A cerebral aneurysm is a dilation of a blood vessel that compromises the integrity of the vessel wall, often times leading to rupture. It is estimated that 1 in 50 people are living with an unruptured cerebral aneurysm. The rupture of a cerebral aneurysm leads to a Subarachnoid Hemorrhage (SAH), a medical emergency with a 45% mortality rate within the initial 30 days following rupture. In the United States, 14,000 people die from a SAH each year. Currently there are two methods for treating cerebral aneurysms: surgical and endovascular. Surgical clipping is the placement of a metallic clip across the aneurysm, secluding the aneurysm from blood flow. Endovascular treatments encompass the use of embolic coils or stents. Over the past decade, endovascular treatments have become the standard of care for cerebral aneurysms and clinical studies have demonstrated the advantages of endovascular treatments over classical surgical methods. Nevertheless, fluid dynamic outcomes of treatment are poorly understood and there are limited quantitative methods for measuring the efficacy of endovascular devices.
The objective of this study was to develop a new, cost effective method for creating accurate, transparent, scale models of cerebral aneurysms derived from real anatomical data. The cerebral aneurysm models are created with an interdisciplinary approach that repurposes traditional and modern modeling techniques typically used by artists. The intended model, while using artistic techniques and materials, would need to meet the rigorous requirements of Particle Image Velocimetry [PIV] (optically transparent, low refractive index – 1.465, and non-reactive to the experimentation laser) as well as achieve high accuracy from anatomical data.
We have working pipeline for the creation of the anatomically-accurate models. The models have shown to have no appreciable volumetric differences from computation models; more studies will be needed to verify any appreciable deformities. Current experimentations are testing the limits regarding size as well as tortuosity of anatomical models.