Person:

Perrin, Douglas

The manipulation of fast moving, delicate tissues in beating heart procedures presents a considerable challenge to the surgeon. A robotic force tracking system can assist the surgeon by applying precise contact forces to the beating heart during surgical manipulation. Standard force control approaches cannot safely attain the required bandwidth for this application due to vibratory modes within the robot structure. These vibrations are a limitation even for single degree of freedom systems driving long surgical instruments. These bandwidth limitations can be overcome by incorporating feed-forward motion terms in the control law. For intracardiac procedures, the required motion estimates can be derived from 3D ultrasound imaging. Dynamic analysis shows that a force controller with feed-forward motion terms can provide safe and accurate force tracking for contact with structures within the beating heart. In vivo validation confirms that this approach confers a 50% reduction in force fluctuations when compared to a standard force controller and a 75% reduction in fluctuations when compared to manual attempts to maintain the same force.

The manipulation of fast moving, delicate tissues in beating heart procedures presents a considerable challenge to surgeons. We present a new robotic force stabilization system that assists surgeons by maintaining a constant contact force with the beating heart. The system incorporates a novel, miniature uniaxial force sensor that is mounted to surgical instrumentation to measure contact forces during surgical manipulation. Using this sensor in conjunction with real-time tissue motion information derived from 3D ultrasound, we show that a force controller with feed-forward motion terms can provide safe and accurate force stabilization in an in vivo contact task against the beating mitral valve annulus. This confers a 50% reduction in force fluctuations when compared to a standard force controller and a 75% reduction in fluctuations when compared to manual attempts to maintain the same force.

Surgical repair of the mitral valve results in better outcomes than valve replacement, yet diseased valves are often replaced due to the technical difficulty of the repair process. A surgical planning system based on patient-specific medical images that allows surgeons to simulate and compare potential repair strategies could greatly improve surgical outcomes. The system must simulate valve closure quickly and handle the complex boundary conditions imposed by the chords that tether the valve leaflets. We have developed a process for generating a triangulated mesh of the valve surface from volumetric image data of the opened valve. The closed position of the mesh is then computed using a mass-spring model of dynamics. In the mass-spring model, triangle sides are treated as linear springs supporting only tension. Chords are also treated as linear springs, and self-collisions are detected and handled inelastically. The equations of motion are solved using implicit numerical integration. The simulated closed state is compared with an image of the same valve taken in the closed state to assess accuracy of the model. The model exhibits rapid valve closure and is able to predict the closed state of the valve with reasonable accuracy.

An accurate and reproducible segmentation of the mitral valve annulus from 3D ultrasound is useful to clinicians and researchers in applications such as pathology diagnosis and mitral valve modeling. Current segmentation methods, however, are based on 2D information, resulting in inaccuracies and a lack of spatial coherence. We present a segmentation algorithm which, given a single user-specified point near the center of the valve, uses maxflow and active contour methods to delineate the annulus geometry in 3D. Preliminary comparisons to manual segmentations and a sensitivity study show the algorithm is both accurate and robust.