Application of Augmented Reality in Robot-Assisted Mitral Valve Repair Surgery
A Feasibility Study
Jette J. Peek (Erasmus MC)
Klaus Hildebrandt (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Xucong Zhang (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Rohit K. Kharbanda (Dutch Institute for Heart and Lung Surgery, Leiden University Medical Center)
Maurice A.P. Oudeman (Dutch Institute for Heart and Lung Surgery, Amsterdam UMC)
Robert J.M. Klautz (Dutch Institute for Heart and Lung Surgery, Leiden University Medical Center)
Meindert Palmen (Dutch Institute for Heart and Lung Surgery, Leiden University Medical Center)
Edris A.F. Mahtab (Dutch Institute for Heart and Lung Surgery, Leiden University Medical Center)
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Abstract
Objective:
In mitral valve surgery, it is important to be aware of adjacent intraoperatively invisible anatomy, to avoid complications and enhance safety. In this feasibility study, we aimed to develop semi-automated intraoperative 3-dimensional (3D) augmented reality (3D-AR) overlays for robotic mitral valve repair.
Methods:
In 5 patients undergoing robot-assisted mitral valve repair, a 3D point cloud was generated, using intraoperatively recorded images from both eyes of the stereoscopic da Vinci camera (Intuitive Surgical, Sunnyvale, CA, USA). An intraoperative 3D-AR overlay was created using a scale-adaptive iterative closest point algorithm and landmarks placed on the mitral valve annulus. Finally, important anatomical structures such as the circumflex artery, Koch’s triangle, and aortic valve leaflets could be visualized as a 3D-AR overlay on top of the surgical vision. To evaluate the accuracy, these 3D point clouds were validated by calculating the 3D point cloud accuracy and landmark registration error (LRE).
Results:
The 3D point clouds and 3D-AR overlays were successfully created for all 5 patients. The 3D point clouds were accurate, with a median error of −0.92 mm, and the LRE was 5.12 mm. The time for creating the 3D-AR overlay was approximately 5 min. Besides creating the 3D-AR overlays, we could visualize the models directly within the robotic console during the surgical procedure.
Conclusions:
We present an algorithm for generating accurate semiautomatic 3D-AR overlays, visualizing essential anatomical structures during robot-assisted mitral valve repair. This may lead to automated intraoperative 3D-AR vision during robotic cardiac surgery, with the potential of increasing safety, accuracy, and efficiency.
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