Paper Info
Title
Improving Understanding of Long-Term Cardiac Functional Remodelling via Cross-Sectional Analysis of Polyaffine Motion Parameters.
Abstract
Changes in cardiac motion dynamics occur as a direct result of alterations in structure, hemodynamics, and electrical activation. Abnormal ventricular motion compromises long-term sustainability of heart function. While motion abnormalities are reasonably well documented and have been identified for many conditions, the remodelling process that occurs as a condition progresses is not well understood. Thanks to the recent development of a method to quantify full ventricular motion (as opposed to 1D abstractions of the motion) with few comparable parameters, population-based statistical analysis is possible. A method for describing functional remodelling is proposed by performing statistical cross-sectional analysis of spatio-temporally aligned subject-specific polyaffine motion parameters. The proposed method is applied to pathological and control datasets to compare functional remodelling occurring as a process of disease as opposed to a process of ageing.
Year
DOI
Venue
2017
10.1007/978-3-319-59448-4_6
Lecture Notes in Computer Science
Field
DocType
Volume
Population,Biological system,Simulation,Canonical correlation,Computer science,Motion parameter,Cardiac motion,Statistical analysis
Conference
10263
ISSN
Citations 
PageRank 
0302-9743
0
0.34
References 
Authors
6
3
Name
Order
Citations
PageRank
Kristin McLeod19710.68
Maxime Sermesant21111122.97
Xavier Pennec35021357.08