Evaluation of a Desktop 3D Printed Rigid Refractive-Indexed-Matched Flow Phantom for PIV Measurements on Cerebral Aneurysms.

PURPOSE: Fabrication of a suitable flow model or phantom is critical to the study of biomedical fluid dynamics using optical flow visualization and measurement methods. The main difficulties arise from the optical properties of the model material, accuracy of the geometry and ease of fabrication. METHODS: Conventionally an investment casting method has been used, but recently advancements in additive manufacturing techniques such as 3D printing have allowed the flow model to be printed directly with minimal post-processing steps. This study presents results of an investigation into the feasibility of fabrication of such models suitable for particle image velocimetry (PIV) using a common 3D printing Stereolithography process and photopolymer resin. RESULTS: An idealised geometry of a cerebral aneurysm was printed to demonstrate its applicability for PIV experimentation. The material was shown to have a refractive index of 1.51, which can be refractive matched with a mixture of de-ionised water with ammonium thiocyanate (NH4SCN). The images were of a quality that after applying common PIV pre-processing techniques and a PIV cross-correlation algorithm, the results produced were consistent within the aneurysm when compared to previous studies. CONCLUSIONS: This study presents an alternative low-cost option for 3D printing of a flow phantom suitable for flow visualization simulations. The use of 3D printed flow phantoms reduces the complexity, time and effort required compared to conventional investment casting methods by removing the necessity of a multi-part process required with investment casting techniques.

Computational modelling of clot development in patient-specific cerebral aneurysm cases.

UNLABELLED: ESSENTIALS: Clotting in cerebral aneurysms is a process that can either stabilize the aneurysm or lead to rupture. A patient-specific computational model capable of predicting cerebral aneurysm thrombosis is presented. The different clotting outcomes highlight the importance of personalization of treatment. Once validated, the model can be used to tailor treatment and to clarify clotting processes in aneurysms. BACKGROUND: In cerebral aneurysms, clotting can either stabilize the aneurysm sac via aneurysm occlusion, or it can have a detrimental effect by giving rise to embolic occlusion. OBJECTIVE: The work presented in this study details the development of an in silico model that combines all the salient, clinically relevant features of cerebral aneurysm clotting. A comprehensive computational model of clotting that accounts for biochemical complexity coupled with three-dimensional hemodynamics in image-derived patient aneurysms and in the presence of virtually implanted interventional devices is presented. METHODS: The model is developed and presented in two stages. First, a two-dimensional computational model of clotting is presented for an idealized geometry. This enables verification of the methods with existing, physiological data before the pathological state is considered. This model is used to compare the results predicted by two different underlying biochemical cascades. The two-dimensional model is then extended to image-derived, three-dimensional aneurysmal topologies by incorporating level set methods, demonstrating the potential use of this model. RESULTS AND CONCLUSION: As a proof of concept, comparisons are then made between treated and untreated aneurysms. The prediction of different clotting outcomes for different patients demonstrates that with further development, refinement and validation, this methodology could be used for patient-specific interventional planning.