Automatic 3D tracking of cardiac material markers using slice-following and harmonic-phase MRI

A comprehensive comparison between shortest-path HARP refinement, SinMod, and DENSEanalysis processing tools applied to CSPAMM and DENSE images

We addressed comprehensively the performance of Shortest-Path HARP Refinement (SP-HR), SinMod, and DENSEanalysis using 2D slices of synthetic CSPAMM and DENSE images with realistic contrasts obtained from 3D phantoms. The three motion estimation techniques were interrogated under ideal and no-ideal conditions (with MR induced artifacts, noise, and through-plane motion), considering several resolutions and noise levels. Under noisy conditions, and for isotropic pixel sizes of 1.5 mm and 3.0 mm in CSPAMM and DENSE images respectively, the nRMSE obtained for the circumferential and radial strain components were 10.7 ± 10.8% and 25.5 ± 14.8% using SP-HR, 11.9 ± 2.5% and 29.3 ± 6.5% using SinMod, and 6.4 ± 2.0% and 18.2 ± 4.6% using DENSEanalysis. Overall, the results showed that SP-HR tends to fail for large tissue motions, whereas SinMod and DENSEanalysis gave accurate displacement and strain field estimations, being the last which performed the best.

Meshless deformable models for 3D cardiac motion and strain analysis from tagged MRI

Tagged magnetic resonance imaging (TMRI) provides a direct and noninvasive way to visualize the in-wall deformation of the myocardium. Due to the through-plane motion, the tracking of 3D trajectories of the material points and the computation of 3D strain field call for the necessity of building 3D cardiac deformable models. The intersections of three stacks of orthogonal tagging planes are material points in the myocardium. With these intersections as control points, 3D motion can be reconstructed with a novel meshless deformable model (MDM). Volumetric MDMs describe an object as point cloud inside the object boundary and the coordinate of each point can be written in parametric functions. A generic heart mesh is registered on the TMRI with polar decomposition. A 3D MDM is generated and deformed with MR image tagging lines. Volumetric MDMs are deformed by calculating the dynamics function and minimizing the local Laplacian coordinates. The similarity transformation of each point is computed by assuming its neighboring points are making the same transformation. The deformation is computed iteratively until the control points match the target positions in the consecutive image frame. The 3D strain field is computed from the 3D displacement field with moving least squares. We demonstrate that MDMs outperformed the finite element method and the spline method with a numerical phantom. Meshless deformable models can track the trajectory of any material point in the myocardium and compute the 3D strain field of any particular area. The experimental results on in vivo healthy and patient heart MRI show that the MDM can fully recover the myocardium motion in three dimensions.

A robust and accurate center-frequency estimation (RACE) algorithm for improving motion estimation performance of SinMod on tagged cardiac MR images without known tagging parameters

A robust and accurate center-frequency (CF) estimation (RACE) algorithm for improving the performance of the local sine-wave modeling (SinMod) method, which is a good motion estimation method for tagged cardiac magnetic resonance (MR) images, is proposed in this study. The RACE algorithm can automatically, effectively and efficiently produce a very appropriate CF estimate for the SinMod method, under the circumstance that the specified tagging parameters are unknown, on account of the following two key techniques: (1) the well-known mean-shift algorithm, which can provide accurate and rapid CF estimation; and (2) an original two-direction-combination strategy, which can further enhance the accuracy and robustness of CF estimation. Some other available CF estimation algorithms are brought out for comparison. Several validation approaches that can work on the real data without ground truths are specially designed. Experimental results on human body in vivo cardiac data demonstrate the significance of accurate CF estimation for SinMod, and validate the effectiveness of RACE in facilitating the motion estimation performance of SinMod.

Effect of through-plane motion on left ventricular rotation: a study using slice-following harmonic phase imaging

Noninvasive quantification of regional left ventricular rotation may improve understanding of cardiac function. Current methods used to quantify rotation typically acquire data on a set of prescribed short-axis slices, neglecting effects due to through-plane myocardial motion. We combine principles of slice-following tagged imaging with harmonic phase analysis methods to account for through-plane motion in regional rotation measurements. We compare rotation and torsion measurements obtained using our method to those obtained from imaging datasets acquired without slice-following. Our results in normal volunteers demonstrate differences in the general trends of average and regional rotation-time plots in midbasal slices and the rotation versus circumferential strain loops. We observe substantial errors in measured peak average rotation of the order of 58% for basal slices (due to change in the pattern of the curve), -6.6% for midventricular slices, and -8.5% for apical slices; and an average error in base-to-apex torsion of 19% when through-plane motion is not considered. This study concludes that due to an inherent base-to-apex gradient in rotation that exists in the left ventricular, accounting for through-plane motion is critical to the accuracy of left ventricular rotation quantification.

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.

3D left ventricular strain from unwrapped harmonic phase measurements

PURPOSE

To validate a method for measuring 3D left ventricular (LV) strain from phase-unwrapped harmonic phase (HARP) images derived from tagged cardiac magnetic resonance imaging (MRI).

MATERIALS AND METHODS

A set of 40 human subjects were imaged with tagged MRI. In each study the HARP phase was computed and unwrapped in each short-axis and long-axis image. Inconsistencies in unwrapped phase were resolved using branch cuts manually placed with a graphical user interface. 3D strain maps were computed for all imaged timeframes in each study. The strain from unwrapped phase (SUP) and displacements were compared to those estimated by a feature-based (FB) technique and a HARP technique.

RESULTS

3D strain was computed in each timeframe through systole and mid-diastole in approximately 30 minutes per study. The standard deviation of the difference between strains measured by the FB and the SUP methods was less than 5% of the average of the strains from the two methods. The correlation between peak circumferential strain measured using the SUP and HARP techniques was over 83%.

CONCLUSION

The SUP technique can reconstruct full 3D strain maps from tagged MR images through the cardiac cycle in a reasonable amount of time and user interaction compared to other 3D analysis methods.

Analytical method to measure three-dimensional strain patterns in the left ventricle from single slice displacement data

BACKGROUND

Displacement encoded Cardiovascular MR (CMR) can provide high spatial resolution measurements of three-dimensional (3D) Lagrangian displacement. Spatial gradients of the Lagrangian displacement field are used to measure regional myocardial strain. In general, adjacent parallel slices are needed in order to calculate the spatial gradient in the through-slice direction. This necessitates the acquisition of additional data and prolongs the scan time. The goal of this study is to define an analytic solution that supports the reconstruction of the out-of-plane components of the Lagrangian strain tensor in addition to the in-plane components from a single-slice displacement CMR dataset with high spatio-temporal resolution. The technique assumes incompressibility of the myocardium as a physical constraint.

RESULTS

The feasibility of the method is demonstrated in a healthy human subject and the results are compared to those of other studies. The proposed method was validated with simulated data and strain estimates from experimentally measured DENSE data, which were compared to the strain calculation from a conventional two-slice acquisition.

CONCLUSION

This analytical method reduces the need to acquire data from adjacent slices when calculating regional Lagrangian strains and can effectively reduce the long scan time by a factor of two.

Myocardial tissue tagging with cardiovascular magnetic resonance

Cardiovascular magnetic resonance (CMR) is currently the gold standard for assessing both global and regional myocardial function. New tools for quantifying regional function have been recently developed to characterize early myocardial dysfunction in order to improve the identification and management of individuals at risk for heart failure. Of particular interest is CMR myocardial tagging, a non-invasive technique for assessing regional function that provides a detailed and comprehensive examination of intra-myocardial motion and deformation. Given the current advances in gradient technology, image reconstruction techniques, and data analysis algorithms, CMR myocardial tagging has become the reference modality for evaluating multidimensional strain evolution in the human heart. This review presents an in depth discussion on the current clinical applications of CMR myocardial tagging and the increasingly important role of this technique for assessing subclinical myocardial dysfunction in the setting of a wide variety of myocardial disease processes.

Biomechanically-constrained 4D estimation of myocardial motion

We propose a method for the analysis of cardiac images with the goal of reconstructing the motion of the ventricular walls. The main feature of our method is that the inversion parameter field is the active contraction of the myocardial fibers. This is accomplished with a biophysically-constrained, four-dimensional (space plus time) formulation that aims to complement information that can be gathered from the images by a priori knowledge of cardiac mechanics. Our main hypothesis is that by incorporating biophysical information, we can generate more informative priors and thus, more accurate predictions of the ventricular wall motion. In this paper, we outline the formulation, discuss the computational methodology for solving the inverse motion estimation, and present preliminary validation using synthetic and tagged MR images. The overall method uses patient-specific imaging and fiber information to reconstruct the motion. In these preliminary tests, we verify the implementation and conduct a parametric study to test the sensitivity of the model to material properties perturbations, model errors, and incomplete and noisy observations.

Preliminary validation of angle-independent myocardial elastography using MR tagging in a clinical setting

Myocardial elastography (ME), a radio-frequency (RF) based speckle tracking technique, was employed in order to image the entire two-dimensional (2D) transmural deformation field in full echocardiographic views and was validated against tagged magnetic resonance imaging (tMRI) in normal as well as reperfused (i.e., treated myocardial infarction [MI]) human left ventricles. RF ultrasound and tMRI frames were acquired at the papillary muscle level in 2D short-axis (SA) views at the frame rates of 136 (fps; real-time) and 33 fps (electrocardiogram [ECG]-gated), respectively. In ME, in-plane, 2D (lateral and axial) incremental displacements were iteratively estimated using one-dimensional (1D) cross-correlation and recorrelation techniques in a 2D search with a 1D matching kernel. In tMRI, cardiac motion was estimated by a template-matching algorithm on a 2D grid-shaped mesh. In both ME and tMRI, cumulative 2D displacements were obtained and then used to estimate 2D Lagrangian finite systolic strains, from which polar (i.e., radial and circumferential) strains, namely angle-independent measures, were further obtained through coordinate transformation. Principal strains, which are angle-independent and less centroid-dependent than polar strains, were also computed and imaged based on the 2D finite strains using methodology previously established. Both qualitatively and quantitatively, angle-independent ME is shown to be capable of (1) estimating myocardial deformation in good agreement with tMRI estimates in a clinical setting and of (2) differentiating abnormal from normal myocardium in a full left-ventricular view. The principal strains were concluded to be a potential diagnostic measure for detection of cardiac disease with reduced centroid dependence.

Direct three-dimensional myocardial strain tensor quantification and tracking using zHARP

Images of myocardial strain can be used to diagnose heart disease, plan and monitor treatment, and to learn about cardiac structure and function. Three-dimensional (3D) strain is typically quantified using many magnetic resonance (MR) images obtained in two or three orthogonal planes. Problems with this approach include long scan times, image misregistration, and through-plane motion. This article presents a novel method for calculating cardiac 3D strain using a stack of two or more images acquired in only one orientation. The zHARP pulse sequence encodes in-plane motion using MR tagging and out-of-plane motion using phase encoding, and has been previously shown to be capable of computing 3D displacement within a single image plane. Here, data from two adjacent image planes are combined to yield a 3D strain tensor at each pixel; stacks of zHARP images can be used to derive stacked arrays of 3D strain tensors without imaging multiple orientations and without numerical interpolation. The performance and accuracy of the method is demonstrated in vitro on a phantom and in vivo in four healthy adult human subjects.

Multi-slice three-dimensional myocardial strain tensor quantification using zHARP

In this article we propose a novel method for calculating cardiac 3-D strain. The method requires the acquisition of myocardial short-axis (SA) slices only and produces the 3-D strain tensor at every point within every pair of slices. Three-dimensional displacement is calculated from SA slices using zHARP which is then used for calculating the local displacement gradient and thus the local strain tensor. There are three main advantages of this method. First, the 3-D strain tensor is calculated for every pixel without interpolation; this is unprecedented in cardiac MR imaging. Second, this method is fast, in part because there is no need to acquire long-axis (LA) slices. Third, the method is accurate because the 3-D displacement components are acquired simultaneously and therefore reduces motion artifacts without the need for registration. This article presents the theory of computing 3-D strain from two slices using zHARP, the imaging protocol, and both phantom and in-vivo validation.