Localized Shape Variations for Classifying Wall Motion in Echocardiograms

Leung, K. Y. Esther; Bosch, Johan G.

doi:10.1007/978-3-540-75757-3_7

Cited by 18 publications

(9 citation statements)

References 15 publications

(19 reference statements)

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“…Much of the previous work, however, has been of a qualitative nature or based on assumptions regarding ideal geometry of the ventricle. Furthermore, many earlier studies are based on 2-D models of short and/or long axis from ventriculography (4,20,30,31,33), MRI (3), and echocardiography (29).…”

Section: Discussionmentioning

confidence: 99%

Left ventricular regional wall curvedness and wall stress in patients with ischemic dilated cardiomyopathy

Zhong

Su²,

Yeo³

et al. 2009

American Journal of Physiology-Heart and Circulatory Physiology

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Geometric remodeling of the left ventricle (LV) after myocardial infarction is associated with changes in myocardial wall stress. The objective of this study was to determine the regional curvatures and wall stress based on three-dimensional (3-D) reconstructions of the LV using MRI. Ten patients with ischemic dilated cardiomyopathy (IDCM) and 10 normal subjects underwent MRI scan. The IDCM patients also underwent delayed gadolinium-enhancement imaging to delineate the extent of myocardial infarct. Regional curvedness, local radii of curvature, and wall thickness were calculated. The percent curvedness change between end diastole and end systole was also calculated. In normal heart, a short- and long-axis two-dimensional analysis showed a 41 +/- 11% and 45 +/- 12% increase of the mean of peak systolic wall stress between basal and apical sections, respectively. However, 3-D analysis showed no significant difference in peak systolic wall stress from basal and apical sections (P = 0.298, ANOVA). LV shape differed between IDCM patients and normal subjects in several ways: LV shape was more spherical (sphericity index = 0.62 +/- 0.08 vs. 0.52 +/- 0.06, P < 0.05), curvedness at end diastole (mean for 16 segments = 0.034 +/- 0.0056 vs. 0.040 +/- 0.0071 mm(-1), P < 0.001) and end systole (mean for 16 segments = 0.037 +/- 0.0068 vs. 0.067 +/- 0.020 mm(-1), P < 0.001) was affected by infarction, and peak systolic wall stress was significantly increased at each segment in IDCM patients. The 3-D quantification of regional wall stress by cardiac MRI provides more precise evaluation of cardiac mechanics. Identification of regional curvedness and wall stresses helps delineate the mechanisms of LV remodeling in IDCM and may help guide therapeutic LV restoration.

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Section: Discussionmentioning

confidence: 99%

Left ventricular regional wall curvedness and wall stress in patients with ischemic dilated cardiomyopathy

Zhong

Su²,

Yeo³

et al. 2009

American Journal of Physiology-Heart and Circulatory Physiology

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“…Lekadir et al (2007) model LV deformation as interlandmark motion in a local circular coordinate system in which anomalies present themselves as outliers. Leung and Bosch (2007) create a sparse shape variation decomposition using PCA and subsequent orthomax rotations to characterize local abnormal deformations, while Syeda-Mahmood et al (2007) use registration and the associated deformation patterns to characterize deformation abnormalities in 2D ultrasound sequences.…”

Section: Clinical Contextmentioning

confidence: 99%

Bilinear Models for Spatio-Temporal Point Distribution Analysis

et al. 2009

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In this work we describe the usage of bilinear statistical models as a means of factoring the shape variability into two components attributed to inter-subject variation and to the intrinsic dynamics of the human heart. We show that it is feasible to reconstruct the shape of the heart at discrete points in the cardiac cycle. Provided we are given a small number of shape instances representing the same heart at different points in the same cycle, we can use the bilinear model to establish this.Using a temporal and a spatial alignment step in the preprocessing of the shapes, around half of the reconstruction errors were on the order of the axial image resolution of 2 mm, and over 90% was within 3.5 mm. From this, we conclude that the dynamics were indeed separated from the inter-subject variability in our dataset.

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“…Recent researches ([3] [4]) have introduced methods that take into account all morphology of the left ventricle in order to localize myocardial regions showing abnormal contractile behavior based on statistics trained from healthy wall motion. Previous studies have applied the medial model to the right/left ventricle deformations and concluded that the medial model can capture the deformation of the left and right ventricles along with the changes of their wall thickness over time [5].…”

Section: Introductionmentioning

confidence: 99%

Left ventricle motion classification in the medial surface shape space

Taimouri

Hua

2013

2013 IEEE 10th International Symposium on Biomedical Imaging

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The wall thickness is known as a valuable measure for the cardiac diagnosis. From the geometric point of view, it can be considered as a function defined on the 2D manifold of the medial surface. This paper presents a novel classification method based on medial representation to diagnose and detect the myopathic regions on the left ventricle. A shape space is proposed and constructed based on the changes of the left ventricle wall thickness, in which two shape descriptors are introduced which show remarkable performance to distinguish normal and abnormal left ventricle deformations. The experimental results show that this method can automatically classify the healthy and myopathic subjects and detect myopathic regions on the left ventricle well.

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Localized Shape Variations for Classifying Wall Motion in Echocardiograms

Cited by 18 publications

References 15 publications

Left ventricular regional wall curvedness and wall stress in patients with ischemic dilated cardiomyopathy

Left ventricular regional wall curvedness and wall stress in patients with ischemic dilated cardiomyopathy

Bilinear Models for Spatio-Temporal Point Distribution Analysis

Left ventricle motion classification in the medial surface shape space

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