Application of a non-linear image registration algorithm to quantitative analysis of T2 relaxation time in transgenic mouse models of AD pathology

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.