Clinical evaluation of respiratory motion compensation for anatomical roadmap guided cardiac electrophysiology procedures

Ma, YingLiang ORCID: https://orcid.org/0000-0001-5770-5843, King, Andy P., Gogin, Nicolas, Gijsbers, Geert, Rinaldi, C. A., Gill, Jaswinder, Razavi, Reza and Rhode, Kawal S. (2012) Clinical evaluation of respiratory motion compensation for anatomical roadmap guided cardiac electrophysiology procedures. IEEE Transactions on Biomedical Engineering, 59 (1). pp. 122-131. ISSN 0018-9294

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Abstract

X-ray fluoroscopically guided cardiac electrophysiological procedures are routinely carried out for diagnosis and treatment of cardiac arrhythmias. X-ray images have poor soft tissue contrast and, for this reason, overlay of static 3-D roadmaps derived from preprocedural volumetric data can be used to add anatomical information. However, the registration between the 3-D roadmap and the 2-D X-ray image can be compromised by patient respiratory motion. Three methods were designed and evaluated to correct for respiratory motion using features in the 2-D X-ray images. The first method is based on tracking either the diaphragm or the heart border using the image intensity in a region of interest. The second method detects the tracheal bifurcation using the generalized Hough transform and a 3-D model derived from 3-D preoperative volumetric data. The third method is based on tracking the coronary sinus (CS) catheter. This method uses blob detection to find all possible catheter electrodes in the X-ray image. A cost function is applied to select one CS catheter from all catheter-like objects. All three methods were applied to X-ray images from 18 patients undergoing radiofrequency ablation for the treatment of atrial fibrillation. The 2-D target registration errors (TRE) at the pulmonary veins were calculated to validate the methods. A TRE of 1.6 mm ± 0.8 mm was achieved for the diaphragm tracking; 1.7 mm ± 0.9 mm for heart border tracking, 1.9 mm ± 1.0 mm for trachea tracking, and 1.8 mm ± 0.9 mm for CS catheter tracking. We present a comprehensive comparison between the techniques in terms of robustness, as computed by tracking errors, and accuracy, as computed by TRE using two independent approaches.

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
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Depositing User: LivePure Connector
Date Deposited: 04 Jan 2023 17:33
Last Modified: 19 May 2023 09:40
URI: https://ueaeprints.uea.ac.uk/id/eprint/90395
DOI: 10.1109/TBME.2011.2168393

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