RESUMO
The existing literature on the magnetic resonance imaging of murine models of Alzheimer's disease is reviewed. Particular attention is paid to the possibilities for the early detection of the disease. To this effect, not only are relaxometric and volumetric approaches discussed, but also mathematical models for plaque distribution and aggregation. Image analysis plays a prominent role in this line of research, as stochastic image models and texture analysis have shown some success in the classification of subjects affected by Alzheimer's disease. It is concluded that relaxometric approaches seem to be a promising candidate for the task at hand, especially when combined with sophisticated image analysis, and when data from more than one time-point is available. There have been few longitudinal studies of mice models so far, so this direction of research warrants future efforts.
