Background: Carotid atherosclerosis is one of the main underlying inducements of stroke, which is a leading cause of disability. The morphological feature and biomechanical environment have been found to play… Click to show full abstract
Background: Carotid atherosclerosis is one of the main underlying inducements of stroke, which is a leading cause of disability. The morphological feature and biomechanical environment have been found to play important roles in atherosclerotic plaque progression. However, the biomechanics in each patient’s blood vessel is complicated and unique. Method: To analyse the biomechanical risk of the patient-specific carotid stenosis, this study used the fluid-structure interaction (FSI) computational biomechanical model. This model coupled both structural and hemodynamic analysis. Two patients with carotid stenosis planned for carotid endarterectomy were included in this study. The 3D models of carotid bifurcation were reconstructed using our in-house-developed protocol based on multisequence magnetic resonance imaging (MRI) data. Patient-specific flow and pressure waveforms were used in the computational analysis. Multiple biomechanical risk factors including structural and hemodynamic stresses were employed in post-processing to assess the plaque vulnerability. Results: Significant difference in morphological and biomechanical conditions between 2 patients was observed. Patient I had a large lipid core and serve stenosis at carotid bulb. The stenosis changed the cross-sectional shape of the lumen. The blood flow pattern changed consequently and led to a complex biomechanical environment. The FSI results suggested a potential plaque progression may lead to a high-risk plaque, if no proper treatment was performed. The patient II had significant tandem stenosis at both common and internal carotid artery (CCA and ICA). From the results of biomechanical factors, both stenoses had a high potential of plaque progression. Especially for the plaque at ICA branch, the current 2 small plaques might further enlarge and merge as a large vulnerable plaque. The risk of plaque rupture would also increase. Conclusions: Computational biomechanical analysis is a useful tool to provide the biomechanical risk factors to help clinicians assess and predict the patient-specific plaque vulnerability. The FSI computational model coupling the structural and hemodynamic computational analysis, better replicates the in vivo biomechanical condition, which can provide multiple structural and flow-based risk factors to assess plaque vulnerability.
               
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