Deep vein thrombosis is a common disease with potentially serious outcomes, including death from pUlmonary embolism. One of the most widely used forms of prophylaxis is the compression stocking. However, the source of its beneficial effect is poorly understood, hindering improvements in design and application. In this study, a novel approach of subject specific computational modelling, based on magnetic resonance (MR) images, is used to quantify the effects of a grade 1 compression stocking on the venous system of the calf. The focus is the development of methodologies which allow the quantification of biomechar)ical parameters implicated in biological models of the disease. pathophysiology. MR images were acquired from the calves of eight healthy subjects, before and after application of the stocking. The geometry of major deep and superficial veins was then reconstructed in order to quantify the deformations induced by the stocking. Following this, computational fluid dynamics was used to determine the changes to haemodynaniic wall shear stress (WSS), based on observed changes to vessel geometry and sUbject specific velocity waveforms, acquired using Doppler ultrasound. It was found that the stocking was effective at raising WSS in both deep and superficialveins but the effect was more pronounced in the deep veins. Changes to the velocity waveforms due to stocking application were also obserVed which limited the time during which the veins experienced very low WSS. . 11\ finite element (FE) based non-rigid registration algorithm was then developed to calculate the stresses induced in the skeletal muscle by the stocking. The method was used to compare calculated values of hydrostatic pressure with the observed reduction in cross sectional area. The results suggest the method possesses some predictive ability but with low sensitivity. Finally the ability of a basic model of the vein wall to predict the observed deformations is examined.