Strain measurement in the left ventricle during systole with deformable image registration

Probabilistic Modeling for Image Registration Using Radial Basis Functions: Application to Cardiac Motion Estimation

Cardiovascular diseases (CVDs) are the leading cause of death, affecting the cardiac dynamics over the cardiac cycle. Estimation of cardiac motion plays an essential role in many medical clinical tasks. This article proposes a probabilistic framework for image registration using compact support radial basis functions (CSRBFs) to estimate cardiac motion. A variational inference-based generative model with convolutional neural networks (CNNs) is proposed to learn the probabilistic coefficients of CSRBFs used in image deformation. We designed two networks to estimate the deformation coefficients of CSRBFs: the first one solves the spatial transformation using given control points, and the second one models the transformation using drifting control points. The given-point-based network estimates the probabilistic coefficients of control points. In contrast, the drifting-point-based model predicts the probabilistic coefficients and spatial distribution of control points simultaneously. To regularize these coefficients, we derive the bending energy (BE) in the variational bound by defining the covariance of coefficients. The proposed framework has been evaluated on the cardiac motion estimation and the calculation of the myocardial strain. In the experiments, 1409 slice pairs of end-diastolic (ED) and end-systolic (ES) phase in 4-D cardiac magnetic resonance (MR) images selected from three public datasets are employed to evaluate our networks. The experimental results show that our framework outperforms the state-of-the-art registration methods concerning the deformation smoothness and registration accuracy.

Learning Deformable Image Registration From Optimization: Perspective, Modules, Bilevel Training and Beyond

Conventional deformable registration methods aim at solving an optimization model carefully designed on image pairs and their computational costs are exceptionally high. In contrast, recent deep learning-based approaches can provide fast deformation estimation. These heuristic network architectures are fully data-driven and thus lack explicit geometric constraints which are indispensable to generate plausible deformations, e.g., topology-preserving. Moreover, these learning-based approaches typically pose hyper-parameter learning as a black-box problem and require considerable computational and human effort to perform many training runs. To tackle the aforementioned problems, we propose a new learning-based framework to optimize a diffeomorphic model via multi-scale propagation. Specifically, we introduce a generic optimization model to formulate diffeomorphic registration and develop a series of learnable architectures to obtain propagative updating in the coarse-to-fine feature space. Further, we propose a new bilevel self-tuned training strategy, allowing efficient search of task-specific hyper-parameters. This training strategy increases the flexibility to various types of data while reduces computational and human burdens. We conduct two groups of image registration experiments on 3D volume datasets including image-to-atlas registration on brain MRI data and image-to-image registration on liver CT data. Extensive results demonstrate the state-of-the-art performance of the proposed method with diffeomorphic guarantee and extreme efficiency. We also apply our framework to challenging multi-modal image registration, and investigate how our registration to support the down-streaming tasks for medical image analysis including multi-modal fusion and image segmentation.

Cardiac mesh morphing method for finite element modeling of heart failure with preserved ejection fraction

Numerical modeling of heart biomechanics can realistically capture morphological variations in diseases and has been helpful in advancing our understanding of the physiology. Subject-specific models require anatomic representation of medical images, and it is desirable to have a consistently repeatable models for any given morphology. In this study, we propose a novel and easily adaptable cardiac reconstruction algorithm by morphing an existing discretized mesh of an advanced finite element (FE) model, to match anatomies acquired from porcine cardiac magnetic resonance imaging (cMRI) scans. The morphing algorithm involves iterative FE simulations with visco-hyperelastic material properties. The living heart porcine model (LHPM) was chosen as the input baseline FE mesh, in order to preserve detailed anatomical features that cannot be captured in routine scans such as myofiber orientations and conduction pathways. The algorithm was demonstrated for the recreation of porcine hearts of a healthy subject and of a subject induced with heart failure with preserved ejection fraction (HFpEF) conditions, where there were substantial hypertrophy and anatomical alterations. We further used the morphed meshes for FE modeling of cardiac contraction and relaxation, thus demonstrating the applicability of the proposed algorithm in producing viable meshes. The results show that our algorithm can recreate the characteristic anatomical changes of cardiac remodeling, including heart muscle thickening, as well as replicate the reduction in ventricular volume. This algorithm allows for the creation of subject-specific models with the same mesh connectivity, thus enabling spatial comparison and analysis of pathologic progress.

Left ventricle motion estimation for cine MR images using sparse representation with shape constraint

PURPOSE

To propose a left ventricle (LV) motion estimation method based on sparse representation, in order to handle the spatial-varying intensity distortions caused by tissue deformation.

METHODS

For each myocardial landmark, an adaptive dictionary was generated by learning transformations from a training dataset. Then the landmark was tracked using sparse representation. Next, a point distribution model was applied to the overall tracking results. Finally, the dense displacement field of the LV myocardium was estimated based on the correspondence between each landmark. Using the dense displacement field estimated, the circumferential strain was calculated to assess the myocardial function. The performance of the proposed method was quantified by the average perpendicular distance (APD), the Dice metric, and the mean symmetric contour distance (SCD).

RESULTS

Comparing to the state-of-the-art techniques, the smallest value of APD and SCD, and the highest value of Dice can be obtained using the proposed method, for three public cardiac datasets. Moreover, the mean value of strain difference between the proposed method and the commercial software Medis Suite MR was -0.01, while the intraclass correlation coefficient between these two methods was 0.91.

CONCLUSIONS

The proposed method could estimate the dense displacement field of the LV accurately, which outperforms other state-of-the-art techniques. The circumferential strain derived from the proposed method was in excellent agreement with that derived from the Medis Suite MR software, while segmental strain abnormalities were detected for most of the subjects with heart diseases, which indicates the potential of the proposed method for clinical usage.

Estimating cardiomyofiber strain in vivo by solving a computational model

Since heart contraction results from the electrically activated contraction of millions of cardiomyocytes, a measure of cardiomyocyte shortening mechanistically underlies cardiac contraction. In this work we aim to measure preferential aggregate cardiomyocyte ("myofiber") strains based on Magnetic Resonance Imaging (MRI) data acquired to measure both voxel-wise displacements through systole and myofiber orientation. In order to reduce the effect of experimental noise on the computed myofiber strains, we recast the strains calculation as the solution of a boundary value problem (BVP). This approach does not require a calibrated material model, and consequently is independent of specific myocardial material properties. The solution to this auxiliary BVP is the displacement field corresponding to assigned values of myofiber strains. The actual myofiber strains are then determined by minimizing the difference between computed and measured displacements. The approach is validated using an analytical phantom, for which the ground-truth solution is known. The method is applied to compute myofiber strains using in vivo displacement and myofiber MRI data acquired in a mid-ventricular left ventricle section in N=8 swine subjects. The proposed method shows a more physiological distribution of myofiber strains compared to standard approaches that directly differentiate the displacement field.

Three-dimensional biventricular strains in pulmonary arterial hypertension patients using hyperelastic warping

BACKGROUND AND OBJECTIVE

Evaluation of biventricular function is an essential component of clinical management in pulmonary arterial hypertension (PAH). This study aims to examine the utility of biventricular strains derived from a model-to-image registration technique in PAH patients in comparison to age- and gender-matched normal controls.

METHODS

A three-dimensional (3D) model was reconstructed from cine short- and long-axis cardiac magnetic resonance (CMR) images and subsequently partitioned into right ventricle (RV), left ventricle (LV) and septum. The hyperelastic warping method was used to register the meshed biventricular finite element model throughout the cardiac cycle and obtain the corresponding biventricular circumferential, longitudinal and radial strains.

RESULTS

Intra- and inter-observer reproducibility of biventricular strains was excellent with all intra-class correlation coefficients > 0.84. 3D biventricular longitudinal, circumferential and radial strains for RV, LV and septum were significantly decreased in PAH patients compared with controls. Receiver operating characteristic (ROC) analysis showed that the 3D biventricular strains were better early markers (Area under the ROC curve = 0.96 for RV longitudinal strain) of ventricular dysfunction than conventional parameters such as two-dimensional strains and ejection fraction.

CONCLUSIONS

Our highly reproducible methodology holds potential for extending CMR imaging to characterize 3D biventricular strains, eventually leading to deeper understanding of biventricular mechanics in PAH.

Analysis of fiber strain in the human tongue during speech

This study investigates mechanical cooperation among tongue muscles. Five volunteers were imaged using tagged magnetic resonance imaging to quantify spatiotemporal kinematics while speaking. Waveforms of strain in the line of action of fibers (SLAF) were estimated by projecting strain tensors onto a model of fiber directionality. SLAF waveforms were temporally aligned to determine consistency across subjects and correlation across muscles. The cohort exhibited consistent patterns of SLAF, and muscular extension-contraction was correlated. Volume-preserving tongue movement in speech generation can be achieved through multiple paths, but the study reveals similarities in motion patterns and muscular action-despite anatomical (and other) dissimilarities.

CMR-based heart deformation analysis for quantification of hemodynamics and right ventricular dysfunction in patients with CTEPH

INTRODUCTION

Quantification of hemodynamics and right ventricular (RV) function is crucial for pulmonary hypertension (PH). Cardiovascular magnetic resonance-based heart deformation analysis (CMR-HDA) has been used to assess the ventricular strain.

OBJECTIVE

This study was to determine the correlation of right ventricular longitudinal strain (RVLS) assessed with CMR-HDA with RV function as well as hemodynamics in patients with chronic thromboembolic pulmonary hypertension (CTEPH).

METHODS

Thirty-six CTEPH patients were prospectively included in this research. Each patients underwent CMR and right heart catheterization (RHC). RVLS and RV ejection fraction (RVEF) was quantified from cine images acquired with a retrospectively gated turbo FLASH gradient-echo sequence. The late gadolinium enhancement (LGE) images were acquired using a 2D inversion recovery phase-sensitive fast gradient-echo sequence. Hemodynamics were determined with RHC.

RESULTS

Right ventricular longitudinal strain measured with CMR-HDA was -13.99 ± 4.94%. Bland-Altman plots showed statistical agreement with RVLS with low intra- and interobserver variability. RVLS correlated with serum N-terminal-pro-B-type natriuretic peptide (r = 0.615, P < .001). RVLS inversely correlated with RVEF (r = -0.699, P < .001), and it was positively correlated with both RVESV (r = 0.664, P < .001) and myocardial the volume of LGE (r = 0.447, P = .008). Receiver-operating characteristic (ROC) indicated that RVLS values of >-14.20% could be used to predict RVEF <40% with a 100% sensitivity and a 96.7% specificity. Hemodynamically, RVLS was positively correlated with mean pulmonary artery pressure (r = 0.598, P < .001) and pulmonary vascular resistance (r = 0.685, P < .001).

CONCLUSION

Right ventricular longitudinal strain assessed by CMR-HDA is a readily available and reproducible parameters of RV function. RVLS >-14.20% suggests the presence of RV dysfunction.

Current Understanding of the Biomechanics of Ventricular Tissues in Heart Failure

Heart failure is the leading cause of death worldwide, and the most common cause of heart failure is ventricular dysfunction. It is well known that the ventricles are anisotropic and viscoelastic tissues and their mechanical properties change in diseased states. The tissue mechanical behavior is an important determinant of the function of ventricles. The aim of this paper is to review the current understanding of the biomechanics of ventricular tissues as well as the clinical significance. We present the common methods of the mechanical measurement of ventricles, the known ventricular mechanical properties including the viscoelasticity of the tissue, the existing computational models, and the clinical relevance of the ventricular mechanical properties. Lastly, we suggest some future research directions to elucidate the roles of the ventricular biomechanics in the ventricular dysfunction to inspire new therapies for heart failure patients.

Computational quantification of patient-specific changes in ventricular dynamics associated with pulmonary hypertension

Pulmonary arterial hypertension (PAH) causes an increase in the mechanical loading imposed on the right ventricle (RV) that results in progressive changes to its mechanics and function. Here, we quantify the mechanical changes associated with PAH by assimilating clinical data consisting of reconstructed three-dimensional geometry, pressure, and volume waveforms, as well as regional strains measured in patients with PAH (n = 12) and controls (n = 6) within a computational modeling framework of the ventricles. Modeling parameters reflecting regional passive stiffness and load-independent contractility as indexed by the tissue active tension were optimized so that simulation results matched the measurements. The optimized parameters were compared with clinical metrics to find usable indicators associated with the underlying mechanical changes. Peak contractility of the RV free wall (RVFW) γ_RVFW,max was found to be strongly correlated and had an inverse relationship with the RV and left ventricle (LV) end-diastolic volume ratio (i.e., RVEDV/LVEDV) (RVEDV/LVEDV)+ 0.44, R² = 0.77). Correlation with RV ejection fraction (R² = 0.50) and end-diastolic volume index (R² = 0.40) were comparatively weaker. Patients with with RVEDV/LVEDV > 1.5 had 25% lower γ_RVFW,max (P < 0.05) than that of the control. On average, RVFW passive stiffness progressively increased with the degree of remodeling as indexed by RVEDV/LVEDV. These results suggest a mechanical basis of using RVEDV/LVEDV as a clinical index for delineating disease severity and estimating RVFW contractility in patients with PAH.NEW & NOTEWORTHY This article presents patient-specific data assimilation of a patient cohort and physical description of clinical observations.

Hierarchical Template Matching for 3D Myocardial Tracking and Cardiac Strain Estimation

Myocardial tracking and strain estimation can non-invasively assess cardiac functioning using subject-specific MRI. As the left-ventricle does not have a uniform shape and functioning from base to apex, the development of 3D MRI has provided opportunities for simultaneous 3D tracking, and 3D strain estimation. We have extended a Local Weighted Mean (LWM) transformation function for 3D, and incorporated in a Hierarchical Template Matching model to solve 3D myocardial tracking and strain estimation problem. The LWM does not need to solve a large system of equations, provides smooth displacement of myocardial points, and adapt local geometric differences in images. Hence, 3D myocardial tracking can be performed with 1.49 mm median error, and without large error outliers. The maximum error of tracking is up to 24% reduced compared to benchmark methods. Moreover, the estimated strain can be insightful to improve 3D imaging protocols, and the computer code of LWM could also be useful for geo-spatial and manufacturing image analysis researchers.

3-D Measurements of Acceleration-Induced Brain Deformation via Harmonic Phase Analysis and Finite-Element Models

OBJECTIVE

To obtain dense spatiotemporal measurements of brain deformation from two distinct but complementary head motion experiments: linear and rotational accelerations.

METHODS

This study introduces a strategy for integrating harmonic phase analysis of tagged magnetic resonance imaging (MRI) and finite-element models to extract mechanically representative deformation measurements. The method was calibrated using simulated as well as experimental data, demonstrated in a phantom including data with image artifacts, and used to measure brain deformation in human volunteers undergoing rotational and linear acceleration.

RESULTS

Evaluation methods yielded a displacement error of 1.1 mm compared to human observers and strain errors between [Formula: see text] for linear acceleration and [Formula: see text] for rotational acceleration. This study also demonstrates an approach that can reduce error by 86% in the presence of corrupted data. Analysis of results shows consistency with 2-D motion estimation, agreement with external sensors, and the expected physical behavior of the brain.

CONCLUSION

Mechanical regularization is useful for obtaining dense spatiotemporal measurements of in vivo brain deformation under different loading regimes.

SIGNIFICANCE

The measurements suggest that the brain's 3-D response to mild accelerations includes distinct patterns observable using practical MRI resolutions. This type of measurement can provide validation data for computer models for the study of traumatic brain injury.

A Computational Cardiac Model for the Adaptation to Pulmonary Arterial Hypertension in the Rat

Pulmonary arterial hypertension (PAH) imposes pressure overload on the right ventricle (RV), leading to RV enlargement via the growth of cardiac myocytes and remodeling of the collagen fiber architecture. The effects of these alterations on the functional behavior of the right ventricular free wall (RVFW) and organ-level cardiac function remain largely unexplored. Computational heart models in the rat (RHMs) of the normal and hypertensive states can be quite valuable in simulating the effects of PAH on cardiac function to gain insights into the pathophysiology of underlying myocardium remodeling. We thus developed high-fidelity biventricular finite element RHMs for the normal and post-PAH hypertensive states using extensive experimental data collected from rat hearts. We then applied the RHM to investigate the transmural nature of RVFW remodeling and its connection to wall stress elevation under PAH. We found a strong correlation between the longitudinally-dominated fiber-level adaptation of the RVFW and the transmural alterations of relevant wall stress components. We further conducted several numerical experiments to gain new insights on how the RV responds both normally and in the post-PAH state. We found that the effect of pressure overload alone on the increased contractility of the RV is comparable to the effects of changes in the RV geometry and stiffness. Furthermore, our RHMs provided fresh perspectives on long-standing questions of the functional role of the interventricular septum in RV function. Specifically, we demonstrated that an inaccurate identification of the mechanical adaptation of the septum can lead to a significant underestimation of RVFW contractility in the post-PAH state. These findings show how integrated experimental-computational models can facilitate a more comprehensive understanding of the cardiac remodeling events during PAH.

A Plugin Framework for Extending the Simulation Capabilities of FEBio

The FEBio software suite is a set of software tools for nonlinear finite element analysis in biomechanics and biophysics. FEBio employs mixture theory to account for the multiconstituent nature of biological materials, integrating the field equations for irreversible thermodynamics, solid mechanics, fluid mechanics, mass transport with reactive species, and electrokinetics. This communication describes the development and application of a new "plugin" framework for FEBio. Plugins are dynamically linked libraries that allow users to add new features and to couple FEBio with other domain-specific software applications without modifying the source code directly. The governing equations and simulation capabilities of FEBio are reviewed. The implementation, structure, use, and application of the plugin framework are detailed. Several example plugins are described in detail to illustrate how plugins enrich, extend, and leverage existing capabilities in FEBio, including applications to deformable image registration, constitutive modeling of biological tissues, coupling to an external software package that simulates angiogenesis using a discrete computational model, and a nonlinear reaction-diffusion solver. The plugin feature facilitates dissemination of new simulation methods, reproduction of published results, and coupling of FEBio with other domain-specific simulation approaches such as compartmental modeling, agent-based modeling, and rigid-body dynamics. We anticipate that the new plugin framework will greatly expand the range of applications for the FEBio software suite and thus its impact.

Quantification of Biventricular Strains in Heart Failure With Preserved Ejection Fraction Patient Using Hyperelastic Warping Method

Heart failure (HF) imposes a major global health care burden on society and suffering on the individual. About 50% of HF patients have preserved ejection fraction (HFpEF). More intricate and comprehensive measurement-focused imaging of multiple strain components may aid in the diagnosis and elucidation of this disease. Here, we describe the development of a semi-automated hyperelastic warping method for rapid comprehensive assessment of biventricular circumferential, longitudinal, and radial strains that is physiological meaningful and reproducible. We recruited and performed cardiac magnetic resonance (CMR) imaging on 30 subjects [10 HFpEF, 10 HF with reduced ejection fraction patients (HFrEF) and 10 healthy controls]. In each subject, a three-dimensional heart model including left ventricle (LV), right ventricle (RV), and septum was reconstructed from CMR images. The hyperelastic warping method was used to reference the segmented model with the target images and biventricular circumferential, longitudinal, and radial strain-time curves were obtained. The peak systolic strains are then measured and analyzed in this study. Intra- and inter-observer reproducibility of the biventricular peak systolic strains was excellent with all ICCs > 0.92. LV peak systolic circumferential, longitudinal, and radial strain, respectively, exhibited a progressive decrease in magnitude from healthy control→HFpEF→HFrEF: control (-15.5 ± 1.90, -15.6 ± 2.06, 41.4 ± 12.2%); HFpEF (-9.37 ± 3.23, -11.3 ± 1.76, 22.8 ± 13.1%); HFrEF (-4.75 ± 2.74, -7.55 ± 1.75, 10.8 ± 4.61%). A similar progressive decrease in magnitude was observed for RV peak systolic circumferential, longitudinal and radial strain: control (-9.91 ± 2.25, -14.5 ± 2.63, 26.8 ± 7.16%); HFpEF (-7.38 ± 3.17, -12.0 ± 2.45, 21.5 ± 10.0%); HFrEF (-5.92 ± 3.13, -8.63 ± 2.79, 15.2 ± 6.33%). Furthermore, septum peak systolic circumferential, longitudinal, and radial strain magnitude decreased gradually from healthy control to HFrEF: control (-7.11 ± 1.81, 16.3 ± 3.23, 18.5 ± 8.64%); HFpEF (-6.11 ± 3.98, -13.4 ± 3.02, 12.5 ± 6.38%); HFrEF (-1.42 ± 1.36, -8.99 ± 2.96, 3.35 ± 2.95%). The ROC analysis indicated LV peak systolic circumferential strain to be the most sensitive marker for differentiating HFpEF from healthy controls. Our results suggest that the hyperelastic warping method with the CMR-derived strains may reveal subtle impairment in HF biventricular mechanics, in particular despite a "normal" ventricular ejection fraction in HFpEF.

Equilibrated warping: Finite element image registration with finite strain equilibrium gap regularization

In this paper, we propose a novel continuum finite strain formulation of the equilibrium gap regularization for image registration. The equilibrium gap regularization essentially penalizes any deviation from the solution of a hyperelastic body in equilibrium with arbitrary loads prescribed at the boundary. It thus represents a regularization with strong mechanical basis, especially suited for cardiac image analysis. We describe the consistent linearization and discretization of the regularized image registration problem, in the framework of the finite elements method. The method is implemented using FEniCS & VTK, and distributed as a freely available python library. We show that the equilibrated warping method is effective and robust: regularization strength and image noise have minimal impact on motion tracking, especially when compared to strain-based regularization methods such as hyperelastic warping. We also show that equilibrated warping is able to extract main deformation features on both tagged and untagged cardiac magnetic resonance images.

Right Ventricular Fiber Structure as a Compensatory Mechanism in Pressure Overload: A Computational Study

Right ventricular failure (RVF) is a lethal condition in diverse pathologies. Pressure overload is the most common etiology of RVF, but our understanding of the tissue structure remodeling and other biomechanical factors involved in RVF is limited. Some remodeling patterns are interpreted as compensatory mechanisms including myocyte hypertrophy, extracellular fibrosis, and changes in fiber orientation. However, the specific implications of these changes, especially in relation to clinically observable measurements, are difficult to investigate experimentally. In this computational study, we hypothesized that, with other variables constant, fiber orientation alteration provides a quantifiable and distinct compensatory mechanism during RV pressure overload (RVPO). Numerical models were constructed using a rabbit model of chronic pressure overload RVF based on intraventricular pressure measurements, CINE magnetic resonance imaging (MRI), and diffusion tensor MRI (DT-MRI). Biventricular simulations were conducted under normotensive and hypertensive boundary conditions using variations in RV wall thickness, tissue stiffness, and fiber orientation to investigate their effect on RV pump function. Our results show that a longitudinally aligned myocardial fiber orientation contributed to an increase in RV ejection fraction (RVEF). This effect was more pronounced in response to pressure overload. Likewise, models with longitudinally aligned fiber orientation required a lesser contractility for maintaining a target RVEF against elevated pressures. In addition to increased wall thickness and material stiffness (diastolic compensation), systolic mechanisms in the forms of myocardial fiber realignment and changes in contractility are likely involved in the overall compensatory responses to pressure overload.

Improved segmental myocardial strain reproducibility using deformable registration algorithms compared with feature tracking cardiac MRI and speckle tracking echocardiography

BACKGROUND

Segmental myocardial strain using feature tracking (FT) cardiac MRI is not acceptable due to poor reproducibility.

PURPOSE

To assess the reproducibility of left ventricle (LV) segmental myocardial strain measured by deformation registration algorithm (DRA).

STUDY TYPE

Prospective clinical trial.

SUBJECTS

Sixteen healthy volunteers and 28 hypertrophic cardiomyopathy (HCM) patients.

FIELD STRENGTH/SEQUENCE

Retrospective ECG gating cardiac MRI imaging was performed at 3.0T with a steady-state free precession (SSFP) sequence.

ASSESSMENT

LV global and segmental myocardial strains were analyzed by DRA, FT, and speckle tracking echocardiography (STE) by two experienced observers and the reproducibility of global and segmental strains were compared.

STATISTICAL TESTS

Reproducibility was tested by coefficient of variation (COV) and intraclass correlation coefficient (ICC). Receiver operator curves as well as comparison of areas under the curve (AUC) were analyzed.

RESULTS

DRA showed the best observer agreement on segmental strain evaluated by ICC, LS (longitudinal strain): intraobserver variability range (0.98,1.00), interobserver variability range (0.83,0.92), CS (circumferential strain): intraobserver variability range (0.90,0.99), interobserver variability range (0.80,0.97), RS (radial strain): intraobserver variability range (0.84,0.99), interobserver variability range (0.85,0.99). Segmental LS, CS, and RS agreements evaluated by COV for FT and STE were poor. LV global myocardial strain of HCM was significantly lower than controls for all applied techniques, but global CS by DRA had better accuracy compared to FT or STE for distinguishing HCM from healthy subjects: AUC 0.880 (DRA) vs. 0.577 (FT) or 0.736 (STE), P < 0.05.

DATA CONCLUSIONS

DRA is a reliable and robust analysis tool for segmental myocardial strain. Global CS by DRA allows discrimination between HCM and normal controls with better accuracy compared with FT and STE.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2018;48:404-414.

Patient-Specific Computational Analysis of Ventricular Mechanics in Pulmonary Arterial Hypertension

Patient-specific biventricular computational models associated with a normal subject and a pulmonary arterial hypertension (PAH) patient were developed to investigate the disease effects on ventricular mechanics. These models were developed using geometry reconstructed from magnetic resonance (MR) images, and constitutive descriptors of passive and active mechanics in cardiac tissues. Model parameter values associated with ventricular mechanical properties and myofiber architecture were obtained by fitting the models with measured pressure-volume loops and circumferential strain calculated from MR images using a hyperelastic warping method. Results show that the peak right ventricle (RV) pressure was substantially higher in the PAH patient (65 mmHg versus 20 mmHg), who also has a significantly reduced ejection fraction (EF) in both ventricles (left ventricle (LV): 39% versus 66% and RV: 18% versus 64%). Peak systolic circumferential strain was comparatively lower in both the left ventricle (LV) and RV free wall (RVFW) of the PAH patient (LV: -6.8% versus -13.2% and RVFW: -2.1% versus -9.4%). Passive stiffness, contractility, and myofiber stress in the PAH patient were all found to be substantially increased in both ventricles, whereas septum wall in the PAH patient possessed a smaller curvature than that in the LV free wall. Simulations using the PAH model revealed an approximately linear relationship between the septum curvature and the transseptal pressure gradient at both early-diastole and end-systole. These findings suggest that PAH can induce LV remodeling, and septum curvature measurements may be useful in quantifying transseptal pressure gradient in PAH patients.

Automated Description of Regional Left Ventricular Motion in Patients With Cardiac Amyloidosis: A Quantitative Study Using Heart Deformation Analysis

OBJECTIVE

The purpose of this article is to test the hypothesis that heart deformation analysis can automatically quantify regional myocardial motion patterns in patients with cardiac amyloidosis.

SUBJECTS AND METHODS

Eleven patients with cardiac amyloidosis and 11 healthy control subjects were recruited to undergo cardiac MRI. Cine images were analyzed using heart deformation analysis and feature tracking. Heart deformation analysis-derived myocardial motion indexes in radial and circumferential directions, including radial and circumferential displacement, radial and circumferential velocity, radial and circumferential strain, and radial and circumferential strain rate, were compared between the two groups.

RESULTS

) than did healthy control subjects. Heart deformation analysis-derived indexes correlated with feature tracking-derived indexes (r = 0.411 and 0.552).

CONCLUSION

Heart deformation analysis is able to automatically quantify regional myocardial motion in patients with cardiac amyloidosis without the need for operator interaction.

Motion Estimation with Finite-Element Biomechanical Models and Tracking Constraints from Tagged MRI

Noninvasive measurements of tissue deformation provide bio-mechanical insights of an organ, which can be used as clinical functional biomarkers or experimental data for validating computational simulations. However, acquisition of 3D displacement information is susceptible to experimental inconsistency and limited scan time. In this research, we describe the process of tracking tagged magnetic resonance imaging (MRI) as enforcing harmonic phase conservation in finite-element (FE) models. This concept is demonstrated as a tool for motion estimation in a brain motion phantom, the heart, and the tongue. Our results demonstrate that the new methodology offers robustness to edge and large-displacement artifacts, and that it can be seamlessly coupled with numerical simulations for estimating fiber stretch in residually stressed tissue, or for inverse identification of muscle activation.

A Novel Method for Estimating Myocardial Strain: Assessment of Deformation Tracking Against Reference Magnetic Resonance Methods in Healthy Volunteers

We developed a novel method for tracking myocardial deformation using cardiac magnetic resonance (CMR) cine imaging. We hypothesised that circumferential strain using deformation-tracking has comparable diagnostic performance to a validated method (Displacement Encoding with Stimulated Echoes- DENSE) and potentially diagnostically superior to an established cine-strain method (feature-tracking). 81 healthy adults (44.6 ± 17.7 years old, 47% male), without any history of cardiovascular disease, underwent CMR at 1.5 T including cine, DENSE, and late gadolinium enhancement in subjects >45 years. Acquisitions were divided into 6 segments, and global and segmental peak circumferential strain were derived and analysed by age and sex. Peak circumferential strain differed between the 3 groups (DENSE: −19.4 ± 4.8%; deformation-tracking: −16.8 ± 2.4%; feature-tracking: −28.7 ± 4.8%) (ANOVA with Tukey post-hoc, F-value 279.93, p < 0.01). DENSE and deformation-tracking had better reproducibility than feature-tracking. Intra-class correlation co-efficient was >0.90. Larger magnitudes of strain were detected in women using deformation-tracking and DENSE, but not feature-tracking. Compared with a reference method (DENSE), deformation-tracking using cine imaging has similar diagnostic performance for circumferential strain assessment in healthy individuals. Deformation-tracking could potentially obviate the need for bespoke strain sequences, reducing scanning time and is more reproducible than feature-tracking.

Heart deformation analysis: the distribution of regional myocardial motion patterns at left ventricle

The aim of the present study was to test the hypothesis that heart deformation analysis (HDA) is able to discriminate regional myocardial motion patterns on the left ventricle (LV). Totally 21 healthy volunteers (15 men and 6 women) without documented cardiovascular diseases were recruited. Cine MRI was performed on those subjects at four-chamber, two-chamber, and short-axis views. The variations of segmental myocardial motion indices of the LV, which were measured with the HDA tool, were investigated. Regional displacement, velocity, strain and strain rate were compared between lateral wall and septal wall using t tests. There are significant variations (CoV = 18.0-72.4%) of myocardial motion indices (average over 21 subjects) among 16 myocardial segments. There are significant differences (p < 0.05) between displacement, velocity, strain and strain rate measured at lateral and septal areas of the LV. In conclusion, HDA is able to present different regional LV motion patterns from multiple aspects in healthy volunteers.

Heart deformation analysis for automated quantification of cardiac function and regional myocardial motion patterns: A proof of concept study in patients with cardiomyopathy and healthy subjects

OBJECTIVE

To test the performance of HDA in characterizing left ventricular (LV) function and regional myocardial motion patterns in the context of cardiomyopathy based on cine cardiovascular magnetic resonance (CMR).

MATERIALS AND METHODS

Following the approval of the institutional review board (IRB), standard cine images of 45 subjects, including 15 healthy volunteers, 15 patients with hypertrophic cardiomyopathy (HCM) and 15 patients with dilated cardiomyopathy (DCM) were retrospectively analyzed using HDA. The variations of LV ejection fraction (LVEF), LV mass (LVM), and regional myocardial motion indices, including radial (Drr), circumferential (Dcc) displacement, radial (Vrr) and circumferential (Vcc) velocity, radial (Err), circumferential (Ecc) and shear (Ess) strain and radial (SRr) and circumferential (SRc) strain rate, were calculated and compared among subject groups. Inter-study reproducibility of HDA-derived myocardial motion indices were tested on 15 volunteers by using intra-class correlation coefficient (ICC) and coefficient of variation (CoV).

RESULTS

HDA identified significant differences in cardiac function and motion indices between subject groups. DCM patients had significantly lower LVEF (33.5±9.65%), LVM (105.88±21.93g), peak Drr (0.29±0.11cm), Vrr-sys (2.14±0.72cm/s), Err (0.17±0.08), Ecc (-0.08±0.03), SRr-sys (0.91±0.44s(-1)) and SRc-sys (-0.64±0.27s(-1)) compared to the other two groups. HCM patients demonstrated increased LVM (171.69±34.19) and lower peak Vcc-dia (0.78±0.30cm/s) than other subjects. Good inter-study reproducibility was found for all HDA-derived myocardial indices in healthy volunteers (ICC=0.664-0.942, CoV=15.1%-37.1%).

CONCLUSION

Without the need for operator interaction, HDA is a reproducible method for the automated characterization of global and regional LV function in the context of cardiomyopathy.

Heart deformation analysis: measuring regional myocardial velocity with MR imaging

The aim of the present study was to test the hypothesis that heart deformation analysis (HDA) may serve as an alternative for the quantification of regional myocardial velocity. Nineteen healthy volunteers (14 male and 5 female) without documented cardiovascular diseases were recruited following the approval of the institutional review board (IRB). For each participant, cine images (at base, mid and apex levels of the left ventricle [LV]) and tissue phase mapping (TPM, at same short-axis slices of the LV) were acquired within a single magnetic resonance (MR) scan. Regional myocardial velocities in radial and circumferential directions acquired with HDA (Vrr and Vcc) and TPM (Vr and VФ) were measured during the cardiac cycle. HDA required shorter processing time compared to TPM (2.3 ± 1.1 min/case vs. 9.5 ± 3.7 min/case, p < 0.001). Moderate to good correlations between velocity components measured with HDA and TPM could be found on multiple myocardial segments (r = 0.460-0.774) and slices (r = 0.409-0.814) with statistical significance (p < 0.05). However, significant biases of velocity measures at regional myocardial areas between HDA and TPM were also noticed. By providing comparable velocity measures as TPM does, HDA may serve as an alternative for measuring regional myocardial velocity with a faster image processing procedure.

Automated Assessment of Left Ventricular Function and Mass Using Heart Deformation Analysis: Initial Experience in 160 Older Adults

RATIONALE AND OBJECTIVES

To assess the performance of automated quantification of left ventricular function and mass based on heart deformation analysis (HDA) in asymptomatic older adults.

MATERIALS AND METHODS

This study complied with Health Insurance Portability and Accountability Act regulations. Following the approval of the institutional review board, 160 asymptomatic older participants were recruited for cardiac magnetic resonance imaging including two-dimensional cine images covering the entire left ventricle in short-axis view. Data analysis included the calculation of left ventricular ejection fraction (LVEF), left ventricular mass (LVM), and cardiac output (CO) using HDA and standard global cardiac function analysis (delineation of end-systolic and end-diastolic left ventricle epi- and endocardial borders). The agreement between methods was evaluated using intraclass correlation coefficient (ICC) and coefficient of variation (CoV).

RESULTS

HDA had a shorter processing time than the standard method (1.5 ± 0.3 min/case vs. 5.8 ± 1.4 min/case, P < 0.001). There was good agreement for LVEF (ICC = 0.552, CoV = 10.5%), CO (ICC = 0.773, CoV = 13.5%), and LVM (ICC = 0.859, CoV = 14.5%) acquired with the standard method and HDA. There was a systemic bias toward lower LVEF (62.8% ± 8.3% vs. 69.3% ± 6.7%, P < 0.001) and CO (4.4 ± 1.0 L/min vs. 4.8 ± 1.3 L/min, P < 0.001) by HDA compared to the standard technique. Conversely, HDA overestimated LVM (114.8 ± 30.1 g vs. 100.2 ± 29.0 g, P < 0.001) as compared to the reference method.

CONCLUSIONS

HDA has the potential to measure LVEF, CO, and LVM without the need for user interaction based on standard cardiac two-dimensional cine images.

Ultrasound guidance for beating heart mitral valve repair augmented by synthetic dynamic CT

Minimally invasive valvular intervention commonly requires intra-procedural navigation to provide spatial and temporal information of relevant cardiac structures and device components. Recently intra-procedural trans-esophageal echocardiography (TEE) has been exploited for this purpose due to its accessibility, low cost, ease of use, and real-time imaging capacity. However, the position and orientation of tissue targets relative to surgical tools can be challenging to perceive, particularly using 2D imaging planes. In this paper, we propose the use of CT images to provide a high-quality 3D context to enhance ultrasound images through image registration, providing an augmented guidance system with minimal impact on standard clinical workflow. We also describe an approach to generate synthetic 4D CT images through non-rigid registration of available ultrasound. This can be employed to avoid a requirement for higher radiation. Synthetic CT images were validated through direct comparison of synthetic and real multi-phase CT images. Validation of CT and ultrasound image registration was performed for both dynamic and synthetic CT image datasets. Our results demonstrated that the synthetically generated dynamic CT images provide similar anatomical representation for relevant cardiac anatomy relative to real dynamic CT images, and similar high registration accuracy that can be achieved for intra-procedural TEE to this versus real dynamic CT images.

Higher-Order Motion-Compensation for In Vivo Cardiac Diffusion Tensor Imaging in Rats

Motion of the heart has complicated in vivo applications of cardiac diffusion MRI and diffusion tensor imaging (DTI), especially in small animals such as rats where ultra-high-performance gradient sets are currently not available. Even with velocity compensation via, for example, bipolar encoding pulses, the variable shot-to-shot residual motion-induced spin phase can still give rise to pronounced artifacts. This study presents diffusion-encoding schemes that are designed to compensate for higher-order motion components, including acceleration and jerk, which also have the desirable practical features of minimal TEs and high achievable b-values. The effectiveness of these schemes was verified numerically on a realistic beating heart phantom, and demonstrated empirically with in vivo cardiac diffusion MRI in rats. Compensation for acceleration, and lower motion components, was found to be both necessary and sufficient for obtaining diffusion-weighted images of acceptable quality and SNR, which yielded the first in vivo cardiac DTI demonstrated in the rat. These findings suggest that compensation for higher order motion, particularly acceleration, can be an effective alternative solution to high-performance gradient hardware for improving in vivo cardiac DTI.

Finite-Element Extrapolation of Myocardial Structure Alterations Across the Cardiac Cycle in Rats

Myocardial microstructures are responsible for key aspects of cardiac mechanical function. Natural myocardial deformation across the cardiac cycle induces measurable structural alteration, which varies across disease states. Diffusion tensor magnetic resonance imaging (DT-MRI) has become the tool of choice for myocardial structural analysis. Yet, obtaining the comprehensive structural information of the whole organ, in 3D and time, for subject-specific examination is fundamentally limited by scan time. Therefore, subject-specific finite-element (FE) analysis of a group of rat hearts was implemented for extrapolating a set of initial DT-MRI to the rest of the cardiac cycle. The effect of material symmetry (isotropy, transverse isotropy, and orthotropy), structural input, and warping approach was observed by comparing simulated predictions against in vivo MRI displacement measurements and DT-MRI of an isolated heart preparation at relaxed, inflated, and contracture states. Overall, the results indicate that, while ventricular volume and circumferential strain are largely independent of the simulation strategy, structural alteration predictions are generally improved with the sophistication of the material model, which also enhances torsion and radial strain predictions. Moreover, whereas subject-specific transversely isotropic models produced the most accurate descriptions of fiber structural alterations, the orthotropic models best captured changes in sheet structure. These findings underscore the need for subject-specific input data, including structure, to extrapolate DT-MRI measurements across the cardiac cycle.

Characterization of regional deformation and material properties of the intact explanted vein by microCT and computational analysis

PURPOSE

Detailed mechanical information of the vein is important to better understand remodeling of the vessel in disease states, but has been difficult to obtain due to its thinness, unique geometry, and limitations of mechanical testing. This study presents a novel method for characterizing deformation of the intact explanted vein under physiological loads and determining its material properties by combining high-resolution imaging and computational analysis.

METHODS

High-resolution CT (microCT) was used to image an iodine-stained, excised porcine internal jugular vein sample under extension to 100% and 120% of in situ length, and inflation and 2, 10, 20 mmHg of pressure, inside a microCT-compatible hydrostatic loading chamber. Regional strains were measured with the finite element (FE) image registration method known as Hyperelastic Warping. Material properties were approximated with inverse FE characterization by optimizing stiffness-related coefficients so to match simulated strains to the experimental measurements.

RESULTS

The observed morphology and regional strain of the vein were found to be relatively heterogeneous. The regional variability in the measured strain was primarily driven by geometry. Although iodine treatment may result in tissue stiffening, which requires additional investigation, it is effective in allowing detailed detection of vein geometry.

CONCLUSIONS

The feasibility and utility of using microCT and computational analysis to characterize mechanical responses and material properties of the vein were demonstrated. The presented method is a promising alternative or addition to mechanical testing for characterizing veins or other similarly delicate vessels in their native anatomical configuration under a wide range of realistic or simulated environmental and loading conditions.

Ventricular mechanics: techniques and applications

Magnetic resonance assessment of regional myocardial function is a novel potentially important tool for early identification of cardiac pathology. Many cardiac magnetic resonance techniques have been developed for detection and quantification of regional strain abnormalities including steady-state free-precession CINE, tagging, displacement encoding with stimulated echoes, strain encoding imaging, and feature tracking. Potential clinical applications of magnetic resonance strain imaging include early detection of systolic dysfunction in heart failure patients with both ischemic and nonischemic etiologies.

In vivo strain assessment of the abdominal aortic aneurysm

The only criteria currently used to inform surgical decision for abdominal aortic aneurysms are maximum diameter (>5.5 cm) and rate of growth, even though several studies have identified the need for more specific indicators of risk. Patient-specific biomechanical variables likely to affect rupture risk would be a valuable addition to the science of understanding rupture risk and prove to be a life saving benefit for patients. Local deformability of the aorta is related to the local mechanical properties of the wall and may provide indication on the state of weakening of the wall tissue. We propose a 3D image-based approach to compute aortic wall strain maps in vivo. The method is applicable to a variety of imaging modalities that provide sequential images at different phases in the cardiac cycle. We applied the method to a series of abdominal aneurysms imaged using cine-MRI obtaining strain maps at different phases in the cardiac cycle. These maps could be used to evaluate the distensibility of an aneurysm at baseline and at different follow-up times and provide an additional index to clinicians to facilitate decisions on the best course of action for a specific patient.

Left ventricular strain and its pattern estimated from cine CMR and validation with DENSE

Measurement of local strain provides insight into the biomechanical significance of viable myocardium. We attempted to estimate myocardial strain from cine cardiovascular magnetic resonance (CMR) images by using a b-spline deformable image registration method. Three healthy volunteers and 41 patients with either recent or chronic myocardial infarction (MI) were studied at 1.5 Tesla with both cine and DENSE CMR. Regional circumferential and radial left ventricular strains were estimated from cine and DENSE acquisitions. In all healthy volunteers, there was no difference for peak circumferential strain (- 0.18 ± 0.04 versus - 0.18 ± 0.03, p = 0.76) between cine and DENSE CMR, however peak radial strain was overestimated from cine (0.84 ± 0.37 versus 0.49 ± 0.2, p < 0.01). In the patient study, the peak strain patterns predicted by cine were similar to the patterns from DENSE, including the strain evolution related to recovery time and strain patterns related to MI scar extent. Furthermore, cine-derived strain disclosed different strain patterns in MI and non-MI regions, and regions with transmural and non-transmural MI as DENSE. Although there were large variations with radial strain measurements from cine CMR images, useful circumferential strain information can be obtained from routine clinical CMR imaging. Cine strain analysis has potential to improve the diagnostic yield from routine CMR imaging in clinical practice.

Accurate high-resolution measurements of 3-D tissue dynamics with registration-enhanced displacement encoded MRI

Displacement fields are important to analyze deformation, which is associated with functional and material tissue properties often used as indicators of health. Magnetic resonance imaging (MRI) techniques like DENSE and image registration methods like Hyperelastic Warping have been used to produce pixel-level deformation fields that are desirable in high-resolution analysis. However, DENSE can be complicated by challenges associated with image phase unwrapping, in particular offset determination. On the other hand, Hyperelastic Warping can be hampered by low local image contrast. The current work proposes a novel approach for measuring tissue displacement with both DENSE and Hyperelastic Warping, incorporating physically accurate displacements obtained by the latter to improve phase characterization in DENSE. The validity of the proposed technique is demonstrated using numerical and physical phantoms, and in vivo small animal cardiac MRI.

A new method for the in vivo identification of mechanical properties in arteries from cine MRI images: theoretical framework and validation

Quantifying the stiffness properties of soft tissues is essential for the diagnosis of many cardiovascular diseases such as atherosclerosis. In these pathologies it is widely agreed that the arterial wall stiffness is an indicator of vulnerability. The present paper focuses on the carotid artery and proposes a new inversion methodology for deriving the stiffness properties of the wall from cine-MRI (magnetic resonance imaging) data. We address this problem by setting-up a cost function defined as the distance between the modeled pixel signals and the measured ones. Minimizing this cost function yields the unknown stiffness properties of both the arterial wall and the surrounding tissues. The sensitivity of the identified properties to various sources of uncertainty is studied. Validation of the method is performed on a rubber phantom. The elastic modulus identified using the developed methodology lies within a mean error of 9.6%. It is then applied to two young healthy subjects as a proof of practical feasibility, with identified values of 625 kPa and 587 kPa for one of the carotid of each subject.

Deformable medical image registration: a survey

Deformable image registration is a fundamental task in medical image processing. Among its most important applications, one may cite: 1) multi-modality fusion, where information acquired by different imaging devices or protocols is fused to facilitate diagnosis and treatment planning; 2) longitudinal studies, where temporal structural or anatomical changes are investigated; and 3) population modeling and statistical atlases used to study normal anatomical variability. In this paper, we attempt to give an overview of deformable registration methods, putting emphasis on the most recent advances in the domain. Additional emphasis has been given to techniques applied to medical images. In order to study image registration methods in depth, their main components are identified and studied independently. The most recent techniques are presented in a systematic fashion. The contribution of this paper is to provide an extensive account of registration techniques in a systematic manner.

A Comparison of Hyperelastic Warping of PET Images with Tagged MRI for the Analysis of Cardiac Deformation

The objectives of the following research were to evaluate the utility of a deformable image registration technique known as hyperelastic warping for the measurement of local strains in the left ventricle through the analysis of clinical, gated PET image datasets. Two normal human male subjects were sequentially imaged with PET and tagged MRI imaging. Strain predictions were made for systolic contraction using warping analyses of the PET images and HARP based strain analyses of the MRI images. Coefficient of determination R (2) values were computed for the comparison of circumferential and radial strain predictions produced by each methodology. There was good correspondence between the methodologies, with R (2) values of 0.78 for the radial strains of both hearts and from an R (2) = 0.81 and R (2) = 0.83 for the circumferential strains. The strain predictions were not statistically different (P ≤ 0.01). A series of sensitivity results indicated that the methodology was relatively insensitive to alterations in image intensity, random image noise, and alterations in fiber structure. This study demonstrated that warping was able to provide strain predictions of systolic contraction of the LV consistent with those provided by tagged MRI Warping.

Increased strain levels and water content in brain tissue after decompressive craniotomy

BACKGROUND

At present there is a debate on the effectiveness of the decompressive craniotomy (DC). Stretching of axons was speculated to contribute to the unfavourable outcome for the patients. The quantification of strain level could provide more insight into the potential damage to the axons. The aim of the present study was to evaluate the strain level and water content (WC) of the brain tissue for both the pre- and post-craniotomy period.

METHODS

The stretching of brain tissue was quantified retrospectively based on the computerised tomography (CT) images of six patients before and after DC by a non-linear image registration method. WC was related to specific gravity (SG), which in turn was related to the Hounsfield unit (HU) value in the CT images by a photoelectric correction according to the chemical composition of brain tissue.

RESULTS

For all the six patients, the strain level showed a substantial increase in the brain tissue close to the treated side of DC compared with that found at the pre-craniotomy period and ranged from 24 to 55 % at the post-craniotomy period. Increase of strain level was also observed at the brain tissue opposite to the treated side, however, to a much lesser extent. The mean area of craniotomy was found to be 91.1 ± 12.7 cm(2). The brain tissue volume increased from 27 to 127 ml, corresponding to 1.65 % and 8.13 % after DC in all six patients. Also, the increased volume seemed to correlate with increased strain level. Specifically, the overall WC of brain tissue for two patients evaluated presented a significant increase after the treatment compared with the condition seen before the treatment. Furthermore, the Glasgow Coma Scale (GCS) improved in four patients after the craniotomy, while two patients died. The GCS did not seem to correlate with the strain level.

CONCLUSIONS

We present a new numerical method to quantify the stretching or strain level of brain tissue and WC following DC. The significant increase in strain level and WC in the post-craniotomy period may cause electrophysiological changes in the axons, resulting in loss of neuronal function. Hence, this new numerical method provides more insight of the consequences following DC and may be used to better define the most optimal size and area of the craniotomy in reducing the strain level development.

A framework of whole heart extracellular volume fraction estimation for low-dose cardiac CT images

Cardiac CT (CCT) is widely available and has been validated for the detection of focal myocardial scar using a delayed enhancement technique in this paper. CCT, however, has not been previously evaluated for quantification of diffuse myocardial fibrosis. In our investigation, we sought to evaluate the potential of low-dose CCT for the measurement of myocardial whole heart extracellular volume (ECV) fraction. ECV is altered under conditions of increased myocardial fibrosis. A framework consisting of three main steps was proposed for CCT whole heart ECV estimation. First, a shape-constrained graph cut (GC) method was proposed for myocardium and blood pool segmentation on postcontrast image. Second, the symmetric demons deformable registration method was applied to register precontrast to postcontrast images. So the correspondences between the voxels from precontrast to postcontrast images were established. Finally, the whole heart ECV value was computed. The proposed method was tested on 20 clinical low-dose CCT datasets with precontrast and postcontrast images. The preliminary results demonstrated the feasibility and efficiency of the proposed method.

Validation of continuously tagged MRI for the measurement of dynamic 3D skeletal muscle tissue deformation

PURPOSE

Typically spatial modulation of the magnetization (SPAMM) tagged magnetic resonance imaging (MRI) requires many repeated motion cycles limiting the applicability to highly repeatable tissue motions only. This paper describes the validation of a novel SPAMM tagged MRI and post-processing framework for the measurement of complex and dynamic 3D soft tissue deformation following just three motion cycles. Techniques are applied to indentation induced deformation measurement of the upper arm and a silicone gel phantom.

METHODS

A SPAMM tagged MRI methodology is presented allowing continuous (3.3-3.6 Hz) sampling of 3D dynamic soft tissue deformation using non segmented 3D acquisitions. The 3D deformation is reconstructed by the combination of three mutually orthogonal tagging directions, thus requiring only three repeated motion cycles. In addition a fully automatic post-processing framework is presented employing Gabor scale-space and filter-bank analysis for tag extrema segmentation and triangulated surface fitting aided by Gabor filter bank derived surface normals. Deformation is derived following tracking of tag surface triplet triangle intersections. The dynamic deformation measurements were validated using indentation tests (∼20 mm deep at 12 mm/s) on a silicone gel soft tissue phantom containing contrasting markers which provide a reference measure of deformation. In addition, the techniques were evaluated in vivo for dynamic skeletal muscle tissue deformation measurement during indentation of the biceps region of the upper arm in a volunteer.

RESULTS

For the phantom and volunteer tag point location precision were 44 and 92 μm, respectively resulting in individual displacements precisions of 61 and 91 μm, respectively. For both the phantom and volunteer data cumulative displacement measurement accuracy could be evaluated and the difference between initial and final locations showed a mean and standard deviation of 0.44 and 0.59 mm for the phantom and 0.40 and 0.73 mm for the human data. Finally accuracy of (cumulative) displacement was evaluated using marker tracking in the silicone gel phantom. Differences between true and predicted marker locations showed a mean of 0.35 mm and a standard deviation of 0.63 mm.

CONCLUSIONS

A novel SPAMM tagged MRI and fully automatic post-processing framework for the measurement of complex 3D dynamic soft tissue deformation following just three repeated motion cycles was presented. The techniques demonstrate dynamic measurement of complex 3D soft tissue deformation at subvoxel accuracy and precision and were validated for 3.3-3.6 Hz sampling of deformation speeds up to 12 mm/s.

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.

Clinical benefits of integrating cardiac and vascular models

INTRODUCTION

Recent advances in computational methods and medical imaging techniques have enabled non-invasive exploration of cardiovascular pathologies, from cardiac level to complex arterial networks. The potential of cardiac and vascular modeling in guiding and monitoring therapies could be further extended through the integration of the two systems.

AREAS COVERED

This review includes advances in methods for cardiac electromechanics and vascular flow simulations. The results of a literature search depicting the state of the art in cardiac and vascular modeling are reviewed. The paper goes on to address the benefits and challenges of combined cardiovascular modeling, highlighting the relevance of specific cardiovascular features and implementation. Various alternative approaches and insights on future directions are presented and analyzed with respect to their applicability to clinical practice.

EXPERT OPINION

The article has emerged from the exploration of currently available cardiac and vascular mathematical tools and their corresponding clinical application. The summarized analysis suggests that future efforts should be aimed at developing more accurate and patient-specific mathematical models integrating cardiac and vascular functions to enhance the knowledge of cardiovascular pathologies.

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.