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DOI 10.1016/j.media.2013.02.007

Медицинская библиотека · Medical image analysis · 2013

Automatic carotid artery distensibility measurements from CTA using nonrigid registration.

Hameeteman K, Rozie S, Metz C T, Manniesing R, van Walsum T, van der Lugt A, Niessen W J, Klein S

СтатьяПоддержка исследования: вне правительства СШАПеревод пока не подготовлен

Аннотация

The distensibility of a blood vessel is a marker of atherosclerotic disease. In this paper we investigate the feasibility of measuring carotid artery distensibility on 4D CTA, both manually and using a new automatic method. On 4D CTA datasets manual (n=38) and automatic (n=76) measurements of the carotid distensibility were performed. A subset (n=10) of the manual annotations were repeated by a second observer. The interobserver variability was assessed using a Bland-Altman analysis and appeared to be too large to reliably measure the distensibility using manual annotation. We compared two versions of the automatic method: one using 3D registration and one using a 4D registration method. The latter resulted in a more smooth deformation over time. The automatic method was evaluated using a synthetic deformation and by investigating whether known relations with cardiovascular risk factors could be reproduced. The relation between distensibility and cardiovascular risk factors was tested with a Mann-Whitney U test. Automatic measurements revealed an association with hypertension whereas the manual measurements did not. This relation has been found by other studies too. We conclude that carotid artery distensibility measurements should be performed automatically and that the method described in this paper is suitable for that. All CTA datasets and related clinical data used in this study can be downloaded from our website (http://ctadist.bigr.nl).

Для цитирования: Hameeteman K, Rozie S, Metz C T, Manniesing R, van Walsum T, van der Lugt A, Niessen W J, Klein S. Automatic carotid artery distensibility measurements from CTA using nonrigid registration.. Medical image analysis. 2013. DOI: 10.1016/j.media.2013.02.007.

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