Enhanced brain arteries and aneurysms analysis using a CAE-CFD approach

Brain aneurysms, also known as cerebral aneurysms or intracranial aneurysms, affect approximately 3.2% of the global population and are responsible for nearly 500,000 deaths annually. Remarkably, half of these fatalities occur in individuals under the age of 50, with women at higher risk than men (3:2 ratio). Neurologists, neuroradiologists, and neurosurgeons are therefore exploring ways to minimize potentially fatal outcomes. One tool used to detect these aneurysms is magnetic resonance angiography (MRA). Yet, misdiagnosis or suboptimal treatment occurs in up to one-quarter of patients upon initial medical consultation. Hence, it is essential to develop better approaches that enable doctors to detect brain aneurysms from MRA images. We propose a novel approach using a computer-aided engineering (CAE) process to analyze the aneurysm and surrounding arterial structures. In this CAE process, 2D or 3D MRA images were converted to computer-aided design (CAD) models that facilitate analysis of blood flow patterns using computational fluid dynamics (CFD). The CFD simulations computed hemodynamic parameters such as wall shear stress (WSS), velocity vectors representing blood flow direction and speed, and particle tracking to visualize blood flow patterns, which are crucial for assessing rupture risk. This innovative modeling and simulation approach improved our ability to predict aneurysm behavior, increasing risk assessment accuracy and potentially supporting better surgical planning. Our preliminary research indicates that this methodology may assist as a simulation tool to explore treatment decisions. Clinical testing may lead to advanced neurosurgical diagnostics and might eventually pave the way for more effective personalized treatment strategies for brain aneurysms.