Simulation of two-dimensional tagged MRI

A Framework for the Generation of Realistic Synthetic Cardiac Ultrasound and Magnetic Resonance Imaging Sequences From the Same Virtual Patients

The use of synthetic sequences is one of the most promising tools for advanced in silico evaluation of the quantification of cardiac deformation and strain through 3-D ultrasound (US) and magnetic resonance (MR) imaging. In this paper, we propose the first simulation framework which allows the generation of realistic 3-D synthetic cardiac US and MR (both cine and tagging) image sequences from the same virtual patient. A state-of-the-art electromechanical (E/M) model was exploited for simulating groundtruth cardiac motion fields ranging from healthy to various pathological cases, including both ventricular dyssynchrony and myocardial ischemia. The E/M groundtruth along with template MR/US images and physical simulators were combined in a unified framework for generating synthetic data. We efficiently merged several warping strategies to keep the full control of myocardial deformations while preserving realistic image texture. In total, we generated 18 virtual patients, each with synthetic 3-D US, cine MR, and tagged MR sequences. The simulated images were evaluated both qualitatively by showing realistic textures and quantitatively by observing myocardial intensity distributions similar to real data. In particular, the US simulation showed a smoother myocardium/background interface than the state-of-the-art. We also assessed the mechanical properties. The pathological subjects were discriminated from the healthy ones by both global indexes (ejection fraction and the global circumferential strain) and regional strain curves. The synthetic database is comprehensive in terms of both pathology and modality, and has a level of realism sufficient for validation purposes. All the 90 sequences are made publicly available to the research community via an open-access database.

Optimization of tagged MRI for quantification of liver stiffness using computer simulated data

The heartbeat has been proposed as an intrinsic source of motion that can be used in combination with tagged Magnetic Resonance Imaging (MRI) to measure displacements induced in the liver as an index of liver stiffness. Optimizing a tagged MRI acquisition protocol in terms of sensitivity to these displacements, which are in the order of pixel size, is necessary to develop the method as a quantification tool for staging fibrosis. We reproduced a study of cardiac-induced strain in the liver at 3T and simulated tagged MR images with different grid tag patterns to evaluate the performance of the Harmonic Phase (HARP) image analysis method and its dependence on the parameters of tag spacing and grid angle. The Partial Volume Effect (PVE), T1 relaxation, and different levels of noise were taken into account. Four displacement fields of increasing intensity were created and applied to the tagged MR images of the liver. These fields simulated the deformation at different liver stiffnesses. An Error Index (EI) was calculated to evaluate the estimation accuracy for various parameter values. In the absence of noise, the estimation accuracy of the displacement fields increased as tag spacings decreased. EIs for each of the four displacement fields were lower at 0° and the local minima of the EI were found to correspond to multiples of pixel size. The accuracy of the estimation decreased for increasing levels of added noise; as the level increased, the improved estimation caused by decreasing the tag spacing tended to zero. The optimal tag spacing turned out to be a compromise between the smallest tag period that is a multiple of the pixel size and is achievable in a real acquisition and the tag spacing that guarantees an accurate liver displacement measure in the presence of realistic levels of noise.

A magnetic resonance software simulator for the evaluation of myocardial deformation estimation

This paper proposes a methodology to design a physiologically realistic computer simulator of images of the left ventricle myocardium based on a patient-specific biomechanical model. The simulator takes a magnetic resonance image of a given patient at end diastole, uses a manual segmentation of that image to model the geometry of the myocardium and sets the parameters of the constitutive model used for biomechanical simulation according to a regional labeling of the contractility of the myocardium for that patient. The simulated deformations are used to warp the magnetic resonance dataset throughout the cardiac cycle to generate different image modalities. The simulator is validated by quantifying its ability to model actual deformations in a set of patients affected by an acute myocardial infarction. Specifically a high correlation has been encountered between the ejection fraction derived from the simulated end systolic deformation of the myocardium and the myocardium segmented from actual data. Additionally, most of the parameters that describe the simulated deformation compare well with reported values. Overall, the simulator is intended as a testbed for extensive comparisons of myocardial motion tracking methods due to its ability to relate the impaired myocardial function with the associated ventricular remodeling, a novel contribution in the literature of cardiac image simulators.

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.

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.

The SIMRI project: a versatile and interactive MRI simulator

This paper gives an overview of SIMRI, a new 3D MRI simulator based on the Bloch equation. This simulator proposes an efficient management of the T2* effect, and in a unique simulator integrates most of the simulation features that are offered in different simulators. It takes into account the main static field value and enables realistic simulations of the chemical shift artifact, including off-resonance phenomena. It also simulates the artifacts linked to the static field inhomogeneity like those induced by susceptibility variation within an object. It is implemented in the C language and the MRI sequence programming is done using high level C functions with a simple programming interface. To manage large simulations, the magnetization kernel is implemented in a parallelized way that enables simulation on PC grid architecture. Furthermore, this simulator includes a 1D interactive interface for pedagogic purpose illustrating the magnetization vector motion as well as the MRI contrasts.

Simulation of tagged MR images with linear tetrahedral solid elements

Computer simulation of tagged magnetic resonance (MR) images is presented using signals derived from connected solid triangular or tetrahedral elements. Simulation provides precisely-known deformations for validating tag quantification algorithms. MR imaging signal is derived by Fourier-transforming over a standard element, then mapping to actual elements via transformations. Linear intensity variations over the element are interpolated from vertex intensities determined by tag calculations.

Serial motion assessment by reference tracking (SMART): application to detection of local functional impact of chronic myocardial ischemia

PURPOSE

To compare measurements of wall motion and thickening with and without correcting for cardiac twisting and shortening.

METHOD

Inversion recovery Gd-DPTA perfusion and cine motion MRI were performed on 12 pigs with chronic ischemia induced by ameroid occluder. Analyses were based on conventional fixed plane imaging and serial motion assessment by reference tracking (SMART).

RESULTS

Normal motion was 31.3 +/- 1.9%, and normal wall thickening was 41.4 +/- 2.2%. At the maximum perfusion defect, SMART wall motion was 10.5 +/- 2.4% and fixed wall motion was 20.6 +/- 1.7% (p < 0.004), SMART wall thickening was 20.1 +/- 4.4%, and fixed wall thickening was 32 +/- 1.9% (p < 0.03).

CONCLUSION

SMART measurements of wall thickening and motion detect much smaller thickening and motion in ischemic myocardium than fixed radial metrics. SMART data, covering the entire heart, should prove twice as sensitive to abnormalities in motion and thickening, such as any produced by ischemic heart disease or improved by treatment.

Ultrafast MR grid-tagging sequence for assessment of local mechanical properties of the lungs

While MR imaging with tagged magnetization has shown great utility in the study of muscle mechanics, the evaluation of pulmonary mechanics has long been hindered by the technical difficulties in MR imaging of lung parenchyma. In this study, a fast MR grid-tagging technique is described for dynamic assessment of regional pulmonary deformation. The method is based on a fast FLASH sequence with short TR and short TE. Tagging was achieved by using double DANTE pulse train or inversion pulses. Our results show that this technique is able to detect changes of the tagging grid caused by physiological deformation of the lung. Quantitative analysis of the data shows that this method is capable of assessing local pulmonary mechanics. The application of this technique could improve our understanding of ventilatory control, and thus provide a unique metric for assessing pulmonary disorders. Magn Reson Med 45:24-28, 2001.

Detailed motion analysis of the left ventricular myocardium using an MR tagging method with a dense grid

Detailed analysis of myocardial deformation through a whole cardiac cycle was accomplished using a tagging method with a high-density grid. Four sets of tagged images with a 4-mm-spacing grid were measured by generating four tagging pulses arranged at regular intervals in the cardiac cycle. Through each set of images, tag intersections were tracked semi-automatically. The estimated motions of tag intersections were concatenated so that sequential positions of myocardium were connected through a whole cardiac cycle. In vitro evaluation of the precision of this technique showed that the mean error of tracked 4-mm tag intersections was less than 0.47 +/- 0.17 mm, even on the quite low-contrast images, and the concatenation error caused by double concatenation was comparable to the interpolation error in the subendocardial area obtained with 8-mm tag intersection motion. The small difference between the two mean distance curves of the in vivo evaluation indicated that the method is useful for analyzing heart wall abnormalities. Magn Reson Med 44:73-82, 2000.

Improving contrast and tracking of tags in cardiac magnetic resonance images

Cardiac tagging permits non-invasive study of myocardial motion with high accuracy. Unfortunately, tagging contrast is impaired at later heart phases due to longitudinal relaxation. Histogram modification is presented as a method for improving contrast in later, faded images of a tagging series by altering these images such that their intensity histograms approximate the shape of the first, unfaded image of the series. This technique greatly improves the contrast and facilitates automatic detection of tags. Furthermore, a method is described for automatically tracking tag positions in short-axis images of the left ventricle modulated with a tagging grid. The method differs from previously reported methods in that, in one single filtering process in the Fourier domain, both the grid crossings as well as the grid centers are detected, and thus increased sampling resolution is obtained. The method was validated by applying a mathematical model of left ventricular motion to tagged images of the thigh muscle. The average discrepancy between theoretically predicted and automatically detected tag positions was 0.04 +/- 0.17 mm (mean +/- SD).

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

Magnetic resonance (MR) tagging has been shown to be a useful technique for noninvasively measuring the deformation of an in vivo heart. An important step in analyzing tagged images is the identification of tag lines in each image of a cine sequence. Most existing tag identification algorithms require user defined myocardial contours. Contour identification, however, is time consuming and requires a considerable amount of user intervention. In this paper, a new method for identifying tag lines, which we call the ML/MAP method, is presented that does not require user defined myocardial contours. The ML/MAP method is composed of three stages. First, a set of candidate tag line centers is estimated across the entire region-of-interest (ROI) with a snake algorithm based on a maximum-likelihood (ML) estimate of the tag center. Next, a maximum a posteriori (MAP) hypothesis test is used to detect the candidate tag centers that are actually part of a tag line. Finally, a pruning algorithm is used to remove any detected tag line centers that do not meet a spatio-temporal continuity criterion. The ML/MAP method is demonstrated on data from ten in vivo human hearts.

Frequency-domain simulation of MR tagging

Simulation of MR images is a useful tool for offline sequence development and as an aid to understanding image formation. One particular application of simulation is MR tagging, which is used for tracking myocardial motion. Simple spatial-domain methods cannot adequately represent effects common in these images, such as motion artifact and signal wrap. An existing frequency-domain model is shown to be inappropriate for tagged images, and an extension based on the Bloch equations and Fourier shift theorem is described to correct this. Software incorporating the new model is used to generate ideal tag intensity profiles and to accurately simulate tagged images. The shifted k-space patterns associated with tagged images, and their dependence on the order of the binomial tagging sequence, are explained. An application of the Fourier shift theorem is suggested that allows more rapid simulation of static tagged images.