Estimation and detection of myocardial tags in MR image without user-defined myocardial contours

A graph theoretic approach for computing 3D+time biventricular cardiac strain from tagged MRI data

Tagged magnetic resonance imaging (tMRI) is a well-established method for evaluating regional mechanical function of the heart. Many techniques have been developed to compute 2D or 3D cardiac deformation and strain from tMRI images. In this paper, we present a new method for measuring 3D plus time biventricular myocardial strain from tMRI data. The method is composed of two parts. First, we use a Gabor filter bank to extract tag points along tag lines. Second, each tag point is classified to one of a set of indexed reference tag lines using a point classification with graph cuts (PCGC) algorithm and a motion compensation technique. 3D biventricular deformation and strain is computed at each image time frame from the classified tag points using a previously published finite difference method. The strain computation is fully automatic after myocardial contours are defined near end-diastole and end-systole. An in-vivo dataset composed of 30 human imaging studies with a range of pathologies was used for validation. Strains computed with the PCGC method with no manual corrections were compared to strains computed from both manually placed tag points and a manually-corrected unwrapped phase method. A typical cardiac imaging study with 10 short-axis slices and 6 long-axis slices required 30 min for contouring followed by 44 min of automated processing. The results demonstrate that the proposed method can reconstruct accurate 3D plus time cardiac strain maps with minimal user intervention.

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.

Reversible jump MCMC methods for fully automatic motion analysis in tagged MRI

Tagged magnetic resonance imaging (tMRI) is a well-known noninvasive method for studying regional heart dynamics. It offers great potential for quantitative analysis of a variety of kine(ma)tic parameters, but its clinical use has so far been limited, in part due to the lack of robustness and accuracy of existing tag tracking algorithms in dealing with low (and intrinsically time-varying) image quality. In this paper, we evaluate the performance of four frequently used concepts found in the literature (optical flow, harmonic phase (HARP) magnetic resonance imaging, active contour fitting, and non-rigid image registration) for cardiac motion analysis in 2D tMRI image sequences, using both synthetic image data (with ground truth) and real data from preclinical (small animal) and clinical (human) studies. In addition we propose a new probabilistic method for tag tracking that serves as a complementary step to existing methods. The new method is based on a Bayesian estimation framework, implemented by means of reversible jump Markov chain Monte Carlo (MCMC) methods, and combines information about the heart dynamics, the imaging process, and tag appearance. The experimental results demonstrate that the new method improves the performance of even the best of the four previous methods. Yielding higher consistency, accuracy, and intrinsic tag reliability assessment, the proposed method allows for improved analysis of cardiac motion.

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.

Comparison of different grid of tags detection methods in tagged cardiac MR imaging

PURPOSE

Non-invasive imaging assessment of cardiac function is important in cardiovascular disease diagnosis, especially for evaluation of local cardiac motion. Tagged cardiac MRI has been developed for this purpose, but evaluation of the results requires quantification and automation.

METHODS

Two methods utilizing active contour modeling for wall motion extraction based on tagged cardiac MRI scans were evaluated based on properties of tracking methods in the image domain and frequency domain. Three criteria were used: accuracy, inter-subject and intra-subject sensitivity. The tracking results were evaluated by a medical expert. The evaluation methodology and its possible generalization to other diagnostic methods were considered.

RESULTS

Image domain and frequency domain analysis of tagged cardiac MRI data sets were evaluated demonstrating that the image domain method provides better results. The image domain method method is much more resistant to changes in the data, this time, due to a different subject being scanned. The frequency domain approach is not suitable for clinical applications, as the global error is significantly increased (more than 20%).

CONCLUSION

The image domain method was found most effective, and it can generate a set of clearly identified parameters. The evaluation approach can be an interesting alternative to classical psychovisual studies which are time-consuming and often fastidious for clinicians.

A multiresolution method for tagline detection and indexing

Tagline detection and indexing are challenging tasks due to complicated anatomical properties and imaging noise. In this paper, we will address the following two important issues in tagline detection: 1) an automatic method independent from imaging approaches with improved robustness and accuracy and 2) tagline indexing that matches taglines in task and reference images for postprocessing. Our method consists of two steps: First, a wavelet decomposition is performed on a tagged magnetic resonance (tMR) image. Subband correlation is used to dampen anatomical boundaries but enhance taglines. A tagline map is created by segmenting a reconstructed image using pseudowavelet reconstruction. Next, tagline pixels are grouped into clusters and isolated small line segments are eliminated. A snake method is then used to index and recover broken taglines. Our method has been validated with 320 tMR tongue images. Measurement of tagline accuracy was performed by computing tag pixel displacement. Without assumptions on tagline models, it detects taglines automatically. Comparison studies were conducted against the harmonic phase method. Our experiments resulted in a p-value of 1E-6 with one-way ANOVA, which indicates a significant improvement in accuracy and robustness.

Segmentation of myocardial boundaries in tagged cardiac MRI using active contours: a gradient-based approach integrating texture analysis

The noninvasive assessment of cardiac function is of first importance for the diagnosis of cardiovascular diseases. Among all medical scanners only a few enables radiologists to evaluate the local cardiac motion. Tagged cardiac MRI is one of them. This protocol generates on Short-Axis (SA) sequences a dark grid which is deformed in accordance with the cardiac motion. Tracking the grid allows specialists a local estimation of cardiac geometrical parameters within myocardium. The work described in this paper aims to automate the myocardial contours detection in order to optimize the detection and the tracking of the grid of tags within myocardium. The method we have developed for endocardial and epicardial contours detection is based on the use of texture analysis and active contours models. Texture analysis allows us to define energy maps more efficient than those usually used in active contours methods where attractor is often based on gradient and which were useless in our case of study, for quality of tagged cardiac MRI is very poor.

Maximum a posteriori strategy for the simultaneous motion and material property estimation of the heart

In addition to its technical merits as a challenging nonrigid motion and structural integrity analysis problem, quantitative estimation of cardiac regional functions and material characteristics has significant physiological and clinical value. We developed a stochastic finite-element framework for the simultaneous recovery of myocardial motion and material parameters from medical image sequences with an extended Kalman filter approach, and we have shown that this simultaneous estimation strategy achieves more accurate and robust results than separated motion and material estimation efforts. In this paper, we present a new computational strategy for the framework based upon the maximum a posteriori estimation principles, realized through the extended Kalman smoother, that produces a sequence of kinematics state and material parameter estimation of the entire myocardium, including the endocardial, epicardial, and midwall tissues. The system dynamics equations of the heart are constructed using a biomechanical model with stochastic parameters, and the tissue material and deformation parameters are jointly estimated from the periodic imaging data. Noise-corrupted synthetic image sequences with known kinematics and material parameters are used to assess the accuracy and robustness of the framework. Experiments with canine magnetic resonance tagging and phase-contrast image sequences have been conducted with very promising results, as validated through comparison to the histological staining of postmortem myocardium.

Quantitative comparison of 2D and 3D circumferential strain using MRI tagging in normal and LBBB hearts

The response to cardiac resynchronization therapy (CRT), which is applied to patients with heart failure (HF) and left bundle-branch block (LBBB), can be predicted from the mechanical dyssynchrony measured on circumferential strain. Circumferential strain can be assessed by either 2D or 3D strain analysis. In this study was evaluated the difference between 2D and 3D circumferential strain using MR tagging with high temporal resolution (14 ms). Six healthy volunteers and five patients with LBBB were evaluated. We compared the 2D and 3D circumferential strains by computing the mechanical dyssynchrony and the cross correlation (r) between 2D and 3D strain curves, and by quantifying the differences in peak circumferential shortening, time to onset, and time to peak of shortening. The obtained maximum r(2) values were 0.97 +/- 0.03 and 0.87 +/- 0.16 for the healthy and LBBB populations, respectively, and thus showed a good similarity between 2D and 3D strain curves. No significant difference was observed between 2D and 3D in time to onset, time to peak, or peak circumferential shortening. Thus, to measure dyssynchrony, 2D strain analysis will suffice. Since 2D analysis is easier to implement than 3D analysis, this finding brings the application of MRI tagging and strain analysis closer to the clinical routine.

State-space analysis of cardiac motion with biomechanical constraints

Quantitative estimation of nonrigid motion from image sequences has important technical and practical significance. State-space analysis provides powerful and convenient ways to construct and incorporate the physically meaningful system dynamics of an object, the image-derived observations, and the process and measurement noise disturbances. In this paper, we present a biomechanical-model constrained state-space analysis framework for the multiframe estimation of the periodic cardiac motion and deformation. The physical constraints take the roles as spatial regulator of the myocardial behavior and spatial filter/interpolator of the data measurements, while techniques from statistical filtering theory impose spatiotemporal constraints to facilitate the incorporation of multiframe information to generate optimal estimates of the heart kinematics. Physiologically meaningful results have been achieved from estimated displacement fields and strain maps using in vivo left ventricular magnetic resonance tagging and phase contrast image sequences, which provide the tag-tag and tag-boundary displacement inputs, and the mid-wall instantaneous velocity information and boundary displacement measures, respectively.

Cardiac motion analysis using nonlinear biomechanical constraints

Quantitative assessment of the motion and deformation variability of the heart has important implications for the understanding, diagnosis, and treatment of cardiac diseases. Various existing image-based approaches typically rely on linear constraining models which are however physically implausible. In this paper, we present a biomechnically constrained framework for the estimation of left ventricle deformation from medical image sequences using more realistic nonlinear geometry and material models. Once the myocardial boundaries and the sparse corresponding boundary points are derived from an active region model, we construct the cardiac dynamics where the left ventricle is modelled as an Mooney-Rivlin material undergoing large deformation. We then rely on the Newmark scheme to perform frame-to-frame estimation of the cardiac motion/deformation parameters. Experiments have been performed with 3D cardiac MR image sequences with very encouraging results.

Atherosclerosis imaging and heart failure

Coronary atherosclerosis is the most important primary etiologic factor predisposing to the development of heart failure. The mechanisms by which coronary atherosclerosis lead to heart failure likely involve the initial development of regional myocardial dysfunction, later progressing to global ventricular failure and symptomatic congestive disease. A variety of imaging strategies have been investigated for their value in identifying and characterizing markers of atherosclerosis in the effort to detect early cardiac disease. Non-invasive imaging techniques for assessing anatomic or functional manifestations of atherosclerosis include carotid ultrasonography, coronary computed tomography, cardiovascular magnetic resonance imaging, brachial artery reactivity testing, and the ankle-brachial index. Many of these imaging methods are shown to have accuracy, reliability, and the potential to add value to an office-based cardiovascular risk assessment. Further development of such imaging methods could facilitate early intervention in the development of myocardial dysfunction while enhancing our understanding of the natural course of atherosclerotic disease.

A non-rigid registration approach for quantifying myocardial contraction in tagged MRI using generalized information measures

We address the problem of quantitatively assessing myocardial function from tagged MRI sequences. We develop a two-step method comprising (i) a motion estimation step using a novel variational non-rigid registration technique based on generalized information measures, and (ii) a measurement step, yielding local and segmental deformation parameters over the whole myocardium. Experiments on healthy and pathological data demonstrate that this method delivers, within a reasonable computation time and in a fully unsupervised way, reliable measurements for normal subjects and quantitative pathology-specific information. Beyond cardiac MRI, this work redefines the foundations of variational non-rigid registration for information-theoretic similarity criteria with potential interest in multimodal medical imaging.

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.

Combined tag tracking and strain reconstruction from tagged cardiac MR images without user-defined myocardial contours

PURPOSE

To develop an unsupervised method for measuring quantitative three-dimensional regional strain in the left ventricular wall from tagged cardiac MR images.

MATERIALS AND METHODS

A total of 10 normal human volunteers and eight patients with myocardial infarction were imaged using a parallel tagged imaging protocol. Each study was analyzed using the combined tag tracking and strain reconstruction (COTTER) algorithm. In contrast to existing techniques, which first track tag lines independently in each slice, then reconstruct myocardial deformation, the COTTER algorithm fits a three-dimensional cardiac deformation model directly to the image data. This approach ensures that tag line positions identified in the image data are consistent from slice to slice. A total of 10 imaging studies (six normals, four patients) were used to optimize parameters of the COTTER algorithm.

RESULTS

In the remaining eight imaging studies, the root-mean-square difference between tags tracked by COTTER and user-supervised analysis was 0.66 pixels at end-systole. The correlation coefficient between circumferential shortening strains at end-systole computed by COTTER and user-supervised analysis was 0.84 (P < 0.005) at the midwall.

CONCLUSION

The COTTER algorithm can compute accurate measurements of three-dimensional regional strain without user supervision.

Fast tracking of cardiac motion using 3D-HARP

MR tagging is considered as a valuable technique to evaluate regional myocardial function quantitatively and noninvasively, however the cumbersome and time-consuming post-processing procedures for cardiac motion tracking still hinder its application to routine clinical examination. We present a fast and semiautomatic method for tracking 3D cardiac motion from short-axis (SA) and long-axis (LA) tagged MRI images. The technique, called 3D-HARP (HARmonic Phase), is based on the HARP method and extends this method to track 3D motion. A material mesh model is built to represent a collection of material points inside the left ventricle (LV) wall. The phase time-invariance property of material points is used to track the mesh points. For a series of 9 timeframe MRI images, the total time required for initializing settings, building the mesh, and tracking 3D cardiac motion is approximately 10 minutes. Further analysis of Langrangian strain and twist angle demonstrates that during systole, the lateral LV wall shows a greater strain values than the septum and the SA slices from the base to the apex show a gradual change in twist pattern.

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.

Stochastic finite element framework for simultaneous estimation of cardiac kinematic functions and material parameters

A stochastic finite element framework is presented for the simultaneous estimation of the cardiac kinematic functions and material model parameters from periodic medical image sequences. While existing biomechanics studies of the myocardial material constitutive laws have assumed known tissue kinematic measurements, and image analysis efforts on cardiac kinematic functions have relied on fixed constraining models of mathematical or mechanical nature, we illustrate through synthetic data that a probabilistic joint estimation strategy is needed to achieve more robust and accurate analysis of the kinematic functions and material parameters at the same time. For a particular a priori constraining material model with uncertain subject-dependent parameters and a posteriori noisy imaging based observations, our strategy combines the stochastic differential equations of the myocardial dynamics with the finite element method, and the material parameters and the imaging data are treated as random variables with known prior statistics. After the conversion to state space representation, the extended Kalman filtering procedures are adopted to linearize the equations and to provide the joint estimates in an approximate optimal sense. The estimation bias and convergence issues are addressed, and we conclude experimentally that it is possible to adopt this biomechanical model based multiframe estimation approach to achieve converged estimates because of the periodic nature of the cardiac dynamics. The effort is validated using synthetic data sequence with known kinematics and material parameters. Further, under linear elastic material model, estimation results using canine magnetic resonance phase contrast image sequences are presented, which are in very good agreement with histological tissue staining results, the current gold standards.

Unsupervised reconstruction of a three-dimensional left ventricular strain from parallel tagged cardiac images

A new algorithm, called the Unsupervised Tag ExTraction and Heart strain(E) Reconstruction (UNTETHER) algorithm, is presented for quantifying three-dimensional (3D) myocardial strain in tagged cardiac MR images. Five human volunteers and five postinfarct patients were imaged. 3D strains measured by UNTETHER and a user-supervised technique were compared. Each study was analyzed in 49 +/- 8 min with UNTETHER, compared to approximately 4 hr with the user-supervised technique. For pooled human data, the correlation coefficient between the two methods for circumferential shortening (E(cc)) was r = 0.91 at the mid-wall (P < 0.0005). UNTETHER is capable of measuring wall motion abnormalities resulting from coronary artery disease, and has the potential to overcome the main limitations (time and user-supervision requirements) to routine clinical use of tagged cardiac MRI.

Automated Segmentation of the Left and Right Ventricles in 4D Cardiac SPAMM Images

In this paper we describe a completely automated volume-based method for the segmentation of the left and right ventricles in 4D tagged MR (SPAMM) images for quantitative cardiac analysis. We correct the background intensity variation in each volume caused by surface coils using a new scale-based fuzzy connectedness procedure. We apply 3D grayscale opening to the corrected data to create volumes containing only the blood filled regions. We threshold the volumes by minimizing region variance or by an adaptive statistical thresholding method. We isolate the ventricular blood filled regions using a novel approach based on spatial and temporal shape similarity. We use these regions to define the endocardium contours and use them to initialize an active contour that locates the epicardium through the gradient vector flow of an edgemap of a grayscale-closed image. Both quantitative and qualitative results on normal and diseased patients are presented.

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.

Reconstruction of time-varying 3-D left-ventricular shape from multiview X-ray cineangiocardiograms

This paper reports on the clinical application of a system for recovering the time-varying three-dimensional (3-D) left-ventricular (LV) shape from multiview X-ray cineangiocardiograms. Considering that X-ray cineangiocardiography is still commonly employed in clinical cardiology and computational costs for 3-D recovery and visualization are rapidly decreasing, it is meaningful to develop a clinically applicable system for 3-D LV shape recovery from X-ray cineangiocardiograms. The system is based on a previously reported closed-surface method of shape recovery from two-dimensional occluding contours with multiple views. To apply the method to "real" LV cineangiocardiograms, user-interactive systems were implemented for preprocessing, including detection of LV contours, calibration of the imaging geometry, and setting of the LV model coordinate system. The results for three real LV angiographic image sequences are presented, two with fixed multiple views (using supplementary angiography) and one with rotating views. 3-D reconstructions utilizing different numbers of views were compared and evaluated in terms of contours manually traced by an experienced radiologist. The performance of the preprocesses was also evaluated, and the effects of variations in user-specified parameters on the final 3-D reconstruction results were shown to be sufficiently small. These experimental results demonstrate the potential usefulness of combining multiple views for 3-D recovery from "real" LV cineangiocardiograms.

Left ventricular motion reconstruction from planar tagged MR images: a comparison

Through recent development of MR techniques, it is now possible to assess regional myocardial wall function in a non-invasive way. Using MR tagging, space is marked with planes which deform with the tissue, providing markers for tracking the local motion of the myocardium. Numerous methods to reconstruct the three-dimensional displacement field have been developed. The aim of this article is to provide a framework to quantitatively compare the performance of four methods the authors have developed. Five sets of experiments are described, and their results are reported. Instructions are also provided to perform similar tests on any method using the same data. The experiments show that some characteristic properties of the methods, such as sensitivity to noise or spatial resolution, can be quantitatively classified. Cross-comparison of performances show what range values for these properties can be considered acceptable.