Fast LV motion estimation using subspace approximation techniques

MulViMotion: Shape-Aware 3D Myocardial Motion Tracking From Multi-View Cardiac MRI

Recovering the 3D motion of the heart from cine cardiac magnetic resonance (CMR) imaging enables the assessment of regional myocardial function and is important for understanding and analyzing cardiovascular disease. However, 3D cardiac motion estimation is challenging because the acquired cine CMR images are usually 2D slices which limit the accurate estimation of through-plane motion. To address this problem, we propose a novel multi-view motion estimation network (MulViMotion), which integrates 2D cine CMR images acquired in short-axis and long-axis planes to learn a consistent 3D motion field of the heart. In the proposed method, a hybrid 2D/3D network is built to generate dense 3D motion fields by learning fused representations from multi-view images. To ensure that the motion estimation is consistent in 3D, a shape regularization module is introduced during training, where shape information from multi-view images is exploited to provide weak supervision to 3D motion estimation. We extensively evaluate the proposed method on 2D cine CMR images from 580 subjects of the UK Biobank study for 3D motion tracking of the left ventricular myocardium. Experimental results show that the proposed method quantitatively and qualitatively outperforms competing methods.

Regional cardiac function analysis from tagged MRI images. Comparison of techniques: Harmonic-Phase (HARP) versus Sinusoidal-Modeling (SinMod) analysis

Cardiac MRI tagging is a valuable technique for evaluating regional heart function. Currently, there are a number of different techniques for analyzing the tagged images. Specifically, k-space-based analysis techniques showed to be much faster than image-based techniques, where harmonic-phase (HARP) and sine-wave modeling (SinMod) stand as two famous techniques of the former group, which are frequently used in clinical studies. In this study, we compared HARP and SinMod and studied inter-observer variability between the two techniques for evaluating myocardial strain and apical-to-base torsion in numerical phantom, nine healthy controls, and thirty diabetic patients. Based on the ground-truth numerical phantom measurements (strain = -20% and rotation angle = -4.4°), HARP and SinMod resulted in overestimation (in absolute value terms) of strain by 1% and 5% (strain values), and of rotation angle by 0.4° and 2.0°, respectively. For the in-vivo results, global strain and torsion ranges were -10.6% to -35.3% and 1.8°/cm to 12.7°/cm in patients, and -17.8% to -32.7% and 1.8°/cm to 12.3°/cm in volunteers. On average, SinMod overestimated strain measurements by 5.7% and 5.9% (strain values) in the patients and volunteers, respectively, compared to HARP, and overestimated torsion measurements by 2.9°/cm and 2.5°/cm in the patients and volunteers, respectively, compared to HARP. Location-wise, the ranges for basal, mid-ventricular, and apical strain in patients (volunteers) were -8.4% to -31.5% (-11.6% to -33.3%), -6.3% to -37.2% (-17.8% to -33.3%), and -5.2% to -38.4% (-20.0% to -33.2%), respectively. SinMod overestimated strain in the basal, mid-ventricular, and apical slices by 4.7% (5.7%), 5.9% (5.5%), and 8.9% (6.8%), respectively, compared to HARP in the patients (volunteers). Nevertheless, there existed good correlation between the HARP and SinMod measurements. Finally, there were no significant strain or torsion measurement differences between patients and volunteers. There existed good inter-observer agreement, as all measurement differences lied within the Bland-Altman ± 2 standard-deviation (SD) difference limits. In conclusion, despite the consistency of the results by either HARP or SinMod and acceptable agreement of the generated strain and torsion patterns by both techniques, SinMod systematically overestimated the measurements compared to HARP. Under current operating conditions, the measurements from HARP and SinMod cannot be used interchangeably.

Quantification of regional myocardial wall motion by cardiovascular magnetic resonance

Cardiovascular magnetic resonance (CMR) is a versatile tool that also allows comprehensive and accurate measurement of both global and regional myocardial contraction. Quantification of regional wall motion parameters, such as strain, strain rate, twist and torsion, has been shown to be more sensitive to early-stage functional alterations. Since the invention of CMR tagging by magnetization saturation in 1988, several CMR techniques have been developed to enable the measurement of regional myocardial wall motion, including myocardial tissue tagging, phase contrast mapping, displacement encoding with stimulated echoes (DENSE), and strain encoded (SENC) imaging. These techniques have been developed with their own advantages and limitations. In this review, two widely used and closely related CMR techniques, i.e., tissue tagging and DENSE, will be discussed from the perspective of pulse sequence development and image-processing techniques. The clinical and preclinical applications of tissue tagging and DENSE in assessing wall motion mechanics in both normal and diseased hearts, including coronary artery diseases, hypertrophic cardiomyopathy, aortic stenosis, and Duchenne muscular dystrophies, will be discussed.

Cardiac motion and deformation recovery from MRI: a review

Magnetic resonance imaging (MRI) is a highly advanced and sophisticated imaging modality for cardiac motion tracking and analysis, capable of providing 3D analysis of global and regional cardiac function with great accuracy and reproducibility. In the past few years, numerous efforts have been devoted to cardiac motion recovery and deformation analysis from MR image sequences. Many approaches have been proposed for tracking cardiac motion and for computing deformation parameters and mechanical properties of the heart from a variety of cardiac MR imaging techniques. In this paper, an updated and critical review of cardiac motion tracking methods including major references and those proposed in the past ten years is provided. The MR imaging and analysis techniques surveyed are based on cine MRI, tagged MRI, phase contrast MRI, DENSE, and SENC. This paper can serve as a tutorial for new researchers entering the field.

Myocardial tagging by cardiovascular magnetic resonance: evolution of techniques--pulse sequences, analysis algorithms, and applications

Cardiovascular magnetic resonance (CMR) tagging has been established as an essential technique for measuring regional myocardial function. It allows quantification of local intramyocardial motion measures, e.g. strain and strain rate. The invention of CMR tagging came in the late eighties, where the technique allowed for the first time for visualizing transmural myocardial movement without having to implant physical markers. This new idea opened the door for a series of developments and improvements that continue up to the present time. Different tagging techniques are currently available that are more extensive, improved, and sophisticated than they were twenty years ago. Each of these techniques has different versions for improved resolution, signal-to-noise ratio (SNR), scan time, anatomical coverage, three-dimensional capability, and image quality. The tagging techniques covered in this article can be broadly divided into two main categories: 1) Basic techniques, which include magnetization saturation, spatial modulation of magnetization (SPAMM), delay alternating with nutations for tailored excitation (DANTE), and complementary SPAMM (CSPAMM); and 2) Advanced techniques, which include harmonic phase (HARP), displacement encoding with stimulated echoes (DENSE), and strain encoding (SENC). Although most of these techniques were developed by separate groups and evolved from different backgrounds, they are in fact closely related to each other, and they can be interpreted from more than one perspective. Some of these techniques even followed parallel paths of developments, as illustrated in the article. As each technique has its own advantages, some efforts have been made to combine different techniques together for improved image quality or composite information acquisition. In this review, different developments in pulse sequences and related image processing techniques are described along with the necessities that led to their invention, which makes this article easy to read and the covered techniques easy to follow. Major studies that applied CMR tagging for studying myocardial mechanics are also summarized. Finally, the current article includes a plethora of ideas and techniques with over 300 references that motivate the reader to think about the future of CMR tagging.

Estimating Myocardial Motion by 4D Image Warping

A method for spatio-temporally smooth and consistent estimation of cardiac motion from MR cine sequences is proposed. Myocardial motion is estimated within a 4-dimensional (4D) registration framework, in which all 3D images obtained at different cardiac phases are simultaneously registered. This facilitates spatio-temporally consistent estimation of motion as opposed to other registration-based algorithms which estimate the motion by sequentially registering one frame to another. To facilitate image matching, an attribute vector (AV) is constructed for each point in the image, and is intended to serve as a "morphological signature" of that point. The AV includes intensity, boundary, and geometric moment invariants (GMIs). Hierarchical registration of two image sequences is achieved by using the most distinctive points for initial registration of two sequences and gradually adding less-distinctive points to refine the registration. Experimental results on real data demonstrate good performance of the proposed method for cardiac image registration and motion estimation. The motion estimation is validated via comparisons with motion estimates obtained from MR images with myocardial tagging.

Biventricular myocardial strains via nonrigid registration of anatomical NURBS model [corrected]

We present research in which both left and right ventricular deformation is estimated from tagged cardiac magnetic resonance imaging using volumetric deformable models constructed from nonuniform rational B-splines (NURBS). The four model types considered and compared for the left ventricle include two Cartesian NURBS models--one with a cylindrical parameter assignment and one with a prolate spheroidal parameter assignment. The remaining two are non-Cartesian, i.e., prolate spheroidal and cylindrical each with their respective prolate spheroidal and cylindrical parameter assignment regimes. These choices were made based on the typical shape of the left ventricle. For each frame starting with end-diastole, a NURBS model is constructed by fitting two surfaces with the same parameterization to the corresponding set of epicardial and endocardial contours from which a volumetric model is created. Using normal displacements of the three sets of orthogonal tag planes as well as displacements of contour/tag line intersection points and tag plane intersection points, one can solve for the optimal homogeneous coordinates, in a weighted least squares sense, of the control points of the deformed NURBS model at end-diastole using quadratic programming. This allows for subsequent nonrigid registration of the biventricular model at end-diastole to all later time frames. After registration of the model to all later time points, the registered NURBS models are temporally lofted in order to create a comprehensive four-dimensional NURBS model. From the lofted model, we can extract three-dimensional myocardial deformation fields and corresponding Lagrangian and Eulerian strain maps which are local measures of nonrigid deformation. The results show that, in the case of simulated data, the quadratic Cartesian NURBS models with the cylindrical and prolate spheroidal parameter assignments outperform their counterparts in predicting normal strain. The decreased complexity associated with the Cartesian model with the cylindrical parameter assignment prompted its use for subsequent calculations. Lagrangian strains in three canine data, a normal human, and a patient with history of myocardial infarction are presented. Eulerian strains for the normal human data are also included.

Fast tracking of cardiac motion using 3D-HARP

Magnetic resonance (MR) tagging is capable of accurate, noninvasive quantification of regional myocardial function. Routine clinical use, however, is hindered by cumbersome and time-consuming postprocessing procedures. We propose a fast, semiautomatic method for tracking three-dimensional (3-D) cardiac motion from a temporal sequence of short- and long-axis tagged MR images. The new method, called 3-D-HARmonic Phase (3D-HARP), extends the HARP approach, previously described for two-dimensional (2-D) tag analysis, to 3-D. A 3-D material mesh model is built to represent a collection of material points inside the left ventricle (LV) wall at a reference time. Harmonic phase, a material property that is time-invariant, is used to track the motion of the mesh through a cardiac cycle. Various motion-related functional properties of the myocardium, such as circumferential strain and left ventricular twist, are computed from the tracked mesh. The correlation analysis of 3D-HARP and FINDTAGS + Tag Strain(E) Analysis (TEA), which are well-established tag analysis techniques, shows that the regression coefficients of circumferential strain (E(CC)) and twist angle are r2 = 0.8605 and r2 = 0.8645, respectively. The total time required for tracking 3-D cardiac motion is approximately 10 min in a 9 timeframe tagged MRI dataset and has the potential to be much faster.

LV Shape and Motion: B-Spline-Based Deformable Model and Sequential Motion Decomposition

In this paper, we extend a previous work by J. Park and propose a uniform framework to reconstruct left ventricle (LV) geometry/motion from tagged MR images. In our work, the LV is modeled as a generalized prolate spheroid, and its motion is decomposed into four components-global translation, polar radial/z-axis compression, twisting, and bending. By formulating model parameters as tensor products of B-splines, we develop efficient algorithms to quickly reconstruct LV geometry/motion from extracted boundary contours and tracked planar tags. Experiments on both synthesized and in vivo data are also reported.

Reconstruction of nonuniformly sampled images in spline spaces

This paper presents a novel approach to the reconstruction of images from nonuniformly spaced samples. This problem is often encountered in digital image processing applications. Nonrecursive video coding with motion compensation, spatiotemporal interpolation of video sequences, and generation of new views in multicamera systems are three possible applications. We propose a new reconstruction algorithm based on a spline model for images. We use regularization, since this is an ill-posed inverse problem. We minimize a cost function composed of two terms: one related to the approximation error and the other related to the smoothness of the modeling function. All the processing is carried out in the space of spline coefficients; this space is discrete, although the problem itself is of a continuous nature. The coefficients of regularization and approximation filters are computed exactly by using the explicit expressions of B-spline functions in the time domain. The regularization is carried out locally, while the computation of the regularization factor accounts for the structure of the nonuniform sampling grid. The linear system of equations obtained is solved iteratively. Our results show a very good performance in motion-compensated interpolation applications.

Consistent Estimation of Cardiac Motions by 4D Image Registration

A 4D image registration method is proposed for consistent estimation of cardiac motion from MR image sequences. Under this 4D registration framework, all 3D cardiac images taken at different time-points are registered simultaneously, and motion estimated is enforced to be spatiotemporally smooth, thereby overcoming potential limitations of some methods that typically estimate cardiac deformation sequentially from one frame to another, instead of treating the entire set of images as a 4D volume. To facilitate our image matching process, an attribute vector is designed for each point in the image to include intensity, boundary and geometric moment invariants (GMIs). Hierarchical registration of two image sequences is achieved by using the most distinctive points for initial registration of two sequences and gradually adding less-distinctive points for refinement of registration. Experimental results on real data demonstrate good performance of the proposed method in registering cardiac images and estimating motions from cardiac image sequences.

Regenerating MR tagged images using harmonic phase (HARP) methods

Magnetic resonance tagging has proven useful in the visualization and quantification of cardiac motion. Traditionally, tags are designed to have crisp geometric profiles in order to enhance both visualization and detection of tags. Recent image acquisition and analysis methods, however, have been designed to exploit sinusoidal tag profiles. This paper presents a method based on harmonic phase (HARP) concepts to synthesize tag lines that have both crisp profiles and alternative orientations from the original sinusoidal patterns. Results are demonstrated on images acquired with SPAMM, CSPAMM, and fast-HARP pulse sequences.

Extraction of left ventricular contours from left ventriculograms by means of a neural edge detector

We propose a method for extracting the left ventricular (LV) contours from left ventriculograms by means of a neural edge detector (NED) in order to extract the contours which accord with those traced by a cardiologist. The NED is a supervised edge detector based on a modified multilayer neural network, and is trained by use of a modified back-propagation algorithm. The NED can acquire the function of a desired edge detector through training with a set of input images and the desired edges obtained from the contours traced by a cardiologist. The proposed contour-extraction method consists of 1) detection of "subjective edges" by use of the NED; 2) extraction of rough contours by use of low-pass filtering and edge enhancement; and 3) a contour-tracing method based on the contour candidates synthesized from the edges detected by the NED and the rough contours. Through experiments, it was shown that the proposed method was able to extract the contours in agreement with those traced by an experienced cardiologist, i.e., we achieved an average contour error of 6.2% for left ventriculograms at end-diastole and an average difference between the ejection fractions obtained from the manually traced contours and those obtained from the computer-extracted contours of 4.1%.

Biomechanical dynamics of the heart with MRI

Magnetic resonance imaging (MRI) provides a noninvasive way to evaluate the biomechanical dynamics of the heart. MRI can provide spatially registered tomographic images of the heart in different phases of the cardiac cycle, which can be used to assess global cardiac function and regional endocardial surface motion. In addition, MRI can provide detailed information on the patterns of motion within the heart wall, permitting calculation of the evolution of regional strain and related motion variables within the wall. These show consistent patterns of spatial and temporal variation in normal subjects, which are affected by alterations of function due to disease. Although still an evolving technique, MRI shows promise as a new method for research and clinical evaluation of cardiac dynamics.

A MAP framework for tag line detection in SPAMM data using Markov random fields on the B-spline solid

Magnetic resonance (MR) tagging is a technique for measuring heart deformations through creation of a stripe grid pattern on cardiac images. In this paper, we present a maximum a posteriori (MAP) framework for detecting tag lines using a Markov random field (MRF) defined on the lattice generated by three-dimensional (3-D) and four-dimensional (4-D) (3-D + t) uniform sampling of B-spline models. In the 3-D case, MAP estimation is cast for detecting present tag features in the current image given an initial solid from the previous frame (the initial undeformed solid is manually positioned by clicking on corner points of a cube). The method also allows the parameters of the solid model, including the number of knots and the spline order, to be adjusted within the same framework. Fitting can start with a solid with less knots and lower spline order and proceed to one with more knots and/or higher order so as to achieve more accuracy and/or higher order of smoothness. In the 4-D case, the initial model is considered to be the linear interpolation of a sequence of optimal solids obtained from 3-D tracking. The same framework proposed for the 3-D case can once again be applied to arrive at a 4-D B-spline model with a higher temporal order.

Feasibility of detecting cardiac torsion in myocardial perfusion gated SPECT data

BACKGROUND

The dynamic twisting component of cardiac motion is not accounted for by radionuclide techniques so that maps of perfusion and wall thickening are motion-blurred by torsion. This study examined whether torsion can be estimated from gated single photon emission computed tomography data and whether torsion corrections affect cardiac measurements.

METHODS AND RESULTS

Technetium 99m sestamibi myocardial perfusion gated tomograms were selected retrospectively for 52 patients who had x-ray contrast arteriograms: 12 with normal perfusion (group 1), 12 with abnormal perfusion (group 2), and 28 studied after angioplasty (group 3). The 8 gated perfusion maps were transformed by contrast normalization, the count minimums of which were tracked to quantify torsion. Measured torsion was used to correct maps of perfusion and wall thickening. Torsion was found to be visually detectable equally well in groups 1 and 2. Apical torsion was significantly greater for group 1 than groups 2 and 3 (15 degrees +/- 9 degrees vs 9 degrees +/- 15 degrees and 2 degrees +/- 12 degrees ) and was opposite in sign for patients with apical aneurysms (-4 degrees +/- 13 degrees ) and for patients after coronary artery bypass grafting (CABG) (-4 degrees +/- 15 degrees ). Maximum percent count differences were 10% +/- 16% between torsion-corrected versus uncorrected perfusion maps. The greatest wall thickening differences were seen for patients with left ventricular apical aneurysms and for patients after CABG versus group 1 (10% +/- 6% and 8% +/- 6% vs 3% +/- 1%, respectively).

CONCLUSIONS

It is feasible to detect cardiac torsion in the majority of Tc-99m sestamibi myocardial perfusion scans. Abnormal twisting patterns distinguished patients after CABG and those with left ventricular aneurysms from subjects with normal perfusion in a manner similar to magnetic resonance imaging observations.