Feature identification for image-guided transcatheter aortic valve implantation

Pencilla Lang; Martin Rajchl; A. Jonathan McLeod; Michael W. Chu; Terry M. Peters

doi:10.1117/12.911562

17 February 2012 Feature identification for image-guided transcatheter aortic valve implantation

Pencilla Lang, Martin Rajchl, A. Jonathan McLeod, Michael W. Chu, Terry M. Peters

Proceedings Volume 8316, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling; 83162X (2012) https://doi.org/10.1117/12.911562
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

Transcatheter aortic valve implantation (TAVI) is a less invasive alternative to open-heart surgery, and is critically dependent on imaging for accurate placement of the new valve. Augmented image-guidance for TAVI can be provided by registering together intra-operative transesophageal echo (TEE) ultrasound and a model derived from pre-operative CT. Automatic contour delineation on TEE images of the aortic root is required for real-time registration. This study develops an algorithm to automatically extract contours on simultaneous cross-plane short-axis and long-axis (XPlane) TEE views, and register these features to a 3D pre-operative model. A continuous max-flow approach is used to segment the aortic root, followed by analysis of curvature to select appropriate contours for use in registration. Results demonstrate a mean contour boundary distance error of 1.3 and 2.8mm for the short and long-axis views respectively, and a mean target registration error of 5.9mm. Real-time image guidance has the potential to increase accuracy and reduce complications in TAVI.

Citation Download Citation

Pencilla Lang, Martin Rajchl, A. Jonathan McLeod, Michael W. Chu, and Terry M. Peters "Feature identification for image-guided transcatheter aortic valve implantation", Proc. SPIE 8316, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling, 83162X (17 February 2012); https://doi.org/10.1117/12.911562

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