Affiliation:
1. Department of Applied Mechanics and Biomedical Engineering, Indian Institute of Technology Madras 1 , Chennai 600036, India
2. Department of Neurosurgery, Sree Chitra Tirunal Institute for Medical Sciences and Technology 2 , Thiruvananthapuram 695011, India
3. Department of Imaging Sciences and Interventional Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology 3 , Thiruvananthapuram 695011, India
Abstract
Cerebral aneurysms are the bulges in arteries that have the potential to rupture, as thin-walled regions of an aneurysm are more vulnerable. Understanding the correlation between the wall thickness and the corresponding wall stresses can facilitate better prediction using fluid–structure interaction tools. However, obtaining the actual in vivo wall thickness variation of the aneurysm dome and neck is vital for an accurate prediction of wall stresses. Invasive methods of obtaining wall thickness variation of an abnormal artery may further aggravate the rupture risk of these aneurysms. Modeling aneurysmal wall thickness reconstruction, closer to the in vivo conditions from the histopathological slices, is an apt approach to follow. To this end, the present study performs a comparative assessment of uniform, variable, and patient-specific wall thickness on the hemodynamic and biomechanical wall stresses. Simulations show that maximum wall stresses for the uniform, variable, and patient-specific wall thickness are 13.6, 27.6, and 48.4 kPa, respectively. The maximum wall displacements for the uniform, variable, and patient-specific wall thickness were observed to be 58.5, 126, and 162 μm, respectively. It is observed that the uniform wall thickness model is conservative and underestimates the risk in the prediction of biomechanical stresses and wall displacements. Thinner wall regions experience higher stress for the same internal pressure than thicker wall regions, indicating regions that are more susceptible to rupture. The generation of a variable wall thickness model was observed to be an apt approach, as patient-specific wall thickness information can only be retrospective in the current scientific scenario.
Funder
Science Engineering Research Board, DST, Government of India
National Supercomputing Mission, Government of India