A prediction framework for cardiac resynchronization therapy via 4D cardiac motion analysis.

Heng Huang, Li Shen, Rong Zhang, Fillia Makedon, Bruce Hettleman, Justin Pearlman

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

We propose a novel framework to predict pacing sites in the left ventricle (LV) of a heart and its result can be used to assist pacemaker implantation and programming in cardiac resynchronization therapy (CRT), 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, the spherical harmonic (SPHARM) description is employed to model the ventricular surfaces and a novel SPHARM-based surface correspondence approach is proposed to capture the ventricular wall motion. A hierarchical agglomerative clustering technique is applied to the time series of regional wall thickness to identify candidate pacing sites. Using clinical MRI data in our experiments, we demonstrate that the proposed framework can not only effectively identify suitable pacing sites, but also distinguish patients from normal subjects perfectly to help medical diagnosis and prognosis.

Original languageEnglish (US)
Title of host publicationMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Pages704-711
Number of pages8
Volume8
EditionPt 1
StatePublished - 2005
Externally publishedYes

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Cardiac Resynchronization Therapy
Cardiac Resynchronization Therapy Devices
Heart Ventricles
Cluster Analysis
Heart Failure
Therapeutics

Cite this

Huang, H., Shen, L., Zhang, R., Makedon, F., Hettleman, B., & Pearlman, J. (2005). A prediction framework for cardiac resynchronization therapy via 4D cardiac motion analysis. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention (Pt 1 ed., Vol. 8, pp. 704-711)

A prediction framework for cardiac resynchronization therapy via 4D cardiac motion analysis. / Huang, Heng; Shen, Li; Zhang, Rong; Makedon, Fillia; Hettleman, Bruce; Pearlman, Justin.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 8 Pt 1. ed. 2005. p. 704-711.

Research output: Chapter in Book/Report/Conference proceedingChapter

Huang, H, Shen, L, Zhang, R, Makedon, F, Hettleman, B & Pearlman, J 2005, A prediction framework for cardiac resynchronization therapy via 4D cardiac motion analysis. in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Pt 1 edn, vol. 8, pp. 704-711.
Huang H, Shen L, Zhang R, Makedon F, Hettleman B, Pearlman J. A prediction framework for cardiac resynchronization therapy via 4D cardiac motion analysis. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Pt 1 ed. Vol. 8. 2005. p. 704-711
Huang, Heng ; Shen, Li ; Zhang, Rong ; Makedon, Fillia ; Hettleman, Bruce ; Pearlman, Justin. / A prediction framework for cardiac resynchronization therapy via 4D cardiac motion analysis. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 8 Pt 1. ed. 2005. pp. 704-711
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