Imitation Learning for Path Planning in Cardiac Percutaneous Interventions.

Objective: Mitral regurgitation is a valvular heart disease particularly affecting the aging population. Minimally invasive transcatheter procedures offer benefits over traditional open-chest surgery but require significant operator skill and hand-eye coordination, making the learning curve steeper and limiting accessibility. To address these challenges, there is growing research interest in automating these procedures, making it crucial to define safe navigable routes within anatomical structures for robotic operation.

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

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.