Echocardiography without electrocardiogram.

AIMS: automatic detection of the QRS complex on electrocardiogram (ECG) is used on cardiac ultrasound scanners to separate ultrasound image series into cardiac cycles for playback and storage. On small hand-held scanners it is unpractical to connect ECG cables. We therefore aim to do automatic cardiac cycle separation using apical B-mode ultrasound images. METHODS AND RESULTS: cardiac cycle length is estimated by cyclicity analysis of B-mode intensities. To determine a cycle start estimate near QRS, a deformable model is fitted to the left ventricle in real-time. The model is used to initialize and constrain a speckle tracker positioned near the mitral annulus. In the displacement curve generated by the speckle tracker, a time point near maximum distance from the probe is detected as a cardiac cycle start estimate. Validation against ECG was done on 233 recordings from normal subjects and 46 recordings from subjects with coronary pathology. Several test cases were run for each recording to emulate B-mode series starting at all time points in the cardiac cycle. Totally, 11 886 test cases were run. Cycle length estimation was feasible in 98% of normal subject cases and 91% of pathology cases. Median difference in cycle length by ECG was 0 and -3 ms, respectively. Cycle start estimation was feasible in 90% of normal subject cases and 77% of pathology cases. Median difference to cycle start by ECG was 62 and 76 ms, respectively. CONCLUSION: apical B-mode series can automatically be separated into cardiac cycles without using ECG.

Two methods for modifed Doo-Sabin modeling of nonsmooth surfaces-applied to right ventricle modeling.

Purpose: In recent years, there has been increased clinical interest in the right ventricle (RV) of the heart. RV dysfunction is an important prognostic marker for several cardiac diseases. Accurate modeling of the RV shape is important for estimating the performance. We have created computationally effective models that allow for accurate estimation of the RV shape. Approach: Previous approaches to cardiac shape modeling, including modeling the RV geometry, has used Doo-Sabin surfaces. Doo-Sabin surfaces allow effective computation and adapt to smooth, organic surfaces. However, they struggle with modeling sharp corners or ridges without many control nodes. We modified the Doo-Sabin surface to allow for sharpness using weighting of vertices and edges instead. This was done in two different ways. For validation, we compared the standard Doo-Sabin versus the sharp Doo-Sabin models in modeling the RV shape of 16 cardiac ultrasound images, against a ground truth manually drawn by a cardiologist. A Kalman filter fitted the models to the ultrasound images, and the difference between the volume of the model and the ground truth was measured. Results: The two modified Doo-Sabin models both outperformed the standard Doo-Sabin model in modeling the RV. On average, the regular Doo-Sabin had an 8-ml error in volume, whereas the sharp models had 7- and 6-ml error, respectively. Conclusions: Compared with the standard Doo-Sabin, the modified Doo-Sabin models can adapt to a larger variety of surfaces while still being compact models. They were more accurate on modeling the RV shape and could have uses elsewhere.

Semiautomated biventricular segmentation in three-dimensional echocardiography by coupled deformable surfaces.

With the advancement of three-dimensional (3-D) real-time echocardiography in recent years, automatic creation of patient specific geometric models is becoming feasible and important in clinical decision making. However, the vast majority of echocardiographic segmentation methods presented in the literature focus on the left ventricle (LV) endocardial border, leaving segmentation of the right ventricle (RV) a largely unexplored problem, despite the increasing recognition of the RV's role in cardiovascular disease. We present a method for coupled segmentation of the endo- and epicardial borders of both the LV and RV in 3-D ultrasound images. To solve the segmentation problem, we propose an extension of a successful state-estimation segmentation framework with a geometrical representation of coupled surfaces, as well as the introduction of myocardial incompressibility to regularize the segmentation. The method was validated against manual measurements and segmentations in images of 16 patients. Mean absolute distances of [Formula: see text], [Formula: see text], and [Formula: see text] between the proposed and reference segmentations were observed for the LV endocardium, RV endocardium, and LV epicardium surfaces, respectively. The method was computationally efficient, with a computation time of [Formula: see text].

Automated Segmentation of the Right Ventricle in 3D Echocardiography: A Kalman Filter State Estimation Approach.

As the right ventricle's (RV) role in cardiovascular diseases is being more widely recognized, interest in RV imaging, function and quantification is growing. However, there are currently few RV quantification methods for 3D echocardiography presented in the literature or commercially available. In this paper we propose an automated RV segmentation method for 3D echocardiographic images. We represent the RV geometry by a Doo-Sabin subdivision surface with deformation modes derived from a training set of manual segmentations. The segmentation is then represented as a state estimation problem and solved with an extended Kalman filter by combining the RV geometry with a motion model and edge detection. Validation was performed by comparing surface-surface distances, volumes and ejection fractions in 17 patients with aortic insufficiency between the proposed method, magnetic resonance imaging (MRI), and a manual echocardiographic reference. The algorithm was efficient with a mean computation time of 2.0 s. The mean absolute distances between the proposed and manual segmentations were 3.6 ± 0.7 mm. Good agreements of end diastolic volume, end systolic volume and ejection fraction with respect to MRI ( -26±24 mL , -16±26 mL and 0 ± 10%, respectively) and a manual echocardiographic reference (7 ± 30 mL, 13 ± 17 mL and -5±7% , respectively) were observed.

Real-time scan assistant for echocardiography.

A real-time scan assistant (SA) for use with echocardiography is presented. The motivation is to aid nonexpert users in capturing apical 4-chamber views (A4CH) during echocardiography. The algorithm is based on a parametric multi-chamber model of the A4CH view, updated in an extended Kalman filter framework. The regional model goodness-of-fit is used to calculate a score, which is provided to the user during acquisition, together with an icon (emoticon) indicating whether the current view is acceptable or not. The SA was implemented on a commercially available scanner. A feasibility test was performed using two healthy volunteers as models and 10 medical students acting as nonexpert users. The students examined the models on two occasions, separated more than four days in time. Half of the students used the SA during the first exam and no SA at the second exam. The other half used the opposite order. The recordings were later rated by a cardiologist. A Wilcoxon signed pair rank test revealed a statistically significant improvement when using SA. Nine cases were rated as poor without using the SA. In eight (89%) of these cases, view quality improved to acceptable when the SA was used.

Automated septum thickness measurement--a Kalman filter approach.

Interventricular septum thickness in end-diastole (IVSd) is one of the key parameters in cardiology. This paper presents a fast algorithm, suitable for pocket-sized ultrasound devices, for measurement of IVSd using 2D B-mode parasternal long axis images. The algorithm is based on a deformable model of the septum and the mitral valve. The model shape is estimated using an extended Kalman filter. A feasibility study using 32 unselected recordings is presented. The recordings originate from a database consisting of subjects from a normal healthy population. Five patients with suspected hypertrophy were included in the study. Reference B-mode measurements were made by two cardiologists. A paired t-test revealed a non-significant mean difference, compared to the B-mode reference, of (mean±SD) 0.14±1.36 mm (p=0.532). Pearson's correlation coefficient was 0.79 (p<0.001). The results are comparable to the variability between the two cardiologists, which was found to be 1.29±1.23 mm (p<0.001). The results indicate that the method has potential as a tool for rapid assessment of IVSd.

Fast automatic measurement of mitral annulus excursion using a pocket-sized ultrasound system.

We present a fast, automatic method for mitral annulus excursion measurement using pocket-sized ultrasound (PSU). The motivation is to provide PSU users with a rapid measurement of cardiac systolic function. The algorithm combines low-frame-rate tolerance, computational efficiency and automation in a novel way. The method uses a speckle-tracking scheme, initialized and constrained by a deformable model. A feasibility study using 30 apical four-chamber PSU recordings from an unselected patient population revealed an error of (mean ± SD) -1.80 ± 1.96 mm, p < 0.001, when compared with manual anatomic m-mode analysis using laptop scanner data. When only septal side excursion was measured, the mean error was -0.27 ± 1.89 mm, p < 0.001. The accuracy is comparable with previously reported results using semiautomatic methods and full-size scanners. The computation time of 3.7 ms/frame on a laptop computer suggests that a real-time implementation on a PSU device is feasible.

Real-time tracking of the left ventricle in 3D echocardiography using a state estimation approach.

In this paper we present a framework for real-time tracking of deformable contours in volumetric datasets. The framework supports composite deformation models, controlled by parameters for contour shape in addition to global pose. Tracking is performed in a sequential state estimation fashion, using an extended Kalman filter, with measurement processing in information space to effectively predict and update contour deformations in real-time. A deformable B-spline surface coupled with a global pose transform is used to model shape changes of the left ventricle of the heart. Successful tracking of global motion and local shape changes without user intervention is demonstrated on a dataset consisting of 21 3D echocardiography recordings. Real-time tracking using the proposed approach requires a modest CPU load of 13% on a modern computer. The segmented volumes compare to a semi-automatic segmentation tool with 95% limits of agreement in the interval 4.1 +/- 24.6 ml (r = 0.92).