Vascular surgeons take decisions on the revascularization technics when surgery is needed for patients with Lower Extremities Arterial Disease (LEAD). This decision requires experience, good knowledge of official recommandations and new technics and an exhaustive description of the patient status. The Case Based Reasoning (CBR) is a good candidate to clinical decision support. To assess its applicability to LEAD, this study proposes a numerical modelization of patient data in this context, application of hierarchical and heterogenous similarity measures on retrospective data. We showed that similar pathological contexts of patients induce similar revascularization technics, which confirms CBR is usable for our purpose. These experiments need to be reproduced in the future to confirm these results on prospective data.