(untitled) (Transactions on Additive Manufacturing Meets Medicine, 2024)
Neurovascular conditions such as acute ischemic stroke and intracranial aneurysm necessitate complex neurointerventional procedures, posing significant risks including subarachnoid hemorrhage (SAH). Effective training is critical for minimizing these risks, yet current simulation models lack realistic, animal-free training options for managing complications like SAH. This paper aims to develop and integrate a vessel rupture model into the Hamburg Anatomical Neurointerventional Simulator (HANNES), enhancing training for intraoperative complication management. The rupture model was designed by incorporating requirements from both engineers and medical professionals. Key features include modular integration into HANNES, reusability, and adjustable bleeding rates controlled by the training supervisor. The model simulates the perivascular spread of contrast agent, with a point-specific origin and diffuse contour, ensuring realistic SAH visualization on digital subtraction angiography (DSA). The additively manufactured model includes a sponge-filled subarachnoid space and a valve for activating or deactivating the simulated hemorrhage. Evaluations by experienced neuroradiologists demonstrated effective control and realistic appearance of the simulated bleeding, giving the model an overall Likert scale rating of 3.7 out of 5. Identified optimization potentials included the distal bleeding position, while the realistic extravasation of contrast agent was positively noted. The rupture model successfully meets the defined requirements, offering a practical tool for training in the management of neurointerventional complications. Future improvements will address the distal position of the hemorrhage to further optimize the effectiveness of the training, ultimately enhancing the preparedness of neurointerventionists in handling SAH.