Journal article
Novel Indices for Left-Ventricular Dyssynchrony Characterization Based on Highly Automated Segmentation From Real-Time 3-D Echocardiography
Ultrasound in medicine & biology, Vol.39(1), pp.72-88
01/2013
DOI: 10.1016/j.ultrasmedbio.2012.08.019
PMID: 23141901
Abstract
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 three-dimensional (3-D) echocardiography (RT3DE) provides four-dimensional (4-D) (3-D+time) information about the LV and is suitable for LVMD assessment. In this article, the complex left ventricle (LV) shape and motion of 50 RT3DE datasets are represented by novel 4-D descriptors — 4-D 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±1.1 mm 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 4-D 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.
Details
- Title: Subtitle
- Novel Indices for Left-Ventricular Dyssynchrony Characterization Based on Highly Automated Segmentation From Real-Time 3-D Echocardiography
- Creators
- Honghai Zhang - Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA, USAAdemola K Abiose - Department of Internal Medicine, The University of Iowa, Iowa City, IA, USADipti Gupta - Department of Internal Medicine, The University of Iowa, Iowa City, IA, USADwayne N Campbell - Department of Internal Medicine, The University of Iowa, Iowa City, IA, USAJames B Martins - Department of Internal Medicine, The University of Iowa, Iowa City, IA, USAMilan Sonka - Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA, USAAndreas Wahle - Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA, USA
- Resource Type
- Journal article
- Publication Details
- Ultrasound in medicine & biology, Vol.39(1), pp.72-88
- DOI
- 10.1016/j.ultrasmedbio.2012.08.019
- PMID
- 23141901
- NLM abbreviation
- Ultrasound Med Biol
- ISSN
- 0301-5629
- eISSN
- 1879-291X
- Publisher
- Elsevier Inc
- Grant note
- DOI: 10.13039/100000002, name: National Institutes of Health, award: R01 EB004640, R01 HL071809; DOI: 10.13039/100000968, name: American Heart Association, award: GIA 0755798Z
- Language
- English
- Date published
- 01/2013
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Radiation Oncology; Injury Prevention Research Center; Internal Medicine; Ophthalmology and Visual Sciences
- Record Identifier
- 9984046812802771
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