Tensor based morphometry [1] was used to detect
statistically significant regions of neuroanatomical
change over time in a comparison between 36 probable
Alzheimer's Disease patients and 20 age- and sexmatched
controls. Baseline and twelve-month repeat
Magnetic Resonance images underwent tied spatial
normalisation [10] and longitudinal high-dimensional
warps were then estimated. Analyses involved univariate
and multivariate data derived from the longitudinal
deformation fields. The most prominent findings were
expansion of the fluid spaces, and contraction of the
hippocampus and temporal region. Multivariate measures
were notably more powerful, and have the potential to
identify patterns of morphometric difference that would
be overlooked by conventional mass-univariate analysis
