Motion-guided segmentation for cine DENSE MRI

Abstract

Defining myocardial contours is often the most time consuming portion of dynamic cardiac MRI image analysis. Displacement encoding with stimulated echoes (DENSE) is a quantitative MRI technique that encodes tissue displacement into the phase of the complex MRI images. Cine DENSE provides a time series of these images, thus facilitating the non-invasive study of myocardial kinematics. Epicardial and endocardial contours need to be defined at each frame on cine DENSE images for the quantification of regional displacement and strain as a function of time. This work presents a reliable and effective two dimensional semi-automated segmentation technique that uses the encoded motion to project a manually defined region of interest through time. Contours can then easily be extracted for each cardiac phase. This method boasts several advantages, including, 1. parameters are based on practical physiological limits, 2. contours are calculated for the first few cardiac phases, where it is difficult to visually distinguish blood from myocardium, and 3. the method is independent of the shape of the tissue delineated and can be applied to short- or long-axis views, and on arbitrary regions of interest. Motion-guided contours were compared to manual contours for six conventional and six slice-followed mid-ventricular short-axis cine DENSE datasets. Using an area measure of segmentation error, the accuracy of the segmentation algorithm was shown to be similar to inter-observer variability. In addition, a radial segmentation error metric was introduced for short-axis data. The average radial epicardial segmentation error was 0.36±0.08 and 0.40±0.10 pixels for slice followed and conventional cine DENSE, respectively, and the average radial endocardial segmentation error was 0.46±0.12 and 0.46±0.16 pixels for slice following and conventional cine DENSE, respectively. Motion-guided segmentation employs the displacement-encoded phase shifts intrinsic to DENSE MRI to accurately propagate a single set of pre-defined contours throughout the remaining cardiac phases.

Accelerated Dynamic Cardiac MRI Using Motion-Guided Compressed Sensing with Regional Sparsity

“…An integral part of strain analysis of cine DENSE images may involve the automatic propagation of endocardial and epicardial contours across cardiac phases using an algorithm called motion guided segmentation (MGS) (40). The performance of MGS depends on image quality.…”

“…To calculate myocardial strain, initial endocardial and epicardial contours were manually delineated at one cardiac phase and propagated automatically to all other cardiac phases (40). After this segmentation process, the phase-reconstructed images were phase-unwrapped and strain values were calculated (96).…”

“…has emerged as a strain imaging technique that, compared to tagging, has equivalent accuracy and better reproducibility (39), and where strain analysis is less time consuming (35,40,41).…”

Novel Methodology for Quantifying Left-Ventricular Dyssynchrony from Cardiac MRI Using Principal Component Analysis

“…Fat suppression was also used to nullify the signal from fat and improve image quality [16,17]. 2D cine DENSE encodes myocardial displacement in the phase of the images [18] so that myocardial strain is calculated from the phase, rather than the magnitude images as described below. The magnitude and phase images …”

“…Strains were reported as the mean of strain values over all segment pixels. Strains were calculated from cine DENSE images with an algorithm developed in Matlab (MathWorks, Natick, Massachusetts) according to the procedure mentioned above [18]. Normal and C) LBBB-HF canines.…”