Motion estimation from tagged MR image sequences

Using synthetic data generation to train a cardiac motion tag tracking neural network

A CNN based method for cardiac MRI tag tracking was developed and validated. A synthetic data simulator was created to generate large amounts of training data using natural images, a Bloch equation simulation, a broad range of tissue properties, and programmed ground-truth motion. The method was validated using both an analytical deforming cardiac phantom and in vivo data with manually tracked reference motion paths. In the analytical phantom, error was investigated relative to SNR, and accurate results were seen for SNR>10 (displacement error <0.3 mm). Excellent agreement was seen in vivo for tag locations (mean displacement difference = -0.02 pixels, 95% CI [-0.73, 0.69]) and calculated cardiac circumferential strain (mean difference = 0.006, 95% CI [-0.012, 0.024]). Automated tag tracking with a CNN trained on synthetic data is both accurate and precise.

A gradient-based optical-flow cardiac motion estimation method for cine and tagged MR images

A new method is proposed to quantify the myocardial motion from both 2D C(ine)-MRI and T(agged)-MRI sequences. The tag pattern offers natural landmarks within the image that makes it possible to accurately quantify the motion within the myocardial wall. Therefore, several methods have been proposed for T-MRI. However, the lack of salient features within the cardiac wall in C-MRI hampers local motion estimation. Our method aims to ensure the local intensity and shape features invariance during motion through the iterative minimization of a cost function via a random walk scheme. The proposed approach is evaluated on realistic simulated C-MRI and T-MRI sequences. The results show more than 53% improvements on displacement estimation, and more than 24% on strain estimation for both C-MRI and T-MRI sequences, as compared to state-of-the-art cardiac motion estimators. Preliminary experiments on clinical data have shown a good ability of the proposed method to detect abnormal motion patterns related to pathology. If those results are confirmed on large databases, this would open up the possibility for more accurate diagnosis of cardiac function from standard C-MRI examinations and also the retrospective study of prior studies.

Magnetic Resonance Imaging of Contracting Ultrathin Cardiac Tissue

OBJECTIVE

Integrating cardiac-tissue patches into the beating heart and evaluating the long-term effects of such integration on cardiac contractility are two challenges in an emerging field of regenerative medicine. This pilot study presents tools for the imaging of contracting multicellular cardiac tissue constructs (MTCs) in vitro and demonstrates the feasibility of tracking the early development of strand geometry and contractions in ultrathin strands and layers of cardiac tissue using CINE MRI.

APPROACH

Cultured, ultrathin (~50-100-micron) MTCs of rat neonatal cardiomyocytes were plated in rectangular cell chambers (4.5 × 2.0 cm) with and without ultrathin, carbon EP electrodes embedded in the floor of the cell chamber. Two-dimensional, steady-state free precession (SSFP) CINE MRI, cell microscopy, and tissue photography were performed on Days 5-9 of cell development. Potential confounders and MRI artifacts were evaluated using non-contracting cardiac tissues and cell-free chambers filled with the cell-culture medium.

MAIN RESULTS

Synchronized contractions formed by Day 7; individual contracting tissue strands became identifiable by Day 9. The global patterns and details of the strand geometry and movement patterns in the SSFP images were in excellent agreement with microscopic and photographic images. No synchronized movement was identifiable by either microscopy or CINE MRI in the non-contracting MTCs or the cell-free medium. The EP recordings revealed well-defined depolarization and repolarization waveforms; the imaging artifacts generated by the carbon electrodes were small.

SIGNIFICANCE

This pilot study demonstrates the feasibility of imaging cardiac-strand patterns and contractile activity in ultrathin, two-dimensional cardiac tissue in commonly used clinical scanners.

Introduction to a mechanism for automated myocardium boundary detection with displacement encoding with stimulated echoes (DENSE)

Objective:

Displacement ENcoding with Stimulated Echoes (DENSE) is an MRI technique developed to encode phase related to myocardial tissue displacements, and the displacement information directly applied towards detecting left-ventricular (LV) myocardial motion during the cardiac cycle. The purpose of this study is to present a novel, three-dimensional (3D) DENSE displacement-based and magnitude image quantization-based, semi-automated detection technique for myocardial wall motion, whose boundaries are used for rapid and automated computation of 3D myocardial strain.

Methods:

The architecture of this boundary detection algorithm is primarily based on pixelwise spatiotemporal increments in LV tissue displacements during the cardiac cycle and further reinforced by radially searching for pixel-based image gradients in multithreshold quantized magnitude images. This spatiotemporal edge detection methodology was applied to all LV partitions and their subsequent timeframes that lead to full 3D LV reconstructions. It was followed by quantifications of 3D chamber dimensions and myocardial strains, whose rapid computation was the primary motivation behind developing this algorithm. A pre-existing two-dimensional (2D) semi-automated contouring technique was used in parallel to validate the accuracy of the algorithm and both methods tested on DENSE data acquired in (N = 14) healthy subjects. Chamber quantifications between methods were compared using paired t-tests and Bland–Altman analysis established regional strain agreements.

Results:

There were no significant differences in the results of chamber quantifications between the 3D semi-automated and existing 2D boundary detection techniques. This included comparisons of ejection fractions, which were 0.62 ± 0.04 vs 0.60 ± 0.06 (p = 0.23) for apical, 0.60 ± 0.04 vs 0.59 ± 0.05 (p = 0.76) for midventricular and 0.56 ± 0.04 vs 0.58 ± 0.05 (p = 0.07) for basal segments, that were quantified using the 3D semi-automated and 2D pre-existing methodologies, respectively. Bland–Altman agreement between regional strains generated biases of 0.01 ± 0.06, –0.01 ± 0.01 and 0.0 ± 0.06 for the radial, circumferential and longitudinal directions, respectively.

Conclusion:

A new, 3D semi-automated methodology for contouring the entire LV and rapidly generating chamber quantifications and regional strains is presented that was validated in relation to an existing 2D contouring technique.

Advances in knowledge:

This study introduced a scientific tool for rapid, semi-automated generation of clinical information regarding shape and function in the 3D LV.

Myocardial motion analysis based on an optical flow method using tagged MR images

We developed a method of velocimetry based on an optical flow method using quantitative analyses of tagged magnetic resonance (MR) images (tagged MR-optical flow velocimetry, tMR-O velocimetry). The purpose of our study was to examine the accuracy of measurement of the proposed tMR-O velocimetry. We performed retrospective pseudo-electrocardiogram (ECG) gating tagged cine MR imaging on a rotating phantom. We optimized imaging parameters for tagged MR imaging, and validated the accuracy of tMR-O velocimetry. Our results indicated that the difference between the reference velocities and the computed velocities measured using optimal imaging parameters was less than 1%. In addition, we performed tMR-O velocimetry and echocardiography on 10 healthy volunteers, for four sections of the heart (apical, midventricular, and basal sections aligned with the short-axis, and a four-chamber section aligned with the long-axis), and obtained radial and longitudinal myocardial velocities in these sections. We compared the myocardial velocities obtained using tMR-O velocimetry with those obtained using echocardiography. Our results showed good agreement between tMR-O velocimetry and echocardiography in the radial myocardial velocities in three short-axial sections and longitudinal myocardial velocities on the midventricular portion of the four-chamber section in the long-axis. In the study conducted on the rotating phantom, tMR-O velocimetry showed high accuracy; moreover, in the healthy volunteers, the myocardial velocities obtained using tMR-O velocimetry were relatively similar to those obtained using echocardiography. In conclusion, tMR-O velocimetry is a potentially feasible method for analyzing myocardial motion in the human heart.

A Novel Hierarchical Template Matching Model for Cardiac Motion Estimation

Cardiovascular disease diagnosis and prognosis can be improved by measuring patient-specific in-vivo local myocardial strain using Magnetic Resonance Imaging. Local myocardial strain can be determined by tracking the movement of sample muscles points during cardiac cycle using cardiac motion estimation model. The tracking accuracy of the benchmark Free Form Deformation (FFD) model is greatly affected due to its dependency on tunable parameters and regularisation function. Therefore, Hierarchical Template Matching (HTM) model, which is independent of tunable parameters, regularisation function, and image-specific features, is proposed in this article. HTM has dense and uniform points correspondence that provides HTM with the ability to estimate local muscular deformation with a promising accuracy of less than half a millimetre of cardiac wall muscle. As a result, the muscles tracking accuracy has been significantly (p < 0.001) improved (30%) compared to the benchmark model. Such merits of HTM provide reliably calculated clinical measures which can be incorporated into the decision-making process of cardiac disease diagnosis and prognosis.

Phase Vector Incompressible Registration Algorithm for Motion Estimation From Tagged Magnetic Resonance Images

Tagged magnetic resonance imaging has been used for decades to observe and quantify motion and strain of deforming tissue. It is challenging to obtain 3-D motion estimates due to a tradeoff between image slice density and acquisition time. Typically, interpolation methods are used either to combine 2-D motion extracted from sparse slice acquisitions into 3-D motion or to construct a dense volume from sparse acquisitions before image registration methods are applied. This paper proposes a new phase-based 3-D motion estimation technique that first computes harmonic phase volumes from interpolated tagged slices and then matches them using an image registration framework. The approach uses several concepts from diffeomorphic image registration with a key novelty that defines a symmetric similarity metric on harmonic phase volumes from multiple orientations. The material property of harmonic phase solves the aperture problem of optical flow and intensity-based methods and is robust to tag fading. A harmonic magnitude volume is used in enforcing incompressibility in the tissue regions. The estimated motion fields are dense, incompressible, diffeomorphic, and inverse-consistent at a 3-D voxel level. The method was evaluated using simulated phantoms, human brain data in mild head accelerations, human tongue data during speech, and an open cardiac data set. The method shows comparable accuracy to three existing methods while demonstrating low computation time and robustness to tag fading and noise.

A Four-dimensional Motion Field Atlas of the Tongue from Tagged and Cine Magnetic Resonance Imaging

Representation of human tongue motion using three-dimensional vector fields over time can be used to better understand tongue function during speech, swallowing, and other lingual behaviors. To characterize the inter-subject variability of the tongue's shape and motion of a population carrying out one of these functions it is desirable to build a statistical model of the four-dimensional (4D) tongue. In this paper, we propose a method to construct a spatio-temporal atlas of tongue motion using magnetic resonance (MR) images acquired from fourteen healthy human subjects. First, cine MR images revealing the anatomical features of the tongue are used to construct a 4D intensity image atlas. Second, tagged MR images acquired to capture internal motion are used to compute a dense motion field at each time frame using a phase-based motion tracking method. Third, motion fields from each subject are pulled back to the cine atlas space using the deformation fields computed during the cine atlas construction. Finally, a spatio-temporal motion field atlas is created to show a sequence of mean motion fields and their inter-subject variation. The quality of the atlas was evaluated by deforming cine images in the atlas space. Comparison between deformed and original cine images showed high correspondence. The proposed method provides a quantitative representation to observe the commonality and variability of the tongue motion field for the first time, and shows potential in evaluation of common properties such as strains and other tensors based on motion fields.

Visualization of Sliding and Deformation of Orbital Fat During Eye Rotation

Purpose

Little is known about the way orbital fat slides and/or deforms during eye movements. We compared two deformation algorithms from a sequence of MRI volumes to visualize this complex behavior.

Methods

Time-dependent deformation data were derived from motion-MRI volumes using Lucas and Kanade Optical Flow (LK3D) and nonrigid registration (B-splines) deformation algorithms. We compared how these two algorithms performed regarding sliding and deformation in three critical areas: the sclera-fat interface, how the optic nerve moves through the fat, and how the fat is squeezed out under the tendon of a relaxing rectus muscle. The efficacy was validated using identified tissue markers such as the lens and blood vessels in the fat.

Results

Fat immediately behind the eye followed eye rotation by approximately one-half. This was best visualized using the B-splines technique as it showed less ripping of tissue and less distortion. Orbital fat flowed around the optic nerve during eye rotation. In this case, LK3D provided better visualization as it allowed orbital fat tissue to split. The resolution was insufficient to visualize fat being squeezed out between tendon and sclera.

Conclusion

B-splines performs better in tracking structures such as the lens, while LK3D allows fat tissue to split as should happen as the optic nerve slides through the fat. Orbital fat follows eye rotation by one-half and flows around the optic nerve during eye rotation.

Translational Relevance

Visualizing orbital fat deformation and sliding offers the opportunity to accurately locate a region of cicatrization and permit an individualized surgical plan.

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.

Whole-body FDG PET-MR oncologic imaging: pitfalls in clinical interpretation related to inaccurate MR-based attenuation correction

Simultaneous data collection for positron emission tomography and magnetic resonance imaging (PET/MR) is now a reality. While the full benefits of concurrently acquiring PET and MR data and the potential added clinical value are still being evaluated, initial studies have identified several important potential pitfalls in the interpretation of fluorodeoxyglucose (FDG) PET/MRI in oncologic whole-body imaging, the majority of which being related to the errors in the attenuation maps created from the MR data. The purpose of this article was to present such pitfalls and artifacts using case examples, describe their etiology, and discuss strategies to overcome them. Using a case-based approach, we will illustrate artifacts related to (1) Inaccurate bone tissue segmentation; (2) Inaccurate air cavities segmentation; (3) Motion-induced misregistration; (4) RF coils in the PET field of view; (5) B0 field inhomogeneity; (6) B1 field inhomogeneity; (7) Metallic implants; (8) MR contrast agents.

Myocardial motion estimation of tagged cardiac magnetic resonance images using tag motion constraints and multi-level b-splines interpolation

Myocardial motion estimation of tagged cardiac magnetic resonance (TCMR) images is of great significance in clinical diagnosis and the treatment of heart disease. Currently, the harmonic phase analysis method (HARP) and the local sine-wave modeling method (SinMod) have been proven as two state-of-the-art motion estimation methods for TCMR images, since they can directly obtain the inter-frame motion displacement vector field (MDVF) with high accuracy and fast speed. By comparison, SinMod has better performance over HARP in terms of displacement detection, noise and artifacts reduction. However, the SinMod method has some drawbacks: 1) it is unable to estimate local displacements larger than half of the tag spacing; 2) it has observable errors in tracking of tag motion; and 3) the estimated MDVF usually has large local errors. To overcome these problems, we present a novel motion estimation method in this study. The proposed method tracks the motion of tags and then estimates the dense MDVF by using the interpolation. In this new method, a parameter estimation procedure for global motion is applied to match tag intersections between different frames, ensuring specific kinds of large displacements being correctly estimated. In addition, a strategy of tag motion constraints is applied to eliminate most of errors produced by inter-frame tracking of tags and the multi-level b-splines approximation algorithm is utilized, so as to enhance the local continuity and accuracy of the final MDVF. In the estimation of the motion displacement, our proposed method can obtain a more accurate MDVF compared with the SinMod method and our method can overcome the drawbacks of the SinMod method. However, the motion estimation accuracy of our method depends on the accuracy of tag lines detection and our method has a higher time complexity.

Artifacts reduction in strain maps of tagged magnetic resonance imaging using harmonic phase

Tagged Magnetic Resonance Imaging (MRI) is a noninvasive technique for examining myocardial function and deformation. Tagged MRI can also be used in quasi-static MR elastography to acquire strain maps of other biological soft tissues. Harmonic phase (HARP) provides automatic and rapid analysis of tagged MR images for the quantification and visualization of myocardial strain. We propose a new artifact reduction method in strain maps. Image intensity of the DC component is estimated and subtracted from spatial modulation of magnetization (SPAMM) tagged MR images. DC peak interference in harmonic phase extraction is greatly reduced after DC component subtraction. The proposed method is validated using both simulated and MR acquired tagged images. Strain maps are obtained with better accuracy and smoothness after DC component subtraction.

3D harmonic phase tracking with anatomical regularization

This paper presents a novel algorithm that extends HARP to handle 3D tagged MRI images. HARP results were regularized by an original regularization framework defined in an anatomical space of coordinates. In the meantime, myocardium incompressibility was integrated in order to correct the radial strain which is reported to be more challenging to recover. Both the tracking and regularization of LV displacements were done on a volumetric mesh to be computationally efficient. Also, a window-weighted regression method was extended to cardiac motion tracking which helps maintain a low complexity even at finer scales. On healthy volunteers, the tracking accuracy was found to be as accurate as the best candidates of a recent benchmark. Strain accuracy was evaluated on synthetic data, showing low bias and strain errors under 5% (excluding outliers) for longitudinal and circumferential strains, while the second and third quartiles of the radial strain errors are in the (-5%,5%) range. In clinical data, strain dispersion was shown to correlate with the extent of transmural fibrosis. Also, reduced deformation values were found inside infarcted segments.

Identification of left ventricular systolic dysfunction and contraction inhomogeneity in post-infarction patients using a segmental two-parameter empirical deformable model

Various computational models have been developed with an objective to mimic the left ventricular (LV) wall motion and establishing global and regional parameters for evaluating cardiac performance. Recently, a segmental two-parameter empirical deformable model was introduced which performs a non-rigid registration to derive contraction and rotational parameters describing the LV motion. In this work, we assessed the capability of the segmental model in identifying the impairment of the LV contraction in the post-infarction patients. The correlation between the contraction parameter, α/repi defined in this work and the total percentage of infarct was investigated. The temporal pattern of the contraction parameter in each LV segment at the mid ventricular slice was also analyzed throughout the systolic cardiac phases. Our results demonstrated that mean α/repi decreased exponentially with an increase in the infarct percentage. While normal subjects showed synchronous contraction for all LV segments, the presence of infarct regions caused LV dyssynchrony, with the infarcted segments demonstrated abnormal contraction patterns.

Hybrid intensity- and phase-based optical flow tracking of tagged MRI

Accurate tracking of the myocardium tissues in tagged Magnetic Resonance Images (MRI) is essential for evaluating the cardiac function. Current tracking methods utilize either the image intensity or the image phase as landmarks that can be tracked. In either case, the performance is vulnerable to the image quality and the fading of the tag lines. In this work, we propose a hybrid optical flow tracking method that combines both the intensity and the phase features of the image. The method is validated using numerical cardiac phantom as well as real MRI data experiments. Both experiments showed that the proposed method outperforms current intensity-based optical flow tracking and the phase-based HARP method with maximum error of 1 pixel at extreme conditions of tag fading.

Estimating dense cardiac 3D motion using sparse 2D tagged MRI cross-sections

In this work, we describe a new method, an extension of the Large Deformation Diffeomorphic Metric Mapping to estimate three-dimensional deformation of tagged Magnetic Resonance Imaging Data. Our approach relies on performing non-rigid registration of tag planes that were constructed from set of initial reference short axis tag grids to a set of deformed tag curves. We validated our algorithm using in-vivo tagged images of normal mice. The mapping allows us to compute root mean square distance error between simulated tag curves in a set of long axis image planes and the acquired tag curves in the same plane. Average RMS error was 0.31 ± 0.36(SD) mm, which is approximately 2.5 voxels, indicating good matching accuracy.

Speech MRI: morphology and function

Magnetic Resonance Imaging (MRI) plays an increasing role in the study of speech. This article reviews the MRI literature of anatomical imaging, imaging for acoustic modelling and dynamic imaging. It describes existing imaging techniques attempting to meet the challenges of imaging the upper airway during speech and examines the remaining hurdles and future research directions.

[Value of new MR techniques in MR-PET]

The unparalleled soft tissue contrast of magnetic resonance imaging (MRI) and the functional information obtainable with 18-F fluorodeoxyglucose positron emission tomography (FDG-PET) render MR-PET well-suited for oncological and psychiatric imaging. The lack of ionizing radiation with MRI also makes MR-PET a promising modality for oncology patients requiring frequent follow-up and pediatric patients. Lessons learned with PET computed tomography (CT) over the last few years do not directly translate to MR-PET. For example, in PET-CT the Hounsfield units derived from CT are used for attenuation correction (AC). As 511 keV photons emitted in PET examinations are attenuated by the patient's body CT data are converted directly to linear attenuation coefficients (LAC); however, proton density measured by MRI is not directly related to the radiodensity or LACs of biological tissue. Thus, direct conversion to LAC data is not possible making AC more challenging in simultaneous MRI-PET scanning. In addition to these constraints simultaneous MRI-PET acquisitions also improve on some solutions to well-known challenges of hybrid imaging techniques, such as limitations in motion correction. This article reports on initial clinical experiences with simultaneously acquired MRI-PET data, focusing on the potential benefits and limitations of MRI with respect to motion correction as well as metal and attenuation correction artefacts.

Imaging techniques for cardiac strain and deformation: comparison of echocardiography, cardiac magnetic resonance and cardiac computed tomography

Myocardial function assessment is essential for determining the health of the myocardium. Global assessment of myocardial function is widely performed (by estimating the ejection fraction), but many common cardiac diseases initially affect the myocardium on a regional, rather than global basis. Regional myocardial wall motion can be quantified using myocardial strain analysis (a normalized measure of deformation). Myocardial strain can be measured in terms of three normal strains (longitudinal strain, radial strain and circumferential) and six shear strains. Cardiac MRI (cMRI) is usually considered the reference standard for measurement of myocardial strain. The most common cMRI method, termed tagged cMRI, allows full, 3D assessment of regional strain. However, due to its complexity and lengthy times for analysis, tagged cMRI is not usually used outside of academic centers. Tagged cMRI is also primarily used only in research studies. Echocardiography combined with tissue Doppler imaging or a speckle tracking technique is now widely available in the clinical setting. Myocardial strain measurement by echocardiography shows reasonable agreement with cMRI. Limited standardization and differences between vendors represent current limitations of the technique. Cardiac computed tomography (CCT) is the newest and most rapidly growing modality for noninvasive imaging of the heart. While CCT studies are most commonly applied to assess the coronary arteries, CCT is easily adapted to provide functional information for both the left and right ventricles. New methods for CCT assessment of regional myocardial function are being developed. This review outlines the current literature on imaging techniques related to cardiac strain analysis and discusses the strengths and weaknesses of various methods for myocardial strain analysis.

State of the Art in Cardiac Hybrid Technology: PET/MR

Simultaneous PET/MRI is an emerging technique combining two powerful imaging modalities in a single device. The wide variety of available tracers for perfusion and metabolic studies and the high sensitivity of positron emission tomography (PET) combined with the high spatial resolution and soft tissue contrast of magnetic resonance imaging (MRI) in depicting cardiac morphology and function as well as MRI's absence of ionizing radiation makes PET/MRI very attractive to radiologists and clinicians. Nevertheless, PET/MR scientific and clinical promise is to be considered in the context of numerous technical challenges that hinder its use in the clinical setting. For example, in order for a PET system to work correctly within an MR field, major changes are required to the photon detection chain such as the elimination of photomultiplier tubes, etc. Another significant limitation of PET/MRI is the lack of an electron density map (as is the case with PET-CT) that can be readily obtained from MRI (the latter measures proton not electron density) and used to correct PET data for attenuation. Moreover, as with PET-CT, cardiac and respiratory motions cause image degradations that affect image quality and accuracy both in static and dynamic PET imaging. As a result, overcoming these (and other) technical limitations is a very active area of research both in academic institutions as well as industry. In this paper, we review recent literature on cardiac PET/MRI, present the state-of-the-art of this technology, and explore promising preclinical and clinical cardiac applications where PET/MRI could play a substantial role.

MR assessment of regional myocardial mechanics

Regional myocardial function can be measured by several MR techniques including tissue tagging, phase velocity mapping, and more recently, displacement encoding with stimulated echoes (DENSE) and strain encoding (SENC). Each of these techniques was developed separately and has undergone significant change since its original implementation. As a result, in the current literature, the common features and the differences between the techniques and what they measure are often unclear and confusing. This review article delivers an extensively referenced introductory text which clarifies the current methodology from the starting point of the Bloch equations. By doing this in a consistent way for each method, the similarities and differences between them are highlighted. In addition, their capabilities and limitations are discussed, together with their relative advantages and disadvantages. While the focus is on sequence design and development, the principal parameters measured by each technique are also summarized, together with brief results, with the reader being directed to the extensive literature on data processing and clinical applications for more detail.

MRI-based nonrigid motion correction in simultaneous PET/MRI

Respiratory and cardiac motion is the most serious limitation to whole-body PET, resulting in spatial resolution close to 1 cm. Furthermore, motion-induced inconsistencies in the attenuation measurements often lead to significant artifacts in the reconstructed images. Gating can remove motion artifacts at the cost of increased noise. This paper presents an approach to respiratory motion correction using simultaneous PET/MRI to demonstrate initial results in phantoms, rabbits, and nonhuman primates and discusses the prospects for clinical application.

METHODS

Studies with a deformable phantom, a free-breathing primate, and rabbits implanted with radioactive beads were performed with simultaneous PET/MRI. Motion fields were estimated from concurrently acquired tagged MR images using 2 B-spline nonrigid image registration methods and incorporated into a PET list-mode ordered-subsets expectation maximization algorithm. Using the measured motion fields to transform both the emission data and the attenuation data, we could use all the coincidence data to reconstruct any phase of the respiratory cycle. We compared the resulting SNR and the channelized Hotelling observer (CHO) detection signal-to-noise ratio (SNR) in the motion-corrected reconstruction with the results obtained from standard gating and uncorrected studies.

RESULTS

Motion correction virtually eliminated motion blur without reducing SNR, yielding images with SNR comparable to those obtained by gating with 5-8 times longer acquisitions in all studies. The CHO study in dynamic phantoms demonstrated a significant improvement (166%-276%) in lesion detection SNR with MRI-based motion correction as compared with gating (P < 0.001). This improvement was 43%-92% for large motion compared with lesion detection without motion correction (P < 0.001). CHO SNR in the rabbit studies confirmed these results.

CONCLUSION

Tagged MRI motion correction in simultaneous PET/MRI significantly improves lesion detection compared with respiratory gating and no motion correction while reducing radiation dose. In vivo primate and rabbit studies confirmed the improvement in PET image quality and provide the rationale for evaluation in simultaneous whole-body PET/MRI clinical studies.

Accurate two-dimensional cardiac strain calculation using adaptive windowed Fourier transform and Gabor wavelet transform

PURPOSE

Cardiac strain calculated from tagged magnetic resonance (MR) images provides clinicians information about abnormalities of heart-wall motion in patients. It is important to develop an accurate method to determine the cardiac strain efficiently. An adaptive windowed harmonic phase (AWHARP) method is proposed for cardiac strain calculation.

MATERIALS AND METHODS

AWHARP is based on adaptive windowed Fourier transform (AWFT) and 2D Gabor wavelet transform (2D-GWT). The AWFT provides a spatially varying representation of the signal spectra, which allows the harmonic phase (HARP) image to be extracted with high accuracy. Instantaneous spatial frequencies are calculated using 2D-GWT, and the widths of the adaptive windows are then determined according to the instantaneous spatial frequencies for multi-resolution analysis of phase extraction. The proposed method was studied using simulated images and patients' MR images. Both single tagged images (SPAMM) and subtracted tagged images (CSPAMM) were generated using our simulation method, and their results calculated using AWHARP and HARP methods were compared. Normal and pathological tagged MR images were also processed to evaluate the performance of our method.

RESULTS

Our experimental results show that the accuracies of phase and strain images calculated using the AWHARP method are higher than that calculated using the HARP method especially for large tag line deformation. The improvement in accuracies can be up to 3.2 strain (E1) and 17.3 calculation from MR images reveals that the cardiac strain in the end-systolic state is significantly reduced for patients with hypertrophic cardiomyopathy (HCM) compared to that of healthy subjects.

CONCLUSION

The proposed AWHARP is an accurate and efficient method for cardiac strain estimation from MR images. This new algorithm can help clinicians to detect left ventricle dysfunctions and myocardial diseases with accurate cardiac strain analysis.

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.

Motion tracking and strain map computation for quasi-static magnetic resonance elastography

This paper presents a new imaging method for quasi-static magnetic resonance elastography (MRE). Tagged magnetic resonance (MR) imaging of human lower leg was acquired with probe indentation using a MR-compatible actuation system. Indentation force was recorded for soft tissue elasticity reconstruction. Motion tracking and strain map of human lower leg are calculated using a harmonic phase (HARP)-based method. Simulated tagged MR images were constructed and analyzed to validate the HARP-based method. Our results show that the proposed imaging method can be used to generate accurate motion distribution and strain maps of the targeted soft tissue.

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.

Force estimation and prediction from time-varying density images

We present methods for estimating forces which drive motion observed in density image sequences. Using these forces, we also present methods for predicting velocity and density evolution. To do this, we formulate and apply a Minimum Energy Flow (MEF) method which is capable of estimating both incompressible and compressible flows from time-varying density images. Both the MEF and force-estimation techniques are applied to experimentally obtained density images, spanning spatial scales from micrometers to several kilometers. Using density image sequences describing cell splitting, for example, we show that cell division is driven by gradients in apparent pressure within a cell. Using density image sequences of fish shoals, we also quantify 1) intershoal dynamics such as coalescence of fish groups over tens of kilometers, 2) fish mass flow between different parts of a large shoal, and 3) the stresses acting on large fish shoals.

Registration of 4D cardiac CT sequences under trajectory constraints with multichannel diffeomorphic demons

We propose a framework for the nonlinear spatiotemporal registration of 4D time-series of images based on the Diffeomorphic Demons (DD) algorithm. In this framework, the 4D spatiotemporal registration is decoupled into a 4D temporal registration, defined as mapping physiological states, and a 4D spatial registration, defined as mapping trajectories of physical points. Our contribution focuses more specifically on the 4D spatial registration that should be consistent over time as opposed to 3D registration that solely aims at mapping homologous points at a given time-point. First, we estimate in each sequence the motion displacement field, which is a dense representation of the point trajectories we want to register. Then, we perform simultaneously 3D registrations of corresponding time-points with the constraints to map the same physical points over time called the trajectory constraints. Under these constraints, we show that the 4D spatial registration can be formulated as a multichannel registration of 3D images. To solve it, we propose a novel version of the Diffeomorphic Demons (DD) algorithm extended to vector-valued 3D images, the Multichannel Diffeomorphic Demons (MDD). For evaluation, this framework is applied to the registration of 4D cardiac computed tomography (CT) sequences and compared to other standard methods with real patient data and synthetic data simulated from a physiologically realistic electromechanical cardiac model. Results show that the trajectory constraints act as a temporal regularization consistent with motion whereas the multichannel registration acts as a spatial regularization. Finally, using these trajectory constraints with multichannel registration yields the best compromise between registration accuracy, temporal and spatial smoothness, and computation times. A prospective example of application is also presented with the spatiotemporal registration of 4D cardiac CT sequences of the same patient before and after radiofrequency ablation (RFA) in case of atrial fibrillation (AF). The intersequence spatial transformations over a cardiac cycle allow to analyze and quantify the regression of left ventricular hypertrophy and its impact on the cardiac function.

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.

Motion estimation of tagged cardiac magnetic resonance images using variational techniques

This work presents a new method for motion estimation of tagged cardiac magnetic resonance sequences based on variational techniques. The variational method has been improved by adding a new term in the optical flow equation that incorporates tracking points with high stability of phase. Results were obtained through simulated and real data, and were validated by manual tracking and with respect to a reference state-of-the-art method: harmonic phase imaging (HARP). The error, measured in pixels per frame, obtained with the proposed variational method is one order of magnitude smaller than the one achieved by the reference method, and it requires a lower computational cost.

Deformation analysis of 3D tagged cardiac images using an optical flow method

BACKGROUND

This study proposes and validates a method of measuring 3D strain in myocardium using a 3D Cardiovascular Magnetic Resonance (CMR) tissue-tagging sequence and a 3D optical flow method (OFM).

METHODS

Initially, a 3D tag MR sequence was developed and the parameters of the sequence and 3D OFM were optimized using phantom images with simulated deformation. This method then was validated in-vivo and utilized to quantify normal sheep left ventricular functions.

RESULTS

Optimizing imaging and OFM parameters in the phantom study produced sub-pixel root-mean square error (RMS) between the estimated and known displacements in the x (RMSx = 0.62 pixels (0.43 mm)), y (RMSy = 0.64 pixels (0.45 mm)) and z (RMSz = 0.68 pixels (1 mm)) direction, respectively. In-vivo validation demonstrated excellent correlation between the displacement measured by manually tracking tag intersections and that generated by 3D OFM (R >or= 0.98). Technique performance was maintained even with 20% Gaussian noise added to the phantom images. Furthermore, 3D tracking of 3D cardiac motions resulted in a 51% decrease in in-plane tracking error as compared to 2D tracking. The in-vivo function studies showed that maximum wall thickening was greatest in the lateral wall, and increased from both apex and base towards the mid-ventricular region. Regional deformation patterns are in agreement with previous studies on LV function.

CONCLUSION

A novel method was developed to measure 3D LV wall deformation rapidly with high in-plane and through-plane resolution from one 3D cine acquisition.

A new methodology for multiscale myocardial deformation and strain analysis based on tagging MRI

Myocardial deformation and strain can be investigated using suitably encoded cine MRI that admits disambiguation of material motion. Practical limitations currently restrict the analysis to in-plane motion in cross-sections of the heart (2D + time), but the proposed method readily generalizes to 3D + time. We propose a new, promising methodology, which departs from a multiscale algorithm that exploits local scale selection so as to obtain a robust estimate for the velocity gradient tensor field. Time evolution of the deformation tensor is governed by a first-order ordinary differential equation, which is completely determined by this velocity gradient tensor field. We solve this matrix-ODE analytically and present results obtained from healthy volunteers as well as from patient data. The proposed method requires only off-the-shelf algorithms and is readily applicable to planar or volumetric tagging MRI sampled on arbitrary coordinate grids.

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.

Motion in cardiovascular MR imaging

Modern rapid magnetic resonance (MR) imaging techniques have led to widespread use of the modality in cardiac imaging. Despite this progress, many MR studies suffer from image degradation due to involuntary motion during the acquisition. This review describes the type and extent of the motion of the heart due to the cardiac and respiratory cycles, which create image artifacts. Methods of eliminating or reducing the problems caused by the cardiac cycle are discussed, including electrocardiogram gating, subject-specific acquisition windows, and section tracking. Similarly, for respiratory motion of the heart, techniques such as breath holding, respiratory gating, section tracking, phase-encoding ordering, subject-specific translational models, and a range of new techniques are considered.

Movement of the tongue during normal breathing in awake healthy humans

Electromyographic (EMG) activity of the airway muscles suggest that genioglossus is the primary upper airway dilator muscle. However, EMG data do not necessarily translate into tissue motion and most imaging modalities are limited to assessment of the surfaces of the upper airway. In this study, we hypothesized that genioglossus moves rhythmically during the respiratory cycle and that the motion within is inhomogeneous. A 'tagged' magnetic resonance imaging technique was used to characterize respiratory-related tissue motions around the human upper airway in quiet breathing. Motion of airway tissues at different segments of the eupnoeic respiratory cycle was imaged in six adult subjects by triggering the scanner at the end of inspiration. Displacements of the 'tags' were analysed using the harmonic phase method (HARP). Respiratory timing was monitored by a band around the upper abdomen. The genioglossus moved during the respiratory cycle. During expiration, the genioglossus moved posteriorly and during inspiration, it moved anteriorly. The degree of motion varied between subjects. The maximal anteroposterior movement of a point tracked on the genioglossus was 1.02 +/- 0.54 mm (mean +/- s.d.). The genioglossus moved over the geniohyoid muscle, with minimal movement in other muscles surrounding the airway at the level of the soft palate. Local deformation of the tongue was analysed using two-dimensional strain maps. Across the respiratory cycle, positive strains within genioglossus reached peaks of 17.5 +/- 9.3% and negative strains reached peaks of -16.3 +/- 9.3% relative to end inspiration. The patterns of strains were consistent with elongation and compression within a constant volume structure. Hence, these data suggest that even during respiration, the tongue behaves as a muscular hydrostat.