We have used MR DTI to identify relevant brain structures involved in visuospatial processing, in an attempt to link perceptual and attentional impairments to WM changes in Alzheimer's disease (AD) patients. Correlation of DTI measured parameters with results of several neuropsychological tests will be reported here. Several issues related to quantitation of DTI parameters in ROI analysis are addressed. In spite of only a small number of subjects were studied so far, we found not only that AD patients showed significant decrease of white matter (WM) integrity in corpus callosum (CC), most prominent at the posterior portion, but also found significant correlations between the DTI parameters and scores from several neuropsychological tests. Our preliminary results suggest that DTI help to improve the overall accuracy rate in distinguishing between early AD onset and age-related functional decline, and potentially may improve efficiency in differentiating between different types of dementia.
In this paper, we demonstrate a technique for modeling liver motion during the respiratory cycle using intensity-based free-form deformation registration of gated MR images. We acquired 3D MR image sets (multislice 2D) of the abdomen of four volunteers at end-inhalation, end-exhalation, and eight time points in between using respiratory gating. We computed the deformation field between the images using intensity-based rigid and non-rigid registration algorithms. The non-rigid transformation is a free-form deformation with B-spline interpolation between uniformly-spaced control points. The transformations between inhalation and exhalation were visually inspected. Much of the liver motion is cranial-caudal translation, and thus the rigid transformation captures much of the motion. However, there is still substantial residual deformation of up to 2 cm. The free-form deformation produces a motion field that appears on visual inspection to be accurate. This is true for the liver surface, internal liver structures such as the vascular tree, and the external skin surface. We conclude that abdominal organ motion due to respiration can be satisfactorily modeled using an intensity-based non-rigid 4D image registration approach. This allows for an easier and potentially more accurate and patient-specific deformation field computation than physics-based models using assumed tissue properties and acting forces.
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