Tracking myocardial motion from cine DENSE images using spatiotemporal phase unwrapping and temporal fitting

Balanced multipoint displacement encoding for DENSE MRI

Displacement encoding with stimulated echoes (DENSE) is a quantitative imaging technique that encodes tissue displacement in the phase of the acquired signal. Various DENSE sequences have encoded displacement using methods analogous to the simple multipoint methods of phase contrast (PC) MRI. We developed general n-dimension balanced multipoint encoding for DENSE. Using these methods, phase noise variance decreased experimentally by 73.7%, 65.6%, and 61.9% compared with simple methods, which closely matched the theoretical decreases of 75%, 66.7%, and 62.5% for one-dimensional (1D), 2D, and 3D encoding, respectively. Phase noise covariances decreased by 99.2% and 99.3% for balanced 2D and 3D encoding, consistent with the zero-covariance prediction. The direction bias inherent to the simple methods was decreased to almost zero using balanced methods. Reduced phase noise and improved displacement and strain maps using balanced methods were visually observed in phantom and volunteer images. Balanced multipoint encoding can also be applied to PC MRI.

Optimum fuzzy filters for phase-contrast magnetic resonance imaging segmentation

PURPOSE

To develop and validate a multidimensional segmentation and filtering methodology for accurate blood flow velocity field reconstruction from phase-contrast magnetic resonance imaging (PC MRI).

MATERIALS AND METHODS

The proposed technique consists of two steps: (1) the boundary of the vessel is automatically segmented using the active contour approach; and (2) the noise embedded within the segmented vector field is selectively removed using a novel fuzzy adaptive vector median filtering (FAVMF) technique. This two-step segmentation process was tested and validated on 111 synthetically generated PC MRI slices and on 10 patients with congenital heart disease.

RESULTS

The active contour technique was effective for segmenting blood vessels having a sensitivity and specificity of 93.1% and 92.1% using manual segmentation as a reference standard. FAVMF was the superior technique in filtering out noise vectors, when compared with other commonly used filters in PC MRI (P < 0.05). The peak wall shear rate calculated from the PC MRI data (248 +/- 39 sec(-1)), was significantly decreased to (146 +/- 26 sec(-1)) after the filtering process.

CONCLUSION

The proposed two-step segmentation and filtering methodology is more accurate compared to a single-step segmentation process for post-processing of PC MRI data.

Motion-guided segmentation for cine DENSE MRI

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.

Cardiac motion recovery via active trajectory field models

Cardiovascular researchers are constantly developing new and innovative medical imaging technologies, striving to improve the understanding, diagnosis, and treatment of cardiovascular dysfunction. Combining these sophisticated imaging methods with advancements in image understanding via computational intelligence will continue to advance the frontier of cardiovascular medicine. Recently, researchers have turned to a new class of tissue motion imaging techniques, including displacement encoding with stimulated echoes (DENSE) in cardiac magnetic resonance (cMR) imaging, to directly quantify cardiac displacement and produce accurate spatiotemporal measurements of myocardial strain, twist, and torsion. The associated analysis of DENSE cMR and other tissue motion imagery, however, represents a major bottleneck in the study of intramyocardial mechanics. In the computational intelligence area of deformable models, this paper develops an automated motion recovery technique termed active trajectory field models (ATFMs) geared toward these new motion imaging protocols, offering quantitative physiological measurements without the pains of manual analyses. This novel generative deformable model exploits both image information and prior knowledge of cardiac motion, utilizing a point distribution model derived from a training set of myocardial trajectory fields to automatically recover cardiac motion from a noisy image sequence. The effectiveness of the ATFM method is demonstrated by quantifying myocardial motion in 2-D short-axis murine DENSE cMR image sequences both before and after myocardial infarction, producing results comparable to existing semiautomatic analysis methods.

3D myocardial tissue tracking with slice followed cine DENSE MRI

PURPOSE

To track three-dimensional (3D) myocardial tissue motion using slice followed cine displacement encoded imaging with stimulated echoes (DENSE).

MATERIALS AND METHODS

Slice following (SF) has previously been developed for 2D myocardial tagging to compensate for the effect of through-plane motion on 2D tissue tracking. By incorporating SF into a cine DENSE sequence, and applying displacement encoding in three orthogonal directions, we demonstrate the ability to track discrete elements of a slice of myocardium in 3D as the heart moves through the cardiac cycle. The SF cine DENSE tracking algorithm was validated on a moving phantom, and the effects of through-plane motion on 2D cardiac strain were investigated in six healthy subjects.

RESULTS

A through-plane tracking accuracy of 0.46 +/- 0.32 mm was measured for a typical range of myocardial motion using a rotating phantom. In vivo 3D measurements of cardiac motion were consistent with prior myocardial tagging results. Through-plane rotation in a mid-ventricularshort-axis view was shown to decrease the magnitude of the 2D end-systolic circumferential strain by 3.91 +/- 0.43% and increase the corresponding radial strain by 6.01 +/- 1.07%.

CONCLUSION

Slice followed cine DENSE provides an accurate method for 3D tissue tracking.

Semiautomated segmentation of myocardial contours for fast strain analysis in cine displacement-encoded MRI

The purposes of this study were to develop a semiautomated cardiac contour segmentation method for use with cine displacement-encoded MRI and evaluate its accuracy against manual segmentation. This segmentation model was designed with two distinct phases: preparation and evolution. During the model preparation phase, after manual image cropping and then image intensity standardization, the myocardium is separated from the background based on the difference in their intensity distributions, and the endo- and epi-cardial contours are initialized automatically as zeros of an underlying level set function. During the model evolution phase, the model deformation is driven by the minimization of an energy function consisting of five terms: model intensity, edge attraction, shape prior, contours interaction, and contour smoothness. The energy function is minimized iteratively by adaptively weighting the five terms in the energy function using an annealing algorithm. The validation experiments were performed on a pool of cine data sets of five volunteers. The difference between the semiautomated segmentation and manual segmentation was sufficiently small as to be considered clinically irrelevant. This relatively accurate semiautomated segmentation method can be used to significantly increase the throughput of strain analysis of cine displacement-encoded MR images for clinical applications.

Imaging two-dimensional displacements and strains in skeletal muscle during joint motion by cine DENSE MR

The objective of this study was to apply cine magnetic resonance imaging (MRI) using displacement encoding with stimulated echoes (DENSE) to measure the dynamic two-dimensional (2D) displacement and Lagrangian strain fields in the biceps brachii muscle. Six healthy volunteers underwent cine DENSE MRI during repeated elbow flexion against the load of gravity. Displacement encoded dynamic images of the upper arm were acquired with spatial and temporal resolutions of 1.9 x 1.9 mm(2) and 30 ms, respectively. Pixel-wise Lagrangian displacement and strain fields were calculated from the measured images. We extracted the first and second principal strains (E1 and E2) along the centerline and anterior regions of the muscle. E1 and E2 were relatively uniform along the anterior region. However, E1 and E2 were both non-uniform along the centerline region-normalized values for E1 and E2 varied over the ranges of 0.27-1.35, and 0.45-2.36, respectively. The directions of the first and second principal strains varied throughout the muscle and showed that the direction of principal shortening is not necessarily aligned with fascicle direction. This study demonstrates the utility of cine DENSE MRI for analyzing skeletal muscle mechanics and provides data describing the in vivo mechanics of muscle tissue to a level of detail that has not been previously possible.

Left ventricular deformation recovery from cine MRI using an incompressible model

This paper presents a method for 3-D deformation recovery of the left ventricular (LV) wall from anatomical cine magnetic resonance imaging (MRI). The method is based on a deformable model that is incompressible, a desired property since the myocardium has been shown to be nearly incompressible. The LV wall needs to be segmented in an initial frame after which the method automatically determines the deformation everywhere in the LV wall throughout the cardiac cycle. Two studies were conducted to validate the method. In the first study, the deformation recovered from a 3-D anatomical cine MRI of a healthy volunteer was compared against the manual segmentation of the LV wall and against the corresponding 3-D tagged cine MRI. The average volume agreement between the model and the manual segmentation had a false positive rate of 3%, false negative rate of 3%, and true positive rate of 93%. The average distance between the model and manually determined intersections of perpendicular tag planes was 1.6 mm (1.1 pixel). Another set of 3-D anatomical and tagged MRI scans was taken of the same volunteer four months later. The method was applied to the second set and the recovered deformation was very similar to the one obtained from the first set. In the second study, the method was applied to 3-D anatomical cine MRI scans of three patients with ventricular dyssynchrony and three age-matched healthy volunteers. The LV wall deformations recovered for the three normals agreed well and the recovered strains were similar to those reported by other researchers for normal subjects. Strains and displacements of the three patients were clearly smaller than those of the three normals indicating reduced cardiac function. The deformation recovered for the three normals and the three patients was validated against manual segmentation and corresponding tag cine MRI scans and the agreement was similar to that of the first validation study.