Semiautomatic Estimation of Device Size for Left Atrial Appendage Occlusion in 3-D TEE Images

• Type: Article in International Scientific Journal
• Date: 2019-05

Authors

Pedro Morais (Author) Other; João L. Vilaça (Author) Other; Sandro Queirós (Author) Other; Pieter De Meester (Author) Other; Werner Budts (Author) Other; João Manuel R. S. Tavares (Author) FEUP; Jan D'hooge (Author) Other

Journal

Title: IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control

Vol. 66 No. 5

Pages: 922-929

ISSN: 0885-3010

Publisher: IEEE

Indexing

ISI Web of Knowledge - 0 Citations

ISI Web of Science

Scopus - 1 Citation

Scientific classification

CORDIS: Technological sciences

FOS: Medical and Health sciences

Other information

Authenticus ID: P-00Q-JXA

DOI: 10.1109/tuffc.2019.2903886

Abstract (EN): Left atrial appendage (LAA) occlusion is used to reduce the risk of thromboembolism in patients with non-valvular atrial fibrillation by obstructing the LAA through a percutaneously delivered device. Nonetheless, correct device sizing is complex, requiring the manual estimation of different measurements in preprocedural/periprocedural images, which is tedious and time-consuming and with high interobserver and intraobserver variability. In this paper, a semiautomatic solution to estimate the required relevant clinical measurements is described. This solution starts with the 3-D segmentation of the LAA in 3-D transesophageal echocardiographic images, using a constant blind-ended model initialized through a manually defined spline. Then, the segmented LAA surface is aligned with a set of templates, i.e., 3-D surfaces plus relevant measurement planes (manually defined by one observer), transferring the latter to the unknown situation. Specifically, the alignment is performed in three consecutive steps, namely: 1) rigid alignment using the LAA clipping plane position; 2) orientation compensation using the circumflex artery location; and 3) anatomical refinement through a weighted iterative closest point algorithm. The novel solution was evaluated in a clinical database with 20 volumetric TEE images. Two experiments were set up to assess: 1) the sensitivity of the model's parameters and 2) the accuracy of the proposed solution for the estimation of the clinical measurements. Measurement levels manually identified by two observers were used as ground truth. The proposed solution obtained results comparable to the interobserver variability, presenting narrower limits of agreement for all measurements. Moreover, this solution proved to be fast, taking nearly 40 s (manual analysis took 3 min) to estimate the relevant measurements while being robust to the variation of the model's parameters. Overall, the proposed solution showed its potential for fast and robust estimation of the clinical measurements for occluding device selection, proving its added value for clinical practice.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8