## 1 Introduction  
Cardiovascular diseases (CVDs) are the leading cause of death in Europe [1]. Fast and appropriate intervention in various CVDs, such as ischemic strokes, is essential for successful treatment [2]. Angiography is an important diagnostic as well as therapeutic procedure in the endovascular treatment of CVDs. It is essential for the visualization of the vascular system, the identification of pathologies, and the utilization of medical devices using ionizing radiation and contrast agents [3]. The associated radiological techniques, such as digital subtraction angiography (DSA) and roadmap (RM) fluoroscopy, along with medical device control, including the use of stent retrievers, coils, or flow diverters, are complex and require extensive training for neurointerventionalists to acquire the necessary skills [4, 5]. While angiography procedures are generally safe, with only 3.3% of patientsexperiencing minor complications such as transient neurological symptoms [6], their complexity underscores the need for thorough training. Moreover, in cases of ischemic stroke, time to reperfusion is critical, as shorter times have been associated with significantly better clinical outcomes, including reduced mortality and improved functional independence [7].  
Despite its benefits in disease management, occupational ionizing radiation exposure poses risks to medical staff and should be minimized as much as possible [8; 9; 10].  
To minimize these risks and reduce costs, particularly during neurointerventional training, training methods such as computer simulators, vascular silicone simulators, or in vivo models are used. These methods allow for the simulation of basic angiographic procedures such as aneurysm coiling, thrombectomy, or diagnostic DSA, as well as the generation and application of RM [5; 11]. However, the realism of the simulation remains a major challenge, especially in the visualizing representation of silicone simulators outside an angiography room and the performance of procedures such as DSA and RM.  
In this study, we developed and tested the neurointerventional training environment AngioSim (Angiography Simulator) that can simulate angiographic procedures like DSA and RM without the need for ionizing radiation, making handling and visual simulation more realistic. By integrating augmented reality, AngioSim enhances neurointerventional training, reduces the need for radiation exposure for trainees, and provides a cost-effective method while maintaining the characteristics of vascular silicone simulators. Neuroradiologists who participated in an internal neurointerventional training with different simulators were asked to evaluate their experience with AngioSim. Our goal was also to assess the value of AngioSim for neurointerventional training. We hypothesized that AngioSim would offer significant benefits over other simulators, especially over silicone models lacking the simulation of the visual experience through augmented reality.  
This study makes several key contributions. First, we introduce AngioSim, a novel angiography simulation system that integrates augmented reality with a vascular silicone model to realistically simulate fluoroscopy, RM, and DSA without the use of ionizing radiation. We also present a cost-efficient and modular hardware setup based on widely available components, which allows for straightforward implementation in training environments. Furthermore, we evaluate AngioSim's realism, usefulness, and acceptance using feedback from 24 physicians and apply McNemar tests to identify statistically significant differences compared to other training systems. Lastly, we provide open access to the simulator's design and a detailed component list to support transparency, replication, and scalability in medical education.