Alternative Titleロボット補助カテーテル低侵襲手術を支援する新型VRトレーニングシステムに関する研究
Note (General)Cardiovascular diseases are the leading cause of death worldwide except Africa. Vascular interventional surgeries (VIS) have become common alternatives because it has some advantages such as short recovery time, a small incision to the healthy tissue and little postoperative pain. However, prolonged exposure to X‐ray radiation during surgery will cause a serious impact for the surgeons' health. The endovascular robotic systems have been developed to release surgeon from the risks of radiation and heavy radiation‐shielded garments. This system allows surgeons to manipulate catheter via master side over long distance. Compared with traditional VIS, robot‐assisted interventional surgery requires surgeons to be highly skilled at manipulating vascular interventional surgical robot, and the use of robots for surgery has changed surgeons' surgical habits. Surgeons need to be trained at endovascular robotic system to adapt to robot‐assisted interventional surgery.
Traditional training methods, including using live animals, human cadavers and vascular phantom, have many limitations such as expensive, risky and limited morphological models. Virtual reality (VR) interventional training systems for robot‐assisted interventional surgical training have many advantages over traditional training methods. Computer‐based simulation of catheterization procedures provides a versatile solution and can virtually be reused infinite times on both common and rare cases. Moreover, patient‐specific data can be quickly adopted to regenerate the virtual environment, which provides tools for surgeons to plan or rehearse preoperatively to evaluate and optimize the tentative surgical procedure. However, the interventional simulation is still not realistic enough compared with traditional training methods.
In this thesis, we developed a novel virtual reality interventional training system for robot‐assisted interventional surgery. This system includes two parts: the master side and the VR simulator. For master side, we developed a novel haptic force interface to realize haptic feedback. Moreover, a collision protection function with a proximal‐force‐based collision detection algorithm was proposed to improve surgical safety. In case of no collision, transparency of the teleoperated system is realized; in case of collision, the provided haptic force will be amplified. For VR simulator, we proposed a novel method to solve catheterization modeling during the interventional simulation. Our method discretizes the catheter by the collision points. The catheter between two adjacent collision points is treated as thin torsion‐free elastic rods. The deformation of the rod is mainly affected by the force applied at the collision points. Meanwhile, the virtual contact force is determined by the collision points. This simplification makes the model more stable and reduces the computational complexity, and the behavior of the surgical tools can be approximated. Therefore, we realized the catheter interaction simulation and virtual force feedback for the proposed VR interventional training system.
From the experimental studies, the haptic force interface can provide precise force to the operator, and the motion accuracy is enough for the robot‐assisted interventional surgery. The proposed collision detection algorithm can detect the collision in different surgical stages. The proposed method for simulating catheter interaction is enough to achieve satisfactory outcomes and the average running time for solving the deformation between two collision points satisfies the requirement of interventional simulation. The developed VR interventional training system has potential to be used in robot‐assisted interventional surgical training.
Collection (particular)国立国会図書館デジタルコレクション > デジタル化資料 > 博士論文
Date Accepted (W3CDTF)2022-06-05T18:01:14+09:00
Data Provider (Database)国立国会図書館 : 国立国会図書館デジタルコレクション