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Rhode, Kawal, Ma, YingLiang 
ORCID: https://orcid.org/0000-0001-5770-5843, Chandrasena, Angela, King, Andrew, Gao, Gang, Chinchapatnam, Phani, Sermesant, Maxime, Hawkes, David, Schaeffter, Tobias, Gill, Jaswinder and Razavi, Reza
(2008)
Evaluation of the use of multimodality skin markers for the registration of pre-procedure cardiac MR images and intra-procedure x-ray fluoroscopy images for image guided cardiac electrophysiology procedures.
In:
Progress in Biomedical Optics and Imaging - Proceedings of SPIE.
UNSPECIFIED.
ISBN 16057422
Abstract
This paper presents the evaluation of the use of multimodality skin markers for the registration of cardiac magnetic resonance (MR) image data to x-ray fluoroscopy data for the guidance of cardiac electrophysiology procedures. The approach was validated using a phantom study and 3 patients undergoing pulmonary vein (PV) isolation for the treatment of paroxysmal atrial fibrillation. In the patient study, skin markers were affixed to the patients' chest and used to register pre-procedure cardiac MR image data to intra-procedure fluoroscopy data. Registration errors were assessed using contrast angiograms of the left atrium that were available in 2 out of 3 cases. A clinical expert generated "gold standard" registrations by adjusting the registration manually. Target registration errors (TREs) were computed using points on the PV ostia. Ablation locations were computed using biplane x-ray imaging. Registration errors were further assessed by computing the distances of the ablation points to the registered left atrial surface for all 3 patients. The TREs were 6.0 & 3.1mm for patients 1 & 2. The mean ablation point errors were 6.2, 3.8, & 3.0mm for patients 1, 2, & 3. These results are encouraging in the context of a 5mm clinical accuracy requirement for this type of procedure. We conclude that multimodality skin markers have the potential to provide anatomical image integration for x-ray guided cardiac electrophysiology procedures, especially if coupled with an accurate respiratory motion compensation strategy.
| Item Type: | Book Section |
|---|---|
| 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: | 06 Jan 2023 11:32 |
| Last Modified: | 10 Dec 2024 01:12 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/90446 |
| DOI: | 10.1117/12.770172 |
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