Document Detail

A spatiotemporal statistical atlas of motion for the quantification of abnormal myocardial tissue velocities.
MedLine Citation:
PMID:  21315650     Owner:  NLM     Status:  Publisher    
In this paper, we present a new method for the automatic comparison of myocardial motion patterns and the characterization of their degree of abnormality, based on a statistical atlas of motion built from a reference healthy population. Our main contribution is the computation of atlas-based indexes that quantify the abnormality in the motion of a given subject against a reference population, at every location in time and space. The critical computational cost inherent to the construction of an atlas is highly reduced by the definition of myocardial velocities under a small displacements hypothesis. The indexes we propose are of notable interest for the assessment of anomalies in cardiac mobility and synchronicity when applied, for instance, to candidate selection for cardiac resynchronization therapy (CRT). We built an atlas of normality using 2D ultrasound cardiac sequences from 21 healthy volunteers, to which we compared 14 CRT candidates with left ventricular dyssynchrony (LVDYS). We illustrate the potential of our approach in characterizing septal flash, a specific motion pattern related to LVDYS and recently introduced as a very good predictor of response to CRT.
Nicolas Duchateau; Mathieu De Craene; Gemma Piella; Etelvino Silva; Adelina Doltra; Marta Sitges; Bart H Bijnens; Alejandro F Frangi
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-1-26
Journal Detail:
Title:  Medical image analysis     Volume:  -     ISSN:  1361-8423     ISO Abbreviation:  -     Publication Date:  2011 Jan 
Date Detail:
Created Date:  2011-2-14     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9713490     Medline TA:  Med Image Anal     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2010 Elsevier B.V. All rights reserved.
Center for Computational Imaging & Simulation Technologies in Biomedicine, Information & Communication Technologies Department, Universitat Pompeu Fabra, Barcelona, Spain; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Spain.
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