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Duckett, Simon G., Ginks, Matthew R., Knowles, Benjamin R., Ma, Yingliang 
ORCID: https://orcid.org/0000-0001-5770-5843, Shetty, Anoop, Bostock, Julian, Cooklin, Michael, Gill, Jas S., Carr-White, Gerry S., Razavi, Reza, Schaeffter, Tobias, Rhode, Kawal S. and Rinaldi, C. Aldo
(2011)
Advanced image fusion to overlay coronary sinus anatomy with real-time fluoroscopy to facilitate left ventricular lead implantation in CRT.
Pacing and Clinical Electrophysiology, 34 (2).
pp. 226-234.
ISSN 0147-8389
Abstract
Background: Failure rate for left ventricular (LV) lead implantation in cardiac resynchronization therapy (CRT) is up to 12%. The use of segmentation tools, advanced image registration software, and high-fidelity images from computerized tomography (CT) and cardiac magnetic resonance (CMR) of the coronary sinus (CS) can guide LV lead implantation. We evaluated the feasibility of advanced image registration onto live fluoroscopic images to allow successful LV lead placement. Methods: Twelve patients (11 male, 59 ± 16.8 years) undergoing CRT had three-dimensional (3D) whole-heart imaging (six CT, six CMR). Eight patients had at least one previously failed LV lead implant. Using segmentation software, anatomical models of the cardiac chambers, CS, and its branches were overlaid onto the live fluoroscopy using a prototype version of the Philips EP Navigator software to guide lead implantation. Results: We achieved high-fidelity segmentations of cardiac chambers, coronary vein anatomy, and accurate registration between the 3D anatomical models and the live fluoroscopy in all 12 patients confirmed by balloon occlusion angiography. The CS was cannulated successfully in every patient and in 11, an LV lead was implanted successfully. (One patient had no acceptable lead values due to extensive myocardial scar.) Conclusion: Using overlaid 3D segmentations of the CS and cardiac chambers, it is feasible to guide CRT implantation in real time by fusing advanced imaging and fluoroscopy. This enabled successful CRT in a group of patients with previously failed implants. This technology has the potential to facilitate CRT and improve implant success.
| 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 |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 04 Jan 2023 17:34 |
| Last Modified: | 10 Dec 2024 01:41 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/90397 |
| DOI: | 10.1111/j.1540-8159.2010.02940.x |
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