A Replaceable Vascular Model-based Platform for Experience Acquisition in Interventional Surgery

Vascular interventional surgery has been gradually conducted to cure cerebrovascular diseases due to its advantages of smaller incisions and quicker recovery. However, due to the small size and fragile properties of vasculars in human brain, iatrogenic and interventional vascular damages could occur during the surgery. Thus, the operation experience of clinicians is very important. However, for inexperienced novice surgeons, the costs of training surgical experience are high. In order to solve the problems mentioned above, this paper attempts to design an experience acquisition platform for vascular interventional surgery. First, a simple model of vascular was made with wax plates. Then, guidewire transport was carried out in the vascular model through the existing operating platform to simulate the interventional surgery experiment. We use Python to write the Graphical User Interface (GUI) to design the visual operating platform, and import the simulated interventional surgery video into the interface. These operations were carried out based on the model of the patient's real vascular shape, and the frames with dangerous actions in the video were marked and counted, so that the surgeons could analyse the dangerous operation after the operation and improve the operation. From the experimental results, the experience acquisition platform has the ability to mark the dangerous operation of surgeons during surgery. Also, it can provide a low-cost method for the training of novice surgeons.