Med Biol Eng Comput - Automatic segmentation of the aortic root in CT angiography of candidate patients for transcatheter aortic valve implantation.

Tópicos

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Resumo

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.

Resumo Limpo

transcathet aortic valv implant minimalinvas intervent implant prosthet valv patient aortic stenosi accur autom size plan patient select expect reduc advers effect paravalvular leakag stroke segment aortic root cta pivot enabl autom size plan present fulli autom segment algorithm extract aortic root cta volum consist number step first volum interest automat detect centerlin ascend aorta aortic root centerlin determin subsequ high intens due calcif mask next aortic root repres cylindr coordin final aortic root segment use d normal cut method valid manual delin calcul dice coeffici averag distanc error patient method success segment aortic root case mean dice coeffici mean radial absolut error mm interobserv dice coeffici mean error mm propos algorithm show accur result compar manual segment

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