In western countries, cardiovascular disease is the most common cause of death, often related to atherosclerosis which can cause narrowing, rupture or erosion of the arterial wall, and eventually reduction or complete blockage of the blood flow. Nowadays, imaging modalities (MRI, IVUS) have the ability to identify morphological characteristics of rupture-prone plaques. Additionally, recent advances in stent technology (drug elution) have improved the outcome of angioplasty. However, reliable vulnerability analyses require additional information on the mechanical stresses occurring in the lesions structural components. There is also a pressing need to deeper and better understand the mechanical characteristics of the transient expansion of balloon-expandable stent systems inside the arterial wall in order to improve the clinical protocols and decrease in-stent restenosis rates. This thesis presents a computational methodology, able to accurately (i) analyze the mechanical environment of atherosclerotic lesions and consequently identify high-risk plaques, and (ii) simulate the mechanical aspects of angioplasty interventions and study the outcome of different stent designs. In particular, the thesis considers patient-specific models of human stenotic lesions. This is accomplished by means of MRI, automatic segmentation algorithms and NURBS modeling. The inhomogeneity of the plaque is regarded, and the adopted constitutive models account for the nonlinear, anisotropic, incompressible behavior of the arterial constituents. To avoid stability problems during the interaction between the arterial wall and the medical devices, surface smoothing techniques are employed. In order to assess the vulnerability risk of lesions or the performance of stent geometries, novel scalar indices are introduced, linked to mechanical measures such as stress changes. The proposed morpho-mechanical approaches are able to investigate quantitatively the biomechanical behavior of atherosclerotic plaques and to provide clear markers for the patient-specific choice of the optimal stent configuration.