Article

A clustering-based approach for prediction of cardiac resynchronization therapy

Authors:

Li Shen,

Justin PearlmanAuthors Info & Claims

SAC '05: Proceedings of the 2005 ACM symposium on Applied computing

Pages 260 - 266

https://doi.org/10.1145/1066677.1066739

Published: 13 March 2005 Publication History

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Abstract

This paper presents a method for predicting pacing sites in the left ventricle of a heart and its result can be used to assist device programming in cardiac resynchronization therapy (CRT), which is a widely adopted therapy for heart failure patients. In a traditional CRT device deployment, pacing sites are selected without quantitative prediction. That runs the risk of suboptimal benefits. In this work, a surface tracking method is proposed to describe the ventricular wall motion and a hierarchical agglomerative clustering technique is applied to radial motion series to find candidate pacing sites. Using clinical MRI data in our experiments, we show that the proposed method performs as well as we expect. Our approach can not only effectively identify suitable pacing sites, but also distinguish patients from normals perfectly to help medical diagnosis.

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Cited By

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Huang HShen LZhang RMakedon FSaykin APearlman J(2007)A Novel Surface Registration Algorithm With Biomedical Modeling ApplicationsIEEE Transactions on Information Technology in Biomedicine10.1109/TITB.2007.89757711:4(474-482)Online publication date: 1-Jul-2007
https://dl.acm.org/doi/10.1109/TITB.2007.897577
Huang HShen LZhang RMakedon FHettleman BPearlman J(2005)Surface alignment of 3d spherical harmonic modelsProceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I10.1007/11566465_9(67-74)Online publication date: 26-Oct-2005
https://dl.acm.org/doi/10.1007/11566465_9

Index Terms

A clustering-based approach for prediction of cardiac resynchronization therapy
1. Applied computing
  1. Life and medical sciences
2. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Unsupervised learning
        Cluster analysis

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Cardiac resynchronization therapy (CRT) is an established treatment for left bundle branch block (LBBB) resulting in mechanical dyssynchrony. Approximately 1/3 of patients with CRT, however, are non-responders. To understand factors ...
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Abstract Background
Cardiac Resynchronization Therapy (CRT) in dyssynchronous heart failure patients is ineffective in 20–30% of cases. Sub-optimal left ventricular (LV) pacing location can lead to non-response, thus there is interest in LV lead location ...
Graphical abstract

Display Omitted
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Information & Contributors

Information

Published In

SAC '05: Proceedings of the 2005 ACM symposium on Applied computing

March 2005

1814 pages

ISBN:1581139640

DOI:10.1145/1066677

Conference Chair:
Hisham M. Haddad
Kennesaw State University
,
Editor:
Lorie M. Liebrock
New Mexico Institute of Mining and Technology, Socorro, NM
,
Program Chairs:
Andrea Omicini
Alma Mater Studiorum, Universita di Bologna, Italy
,
Roger L. Wainwright
Univerity of Tulsa, OK

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 March 2005

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SAC05: The 2005 ACM Symposium on Applied Computing

March 13 - 17, 2005

New Mexico, Santa Fe

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Cited By

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Huang HShen LZhang RMakedon FSaykin APearlman J(2007)A Novel Surface Registration Algorithm With Biomedical Modeling ApplicationsIEEE Transactions on Information Technology in Biomedicine10.1109/TITB.2007.89757711:4(474-482)Online publication date: 1-Jul-2007
https://dl.acm.org/doi/10.1109/TITB.2007.897577
Huang HShen LZhang RMakedon FHettleman BPearlman J(2005)Surface alignment of 3d spherical harmonic modelsProceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I10.1007/11566465_9(67-74)Online publication date: 26-Oct-2005
https://dl.acm.org/doi/10.1007/11566465_9

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Recommendations

Optimization of cardiac resynchronization therapy based on a cardiac electromechanics-perfusion computational model

A clinical-in silico study on the effectiveness of multipoint bicathodic and cathodic-anodal pacing in cardiac resynchronization therapy

Non-invasive simulated electrical and measured mechanical indices predict response to cardiac resynchronization therapy