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Quantification of Epicardial Fat by Cardiac CT Imaging.

Coppini G, Favilla R, Marraccini P, Moroni D, Pieri G - Open Med Inform J (2010)

Bottom Line: However, many concerns still remain about the methods for measuring epicardial fat, its regional distribution on the myocardium and the accuracy and reproducibility of the measurements.In this paper, a method is proposed for the analysis of single-frame 3D images obtained by the standard acquisition protocol used for coronary calcium scoring.In the design of the method, much attention has been payed to the minimization of user intervention and to reproducibility issues.In particular, the proposed method features a two step segmentation algorithm suitable for the analysis of epicardial fat.In the first step of the algorithm, an analysis of epicardial fat intensity distribution is carried out in order to define suitable thresholds for a first rough segmentation.

View Article: PubMed Central - PubMed

Affiliation: Institute of Clinical Physiology (IFC), Italian National Research Council (CNR), Pisa, Italy.

ABSTRACT
The aim of this work is to introduce and design image processing methods for the quantitative analysis of epicardial fat by using cardiac CT imaging.Indeed, epicardial fat has recently been shown to correlate with cardiovascular disease, cardiovascular risk factors and metabolic syndrome. However, many concerns still remain about the methods for measuring epicardial fat, its regional distribution on the myocardium and the accuracy and reproducibility of the measurements.In this paper, a method is proposed for the analysis of single-frame 3D images obtained by the standard acquisition protocol used for coronary calcium scoring. In the design of the method, much attention has been payed to the minimization of user intervention and to reproducibility issues.In particular, the proposed method features a two step segmentation algorithm suitable for the analysis of epicardial fat. In the first step of the algorithm, an analysis of epicardial fat intensity distribution is carried out in order to define suitable thresholds for a first rough segmentation. In the second step, a variational formulation of level set methods - including a specially-designed region homogeneity energy based on Gaussian mixture models- is used to recover spatial coherence and smoothness of fat depots.Experimental results show that the introduced method may be efficiently used for the quantification of epicardial fat.

No MeSH data available.


Related in: MedlinePlus

Axial views of the identified VoI: (a) apical, (b) mid and (c) basal slice planes. The green curve is the natural cubic spline whose control points have been placed by an experienced observer.
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Figure 3: Axial views of the identified VoI: (a) apical, (b) mid and (c) basal slice planes. The green curve is the natural cubic spline whose control points have been placed by an experienced observer.

Mentions: The volume was then edited as described in Section 2.1, obtaining as a result a VoI containing all the voxels that may contribute to epicardial fat volume. Some views of the VoI are shown in Fig. (3), together with the natural cubic spline curve delineated by an experienced observer.


Quantification of Epicardial Fat by Cardiac CT Imaging.

Coppini G, Favilla R, Marraccini P, Moroni D, Pieri G - Open Med Inform J (2010)

Axial views of the identified VoI: (a) apical, (b) mid and (c) basal slice planes. The green curve is the natural cubic spline whose control points have been placed by an experienced observer.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3095114&req=5

Figure 3: Axial views of the identified VoI: (a) apical, (b) mid and (c) basal slice planes. The green curve is the natural cubic spline whose control points have been placed by an experienced observer.
Mentions: The volume was then edited as described in Section 2.1, obtaining as a result a VoI containing all the voxels that may contribute to epicardial fat volume. Some views of the VoI are shown in Fig. (3), together with the natural cubic spline curve delineated by an experienced observer.

Bottom Line: However, many concerns still remain about the methods for measuring epicardial fat, its regional distribution on the myocardium and the accuracy and reproducibility of the measurements.In this paper, a method is proposed for the analysis of single-frame 3D images obtained by the standard acquisition protocol used for coronary calcium scoring.In the design of the method, much attention has been payed to the minimization of user intervention and to reproducibility issues.In particular, the proposed method features a two step segmentation algorithm suitable for the analysis of epicardial fat.In the first step of the algorithm, an analysis of epicardial fat intensity distribution is carried out in order to define suitable thresholds for a first rough segmentation.

View Article: PubMed Central - PubMed

Affiliation: Institute of Clinical Physiology (IFC), Italian National Research Council (CNR), Pisa, Italy.

ABSTRACT
The aim of this work is to introduce and design image processing methods for the quantitative analysis of epicardial fat by using cardiac CT imaging.Indeed, epicardial fat has recently been shown to correlate with cardiovascular disease, cardiovascular risk factors and metabolic syndrome. However, many concerns still remain about the methods for measuring epicardial fat, its regional distribution on the myocardium and the accuracy and reproducibility of the measurements.In this paper, a method is proposed for the analysis of single-frame 3D images obtained by the standard acquisition protocol used for coronary calcium scoring. In the design of the method, much attention has been payed to the minimization of user intervention and to reproducibility issues.In particular, the proposed method features a two step segmentation algorithm suitable for the analysis of epicardial fat. In the first step of the algorithm, an analysis of epicardial fat intensity distribution is carried out in order to define suitable thresholds for a first rough segmentation. In the second step, a variational formulation of level set methods - including a specially-designed region homogeneity energy based on Gaussian mixture models- is used to recover spatial coherence and smoothness of fat depots.Experimental results show that the introduced method may be efficiently used for the quantification of epicardial fat.

No MeSH data available.


Related in: MedlinePlus