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Communication Dans Un Congrès Année : 2013

Manifold learning characterization of abnormal myocardial motion patterns: application to CRT-induced changes

Résumé

The present paper aims at quantifying the evolution of a given motion pattern under cardiac resynchronization therapy (CRT). It builds upon techniques for population-based cardiac motion quantifica-tion (statistical atlases, for inter-sequence spatiotemporal alignment and the definition of normal/abnormal motion). Manifold learning is used on spatiotemporal maps of myocardial motion abnormalities to represent a given abnormal pattern and to compare any individual to that pattern. The methodology was applied to 2D echocardiographic sequences in a 4-chamber view from 108 subjects (21 healthy volunteers and 87 CRT candidates) at baseline, with pacing ON, and at 12 months follow-up. Experiments confirmed that recovery of a normal motion pattern is a necessary but not su cient condition for CRT response.
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Dates et versions

hal-02320263 , version 1 (18-10-2019)

Identifiants

Citer

Nicolas Duchateau, Gemma Piella, Adelina Doltra, Lluis Mont, Josep Brugada, et al.. Manifold learning characterization of abnormal myocardial motion patterns: application to CRT-induced changes. Functional Imaging and Modeling of the Heart (FIMH), 2013, London, United Kingdom. pp.450-457, ⟨10.1007/978-3-642-38899-6_53⟩. ⟨hal-02320263⟩
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