Article

Subregional neuroanatomical change as a biomarker for Alzheimer's disease

Department of Neurosciences, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.
Proceedings of the National Academy of Sciences (Impact Factor: 9.67). 12/2009; 106(49):20954-9. DOI: 10.1073/pnas.0906053106
Source: PubMed

ABSTRACT

Regions of the temporal and parietal lobes are particularly damaged in Alzheimer's disease (AD), and this leads to a predictable pattern of brain atrophy. In vivo quantification of subregional atrophy, such as changes in cortical thickness or structure volume, could lead to improved diagnosis and better assessment of the neuroprotective effects of a therapy. Toward this end, we have developed a fast and robust method for accurately quantifying cerebral structural changes in several cortical and subcortical regions using serial MRI scans. In 169 healthy controls, 299 subjects with mild cognitive impairment (MCI), and 129 subjects with AD, we measured rates of subregional cerebral volume change for each cohort and performed power calculations to identify regions that would provide the most sensitive outcome measures in clinical trials of disease-modifying agents. Consistent with regional specificity of AD, temporal-lobe cortical regions showed the greatest disease-related changes and significantly outperformed any of the clinical or cognitive measures examined for both AD and MCI. Global measures of change in brain structure, including whole-brain and ventricular volumes, were also elevated in AD and MCI, but were less salient when compared to changes in normal subjects. Therefore, these biomarkers are less powerful for quantifying disease-modifying effects of compounds that target AD pathology. The findings indicate that regional temporal lobe cortical changes would have great utility as outcome measures in clinical trials and may also have utility in clinical practice for aiding early diagnosis of neurodegenerative disease.

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    • "Research projects and clinical practice often demand simultaneous application of structural and functional images by two or more imaging modalities [6] [7] [8]. In these cases special matching and proper aligning of two or more images are required. "
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    ABSTRACT: Clinical practice often requires simultaneous information obtained by two different imaging modalities. Registration algorithms are commonly used for this purpose. Automated procedures are very helpful in cases when the same kind of registration has to be performed on images of a high number of subjects. Radiotherapists would prefer to use the best automated method to assist therapy planning, however there are not accepted procedures for ranking the different registration algorithms. We were interested in developing a method to measure the population level performance of CT-MRI registration algorithms by a parameter of values in the [0,1] interval. Pairs of CT and MRI images were collected from 1051 subjects. Results of an automated registration were corrected manually until a radiologist and a neurosurgeon expert both accepted the result as good. This way 1051 registered MRI images were produced by the same pair of experts to be used as gold standards for the evaluation of the performance of other registration algorithms. Pearson correlation coefficient, mutual information, normalized mutual information, Kullback-Leibler divergence, L1 norm and square L2 norm (dis)similarity measures were tested for sensitivity to indicate the extent of (dis)similarity of a pair of individual mismatched images. The square Hellinger distance proved suitable to grade the performance of registration algorithms at population level providing the developers with a valuable tool to rank algorithms. The developed procedure provides an objective method to find the registration algorithm performing the best on the population level out of newly constructed or available preselected ones. Copyright © 2015. Published by Elsevier GmbH.
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    • "These correlate closely with differences and changes in cognitive performance, supporting their validity as markers of disease progression. Although many current studies examine cortical and substructural volumes (den Heijer et al., 2010; Dewey et al., 2010; Holland et al., 2009; Jack et al., 2003, 2004; Ridha et al., 2008; Vemuri et al., 2008a, 2008b; Wolz et al., 2010), recent research (Apostolova et al., 2010b, 2010c; Chou et al., 2009; Costafreda et al., 2011; Ferrarini et al., 2008; Madsen et al., 2010; Morra et al., 2009b; Qiu et al., 2010; Styner et al., 2005; Thompson et al., ) has demonstrated that surface-based subregional structure analysis offers advantages over volume measures, in some respects. "
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    ABSTRACT: The apolipoprotein E (APOE) e4 allele is the most prevalent genetic risk factor for Alzheimer's disease (AD). Hippocampal volumes are generally smaller in AD patients carrying the e4 allele compared to e4 noncarriers. Here we examined the effect of APOE e4 on hippocampal morphometry in a large imaging database—the Alzheimer's Disease Neuroimaging Initiative (ADNI). We automatically segmented and constructed hippocampal surfaces from the baseline MR images of 725 subjects with known APOE genotype information including 167 with AD, 354 with mild cognitive impairment (MCI), and 204 normal controls. High-order correspondences between hippocampal surfaces were enforced across subjects with a novel inverse consistent surface fluid registration method. Multivariate statistics consisting of multivariate tensor-based morphometry (mTBM) and radial distance were computed for surface deformation analysis. Using Hotelling's T2 test, we found significant morphological deformation in APOE e4 carriers relative to noncarriers in the entire cohort as well as in the nondemented (pooled MCI and control) subjects, affecting the left hippocampus more than the right, and this effect was more pronounced in e4 homozygotes than heterozygotes. Our findings are consistent with previous studies that showed e4 carriers exhibit accelerated hippocampal atrophy; we extend these findings to a novel measure of hippocampal morphometry. Hippocampal morphometry has significant potential as an imaging biomarker of early stage AD. Hum Brain Mapp, 2014. © 2014 Wiley Periodicals, Inc.
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    • "A variety of imaging modalities, including structural and functional ones, has shown distinctive changes in the brains of patients within the AD spectrum [11]. Overt dementia presents marked atrophy in the medial temporal lobe structures [12] [13] along with progressive thinning of the parietotemporal and frontal cortices [14] [15]. The pattern observed in MCI is similar, but to a lesser degree, to that of AD. "
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