Path tracking control of a steerable catheter in transcatheter cardiology interventions.

Xiu Zhang, Aditya Sridhar,Xuan Thao Ha, Syed Zain Mehdi,Andrea Fortuna, Mattia Magro, Angela Peloso, Anna Bicchi,Mouloud Ourak,Andrea Aliverti,Emiliano Votta,Emmanuel Vander Poorten,Elena De Momi

International journal of computer assisted radiology and surgery(2024)

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摘要
PURPOSE:Intracardiac transcatheter interventions allow for reducing trauma and hospitalization stays as compared to standard surgery. In the treatment of mitral regurgitation, the most widely adopted transcatheter approach consists in deploying a clip on the mitral valve leaflets by means of a catheter that is run through veins from a peripheral access to the left atrium. However, precise manipulation of the catheter from outside the body while copying with the path constraints imposed by the vessels remains challenging. METHODS:We proposed a path tracking control framework that provides adequate motion commands to the robotic steerable catheter for autonomous navigation through vascular lumens. The proposed work implements a catheter kinematic model featuring nonholonomic constraints. Relying on the real-time measurements from an electromagnetic sensor and a fiber Bragg grating sensor, a two-level feedback controller was designed to control the catheter. RESULTS:The proposed method was tested in a patient-specific vessel phantom. A median position error between the center line of the vessel and the catheter tip trajectory was found to be below 2 mm, with a maximum error below 3 mm. Statistical testing confirmed that the performance of the proposed method exhibited no significant difference in both free space and the contact region. CONCLUSION:The preliminary in vitro studies presented in this paper showed promising accuracy in navigating the catheter within the vessel. The proposed approach enables autonomous control of a steerable catheter for transcatheter cardiology interventions without the request of calibrating the intuitive parameters or acquiring a training dataset.
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