Key result
Automated 4D graph-cuts track mitral and aortic valve annuli within ~2.5 mm of manual annotations.
Why the study?
Fully automatic segmentation of aortic and mitral valves in dynamic cardiac imaging remains challenging due to rapid leaflet motion and variable visibility across the cardiac cycle.
Does a 4D graph-cuts processing pipeline accurately track aortic and mitral valve displacements compared to manual annotations in dynamic CTA?
Does a 4D graph-cuts processing pipeline accurately track aortic and mitral valve displacements compared to manual annotations in dynamic CTA?
An automated 4D graph-cuts pipeline can accurately track mitral and aortic valve annuli in dynamic CTA, closely matching manual annotations.
Answers are grounded in this paper and cite their sources.
Supports automated valve tracking feasibility in dynamic CTA; leaves open clinical validation in larger cohorts.
The location of the mitral and aortic valves in dynamic cardiac imaging is useful for extracting functional derived parameters such as ejection fraction, valve excursions, and global longitudinal strain, and when performing anatomical structures tracking using slice following or valve intervention's planning. Completely automatic segmentation methods are still challenging tasks because of their fast movements and the different positions that prevent good visibility of the leaflets along the full cardiac cycle. In this article, we propose a processing pipeline to track the displacement of the aortic and mitral valve annuli from high-resolution cardiac four-dimensional computed tomographic angiography (4D-CTA). The proposed method is based on the dynamic separation of left ventricle, left atrium and aorta using statistical shape modeling and an energy minimization algorithm based on graph-cuts and has been evaluated on a set of 15 electrocardiography-gated 4D-CTAs. We report a mean agreement distance between manual annotations and our proposed method of 2.52±1.06 mm for the mitral annulus and 2.00±0.69 mm for the aortic valve annulus based on valve locations detected from manual anatomical landmarks. In addition, we show the effect of detecting the valvular planes on derived functional parameters (ejection fraction, global longitudinal strain, and excursions of the mitral and aortic valves).
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Ortuño et al. (2020) studied this question. Automatic estimation using 4D graph-cuts vs. Manual annotations was evaluated on Mean agreement distance between manual annotations and proposed method. An automatic processing pipeline using 4D graph-cuts tracked mitral and aortic valve annuli displacements with a mean agreement distance to manual annotations of 2.52±1.06 mm and 2.00±0.69 mm.
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