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Automatic segmentation of the aortic root in CT angiography of candidate patients for transcatheter aortic valve implantation

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Abstract

Transcatheter aortic valve implantation is a minimal-invasive intervention for implanting prosthetic valves in patients with aortic stenosis. Accurate automated sizing for planning and patient selection is expected to reduce adverse effects such as paravalvular leakage and stroke. Segmentation of the aortic root in CTA is pivotal to enable automated sizing and planning. We present a fully automated segmentation algorithm to extract the aortic root from CTA volumes consisting of a number of steps: first, the volume of interest is automatically detected, and the centerline through the ascending aorta and aortic root centerline are determined. Subsequently, high intensities due to calcifications are masked. Next, the aortic root is represented in cylindrical coordinates. Finally, the aortic root is segmented using 3D normalized cuts. The method was validated against manual delineations by calculating Dice coefficients and average distance error in 20 patients. The method successfully segmented the aortic root in all 20 cases. The mean Dice coefficient was 0.95 ± 0.03, and the mean radial absolute error was 0.74 ± 0.39 mm, where the interobserver Dice coefficient was 0.95 ± 0.03 and the mean error was 0.68 ± 0.34 mm. The proposed algorithm showed accurate results compared to manual segmentations.

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Acknowledgments

The authors wish to thank for the support from the Technology Foundation STW, The Netherlands, under Grant 11630.

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Authors and Affiliations

  1. Department of Biomedical Engineering and Physics, Academic Medical Center, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands

    M. A. Elattar, E. vanbavel & H. A. Marquering

  2. Department of Cardiology, Academic Medical Center, University of Amsterdam, 1105 AZ, Amsterdam, The Netherlands

    E. M. Wiegerinck & J. Baan Jr.

  3. Department of Radiology, Academic Medical Center, University of Amsterdam, 1105 AZ, Amsterdam, The Netherlands

    R. N. Planken & H. A. Marquering

  4. Department of Electrical Engineering, Eindhoven University of Technology, 5600 MB, Eindhoven, The Netherlands

    H. C. van Assen

Authors
  1. M. A. Elattar
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  2. E. M. Wiegerinck
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  3. R. N. Planken
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  4. E. vanbavel
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  5. H. C. van Assen
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  6. J. Baan Jr.
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  7. H. A. Marquering
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Correspondence to M. A. Elattar.

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Elattar, M.A., Wiegerinck, E.M., Planken, R.N. et al. Automatic segmentation of the aortic root in CT angiography of candidate patients for transcatheter aortic valve implantation. Med Biol Eng Comput 52, 611–618 (2014). https://doi.org/10.1007/s11517-014-1165-7

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  • DOI: https://doi.org/10.1007/s11517-014-1165-7

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