Cardiovascular diseases are the leading causes of death worldwide and improved diagnostic methods are needed for early intervention and to select the most suitable treatment for patients. Currently, carotid artery plaque vulnerability is typically determined by visually assessing ultrasound B-mode images, which is influenced by user-subjectivity. Since plaque vulnerability is correlated to the mechanical properties of the plaque, quantitative techniques are needed to estimate plaque stiffness as a surrogate for plaque vulnerability, which would reduce subjectivity during plaque assessment. The work in this thesis focused on three noninvasive ultrasound-based techniques to quantitatively assess plaque vulnerability and measure arterial stiffness. In Study I, a speckle tracking algorithm was validated in vitro to assess strain in common carotid artery (CCA) phantom plaques and thereafter applied in vivo to carotid atherosclerotic plaques where the strain results were compared to visual assessments by experienced physicians. In Study II, hard and soft CCA phantom plaques were characterized with shear wave elastography (SWE) by using phase and group velocity analysis while being hydrostatically pressurized followed by validating the results with mechanical tensile testing. In Study III, feasibility of assessing the stiffness of simulated plaques and the arterial wall with SWE was demonstrated in an ex vivo setup in small porcine aortas used as a human CCA model. In Study IV, SWE and pulse wave imaging (PWI) were compared when characterizing homogeneous CCA soft phantom plaques. The techniques developed in this thesis have demonstrated potential to characterize carotid artery plaques. The results show that the techniques have the ability to noninvasively evaluate the mechanical properties of carotid artery plaques, provide additional data when visually assessing B-mode images, and potentially provide improved diagnoses for patients suffering from cerebrovascular diseases. / <p>Doctoral thesis in medical technology and medical sciences</p><p>QC 20160921</p>