Noninvasive imaging of cardiac transmembrane potentials within three-dimensional myocardium by means of a realistic geometry anisotropic heart model

We have developed a new approach for imaging cardiac transmembrane potentials (TMPs) within the three-dimensional (3-D) myocardium by means of an anisotropic heart model. The cardiac TMP distribution is estimated from body surface electrocardiograms by minimizing objective functions of the "measured" body surface potential maps (BSPMs) and the heart-model-generated BSPMs. Computer simulation studies have been conducted to evaluate the present 3-D TMP imaging approach using pacing protocols. Simulations of single-site pacing at 24 sites throughout the ventricles, as well as dual-site pacing at 12 pairs of sites in the vicinity of atrio-ventricular ring were performed. The present simulation results show that the correlation coefficient (CC) and relative error (RE) between the "true" and inversely estimated TMP distributions were 0.9915 +/- 0.0041 and 0.1266 +/- 0.0326, for single-site pacing, and 0.9889 +/- 0.0034 and 0.1473 +/- 0.0237 for dual-site pacing, respectively, when 10 microV Gaussian white noise (GWN) was added to the BSPMs. The effects of heart and torso geometry uncertainty were also evaluated by shifting the heart position by 10 mm and altering the torso size by 10%. The CC between the "true" and inversely estimated TMP distributions was above 0.97 when these geometry uncertainties were considered. The present simulation results demonstrate the feasibility of noninvasive estimation of TMP distribution throughout the ventricles from body surface electrocardiographic measurements, and suggest that the present method may become a useful alternative in noninvasive imaging of distributed cardiac electrophysiological processes within the 3-D myocardium.     

A method for quantitative display of three-dimensional regional myocardial function

The DSR (dynamic spatial reconstructor), a multiple X-ray source scanner that generates stop action three-dimensional (3-D) images of a cylindrical volume, was used for quantitative imaging of left ventricular 3-D wall geometry and function in experimentally induced canine left ventricular myocardial infarction. Impaired regional myocardial function was induced by myocardial ischemia or infarction in four mongrel dogs by closed-chest occlusion of the proximal left anterior descending (LAD) coronary artery. At intervals of 6-14 weeks post occlusion, the dogs were scanned with the DSR during biatrial contrast injection. The 3-D shape, extent, and function of hypokinetic myocardium was measured from the DSR images utilizing measurement of the rate of local systolic wall thickening to detect regions of normal, ischemic, or scarred myocardium. The results were compared to scar size and anatomic distribution measured at postmortem examination. The anatomic extent and relationship of hypocontractile to normally contracting muscle was visualized by computer generated, pseudo 3-D shaded surface displays of the left ventricular chamber and by topographic projections of regional wall thickening rates onto a map of the left ventricular endocardial surface. The location of myocardial infarction and the surrounding zone of impaired function is clearly defined by this 3-D CT scanning procedure. The display method presented here provides both localization and quantification of the volume of ischemic and infarcted myocardium.     

Reconstruction and quantification of the carotid artery bifurcation from 3-D ultrasound images

Three-dimensional (3-D) ultrasound is a relatively new technique, which is well suited to imaging superficial blood vessels, and potentially provides a useful, noninvasive method for generating anatomically realistic 3-D models of the peripheral vasculature. Such models are essential for accurate simulation of blood flow using computational fluid dynamics (CFD), but may also be used to quantify atherosclerotic plaque more comprehensively than routine clinical methods. In this paper, we present a spline-based method for reconstructing the normal and diseased carotid artery bifurcation from images acquired using a freehand 3-D ultrasound system. The vessel wall (intima-media interface) and lumen surfaces are represented by a geometric model defined using smoothing splines. Using this coupled wall-lumen model, we demonstrate how plaque may be analyzed automatically to provide a comprehensive set of quantitative measures of size and shape, including established clinical measures, such as degree of (diameter) stenosis. The geometric accuracy of 3-D ultrasound reconstruction is assessed using pulsatile phantoms of the carotid bifurcation, and we conclude by demonstrating the in vivo application of the algorithms outlined to 3-D ultrasound scans from a series of patient carotid arteries.     

Ray phase space approach for 3-D imaging and 3-D optical data representation

We propose a framework to model, analyze and design three-dimensional (3-D) imaging systems. A system engineering approach is adopted which relates 3-D images (real or synthesized) to 3-D objects (real or synthesized) using a novel representation of the optical data which we call "ray phase space". The framework provides a powerful tool for determining the performance of 3-D imaging systems, for generating computational reconstruction of 3-D images and for optimizing 3-D imaging systems.     

Transmural versus nontransmural in situ electrical impedance spectrum for healthy, ischemic, and healed myocardium

Electrical properties of myocardial tissue are anisotropic due to the complex structure of the myocardial fiber orientation and the distribution of gap junctions. For this reason, measured myocardial impedance may differ depending on the current distribution and direction with respect to myocardial fiber orientation and, consequently, according to the measurement method. The objective of this study is to compare the specific impedance spectra of the myocardium measured using two different methods. One method consisted of transmural measurements using an intracavitary catheter and the other method consisted of nontransmural measurements using a four-needle probe inserted into the epicardium. Using both methods, we provide the in situ specific impedance spectrum (magnitude and phase angle) of normal, ischemic, and infarcted pig myocardium tissue from 1 kHz to 1 MHz. Magnitude spectra showed no significant differences between the measurement techniques. However, the phase angle spectra showed significant differences for normal and ischemic tissues according to the measurement technique. The main difference is encountered after 60 min of acute ischeimia in the phase angle spectrum. Healed myocardial tissue showed a small and flat phase angle spectrum in both methods due tothe low content of cells in the transmural infarct scar. In conclusion, both transmural and nontransmural measurements of phase angle spectrum allow the differentiation among normal, ischemic, and infarcted tissue.     

A vision-based technique for objective assessment of burn scars

In this paper a method for the objective assessment of burn scars is proposed. The quantitative measures developed in this research provide an objective way to calculate elastic properties of burn scars relative to the surrounding areas. The approach combines range data and the mechanics and motion dynamics of human tissues. Active contours are employed to locate regions of interest and to find displacements of feature points using automatically established correspondences. Changes in strain distribution over time are evaluated. Given images at two time instances and their corresponding features, the finite element method is used to synthesize strain distributions of the underlying tissues. This results in a physically based framework for motion and strain analysis. Relative elasticity of the burn scar is then recovered using iterative descent search for the best nonlinear finite element model that approximates stretching behavior of the region containing the burn scar. The results from the skin elasticity experiments illustrate the ability to objectively detect differences in elasticity between normal and abnormal tissue. These estimated differences in elasticity are correlated against the subjective judgments of physicians that are presently the practice     

Methodology for Jointly Assessing Myocardial Infarct Extent and Regional Contraction in 3-D CMRI

Automated extraction of quantitative parameters from cardiac magnetic resonance images is crucial for the management of patients with myocardial infarct. This paper proposes a postprocessing procedure to jointly analyze Cine and delayed-enhanced (DE) acquisitions, in order to provide an automatic quantification of myocardial contraction and enhancement parameters and a study of their relationship. For that purpose, the following processes are performed: 1) DE/Cine temporal synchronization and 3-D scan alignment, 2) 3-D DE/Cine rigid registration in a region about the heart, 3) myocardium segmentation on Cine-MRI and superimposition of the epicardial and endocardial contours on the DE images, 4) quantification of the myocardial infarct extent (MIE), 5) study of the regional contractile function using a new index, the amplitude to time ratio (ATR). The whole procedure was applied to ten patients with clinically proven myocardial infarction. The comparison between the MIE and the visually assessed regional function scores demonstrated that the MIE is highly related to the severity of the wall motion abnormality. In addition, it was shown that the newly developed regional myocardial contraction parameter (ATR) decreases significantly in delayed enhanced regions. This largely automated approach enables the combined study of regional MIE and left ventricular function.     

Maximum a Posteriori Strategy for the Simultaneous Motion and Material Property Estimation of the Heart

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

Correspondence between simple 3-D MRI-based computer models and in-vivo EP measurements in swine with chronic infarctions

The aim of this paper was to compare several in-vivo electrophysiological (EP) characteristics measured in a swine model of chronic infarct, with those predicted by simple 3-D MRI-based computer models built from ex-vivo scans (voxel size <1 mm(3)). Specifically, we recorded electroanatomical voltage maps (EAVM) in six animals, and ECG waves during induction of arrhythmia in two of these cases. The infarct heterogeneities (dense scar and border zone) as well as fiber directions were estimated using diffusion weighted DW-MRI. We found a good correspondence (r = 0.9) between scar areas delineated on the EAVM and MRI maps. For theoretical predictions, we used a simple two-variable macroscopic model and computed the propagation of action potential after application of a train of stimuli, with location and timing replicating the stimulation protocol used in the in-vivo EP study. Simulation results are exemplified for two hearts: one with noninducible ventricular tachycardia (VT), and another with a macroreentrant VT (for the latter, the average predicted VT cycle length was 273 ms, compared to a recorded VT of 250 ms).     

Segmentation of medical images using LEGION

Advances in visualization technology and specialized graphic workstations allow clinicians to virtually interact with anatomical structures contained within sampled medical-image datasets. A hindrance to the effective use of this technology is the difficult problem of image segmentation. In this paper, we utilize a recently proposed oscillator network called the locally excitatory globally inhibitory oscillator network (LEGION) whose ability to achieve fast synchrony with local excitation and desynchrony with global inhibition makes it an effective computational framework for grouping similar features and segregating dissimilar ones in an image. We extract an algorithm from LEGION dynamics and propose an adaptive scheme for grouping. We show results of the algorithm to two-dimensional (2-D) and three-dimensional (3-D) (volume) computerized topography (CT) and magnetic resonance imaging (MRI) medical-image datasets. In addition, we compare our algorithm with other algorithms for medical-image segmentation, as well as with manual segmentation. LEGION's computational and architectural properties make it a promising approach for real-time medical-image segmentation.     

Segmentation of the left ventricle of the heart in 3-D+t MRI data using an optimized nonrigid temporal model

Modern medical imaging modalities provide large amounts of information in both the spatial and temporal domains and the incorporation of this information in a coherent algorithmic framework is a significant challenge. In this paper, we present a novel and intuitive approach to combine 3-D spatial and temporal (3-D + time) magnetic resonance imaging (MRI) data in an integrated segmentation algorithm to extract the myocardium of the left ventricle. A novel level-set segmentation process is developed that simultaneously delineates and tracks the boundaries of the left ventricle muscle. By encoding prior knowledge about cardiac temporal evolution in a parametric framework, an expectation-maximization algorithm optimally tracks the myocardial deformation over the cardiac cycle. The expectation step deforms the level-set function while the maximization step updates the prior temporal model parameters to perform the segmentation in a nonrigid sense.     

Fast tracking of cardiac motion using 3D-HARP

Magnetic resonance (MR) tagging is capable of accurate, noninvasive quantification of regional myocardial function. Routine clinical use, however, is hindered by cumbersome and time-consuming postprocessing procedures. We propose a fast, semiautomatic method for tracking three-dimensional (3-D) cardiac motion from a temporal sequence of short- and long-axis tagged MR images. The new method, called 3-D-HARmonic Phase (3D-HARP), extends the HARP approach, previously described for two-dimensional (2-D) tag analysis, to 3-D. A 3-D material mesh model is built to represent a collection of material points inside the left ventricle (LV) wall at a reference time. Harmonic phase, a material property that is time-invariant, is used to track the motion of the mesh through a cardiac cycle. Various motion-related functional properties of the myocardium, such as circumferential strain and left ventricular twist, are computed from the tracked mesh. The correlation analysis of 3D-HARP and FINDTAGS + Tag Strain(E) Analysis (TEA), which are well-established tag analysis techniques, shows that the regression coefficients of circumferential strain (E(CC)) and twist angle are r2 = 0.8605 and r2 = 0.8645, respectively. The total time required for tracking 3-D cardiac motion is approximately 10 min in a 9 timeframe tagged MRI dataset and has the potential to be much faster.     

Three-Dimensional Microwave Imaging Problems Solved Through an Efficient Multiscaling Particle Swarm Optimization

An enhanced multistep strategy based on a multiresolution particle swarm optimizer is proposed for 3-D microwave imaging. The aim of such an integration is to improve the convergence capabilities of the approach and to reduce the dimension of the search space and the computational burden of the optimization strategy, thanks to a constrained control of the particle velocities adaptively determined. This favors the exploitation of the global search capabilities of the particle swarms also in the framework of large-scale 3-D inverse scattering problems. The proposed technique is assessed by considering numerical tests concerned with single and multiple 3-D targets. The results of an experimental testing are also discussed.     

Normal and pathological NCAT image and phantom data based on physiologically realistic left ventricle finite-element models

The four-dimensional (4-D) NURBS-based cardiac-torso (NCAT) phantom, which provides a realistic model of the normal human anatomy and cardiac and respiratory motions, is used in medical imaging research to evaluate and improve imaging devices and techniques, especially dynamic cardiac applications. One limitation of the phantom is that it lacks the ability to accurately simulate altered functions of the heart that result from cardiac pathologies such as coronary artery disease (CAD). The goal of this work was to enhance the 4-D NCAT phantom by incorporating a physiologically based, finite-element (FE) mechanical model of the left ventricle (LV) to simulate both normal and abnormal cardiac motions. The geometry of the FE mechanical model was based on gated high-resolution X-ray multislice computed tomography (MSCT) data of a healthy male subject. The myocardial wall was represented as a transversely isotropic hyperelastic material, with the fiber angle varying from -90 degrees at the epicardial surface, through 0 degrees at the midwall, to 90 degrees at the endocardial surface. A time-varying elastance model was used to simulate fiber contraction, and physiological intraventricular systolic pressure-time curves were applied to simulate the cardiac motion over the entire cardiac cycle. To demonstrate the ability of the FE mechanical model to accurately simulate the normal cardiac motion as well as the abnormal motions indicative of CAD, a normal case and two pathologic cases were simulated and analyzed. In the first pathologic model, a subendocardial anterior ischemic region was defined. A second model was created with a transmural ischemic region defined in the same location. The FE-based deformations were incorporated into the 4-D NCAT cardiac model through the control points that define the cardiac structures in the phantom which were set to move according to the predictions of the mechanical model. A simulation study was performed using the FE-NCAT combination to investigate how the differences in contractile function between the subendocardial and transmural infarcts manifest themselves in myocardial Single photon emission computed tomography (SPECT) images. The normal FE model produced strain distributions that were consistent with those reported in the literature and a motion consistent with that defined in the normal 4-D NCAT beating heart model based on tagged magnetic resonance imaging (MRI) data. The addition of a subendocardial ischemic region changed the average transmural circumferential strain from a contractile value of -0.09 to a tensile value of 0.02. The addition of a transmural ischemic region changed average circumferential strain to a value of 0.13, which is consistent with data reported in the literature. Model results demonstrated differences in contractile function between subendocardial and transmural infarcts and how these differences in function are documented in simulated myocardial SPECT images produced using the 4-D NCAT phantom. Compared with the original NCAT beating heart model, the FE mechanical model produced a more accurate simulation for the cardiac motion abnormalities. Such a model, when incorporated into the 4-D NCAT phantom, has great potential for use in cardiac imaging research. With its enhanced physiologically based cardiac model, the 4-D NCAT phantom can be used to simulate realistic, predictive imaging data of a patient population with varying whole-body anatomy and with varying healthy and diseased states of the heart that will provide a known truth from which to evaluate and improve existing and emerging 4-D imaging techniques used in the diagnosis of cardiac disease.     

Reproducible Classification of Infarct Heterogeneity Using Fuzzy Clustering on Multicontrast Delayed Enhancement Magnetic Resonance Images

Delayed enhancement MRI (DE-MRI) can be used to identify myocardial infarct (MI). Classification of MI into the infarct core and heterogeneous periphery (called the gray zone) on conventional inversion-recovery gradient echo (IR-GRE) DE-MRI images has been related to inducibility for ventricular tachycardia. However, this classification is sensitive to image noise, depends on the signal intensity characteristics in a remote region of myocardium, and requires manual contours of the endocardial border. Image analysis and fuzzy clustering techniques were developed to analyze images acquired using a multicontrast delayed enhancement (MCDE) sequence in order characterize the infarct zones. The MCDE analysis is automated and uses data fitting of signal intensities acquired at multiple inversion times. In a study of 15 patients with chronic MI, the gray zones derived from IR-GRE and MCDE images were comparable. The variability in the gray zone size associated with random noise and operator input was significantly reduced using the MCDE-based analysis compared to the IR-GRE-based analysis. In summary, the MCDE approach yields a more reproducible measure of the infarct core and gray zones on any given data set.     

A modeling approach for burn scar assessment using natural features and elastic property

A modeling approach is presented for quantitative burn scar assessment. Emphases are given to: 1) constructing a finite-element model from natural image features with an adaptive mesh and 2) quantifying the Young's modulus of scars using the finite-element model and regularization method. A set of natural point features is extracted from the images of burn patients. A Delaunay triangle mesh is then generated that adapts to the point features. A three-dimensional finite-element model is built on top of the mesh with the aid of range images providing the depth information. The Young's modulus of scars is quantified with a simplified regularization functional, assuming that the knowledge of the scar's geometry is available. The consistency between the relative elasticity index and the physician's rating based on the Vancouver scale (a relative scale used to rate burn scars) indicates that the proposed modeling approach has high potential for image-based quantitative burn scar assessment.     

Three-Dimensional Microwave Breast Imaging: Dispersive Dielectric Properties Estimation Using Patient-Specific Basis Functions

Breast imaging via microwave tomography involves estimating the distribution of dielectric properties within the patient's breast on a discrete mesh. The number of unknowns in the discrete mesh can be very large for 3-D imaging, and this results in computational challenges. We propose a new approach where the discrete mesh is replaced with a relatively small number of smooth basis functions. The dimension of the tomography problem is reduced by estimating the coefficients of the basis functions instead of the dielectric properties at each element in the discrete mesh. The basis functions are constructed using knowledge of the location of the breast surface. The number of functions used in the basis can be varied to balance resolution and computational complexity. The reduced dimension of the inverse problem enables application of a computationally efficient, multiple-frequency inverse scattering algorithm in 3-D. The efficacy of the proposed approach is verified using two 3-D anatomically realistic numerical breast phantoms. It is shown for the case of single-frequency microwave tomography that the imaging accuracy is comparable to that obtained when the original discrete mesh is used, despite the reduction of the dimension of the inverse problem. Results are also shown for a multiple-frequency algorithm where it is computationally challenging to use the original discrete mesh.      

Efficient electromagnetic source imaging with adaptive standardized LORETA/FOCUSS

Functional brain imaging and source localization based on the scalp's potential field require a solution to an ill-posed inverse problem with many solutions. This makes it necessary to incorporate a priori knowledge in order to select a particular solution. A computational challenge for some subject-specific head models is that many inverse algorithms require a comprehensive sampling of the candidate source space at the desired resolution. In this study, we present an algorithm that can accurately reconstruct details of localized source activity from a sparse sampling of the candidate source space. Forward computations are minimized through an adaptive procedure that increases source resolution as the spatial extent is reduced. With this algorithm, we were able to compute inverses using only 6% to 11% of the full resolution lead-field, with a localization accuracy that was not significantly different than an exhaustive search through a fully-sampled source space. The technique is, therefore, applicable for use with anatomically-realistic, subject-specific forward models for applications with spatially concentrated source activity.