Region-based endocardium tracking on real-time three-dimensional ultrasound.

Matrix-phased array transducers for real-time 3-D ultrasound enable fast, noninvasive visualization of cardiac ventricles. Typically, 3-D ultrasound images are semiautomatically segmented to extract the left ventricular endocardial surface at end-diastole and end-systole. Automatic segmentation and propagation of this surface throughout the entire cardiac cycle is a challenging and cumbersome task. If the position of the endocardial surface is provided at one or two time frames during the cardiac cycle, automated tracking of the surface over the remaining time frames could reduce the workload of cardiologists and optimize analysis of 3-D ultrasound data. In this paper, we applied a region-based tracking algorithm to track the endocardial surface between two reference frames that were manually segmented. To evaluate the tracking of the endocardium, the method was applied to 40 open-chest dog datasets with 484 frames in total. Ventricular geometry and volumes derived from region-based endocardial surfaces and manual tracing were quantitatively compared, showing strong correlation between the two approaches. Statistical analysis showed that the errors from tracking were within the range of interobserver variability of manual tracing. Moreover, our algorithm performed well on ischemia datasets, suggesting that the method is robust-to-abnormal wall motion. In conclusion, the proposed optical flow-based surface tracking method is very efficient and accurate, providing dynamic "interpolation" of segmented endocardial surfaces.

Theoretical quality assessment of myocardial elastography with in vivo validation.

Myocardial elastography (ME), a radio frequency (RF)-based speckle tracking technique with one-dimensional (1-D) cross correlation and novel recorrelation methods in a 2-D search was proposed to estimate and fully image 2-D transmural deformation field and to detect abnormal cardiac function. A theoretical framework was first developed in order to evaluate the performance of 2-D myocardial elastography based on a previously developed 3-D finite-element model of the canine left ventricle. A normal (control) and an ischemic (left-circumflex, LCx) model, which more completely represented myocardial deformation than a kinematic model, were considered. A 2-D convolutional image formation model was first used to generate RF signals for quality assessment of ME in the normal and ischemic cases. A 3-D image formation model was further developed to investigate the effect of the out-of-plane motion on the 2-D, in-plane motion estimation. Both orthogonal, in-plane displacement components (i.e., lateral and axial) between consecutive RF frames were iteratively estimated. All the estimated incremental 2-D displacements from end-diastole (ED) to end-systole (ES) were then accumulated to acquire the cumulative 2-D displacements, which were further used to calculate the cumulative 2-D systolic finite strains. Furthermore, the cumulative systolic radial and circumferential strains, which were angle- and frame-rate independent, were obtained from the 2-D finite-strain components and imaged in full view to detect the ischemic region. We also explored the theoretical understanding of the limitations of our technique for the accurate depiction of disease and validated it in vivo against tagged magnetic resonance imaging (tMRI) in the case of a normal human myocardium in a 2-D short-axis (SA) echocardiographic view. The theoretical framework succeeded in demonstrating that the 2-D myocardial elastography technique was a reliable tool for the complete estimation and depiction of the in-plane myocardial deformation field as well as for accurate identification of pathological mechanical function using established finite-element, left-ventricular canine models. In a preliminary study, the 2-D myocardial elastography was shown capable of imaging myocardial deformation comparable to equivalent tMRI estimates in a clinical setting.

Model-based screening of wall motion measures for detection of ischemia in three-dimensional cardiac images.

Quantitative measurement of left ventricular wall motion can improve clinical diagnosis by providing a more objective approach than qualitative analysis, which is subject to large inter-observer variability. We have developed novel techniques for quantifying left ventricular wall motion in three-dimensional image data sets. In this study, finite element models simulating regional ischemia in the left ventricle were used to screen potential wall motion measures for their capability to detect and evaluate the size of an ischemic region. Preliminary experimental results showed that wall motion analysis of real-time three-dimensional echocardiographic images successfully detected ischemia. Our four-dimensional wall motion analysis system provides an objective and quantitative approach for detecting and assessing the severity of disease.

Parameterization of left ventricular wall motion for detection of regional ischemia.

While qualitative wall motion analysis has proven valuable in clinical cardiology practice, quantitative analyses remain too time-consuming for routine clinical use. Our long-term goal is therefore to develop automated methods for quantitative wall motion analysis. In this paper, we utilize a finite element model of the regionally ischemic canine left ventricle to demonstrate a new approach based on parameterization of the left ventricular endocardial surface in prolate spheroidal coordinates. The parameterization provided a substantial data reduction and enabled simple definition, calculation, and display of three-dimensional fractional shortening (3DFS), a quantitative measure of wall motion analogous to the fractional shortening measure used in 2D analysis. The endocardial surface area displaying akinesis or dyskinesis by 3DFS corresponded closely to simulated ischemic region size and 3DFS identified appropriate wall motion abnormalities during experimental coronary occlusion in a canine pilot study. 3DFS therefore appears to be a reasonable candidate for clinical tests to determine its utility in identifying and quantifying acute regional ischemia in patients. By linking state of the art finite element models to the clinically relevant framework of wall motion analysis, the methods presented here will facilitate formulation, in silico prescreening, and clinical testing of additional candidate measures of wall motion.

Dynamic cardiac information from optical flow using four dimensional ultrasound.

Quantitative analysis of cardiac motion is of great clinical interest in assessing ventricular function. Real-time 3-D (RT3D) ultrasound transducers provide valuable three-dimensional information, from which quantitative measures of cardiac function can be extracted. Such analysis requires segmentation and visual tracking of the left ventricular endocardial border. We present results based on correlation of four-dimensional optical flow motion for temporal tracking of ventricular borders in three dimensional ultrasound data. A displacement field is computed from the optical flow output, and a framework for the computation of dynamic cardiac information is introduced. The method was applied to a clinical data set from a heart transplant patient and dynamic measurements agreed with physiological knowledge as well as experimental results.