Rheumatoid arthritis (RA) is an autoimmune disease in which chronic inflammation of the synovial joints can lead to destruction of cartilage and bone. Pre-clinical studies attempt to uncover the underlying causes by emulating the disease in genetically different mouse strains and characterising the nature and severity of bone shape changes as indicators of pathology. This paper presents a fully automated method for obtaining quantitative measurements of bone destruction from volumetric micro-CT images of a mouse hind paw. A statistical model of normal bone morphology derived from a training set of healthy examples serves as a template against which a given pathological sample is compared. Abnormalities in bone shapes are identified as deviations from the model statistics, characterised in terms of type (erosion / formation) and quantified in terms of severity (percentage affected bone area). The colour-coded magnitudes of the deviations superimposed on a three-dimensional rendering of the paw show at a glance the severity of malformations for the individual bones and joints. With quantitative data it is possible to derive population statistics characterising differences in bone malformations for different mouse strains and in different anatomical regions. The method was applied to data acquired from three different mouse strains. The derived quantitative indicators of bone destruction have shown agreement both with the subjective visual scores and with the previous biological findings. This suggests that pathological bone shape changes can be usefully and objectively identified as deviations from the model statistics.