  In this article, we analyze the morphometry of hippocampus in subjects with
very mild dementia of Alzheimer's type (DAT) and nondemented controls and how
it changes over a two-year period. Morphometric differences with respect to a
template hippocampus were measured by the metric distance obtained from the
Large Deformation Diffeomorphic Metric Mapping (LDDMM) algorithm which was
previously used to calculate dense one-to-one correspondence vector fields
between the shapes. LDDMM assigns metric distances on the space of anatomical
images thereby allowing for the direct comparison and quantization of
morphometric changes. We use various statistical methods to compare the metric
distances in a cross-sectional and longitudinal manner. At baseline, the metric
distances for demented subjects are found not to be significantly different
from those for nondemented subjects. At follow-up, the metric distances for
demented subjects were significantly larger compared to nondemented subjects.
The metric distances for demented subjects increased significantly from
baseline to follow-up but not for nondemented subjects. We also use the metric
distances in logistic regression for diagnostic discrimination of subjects. We
compare metric distances with the volumes and obtain similar results. In
classification, the model that uses volume, metric distance, and volume loss
over time together performs better in detecting DAT. Thus, metric distances
with respect to a template computed via LDDMM can be a powerful tool in
detecting differences in shape in cross-sectional as well as longitudinal
studies.
