Computed Tomography‐Fluoroscopy Image Integration‐Guided Catheter Ablation of Atrial Fibrillation

Sra, Jasbír; Narayan, Girish; Krum, David; Malloy, Angela; Cooley, Ryan; Bhatia, Atul; Dhala, Anwer; Blanck, Zalmen; Nangia, Vikram; Akhtar, Masood

doi:10.1111/j.1540-8167.2006.00734.x

Cited by 125 publications

(55 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recent research in the area of X-ray guidance for electrophysiology (EP) procedures found that augmented fluoroscopy using overlay images rendered from 3-D images (CT, MRI, C-Arm CT) facilitates more precise catheter navigation and a reduction in fluoroscopy time [1][2][3]. Critical structures like the esophagus and the left atrial appendage are invisible under regular fluoroscopy unless contrast agent is applied.…”

Section: Motivationmentioning

confidence: 99%

Catheter Tracking: Filter-Based vs. Learning-Based

Brost

Wimmer

Liao

et al. 2010

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. Atrial fibrillation is the most common sustained arrhythmia. One important treatment option is radio-frequency catheter ablation (RFCA) of the pulmonary veins attached to the left atrium. RFCA is usually performed under fluoroscopic (X-ray) image guidance. Overlay images computed from pre-operative 3-D volumetric data can be used to add anatomical detail otherwise not visible under X-ray. Unfortunately, current fluoro overlay images are static, i.e., they do not move synchronously with respiratory and cardiac motion. A filter-based catheter tracking approach using simultaneous biplane fluoroscopy was previously presented. It requires localization of a circumferential tracking catheter, though. Unfortunately, the initially proposed method may fail to accommodate catheters of different size. It may also detect wrong structures in the presence of high background clutter. We developed a new learning-based approach to overcome both problems. First, a 3-D model of the catheter is reconstructed. A cascade of boosted classifiers is then used to segment the circumferential mapping catheter. Finally, the 3-D motion at the site of ablation is estimated by tracking the reconstructed model in 3-D from biplane fluoroscopy. We compared our method to the previous approach using 13 clinical data sets and found that the 2-D tracking error improved from 1.0 mm to 0.8 mm. The 3-D tracking error was reduced from 0.8 mm to 0.7 mm.

show abstract

Section: Motivationmentioning

confidence: 99%

Catheter Tracking: Filter-Based vs. Learning-Based

Brost

Wimmer

Liao

et al. 2010

Lecture Notes in Computer Science

View full text Add to dashboard Cite

show abstract

“…This technology is available through the commercial EP Navigator platform (Philips Healthcare, The Netherlands). Automatic registration methods include the use of the spine [46] and 3D catheter reconstructions from multiple X-ray views [48,49]. Automatic registration can also be achieved in the setting of hybrid X-ray/MR systems (XMR systems) by pre-calibration and tracking [50, 51••].…”

Section: Multimodal Data Fusionmentioning

confidence: 99%

Modeling and Registration for Electrophysiology Procedures Based on Three-Dimensional Imaging

Rhode

Sermesant

2011

Curr Cardiovasc Imaging Rep

View full text Add to dashboard Cite

Computer models of cardiac electrophysiology (EP) can help to better understand the mechanisms of arrhythmias and to guide interventions. However, model adjustment to patient data (personalization) is a required step that is still challenging from clinical data. The progress in the fusion of multimodal data opens up new possibilities in generating patient-specific models of the heart. In this paper, we present the state-of-the-art in multimodal data fusion for EP procedure guidance and how such integrated data can be used to personalize models and guide interventions.

show abstract

“…When catheter ablation of the pulmonary veins (PVs) is carried out under fluoroscopic guidance, image integration combining pre-operative high-resolution 3-D atrial CT and/or MR volumes with the fluoroscopic images can be used (fluoroscopic overlay image guidance) to overcome the problem that X-ray projection images can not distinguish soft tissue well. The potential advantage of this strategy is the fused display of the actual, real-time fluoroscopic images together with images from CT or MRI depicting high soft-tissue contrast [3,4]. Stateof-the art C-arm systems facilitating 3-D tomographic reconstruction can also be used to obtain volumetric data sets of the heart [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

3D model-based catheter tracking for motion compensation in EP procedures

Brost¹,

Liao

Hornegger³

et al. 2010

Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling

View full text Add to dashboard Cite

Abstract. Atrial fibrillation is the most common sustained heart arrhythmia and a leading cause of stroke. Its treatment by radio-frequency catheter ablation, performed using fluoroscopic image guidance, is gaining increasingly more importance. Two-dimensional fluoroscopic navigation can take advantage of overlay images derived from pre-operative 3-D data to add anatomical details otherwise not visible under X-ray. Unfortunately, respiratory motion may impair the utility of these static overlay images for catheter navigation. We developed an approach for image-based 3-D motion compensation as a solution to this problem. A bi-plane C-arm system is used to take X-ray images of a special circumferential mapping catheter from two directions. In the first step of the method, a 3-D model of the device is reconstructed. Three-dimensional respiratory motion at the site of ablation is then estimated by tracking the reconstructed catheter model in 3-D. This step involves bi-plane fluoroscopy and 2-D/3-D registration. Phantom data and clinical data were used to assess our model-based catheter tracking method. Experiments involving a moving heart phantom yielded an average 2-D tracking error of 1.4 mm and an average 3-D tracking error of 1.1 mm. Our evaluation of clinical data sets comprised 469 bi-plane fluoroscopy frames (938 monoplane fluoroscopy frames). We observed an average 2-D tracking error of 1.0 mm ± 0.4 mm and an average 3-D tracking error of 0.8 mm ± 0.5 mm. These results demonstrate that model-based motion-compensation based on 2-D/3-D registration is both feasible and accurate.

show abstract

Computed Tomography‐Fluoroscopy Image Integration‐Guided Catheter Ablation of Atrial Fibrillation

Abstract: CT-fluoroscopic-guided left atrial ablation is feasible and allows appropriate catheter manipulation in the left atrium.

Cited by 125 publications

References 22 publications

Catheter Tracking: Filter-Based vs. Learning-Based

Catheter Tracking: Filter-Based vs. Learning-Based

Modeling and Registration for Electrophysiology Procedures Based on Three-Dimensional Imaging

3D model-based catheter tracking for motion compensation in EP procedures

Contact Info

Product

Resources

About