Endovascular ultrasound (US) elastography (EVE) was introduced to supplement endovascular US echograms in the assessment of vessel lesions and for endovascular therapy planning. Indeed, changes in the vascular tissue stiffness are characteristic of vessel wall pathologies and EVE appears as a very appropriate imaging technique to outline the elastic properties of vessel walls. Recently, a model-based approach was proposed to assess tissue motion in EVE. It specifically consists of a nonlinear minimization algorithm that was adapted to speckle motion estimation. Regarding the theoretical framework, such an approach considers the speckle as a material property; this assumption then led to the derivation of the optical flow equations, which were suitably combined with the Lagrangian speckle model estimator to provide the full 2-D polar strain tensor. In this study, the proposed algorithm was validated in vitro using a fresh excised human carotid artery. The experimental setup consisted of a cardiovascular imaging system (CVIS) US scanner, working with a 30-MHz mechanical rotating single-element transducer, a digital oscilloscope and a pressuring system. A sequence of radiofrequency (RF) images was collected while incrementally adjusting the intraluminal static pressure steps. The results showed the potential of this 2-D algorithm to characterize and to distinguish an atherosclerotic plaque from the normal vascular tissue. Namely, the geometry as well as some mechanical characteristics of the detected plaque were in good agreement with histology. The results also suggested that there might exist a range of intraluminal pressures for which plaque detectability is optimal.