The Use of Simulation and Deep Learning Models in the Endovascular Treatment of Ruptured Intracranial Aneurysms: A Case Report

Abstract Introduction The current paper presents an examination of the emerging role deep learning-based simulation software in enhancing preprocedural planning for intracranial aneurysm treatment using flow diverters. Intracranial aneurysms pose significant risk due to their potential rupture leading life-threatening subarachnoid hemorrhage. Innovative endovascular options like diverters, which redirect blood and promote healing, are gaining attention. optimizing these procedures is becoming increasingly crucial. Case presentation This study involves a 47-year-old female patient diagnosed with aneurysm. Through diagnostic angiography 3D rotational imaging, complex anatomy was determined need diverter placement ascertained. Sim&Size™ used simulate size diverter, based on patient’s specific vascular anatomy. procedure, including as per simulation, successful. Conclusion significantly contributes enhancement planning. By providing patient-specific simulations, it improves procedural precision reduces complications, thus potentially outcomes. However, quality contingent accuracy input data, does not account physiological dynamics. Despite limitations, this tool represents promising development neurointerventional practice.