Stein Inge Rabben

Semiautomatic contour detection in ultrasound M-mode images.

We have developed a method for semiautomatic contour detection in M-mode images. The method combines tissue Doppler and grey-scale data. It was used to detect: 1. the left endocardium of the septum, the endocardium and epicardium of the posterior wall in 16 left ventricular short-axis M-modes, and 2. the mitral ring in 38 anatomical M-modes extracted pair-wise in 19 apical four-chamber cine-loops (healthy subjects). We validated the results by comparing the computer-generated contours with contours manually outlined by four echocardiographers. For all boundaries, the average distance between the computer-generated contours and the manual outlines was smaller than the average distance between the manual outlines. We also calculated left ventricular wall thickness and diameter at end-diastole and end-systole and lateral and septal mitral ring excursions, and found, on average, clinically negligible differences between the computer-generated indices and the same indices based on manual outlines (0.8-1.8 mm). The results were also within published normal values. In conclusion, this initial study showed that it was feasible in a robust and efficient manner to detect continuous wall boundaries in M-mode images so that tracings of left ventricular wall thickness, diameter and long axis could be derived.

High frame rate strain rate imaging of the interventricular septum in healthy subjects.

OBJECTIVEnIn the present study the feasibility was assessed of a new strain rate imaging method with a very high frame rate of around 300 frames per second.nnnMETHODSnDigital radio-frequency (RF) data were obtained in nine healthy subjects using a sector of 20-30 degrees in an apical four chamber view. The RF data were analysed using a dedicated software package that displays strain rate images and profiles and calculates strain rate values. With the new method, it is possible to study events and spatial-temporal differences in the heart cycle with duration down to 3.5-3 ms, including the pre-ejection period and the isovolumic relaxation period. Since the interventricular septum (IVS) is of crucial importance for the left and right ventricular function, we assessed changes through the heart cycle of the strain rate in the IVS.nnnRESULTSnMean peak systolic strain rate in the healthy subjects was -1.65+/-0.13 s(-1). Mean peak diastolic strain rate during early filling was 3.14+/-0.50 s(-1) and during atrial systole 0.99+/-0.09 s(-1). We found individual differences in the strain rate patterns, but in all subjects, the ventricular contraction started simultaneously in all parts of the septum. After the ejection period, the elongation started before aortic valve closure, in the midinferior septum and propagated towards the apex.nnnCONCLUSIONnHigh frame rate strain rate imaging makes it possible to study rapid deformation patterns in the heart walls.

Automatic detection and tracking of left ventricular landmarks in echocardiography

We introduce a method for automatic detection and tracking of the apex and two landmarks defining the atrioventricular plane in apical views of the left ventricle. The method is based on using tissue Doppler to track a set of candidate points in a cardiac cycle. Each candidate point is given a score based on the gray-scale, the velocity, and the depth profiles. The landmarks with the lowest costs are selected, and measurements are calculated automatically. The method is evaluated by comparing with manual selection by four cardiologists, and the presented results show that the method is robust and extracted measurements are comparable with manual selection.

A kinematic model for simulating physiological left ventricular deformation patterns - a tool for evaluation of myocardial strain imaging

In this study, we have developed a kinematic model of the left ventricle (LV) with physiological wall thickening, short and long axes deformation and torsion. This was done by approximating the LV as a thick-walled ellipsoid. Since the model is described analytically, it is possible to calculate the velocity vector, the Lagrangian strain tensor and the deformation gradient tensor everywhere within the wall. The true strain can then be obtained in any direction from the Lagrangian strain tensor, whereas Doppler-based strain rate (and thereby strain) can be obtained in the beam direction from the deformation gradient tensor. LV diameter, wall thickness and base-to-apex length were measured in 15 healthy individuals, averaged to obtain a representative cardiac cycle and used as input to the model. The deformation patterns of the model were in qualitative agreement with published observation. The model enables researchers to study geometrical artifacts in strain imaging, such as angle dependence and the use of fixed versus moving sample volumes. Furthermore, the model can simulate the motion of a set of point scatterers, and thereby give input to ultrasound simulators for evaluation of strain imaging artifacts.

Real-time volume stitching in 4D echocardiography

Three-dimensional (3D) echocardiography is chal- lenging due to limitation of the data acquisition rate caused by the speed of sound. ECG-gated stitching of data from several cardiac cycles is a possible technique to achieve higher resolution. The aim of this work is two-fold: Firstly, to provide a method for real-time presentation of stitched echocardiographic images acquired over several cardiac cycles, and secondly, to quantify the decrease of geometrical distortion achieved by stitched over non-stitched acquisition of 3D ultrasonic data of the left ventricle (LV). We present a volume stitching algorithm that merges data from N consecutive heart cycles into an assembled data volume which is volume-rendered in real-time. Furthermore, we propose a measure for the geometrical distortion present in ultrasound images. The distortion is calculated for images simulated by sampling a kinematic model of the LV wall. The impact of geometrical distortion on volume measurements is discussed. We conclude that displaying stitched 4D ultrasound data in real-time is feasible and an adequate technique for increasing the volume acquisition rate at a given spatial resolution, and that the geometrical distortion decreases substantially for data with higher volume rate. For a full scan of the LV, stitching over at least four cycles is recommended.

Equations for estimating muscle fiber stress in the left ventricular wall

SummaryLeft ventricular muscle fiber stress is an important parameter in cardiac energetics. Hence, we developed equations for estimating regional fiber stresses in rotationally symmetric chambers, and equatorial and apical fiber stresses in prolate spheroidal chambers. The myocardium was modeled as a soft incompressible material embedding muscle fibers that support forces only in their longitudinal direction. A thin layer of muscle fibers then contributes with a pressure increment determined by the fiber stress and curvature. The fiber curvature depends on the orientation of the fibers, which varies continuously across the wall. However, by assuming rotational symmetry about the long axis of the ventricle and including a longitudinal force balance, we obtained equations where fiber stress is completely determined by the principal curvatures of the middle wall surface, wall thickness, and cavity pressure. The equations were validated against idealized prolate spheroidal chambers, whose wall thicknesses are such that the fiber stress is uniform from the equator to the apex. Because the apex is free to rotate, the resultant moment about the long axis of the LV must be zero. By using this constraint together with our fiberstress equations, we were able to estimate a muscle fiber orientation distribution across the wall that was in qualitative agreement with published measurements.

Detection of the myocardial boundary in the left ventricle from simultaneously acquired triplane ultrasound images using multi view active appearance motion models

We report a new algorithm for detecting the LV myocardial boundary from simultaneously acquired triplane US image sequences using Multi View Active Appearance Motion Models. Coupled boundary detection in three planes can po- tentially increase the accuracy of LV volume measurements, and also increase the robustness of the boundary detection over traditional methods. A database of triplane image sequences from full cardiac cycles, including the standard A4CH, A2CH, and ALAX views were established from 20 volunteers, including 12 healthy persons and 8 persons suffering from heart disease. For each dataset the LV myocardial boundary was manually outlined, and the ED and ES frames were determined visually for phase normalization of the cycles. The evaluation of the MVAAMM was performed using a leave one out approach. The mean point distance between manually and automatically determined contours were 4.1±1.9 mm, the volume error was 7.0±14 ml, and fractional volume error was 8.5±16 %. Volume detection using the automatic method showed excellent correlation to the manual method (R 2 =0.87). Common ultrasound artefacts such as dropouts were handled well by the MVAAMM since the detection in the three image planes were coupled. The views with the largest point distance had one or more foreshortened views. A larger training database may improve the performance in such cases.

Adaptive volume rendering of cardiac 3D ultrasound images: utilizing blood pool statistics

In this paper we introduce and investigate an adaptive direct volume rendering (DVR) method for real-time visualization of cardiac 3D ultrasound. DVR is commonly used in cardiac ultrasound to visualize interfaces between tissue and blood. However, this is particularly challenging with ultrasound images due to variability of the signal within tissue as well as variability of noise signal within the blood pool. Standard DVR involves a global mapping of sample values to opacity by an opacity transfer function (OTF). While a global OTF may represent the interface correctly in one part of the image, it may result in tissue dropouts, or even artificial interfaces within the blood pool in other parts of the image. In order to increase correctness of the rendered image, the presented method utilizes blood pool statistics to do regional adjustments of the OTF. The regional adaptive OTF was compared with a global OTF in a dataset of apical recordings from 18 subjects. For each recording, three renderings from standard views (apical 4-chamber (A4C), inverted A4C (IA4C) and mitral valve (MV)) were generated for both methods, and each rendering was tuned to the best visual appearance by a physician echocardiographer. For each rendering we measured the mean absolute error (MAE) between the rendering depth buffer and a validated left ventricular segmentation. The difference d in MAE between the global and regional method was calculated and t-test results are reported with significant improvements for the regional adaptive method (dA4C = 1.5 ± 0.3 mm, dIA4C = 2.5 ± 0.4 mm, dMV = 1.7 ± 0.2 mm, d.f. = 17, all p < 0.001). This improvement by the regional adaptive method was confirmed through qualitative visual assessment by an experienced physician echocardiographer who concluded that the regional adaptive method produced rendered images with fewer tissue dropouts and less spurious structures inside the blood pool in the vast majority of the renderings. The algorithm has been implemented on a GPU, running an average of 16 fps with a resolution of 512x512x100 samples (Nvidia GTX460).

Knowledge based extraction of the left ventricular endocardial boundary from 2D echocardiograms

Extraction of the endocardial boundary of the left ventricle is a key challenge in cardiac ultrasound imaging. The cardiac anatomy may be difficult to determine automatically without incorporating knowledge of both wall shape and intensity signature into the detection algorithm. The aim of this study is to establish a framework for knowledge based extraction of the left ventricular endocardial boundary. The method is based upon the Snake algorithm where internal and external energy terms are combined into a Snake energy. Instead of using the patient image directly for calculation of the external energy we propose to use the correlation between geometrically normalized images, from the patient and from the database. The ventricular shapes from the database cases are used to compute the internal energy term. One boundary is detected for each case, hence a selection criterion is required. The total Snake energy is evaluated for this purpose and compared to manual selection of the best case. As a preliminary verification of the framework, the ventricular end diastolic and end systolic areas and the ventricular ejection fraction were calculated from the detected boundaries for a set of patient cases, using both manual and automatic database case selection. Using manual case selection, the results are encouraging, but the total Snake energy did not provide a sufficiently robust selection criterion. The strength of the proposed method is its ability to utilize expert knowledge directly for extraction of the endocardial boundary from ultrasound data. Using manual selection of the best case, the calculated parameters from detected boundaries were in good agreement with manual delineation. Further work is required to find a robust selection criterion.

Non-invasive estimation of left ventricular myocardial fiber stress by using subclavian artery pulse tracings and M-mode echocardiography

Myocardial fiber stress is important when assessing LV function hypertrophy and oxygen demand. Non-invasive estimation of muscle fiber stress may be done by utilizing subclavian pulse traces and M-mode Echocardiography. The authors have developed a formula for fiber stress based on chamber dimensions that are easy to obtain by Echocardiography (wall thickness, diameter and long axis length). In addition, they have developed analysis software for estimation of fiber stress. To obtain normal values, they have examined 10 subjects. The normal values for start ejection stress, peak stress and end ejection stress were 37.1+/-9.0, 51.2 +/-17.9 and 27.8+/-8.4 kPa, respectively (mean+/-2SD). The methodology is promising. However, to determine the clinical usefulness of this method the authors also have to obtain normal values in subjects with cardiac diseases related to pressure or volume overload of the left ventricle.