Hybrid echo and X-ray image guidance for cardiac catheterization procedures by using a robotic arm: A feasibility study

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Ma, YingLiang ORCID: https://orcid.org/0000-0001-5770-5843, Penney, Graeme P., Bos, Dennis, Frissen, Peter, Rinaldi, C. Aldo, Razavi, Reza and Rhode, Kawal S. (2010) Hybrid echo and X-ray image guidance for cardiac catheterization procedures by using a robotic arm: A feasibility study. Physics in Medicine and Biology, 55 (13). ISSN 0031-9155

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Abstract

We present a feasibility study on hybrid echocardiography (echo) and x-ray image guidance for cardiac catheterization procedures. A self-tracked, remotely operated robotic arm with haptic feedback was developed that attached to a standard x-ray table. This was used to safely manipulate a three-dimensional (3D) trans-thoracic echo probe during simultaneous x-ray fluoroscopy and echo acquisitions. By a combination of calibration and tracking of the echo and x-ray systems, it was possible to register the 3D echo images with the 2D x-ray images. Visualization of the combined data was achieved by either overlaying triangulated surfaces extracted from segmented echo data onto the x-ray images or by overlaying volume rendered 3D echo data. Furthermore, in order to overcome the limited field of view of the echo probe, it was possible to create extended field of view (EFOV) 3D echo images by co-registering multiple tracked echo data to generate larger roadmaps for procedure guidance. The registration method was validated using a cross-wire phantom and showed a 2D target registration error of 3.5 mm. The clinical feasibility of the method was demonstrated during two clinical cases for patients undergoing cardiac pacing studies. The EFOV technique was demonstrated using two healthy volunteers.

Item Type: Article
Faculty \ School: Faculty of Science > School of Computing Sciences
UEA Research Groups: Faculty of Science > Research Groups > Norwich Epidemiology Centre
Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre
Faculty of Science > Research Groups > Data Science and AI
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Depositing User: LivePure Connector
Date Deposited: 05 Jan 2023 11:30
Last Modified: 10 Dec 2024 01:41
URI: https://ueaeprints.uea.ac.uk/id/eprint/90413
DOI: 10.1088/0031-9155/55/13/N01

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