Modeling of aneurysm progression in anterior cerebral arteries to estimate rupture risk: A computational study

Abstract

A cerebral aneurysm is a medical disorder that occurs when the wall of the cerebral artery ruptures as a result of abnormally high blood pressure. The imaging techniques that are now in use, such as CT and MRI scans, can only show the geometrical information about an aneurysm and cannot determine the risk of rupture that relates to the progression of an aneurysm. In this work, computational modeling was performed to simulate aneurysm progression and to analyze the stress development for a variety of different pressure loading conditions. Image segmentation was utilized to segment one anterior cerebral artery and one anterior communicating artery, both of which were rebuilt to generate aneurysm models at susceptible locations of the aneurysm progression simulation. To represent the various phases of aneurysm development, five different aneurysm sizes with two varying wall thicknesses were identified. The diastolic pressure, the systolic pressure, and the hypertensive pressure were applied to simulate the actual pressure conditions for the anterior cerebral arteries. The rupture risk was determined by analyzing the stress distributions across all of the models. It was estimated that the stresses around the walls of aneurysm varies with an incremental change in both the diameter of the aneurysm and the magnitude of the blood pressure. Aneurysms that were observed to have significant rupture risks were those that had a large diameter and a thin wall and were simulated at high blood pressures. The findings of this research are anticipated to assist medical practitioners in estimating rupture risks with known imaging, based on the diameters of aneurysms, and in early decision making for the treatment of aneurysms.