Automatic carotid artery distensibility measurements from CTA using nonrigid registration.

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).

Carotid wall volume quantification from magnetic resonance images using deformable model fitting and learning-based correction of systematic errors.

We present a method for carotid vessel wall volume quantification from magnetic resonance imaging (MRI). The method combines lumen and outer wall segmentation based on deformable model fitting with a learning-based segmentation correction step. After selecting two initialization points, the vessel wall volume in a region around the bifurcation is automatically determined. The method was trained on eight datasets (16 carotids) from a population-based study in the elderly for which one observer manually annotated both the lumen and outer wall. An evaluation was carried out on a separate set of 19 datasets (38 carotids) from the same study for which two observers made annotations. Wall volume and normalized wall index measurements resulting from the manual annotations were compared to the automatic measurements. Our experiments show that the automatic method performs comparably to the manual measurements. All image data and annotations used in this study together with the measurements are made available through the website http://ergocar.bigr.nl.

Evaluation framework for carotid bifurcation lumen segmentation and stenosis grading.

This paper describes an evaluation framework that allows a standardized and objective quantitative comparison of carotid artery lumen segmentation and stenosis grading algorithms. We describe the data repository comprising 56 multi-center, multi-vendor CTA datasets, their acquisition, the creation of the reference standard and the evaluation measures. This framework has been introduced at the MICCAI 2009 workshop 3D Segmentation in the Clinic: A Grand Challenge III, and we compare the results of eight teams that participated. These results show that automated segmentation of the vessel lumen is possible with a precision that is comparable to manual annotation. The framework is open for new submissions through the website http://cls2009.bigr.nl.