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Proceedings Paper

Automated planning of ablation targets in atrial fibrillation treatment
Author(s): Johannes Keustermans; Stijn De Buck; Hein Heidbüchel; Paul Suetens
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Paper Abstract

Catheter based radio-frequency ablation is used as an invasive treatment of atrial fibrillation. This procedure is often guided by the use of 3D anatomical models obtained from CT, MRI or rotational angiography. During the intervention the operator accurately guides the catheter to prespecified target ablation lines. The planning stage, however, can be time consuming and operator dependent which is suboptimal both from a cost and health perspective. Therefore, we present a novel statistical model-based algorithm for locating ablation targets from 3D rotational angiography images. Based on a training data set of 20 patients, consisting of 3D rotational angiography images with 30 manually indicated ablation points, a statistical local appearance and shape model is built. The local appearance model is based on local image descriptors to capture the intensity patterns around each ablation point. The local shape model is constructed by embedding the ablation points in an undirected graph and imposing that each ablation point only interacts with its neighbors. Identifying the ablation points on a new 3D rotational angiography image is performed by proposing a set of possible candidate locations for each ablation point, as such, converting the problem into a labeling problem. The algorithm is validated using a leave-one-out-approach on the training data set, by computing the distance between the ablation lines obtained by the algorithm and the manually identified ablation points. The distance error is equal to 3.8±2.9 mm. As ablation lesion size is around 5-7 mm, automated planning of ablation targets by the presented approach is sufficiently accurate.

Paper Details

Date Published: 9 March 2011
PDF: 7 pages
Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 796207 (9 March 2011); doi: 10.1117/12.878250
Show Author Affiliations
Johannes Keustermans, Katholieke Univ. Leuven (Belgium)
Stijn De Buck, Univ. Hospital Gasthuisberg, Katholieke Univ. Leuven (Belgium)
Hein Heidbüchel, Univ. Hospital Gasthuisberg, Katholieke Univ. Leuven (Belgium)
Paul Suetens, Katholieke Univ. Leuven (Belgium)

Published in SPIE Proceedings Vol. 7962:
Medical Imaging 2011: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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