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Sep 22, 2014

PhD student Jørn Bersvendsen from GEVU publish in BMC Medical Imaging


 


 

PhD student at GE Vingmed Ultrasound, Jørn Bersvendsen et al. got their study titled; Automatic measurement of aortic annulus diameter in 3-dimensional Transoesophageal echocardiography published in BMC Medical Imaging.

With this study, they have demonstrated the feasibility of an efficient and fully automatic measurement of the aortic annulus in patients with aortic disease. The algorithm robustly measured the aortic annulus diameter, providing measurements indistinguishable from those done by cardiologists.

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BACKGROUND FOR THE STUDY

Transcatheter Aortic Valve Implantation (TAVI) involves percutaneously implanting a biomechanical aortic valve to treat severe aortic stenosis. Because of its minimally invasive nature, TAVI is a viable alternative for patients who are at too high risk to undergo conventional surgical aortic valve replacement.

Precise sizing of the aortic annulus prior to TAVI is required for determining procedure eligibility and for selecting the correct implant size and type. Errors in prosthesis sizing may lead to complications during or after the procedure, such as Paravalvular Aortic Regurgitation (PAR) [1].

In current clinical practice, measurement of the annulus diameter before TAVI is typically done by 2D transthoracic echocardiography, 2D Transoesophageal Echocardiography (TEE) or Multi-Slice Computed Tomography (MSCT).

It has been shown that sizing based on MSCT, as opposed to 2D TEE, results in fewer instances of post operational PAR [2], as 2D modalities can fail to accurately describe the 3D structure of the aortic valve [3-5]. Strong correlations between 3D TEE and MSCT measurements of the annulus diameter [4] indicate feasibility of similar results for a method based on 3D TEE.

We propose an algorithm for automatic annulus measurements operating on 3D TEE images, using a real-time volumetric tracking and segmentation framework presented by Orderud et. al [6,7]. The framework uses an extended Kalman filter to solve a state space estimation formulation of the segmentation problem, and has been applied on the left ventricle.

In this paper, we apply the same framework to model the left ventricular outflow tract and aortic root. We propose a two-stage approach by performing segmentation based on a stiff and deformable surface sequentially. Combined with assimilation of forward and backward tracking, we obtain a fully automatic measurement of the aortic annulus diameter in 3D TEE images.

We validated our results by comparing automatic measurements of 16 recordings to manual measurements made by two cardiologists.

 

Automatic measurement of aortic annulus diameter in 3-dimensional transoesophageal echocardiography.
Bersvendsen J, Beitnes JO, Urheim S, Aakhus S, Samset E. 
BMC Med Imaging. 2014 Sep 8;14(1):31
doi: 10.1186/1471-2342-14-31
PMID: 25200865


ABSTRACT

BACKGROUND:
Transcatheter aortic valve implantation involves percutaneously implanting a biomechanical aortic valve to treat severe aortic stenosis. In order to select a proper device, precise sizing of the aortic valve annulus must be completed.

METHODS:
In this paper, we describe a fully automatic segmentation method to measure the aortic annulus diameter in patients with aortic calcification, operating on 3-dimensional transesophageal echocardiographic images. The method is based on state estimation of a subdivision surface representation of the left ventricular outflow tract and aortic root. The state estimation is solved by an extended Kalman filter driven by edge detections normal to the subdivision surface.

RESULTS:
The method was validated on echocardiographic recordings of 16 patients. Comparison against two manual measurements showed agreements (mean±SD) of -0.3 ± 1.6 and -0.2 ± 2.3 mm for perimeter-derived diameters, compared to an interobserver agreement of -0.1 ± 2.1 mm.

CONCLUSIONS:
With this study, we demonstrated the feasibility of an efficient and fully automatic measurement of the aortic annulus in patients with aortic disease. The algorithm robustly measured the aortic annulus diameter, providing measurements indistinguishable from those done by cardiologists.

Center for Cardiological Innovation