Reproducible extraction of local and global parameters for functional analysis of the left ventricle in 4D MR image data.
OBJECTIVE
Left ventricle (LV) segmentation is required to quantify LV volume and mass parameters. Therefore, spatiotemporal Cine MR sequences in the short and long axis of the heart are acquired. Generally, LV segmentation methods consider short-axis sequences only. The reduced resolution in long-axis direction is one of the main reasons for inaccurate parameter extraction in the apical and basal area. The segmentation approach presented combines short- and long-axis information as well as motion tracking to enable the functional LV analysis in 4D MR Image Data.


METHODS
First, anatomical landmarks like the mitral valve and the apex are defined in long-axis views in diastolic and systolic phase in order to specify the upper and lower boundary of the LV. Second, motion field approximation using non-linear registration enables the automatic contour propagation to all time points. Third, intersection planes are defined parallel to the mitral valve plane covering the whole ventricle. Finally, the 4D LV surface model is generated appending all in-plane contours. The segmentation results in short-axis images are checked and adjusted interactively and quantitative parameters are extracted.


RESULTS
For evaluation the contours of 19 different datasets were traced by two medical experts using a contour drawing tool and the new segmentation tool. The results were compared to evaluate automatic contour propagation, robustness of the segmentation as well as interaction time.


CONCLUSIONS
The automatic contour propagation enables the fast and reproducible generation of a 4D model for the functional analysis of the heart. The interaction time is decreased from approx. 60 minutes to 10 minutes per case. Inter- and intraobserver differences of the extracted parameters are decreased significantly.
Säring
Dennis
D
Department of Medical Informatics, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany. d.saering@uke.uni-hamburg.de
Relan
J
J
Ehrhardt
Jan
J
Müllerleile
K
K
Bahrmeyer
A
A
Groth
M
M
Handels
Heinz
H
D003198:Computer Simulation; D003971:Diastole; D006352:Heart Ventricles / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D019028:Magnetic Resonance Imaging, Cine / Q000295:instrumentation / Q000379:methods*; D008943:Mitral Valve / Q000473:pathology; D008962:Models, Theoretical; D015203:Reproducibility of Results; D013599:Systole; D020257:Ventricular Remodeling