCI versus CN, respectively. Results also show that brain atrophy is almost evenly seen on both sides of the brain for AD subjects, which is different from right-side dominance for aMCI and left-side dominance for naMCI. Furthermore, hippocampal atrophy is seen to be the most significant for aMCI, while Accumbens area and ventricle are most significant for naMCI.
    IEEE Transactions on Biomedical Engineering 08/2014; 61(8):2245-2253. DOI:10.1109/TBME.2014.2310709 · 2.35 Impact Factor
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