Shape and motion analysis of left ventricle dyssynchrony from real-time 3D echocardiography

Zhang, Honghai; Abiose, Ademola K.; Campbell, Dwayne N.; Sonka, Milan; Martins, James B.; Wahle, Andreas

doi:10.1109/isbi.2010.5490101

Cited by 2 publications

(3 citation statements)

References 7 publications

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“…Our findings agree with our earlier preliminary reports that there is no statistically significant difference between the pre- and post-CRT datasets as well as between the responders and non-responders in traditional LV functional indices such as ejection fraction, end-diastolic and end-systolic volumes (Gupta et al, 2011). However, we noticed large changes of PCA scores between pre- and post-CRT in some CRT responders (Zhang et al, 2010b) that indicated the potential for tracking changes of the disease status. Such promise was further confirmed in this paper by the comprehensive pre/post-CRT analyses (Table 1), where the basal segments start to show obvious changes in PCA scores and the classification accuracy using PCA scores of the 4D LV shape reached 80%.…”

Section: Discussionmentioning

confidence: 91%

“…Second, the PCA scores are descriptive and not discriminative indices thus a PCA score b i may not be directly used as LVMD or CRT indicator. Our earlier preliminary study (Zhang et al, 2010b) demonstrated that the PCA scores of pre- and post-CRT datasets, as well as of CRT responders and non-responders, have overlapping distributions that cannot be fully separated by a linear method.…”

Section: Shape and Motion Analysismentioning

confidence: 99%

“…We assessed the capability of these indices in: 1) capturing LVMD induced shape and motion features, 2) identifying and tracking the reverse remodeling process of LV after CRT, and 3) improving CRT outcome prediction. We have previously reported a small subset of preliminary results on PCA (Zhang et al, 2010b) and sphericity indices (Gupta et al, 2011). …”

Section: Introductionmentioning

confidence: 99%

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Novel Indices for Left-Ventricular Dyssynchrony Characterization Based on Highly Automated Segmentation From Real-Time 3-D Echocardiography

Zhang

Abiose

Gupta

et al. 2013

Ultrasound in Medicine & Biology

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Cardiac resynchronization therapy (CRT) using a biventricular pacemaker is an invasive and expensive treatment option for left ventricular mechanical dyssynchrony (LVMD). The CRT candidate selection is a crucial issue due to the unreliability of the current standard CRT indicators. Real-time 3D echocardiography (RT3DE) provides 4D (3D+time) information about the LV and is suitable for LVMD assessment. In this paper, the complex LV shape and motion of 50 RT3DE datasets are represented by novel 4D descriptors—4D sphericity, volume, and shape, from which novel indices were derived by principal component analysis (PCA) and subsequently analyzed by a support vector machine (SVM) classifier to assess their capability of LVMD characterization and CRT outcome prediction. These novel indices outperformed clinical indices and have promising capabilities in disease characterization and great potential in CRT outcome prediction. To enable efficient quantitative RT3DE analysis, a segmentation method was developed to combine the powers of active shape models and optimal graph search. Various aspects of the method were designed to handle varying RT3DE image quality among datasets and LV segments. An application with graphical user interface was developed to provide the user with simple and intuitive control. The developed method was robust to inter-observer variability and produced very good accuracy—3.2±1.1mm absolute surface positioning error, <1 mm mean signed error, and <5% mean volume difference. The computer method’s classification performance was compared with the independent standard, showing that the 4D shape modal indices were not only the most capable of all tested options when employed for disease characterization but also the least sensitive to segmentation imperfections.

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Section: Discussionmentioning

confidence: 91%

Section: Shape and Motion Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Novel Indices for Left-Ventricular Dyssynchrony Characterization Based on Highly Automated Segmentation From Real-Time 3-D Echocardiography

Zhang

Abiose

Gupta

et al. 2013

Ultrasound in Medicine & Biology

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Left-ventricle segmentation in real-time 3D echocardiography using a hybrid active shape model and optimal graph search approach

et al. 2010

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Quantitative analysis of the left ventricular shape and motion patterns associated with left ventricular mechanical dyssynchrony (LVMD) is essential for diagnosis and treatment planning in congestive heart failure. Real-time 3D echocardiography (RT3DE) used for LVMD analysis is frequently limited by heavy speckle noise or partially incomplete data, thus a segmentation method utilizing learned global shape knowledge is beneficial. In this study, the endocardial surface of the left ventricle (LV) is segmented using a hybrid approach combining active shape model (ASM) with optimal graph search. The latter is used to achieve landmark refinement in the ASM framework. Optimal graph search translates the 3D segmentation into the detection of a minimum-cost closed set in a graph and can produce a globally optimal result. Various information -gradient, intensity distributions, and regional-property terms -are used to define the costs for the graph search. The developed method was tested on 44 RT3DE datasets acquired from 26 LVMD patients. The segmentation accuracy was assessed by surface positioning error and volume overlap measured for the whole LV as well as 16 standard LV regions. The segmentation produced very good results that were not achievable using ASM or graph search alone.

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Shape and motion analysis of left ventricle dyssynchrony from real-time 3D echocardiography

Cited by 2 publications

References 7 publications

Novel Indices for Left-Ventricular Dyssynchrony Characterization Based on Highly Automated Segmentation From Real-Time 3-D Echocardiography

Novel Indices for Left-Ventricular Dyssynchrony Characterization Based on Highly Automated Segmentation From Real-Time 3-D Echocardiography

Left-ventricle segmentation in real-time 3D echocardiography using a hybrid active shape model and optimal graph search approach

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