Computational modelling is a powerful tool to identify stresses in diseased arteries and predict which artery or plaque is at immediate or future risk of a cardiovascular event. In this thesis, new methodologies have been developed to further improve computational modelling in diseased arteries. These new methodologies enabled wall stress analysis in AAA geometries obtained via 3D-US and in plaque geometries obtained via combined OCT and IVUS imaging. Further, multidirectional shear stress parameters proved to be importantly affecting plaque composition. Moreover, shear stress in combination with NIRS positive regions produced promising results for predicting plaque progression and composition changes. Therefore, multidirectional shear stress, perhaps in combination with NIRS, could be used as a potential risk factor for plaque progression and changes in plaque composition. Before these factors can be clinically employed, future research should further elucidate the clinical value of shear stress and wall stress as a predictor of changes in disease stage and cardiovascular events.

Additional Metadata
Keywords Biomechanics, computational modeling, fluid mechanics, solid mechanics, shear stress, wall stress, atherosclerosis, helical flow, multidirectional shear stress, abdomical aortic aneurysm, near infrared spectroscopy, optical coherence tomography, intravascular ultrasound
Promotor A.F.W. van der Steen (Ton) , J.J. Wentzel (Jolanda)
Publisher Erasmus University Rotterdam
ISBN 978-94-028-1529-0
Persistent URL
Kok, A.M. (2019, June 19). Computational Biomechanics of Diseased Arteries. Erasmus University Rotterdam. Retrieved from