Septal Flash Assessment on CRT Candidates Based on Statistical Atlases of Motion

Nicolas Duchateau (1) , Mathieu de Craene (1) , Etel Silva (2) , Marta Sitges (2) , Bart Bijnens (1, 3) , Alejandro Frangi (1, 3)

1 CISTIB - Center for Computational Imaging and Simulation Technologies in Biomedicine
2 Cardiology Department, Thorax Clinic Institute, Hospital Cliınic, Institut d'Investigacions Biomèdiques [Barcelona]
3 ICREA - Institució Catalana de Recerca i Estudis Avançats = Catalan Institution for Research and Advanced Studies

In this paper, we propose a complete framework for the automatic detection and quantification of abnormal heart motion patterns using Statistical Atlases of Motion built from healthy populations. The method is illustrated on CRT patients with identified cardiac dyssyn-chrony and abnormal septal motion on 2D ultrasound (US) sequences. The use of the 2D US modality guarantees that the temporal resolution of the image sequences is high enough to work under a small displacements hypothesis. Under this assumption, the computed displacement fields can be directly considered as cardiac velocities. Comparison of subjects acquired with different spatiotemporal resolutions implies the reorientation and temporal normalization of velocity fields in a common space of coordinates. Statistics are then performed on the reoriented vector fields. Results show the ability of the method to correctly detect abnormal motion patterns and quantify their distance to normality. The use of local p-values for quantifying abnormal motion patterns is believed to be a promising strategy for computing new markers of cardiac dyssynchrony for better characterizing CRT candidates.

Domaines: Imagerie médicale

Nicolas Duchateau, Mathieu de Craene, Etel Silva, Marta Sitges, Bart Bijnens, et al.. Septal Flash Assessment on CRT Candidates Based on Statistical Atlases of Motion. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2009, London, United Kingdom. pp.759-766, ⟨10.1007/978-3-642-04271-3_92⟩. ⟨hal-02320756⟩