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ABSTRACT: In this study, we used MRI to analyze quantitative parametric maps of transverse (T(2)) relaxation times in a longitudinal study of transgenic mice expressing mutant forms of amyloid precursor protein (APP), presenilin (PS1), or both (PS/APP), modeling aspects of Alzheimer's disease (AD). The main goal was to characterize the effects of progressive beta-amyloid accumulation and deposition on the biophysical environment of water and to investigate if these measurements would provide early indirect evidence of AD pathological changes in the brains of these mice. Our results demonstrate that at an early age before beta-amyloid deposition, only PS/APP mice show a reduced T(2) in the hippocampus and cortex compared with wild-type non-transgenic (NTg) controls, whereas a statistically significant within-group aging-associated decrease in T(2) values is seen in the cortex and hippocampus of all three transgenic genotypes (APP, PS/APP, and PS) but not in the NTg controls. In addition, for animals older than 12 months, we confirmed our previous report that only the two genotypes that form amyloid plaques (APP and PS/APP) have significantly reduced T(2) values compared with NTg controls. Thus, T(2) changes in these AD models can precede amyloid deposition or even occur in AD models that do not deposit beta-amyloid (PS mice), but are intensified in the presence of amyloid deposition.
NMR in Biomedicine 06/2007; 20(3):343-51. · 3.21 Impact Factor
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ABSTRACT: Transgenic mouse models have been essential for understanding the pathogenesis of Alzheimer's disease (AD) including those that model the deposition process of beta-amyloid (Abeta). Several laboratories have focused on research related to the non-invasive detection of early changes in brains of transgenic mouse models of Alzheimer's pathology. Most of this work has been performed using regional image analysis of individual mouse brains and pooling the results for statistical assessment. Here we report the implementation of a non-linear image registration algorithm to register anatomical and transverse relaxation time (T2) maps estimated from MR images of transgenic mice. The algorithm successfully registered mouse brain magnetic resonance imaging (MRI) volumes and T2 maps, allowing reliable estimates of T2 values for different regions of interest from the resultant combined images. This approach significantly reduced the data processing and analysis time, and improved the ability to statistically discriminate between groups. Additionally, 3D visualization of intra-regional distributions of T2 of the resultant registered images provided the ability to detect small changes between groups that otherwise would not be possible to detect.
Journal of Neuroscience Methods 06/2005; 144(1):91-7. · 1.98 Impact Factor
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ABSTRACT: Transgenic mouse models have been essential for understanding the pathogenesis of Alzheimer's disease (AD) including those that model the deposition process of β-amyloid (Aβ). Several laboratories have focused on research related to the non-invasive detection of early changes in brains of transgenic mouse models of Alzheimer's pathology. Most of this work has been performed using regional image analysis of individual mouse brains and pooling the results for statistical assessment. Here we report the implementation of a non-linear image registration algorithm to register anatomical and transverse relaxation time (T2) maps estimated from MR images of transgenic mice. The algorithm successfully registered mouse brain magnetic resonance imaging (MRI) volumes and T2 maps, allowing reliable estimates of T2 values for different regions of interest from the resultant combined images. This approach significantly reduced the data processing and analysis time, and improved the ability to statistically discriminate between groups. Additionally, 3D visualization of intra-regional distributions of T2 of the resultant registered images provided the ability to detect small changes between groups that otherwise would not be possible to detect.
Journal of Neuroscience Methods.
